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1. Beyond Exact Repeat Missions:Embracing Geodetic Altimetry for Inland Water Monitoring and Modeling

Author: Jiang, Liguang, Nielsen, Karina, Andersen, Ole B., Jiang, Liguang, Nielsen, Karina, and Andersen, Ole B.
Abstract: Satellite radar altimetry has become an essential tool for hydrological research over the past 2 decades. Unlike imagery that quantifies the water dynamics from the horizontal dimension, altimetry observations deliver vertical information, which is crucial for hydrological research. Geodetic mission (GM) altimetry data, characterized by long repeat periods compared to exact repeat missions, have been underutilized in hydrology. This paper aims to advocate for integrating geodetic altimetry data into inland water research and bring awareness to its potential applications. We demonstrated the values of GM data from CryoSat-2, Saral/AltiKa, Jason-1, and Jason-2 through 3 applications: (a) large-scale lake monitoring for improved understanding of regional and global hydrological cycles, (b) retrieval of local geoid undulations over large lakes to enhance the precision of individual water level observations, and (c) mapping river longitudinal profiles and construction of time series of river levels. We believe that the findings of this study will pave the way for more comprehensive utilization of geodetic altimetry data in diverse hydrological applications, ultimately advancing inland water altimetry.
Published: 2024

2. Reservoir Filling Up Problems in a Changing Climate:Insights From CryoSat-2 Altimetry

Author: Wang, Zhiwei, Jiang, Liguang, Nielsen, Karina, Wang, Lei, Wang, Zhiwei, Jiang, Liguang, Nielsen, Karina, and Wang, Lei
Abstract: Recent droughts have severely threatened water security in many regions worldwide. Reservoirs, designed to combat droughts and secure water supply partially, are reported failing to fill up to the total capacity due to severe droughts. How bad is climate affecting reservoir filling up on a global scale? This issue has not been studied. We present a big picture of reservoirs in crisis using satellite altimetry. Thanks to the unique characteristics of CryoSat-2, 525 reservoirs worldwide were investigated during 2010–2022. Results show that most reservoirs (93%) are found not fully filled up at least once. About 21% of reservoirs, which are mainly located in the Southern Hemisphere, show a significant decline in water levels. Moreover, about 20% of reservoirs with larger level fluctuations (>3 m) are located in less developed economies, indicating informed operation rules are needed. Further analyses indicate reservoirs are largely affected by extreme climate events, such as ENSO.
Published: 2024

3. A hydraulic model of the Amur River informed by ICESat-2 elevation

Author: Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, Jiang, Liguang, Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, and Jiang, Liguang
Abstract: Accurate predictions of water surface elevation (WSE) in rivers at high spatial and temporal resolution are important for flood/drought risk assessment and flood/drought forecasting and management. WSE in a river is controlled by three main factors: discharge, riverbed geometry, and hydraulic roughness. In remote and poorly instrumented rivers, discharge and riverbed geometry are highly uncertain and WSE is therefore hard to predict. ICESat-2 laser altimetry provides accurate elevation transects across the river at very high spatial resolution (70 cm along track). This paper demonstrates how ICESat-2 elevation transects can be used to parameterize a basin-scale hydraulic model of a continental-scale river. The workflow is demonstrated for the transboundary Amur River in North-East Asia. Simulated WSE is subsequently validated against a large dataset of in situ and satellite altimetry observations, and we demonstrate that the model can reproduce available WSE observations throughout the basin with an accuracy of 1–2 m.
Published: 2023

4. Stage-Slope-Discharge Relationships Upstream of River Confluences Revealed by Satellite Altimetry

Author: Liu, Jun, Bauer-Gottwein, Peter, Frias, Monica Coppo, Musaeus, Aske Folkmann, Christoffersen, Linda, Jiang, Liguang, Liu, Jun, Bauer-Gottwein, Peter, Frias, Monica Coppo, Musaeus, Aske Folkmann, Christoffersen, Linda, and Jiang, Liguang
Abstract: With increasing coverage, density, and accuracy of the global inland water altimetry record, remote sensing observations of water surface elevation (WSE) and water surface slope (WSS) are becoming available for the world's rivers. In steady, uniform flows, WSS is invariable, while there is a unique one-to-one relationship between WSE and discharge, the rating curve. While the assumptions of steady uniform flow are appropriate for many rivers, they are violated upstream of river confluences. We present a simple analytical hydraulic model of river confluences using the theory of steady, gradually varied flow. We apply the model to four river confluences in the Mississippi-Missouri river system. We determine the spatial extent of the backwater-affected zones and map WSE-discharge and WSS-discharge relationships. We show that coincident measurements of WSE and WSS from new satellite altimetry missions effectively constrain discharge estimates from space in the backwater-affected zones upstream of river confluences.
Published: 2023

5. River hydraulic modeling with ICESat-2 land and water surface elevation

Author: Coppo Frias, Monica, Liu, Suxia, Mo, Xingguo, Nielsen, Karina, Ranndal, Heidi, Jiang, Liguang, Ma, Jun, Bauer-Gottwein, Peter, Coppo Frias, Monica, Liu, Suxia, Mo, Xingguo, Nielsen, Karina, Ranndal, Heidi, Jiang, Liguang, Ma, Jun, and Bauer-Gottwein, Peter
Abstract: Advances in geodetic altimetry instruments are providing more accurate measurements, thus enabling satellite missions to produce useful data for narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation (WSE) measurements in remote areas where in situ data are scarce that can be combined with hydraulic and/or hydrodynamic models to simulate WSE and estimate discharge. In this study, we combine ICESat-2 (Ice, Cloud and land Elevation Satellite) land and water surface elevation measurements with a low-parameterized hydraulic calibration to simulate WSE and discharge without the need for surveyed cross-sectional geometry and a rainfall-runoff model. ICESat-2 provides an opportunity to map river cross-sectional geometry very accurately, with an along-Track resolution of 0.7ĝ€¯m, using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters such as river depth or the roughness coefficient. The low-parameterized model, together with the assumption of steady-state hydraulics, enables the application of a global search algorithm for a spatially uniform parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parameterized models, with a root mean square error (RMSE) of around 0.41ĝ€¯m. With the calibrated model, we can calculate the WSE time series at any chainage point at any time for an available satellite pass within the river reach and estimate discharge from WSE. The discharge estimates are validated with in situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation, resulting in a RMSE of 0.59ĝ€¯m for the entire observation period.
Published: 2023

6. Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets

Author: Zhang, Xingxing, Jiang, Liguang, Liu, Zhaofei, Kittel, Cecile M.M., Yao, Zhijun, Druce, Daniel, Wang, Rui, Tøttrup, Christian, Liu, Jun, Jiang, Hou, Bauer-Gottwein, Peter, Zhang, Xingxing, Jiang, Liguang, Liu, Zhaofei, Kittel, Cecile M.M., Yao, Zhijun, Druce, Daniel, Wang, Rui, Tøttrup, Christian, Liu, Jun, Jiang, Hou, and Bauer-Gottwein, Peter
Abstract: The flow regime change of rivers, especially transboundary rivers, affected by reservoir regulations is evident worldwide and has received much attention. Investigating dam-induced flow regime alterations is essential for understanding potential adverse downstream effects and facilitating dialogue around coordinated water use in transboundary basins, such as the Lancang River Basin (LRB). This study explored the value of combining several types of satellite Earth observation (EO) datasets that monitor different water balance components to constrain the parameter space of lumped conceptual hydrological models. Thus, we aimed to reconstruct the natural flow regimes upstream and downstream of the cascade reservoirs. Specifically, reservoir water storage changes were first estimated using satellite imagery and altimetry datasets. Then, storage changes were combined with hydrological model simulations of reservoir inflow to estimate the regulated flow regime downstream. Our results showed that integrated hydrological modeling combined with EO datasets exhibited better overall performance. Continuous warming and drying of the LRB resulted in a decrease in discharge of approximately 47 %. By comparing the simulated natural and regulated flow regimes, we revealed the pivotal role of the Xiaowan and Nuozhadu reservoirs in regulating natural flows. The wet season shortens (approximately 45 days), the flood peak flattens, and the low flow in the dry season has primarily increases. The two reservoirs attenuated 50 % of the flood peaks in the wet seasons and mitigated droughts by releasing up to 100 % of the natural flows in the dry seasons at the China–Laos border. Overall, these results enhance the understanding of upper reservoir operation, and the approaches can be applied to studies of dammed basins under climate change scenarios when knowledge of the upstream area is limited.
Published: 2023

7. Near real-time altimetry for river monitoring—a global assessment of Sentinel-3

Author: Jiang, Liguang, Zhao, Yanan, Nielsen, Karina, Andersen, Ole B., Bauer-Gottwein, Peter, Jiang, Liguang, Zhao, Yanan, Nielsen, Karina, Andersen, Ole B., and Bauer-Gottwein, Peter
Abstract: For applications such as weather, flood, and drought forecasting that need water level estimates as soon as possible, near real-time (NRT) products are most appropriate. Unlike in-situ sensors for water level measurements, which typically deliver NRT data, satellite altimeters deliver physically meaningful observations with substantial delays after acquisition. The new radar altimetry mission, Sentinel-3, is capable of delivering NRT water levels within a few hours of observation. Currently, it remains unexplored how accurate the NRT product is in the context of river monitoring. This study assesses Sentinel-3A/B NRT products in mapping river water level variations globally. Based on a three-year comparison, we find that the water level derived from NRT is almost as good as that from the delayed products (median root-mean-square error (RMSE): 21.5 cm and 23.5 for S3A and S3B), and both products achieve very similar RMSE values (median: 52.5 cm and 59.0 cm for NRT and non-time critical) against in-situ data at 25 locations. This study highlights the usefulness of Sentinel-3 NRT product for river monitoring and forecasting. And we recommend the NRT product if latency is a primary concern.
Published: 2023

8. A hydraulic model of the Amur River informed by ICESat-2 elevation

Author: Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, Jiang, Liguang, Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, and Jiang, Liguang
Abstract: Accurate predictions of water surface elevation (WSE) in rivers at high spatial and temporal resolution are important for flood/drought risk assessment and flood/drought forecasting and management. WSE in a river is controlled by three main factors: discharge, riverbed geometry, and hydraulic roughness. In remote and poorly instrumented rivers, both discharge and riverbed geometry are highly uncertain and WSE is therefore hard to predict. ICESat-2 laser altimetry provides accurate elevation transects across the river at very high spatial resolution (70 cm along track). This paper demonstrates how ICESat-2 elevation transects can be used to parameterize a basin-scale hydraulic model of a continental-scale river. The workflow is demonstrated for the transboundary Amur River in North-East Asia. Simulated WSE is subsequently validated against a large dataset of in-situ and satellite altimetry observations and we demonstrate that the model can reproduce available WSE observations throughout the basin with an accuracy of 1-2 meters.
Published: 2023

9. Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets

Author: Zhang, Xingxing, Jiang, Liguang, Liu, Zhaofei, Kittel, Cecile M.M., Yao, Zhijun, Druce, Daniel, Wang, Rui, Tøttrup, Christian, Liu, Jun, Jiang, Hou, Bauer-Gottwein, Peter, Zhang, Xingxing, Jiang, Liguang, Liu, Zhaofei, Kittel, Cecile M.M., Yao, Zhijun, Druce, Daniel, Wang, Rui, Tøttrup, Christian, Liu, Jun, Jiang, Hou, and Bauer-Gottwein, Peter
Abstract: The flow regime change of rivers, especially transboundary rivers, affected by reservoir regulations is evident worldwide and has received much attention. Investigating dam-induced flow regime alterations is essential for understanding potential adverse downstream effects and facilitating dialogue around coordinated water use in transboundary basins, such as the Lancang River Basin (LRB). This study explored the value of combining several types of satellite Earth observation (EO) datasets that monitor different water balance components to constrain the parameter space of lumped conceptual hydrological models. Thus, we aimed to reconstruct the natural flow regimes upstream and downstream of the cascade reservoirs. Specifically, reservoir water storage changes were first estimated using satellite imagery and altimetry datasets. Then, storage changes were combined with hydrological model simulations of reservoir inflow to estimate the regulated flow regime downstream. Our results showed that integrated hydrological modeling combined with EO datasets exhibited better overall performance. Continuous warming and drying of the LRB resulted in a decrease in discharge of approximately 47 %. By comparing the simulated natural and regulated flow regimes, we revealed the pivotal role of the Xiaowan and Nuozhadu reservoirs in regulating natural flows. The wet season shortens (approximately 45 days), the flood peak flattens, and the low flow in the dry season has primarily increases. The two reservoirs attenuated 50 % of the flood peaks in the wet seasons and mitigated droughts by releasing up to 100 % of the natural flows in the dry seasons at the China–Laos border. Overall, these results enhance the understanding of upper reservoir operation, and the approaches can be applied to studies of dammed basins under climate change scenarios when knowledge of the upstream area is limited.
Published: 2023

10. Near real-time altimetry for river monitoring—a global assessment of Sentinel-3

Author: Jiang, Liguang, Zhao, Yanan, Nielsen, Karina, Andersen, Ole B, Bauer-Gottwein, Peter, Jiang, Liguang, Zhao, Yanan, Nielsen, Karina, Andersen, Ole B, and Bauer-Gottwein, Peter
Abstract: For applications such as weather, flood, and drought forecasting that need water level estimates as soon as possible, near real-time (NRT) products are most appropriate. Unlike in-situ sensors for water level measurements, which typically deliver NRT data, satellite altimeters deliver physically meaningful observations with substantial delays after acquisition. The new radar altimetry mission, Sentinel-3, is capable of delivering NRT water levels within a few hours of observation. Currently, it remains unexplored how accurate the NRT product is in the context of river monitoring. This study assesses Sentinel-3A/B NRT products in mapping river water level variations globally. Based on a three-year comparison, we find that the water level derived from NRT is almost as good as that from the delayed products (median root-mean-square error (RMSE): 21.5 cm and 23.5 for S3A and S3B), and both products achieve very similar RMSE values (median: 52.5 cm and 59.0 cm for NRT and non-time critical) against in-situ data at 25 locations. This study highlights the usefulness of Sentinel-3 NRT product for river monitoring and forecasting. And we recommend the NRT product if latency is a primary concern.
Published: 2023

11. A hydraulic model of the Amur River informed by ICESat-2 elevation

Author: Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, Jiang, Liguang, Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, and Jiang, Liguang
Abstract: Accurate predictions of water surface elevation (WSE) in rivers at high spatial and temporal resolution are important for flood/drought risk assessment and flood/drought forecasting and management. WSE in a river is controlled by three main factors: discharge, riverbed geometry, and hydraulic roughness. In remote and poorly instrumented rivers, discharge and riverbed geometry are highly uncertain and WSE is therefore hard to predict. ICESat-2 laser altimetry provides accurate elevation transects across the river at very high spatial resolution (70 cm along track). This paper demonstrates how ICESat-2 elevation transects can be used to parameterize a basin-scale hydraulic model of a continental-scale river. The workflow is demonstrated for the transboundary Amur River in North-East Asia. Simulated WSE is subsequently validated against a large dataset of in situ and satellite altimetry observations, and we demonstrate that the model can reproduce available WSE observations throughout the basin with an accuracy of 1–2 m.
Published: 2023

12. A hydraulic model of the Amur River informed by ICESat-2 elevation

Author: Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, Jiang, Liguang, Bauer-Gottwein, Peter, Zakharova, Elena, Coppo Frías, Monica, Ranndal, Heidi, Nielsen, Karina, Christoffersen, Linda, Liu, Jun, and Jiang, Liguang
Abstract: Accurate predictions of water surface elevation (WSE) in rivers at high spatial and temporal resolution are important for flood/drought risk assessment and flood/drought forecasting and management. WSE in a river is controlled by three main factors: discharge, riverbed geometry, and hydraulic roughness. In remote and poorly instrumented rivers, discharge and riverbed geometry are highly uncertain and WSE is therefore hard to predict. ICESat-2 laser altimetry provides accurate elevation transects across the river at very high spatial resolution (70 cm along track). This paper demonstrates how ICESat-2 elevation transects can be used to parameterize a basin-scale hydraulic model of a continental-scale river. The workflow is demonstrated for the transboundary Amur River in North-East Asia. Simulated WSE is subsequently validated against a large dataset of in situ and satellite altimetry observations, and we demonstrate that the model can reproduce available WSE observations throughout the basin with an accuracy of 1–2 m.
Published: 2023

13. Stage-Slope-Discharge Relationships Upstream of River Confluences Revealed by Satellite Altimetry

Author: Liu, Jun, Bauer-Gottwein, Peter, Frias, Monica Coppo, Musaeus, Aske Folkmann, Christoffersen, Linda, Jiang, Liguang, Liu, Jun, Bauer-Gottwein, Peter, Frias, Monica Coppo, Musaeus, Aske Folkmann, Christoffersen, Linda, and Jiang, Liguang
Abstract: With increasing coverage, density, and accuracy of the global inland water altimetry record, remote sensing observations of water surface elevation (WSE) and water surface slope (WSS) are becoming available for the world's rivers. In steady, uniform flows, WSS is invariable, while there is a unique one-to-one relationship between WSE and discharge, the rating curve. While the assumptions of steady uniform flow are appropriate for many rivers, they are violated upstream of river confluences. We present a simple analytical hydraulic model of river confluences using the theory of steady, gradually varied flow. We apply the model to four river confluences in the Mississippi-Missouri river system. We determine the spatial extent of the backwater-affected zones and map WSE-discharge and WSS-discharge relationships. We show that coincident measurements of WSE and WSS from new satellite altimetry missions effectively constrain discharge estimates from space in the backwater-affected zones upstream of river confluences.
Published: 2023

14. River hydraulic modeling with ICESat-2 land and water surface elevation

Author: Coppo Frias, Monica, Liu, Suxia, Mo, Xingguo, Nielsen, Karina, Ranndal, Heidi, Jiang, Liguang, Ma, Jun, Bauer-Gottwein, Peter, Coppo Frias, Monica, Liu, Suxia, Mo, Xingguo, Nielsen, Karina, Ranndal, Heidi, Jiang, Liguang, Ma, Jun, and Bauer-Gottwein, Peter
Abstract: Advances in geodetic altimetry instruments are providing more accurate measurements, thus enabling satellite missions to produce useful data for narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation (WSE) measurements in remote areas where in situ data are scarce that can be combined with hydraulic and/or hydrodynamic models to simulate WSE and estimate discharge. In this study, we combine ICESat-2 (Ice, Cloud and land Elevation Satellite) land and water surface elevation measurements with a low-parameterized hydraulic calibration to simulate WSE and discharge without the need for surveyed cross-sectional geometry and a rainfall–runoff model. ICESat-2 provides an opportunity to map river cross-sectional geometry very accurately, with an along-track resolution of 0.7 m, using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters such as river depth or the roughness coefficient. The low-parameterized model, together with the assumption of steady-state hydraulics, enables the application of a global search algorithm for a spatially uniform parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parameterized models, with a root mean square error (RMSE) of around 0.41 m. With the calibrated model, we can calculate the WSE time series at any chainage point at any time for an available satellite pass within the river reach and estimate discharge from WSE. The discharge estimates are validated with in situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation, resulting in a RMSE of 0.59 m for the entire observation period.
Published: 2023

15. Spatio-temporally varying Strickler coefficient:A calibration approach applied to a Danish river using in-situ water surface elevation and UAS altimetry

Author: Liu, Jun, Jiang, Liguang, Bandini, Filippo, Kittel, Cecile M.M., Balbarini, Nicola, Hansted, Nisha G., Grosen, Henrik, Bauer-Gottwein, Peter, Liu, Jun, Jiang, Liguang, Bandini, Filippo, Kittel, Cecile M.M., Balbarini, Nicola, Hansted, Nisha G., Grosen, Henrik, and Bauer-Gottwein, Peter
Abstract: Hydraulic roughness (e.g., expressed in terms of Manning's or Strickler's coefficient) is an essential input to numerical hydrodynamic models. One way to estimate roughness parameters is by hydraulic inversion, using observed water surface elevation (WSE) collected from gauging stations, satellite platforms, or Unmanned Aerial System (UAS) altimeters. Specifically, UAS altimetry provides close to instantaneous observations of longitudinal profiles and seasonal variations of WSE for various river types, which are helpful for calibrating roughness parameters. However, it is computationally expensive to run high-resolution hydrodynamic models thousands to millions of times as required for the global optimization of distributed parameter sets (e.g., spatio-temporally varying river roughness). This study presents an efficient calibration approach for hydrodynamic models using a simplified steady-state hydraulic solver, UAS altimetry datasets, and in-situ observations. The calibration approach minimized the weighted sum of a misfit term, spatial smoothness penalty, and an a-priori sinusoidal temporal variation constraint. The approach was first demonstrated for several synthetic calibration experiments, and the results indicated that the global search algorithm accurately recovered the variations of Strickler coefficient (Ks) for short river reaches in temporal (due to the seasonal growth cycle of the aquatic vegetation) and spatial (e.g., due to spatially variable density of submerged vegetation) scales. Subsequently, the calibration approach was demonstrated for a real WSE dataset collected at a Danish test site (Vejle Å). In this river, friction is dominated by submerged vegetation growing in the stream and shows strong seasonal and longitudinal variations due to the plant growth cycle and variable vegetation density and species composition. Results indicated that spatio-temporal variation of Ks was required to fit in-situ observations and UAS
Published: 2022

16. High-resolution water level and storage variation datasets for 338 reservoirs in China during 2010-2021

Author: Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Nielsen, Karina, Yin, Jiabo, Liu, Jun, Bauer-Gottwein, Peter, Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Nielsen, Karina, Yin, Jiabo, Liu, Jun, and Bauer-Gottwein, Peter
Abstract: Reservoirs and dams are essential infrastructure in water management; thus, information of their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) is crucial for understanding their properties and interactions in hydrological and biogeochemical cycles. However, knowledge of these reservoir characteristics is scarce or inconsistent at the national scale. Here, we introduce comprehensive reservoir datasets of 338 reservoirs in China, with a total of 470.6km3 storage capacity (50% Chinese reservoir storage capacity). Given the scarcity of publicly available gauged observations and operational applications of satellites for hydrological cycles, we utilize multiple satellite altimetry missions (SARAL/AltiKa, Sentinel-3A and Sentinel-3B, CroySat-2, Jason-3, and ICESat-2) and imagery data from Landsat and Sentinel-2 to produce a comprehensive reservoir dataset on the WSE, SWA, and RWSC during 2010-2021. Validation against gauged measurements of 93 reservoirs demonstrates the relatively high accuracy and reliability of our remotely sensed datasets. (1) Across gauge comparisons of RWSC, the median statistics of the Pearson correlation coefficient (CC), normalized root mean square error (NRMSE), and root mean square error (RMSE) are 0.89, 11%, and 0.021km3, with a total of 91% validated reservoirs (83 of 91) having good RMSE from 0.002 to 0.31km3 and NRMSE values smaller than 20%. (2) Comparisons of WSE retracked by six satellite altimeters and gauges show good agreement. Specifically, the percentages of reservoirs having good and moderate RMSE values smaller than 1.0m for CryoSat-2 (validated in 30 reservoirs), SARAL/AltiKa (9), Sentinel-3A (34), Sentinel-3B (25), Jason-3 (11), and ICESat-2 (26) are 77%, 75%, 79%, 87%, 81%, and 82%, respectively. By taking advantages of six satellite altimeters, we are able to densify WSE observations across spatiotemporal scales. Statistically, around 96% of validated reservoirs (71 of 74)
Published: 2022

17. Estimating Reservoir Release Using Multi‐Source Satellite Datasets and Hydrological Modeling Techniques

Author: Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Tøttrup, Christian, Druce, Daniel, Yin, Jiabo, Nielsen, Karina, Bauer‐gottwein, Peter, Wang, Jun, Zhao, Xin, Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Tøttrup, Christian, Druce, Daniel, Yin, Jiabo, Nielsen, Karina, Bauer‐gottwein, Peter, Wang, Jun, and Zhao, Xin
Abstract: Reservoir release is an essential variable as it affects hydrological processes and water availability downstream. This study aims to estimate reservoir release using a satellite‐based approach, specially focusing on the impacts of inflow simulations and reservoir water storage change (RWSC) on release estimates. Ten inflow simulations based on hydrological models and blending schemes are used in combination with three RWSC estimates based on two satellite‐based approaches. A case study is performed at the Ankang reservoir, China. The results demonstrate that release estimates show high skill, with normalized root‐mean‐square error (NRMSE) less than 0.12 and Kling‐Gupta Efficiency (KGE) over 0.65. The performance of release estimates is varying with and influenced by inflow simulations and RWSC estimates, with NRMSE ranging from 0.09–0.12 and KGE from 0.65–0.74. Based on time‐varying Bayesian Model Averaging (BMA) approaches and synthetic aperture radar (SAR) satellite datasets, more accurate inflow and RWSC estimates can be obtained, thus facilitating substantially release estimates. With multi‐source satellite datasets, temporal scale of reservoir estimates is increased (monthly and bi‐weekly), acting as a key supplement to in situ records. Overall, this study explores the possibility to reconstruct and facilitate reservoir release estimates in poorly gauged dammed basins using hydrological modeling techniques and multi‐source satellite datasets.
Published: 2022

18. Spatio-temporally varying Strickler coefficient:A calibration approach applied to a Danish river using in-situ water surface elevation and UAS altimetry

Author: Liu, Jun, Jiang, Liguang, Bandini, Filippo, Kittel, Cecile M.M., Balbarini, Nicola, Hansted, Nisha G., Grosen, Henrik, Bauer-Gottwein, Peter, Liu, Jun, Jiang, Liguang, Bandini, Filippo, Kittel, Cecile M.M., Balbarini, Nicola, Hansted, Nisha G., Grosen, Henrik, and Bauer-Gottwein, Peter
Published: 2022

19. High-resolution water level and storage variation datasets for 338 reservoirs in China during 2010-2021

Author: Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Nielsen, Karina, Yin, Jiabo, Liu, Jun, Bauer-Gottwein, Peter, Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Nielsen, Karina, Yin, Jiabo, Liu, Jun, and Bauer-Gottwein, Peter
Abstract: Reservoirs and dams are essential infrastructure in water management; thus, information of their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) is crucial for understanding their properties and interactions in hydrological and biogeochemical cycles. However, knowledge of these reservoir characteristics is scarce or inconsistent at the national scale. Here, we introduce comprehensive reservoir datasets of 338 reservoirs in China, with a total of 470.6 km3 storage capacity (50% Chinese reservoir storage capacity). Given the scarcity of publicly available gauged observations and operational applications of satellites for hydrological cycles, we utilize multiple satellite altimetry missions (SARAL/AltiKa, Sentinel-3A and Sentinel-3B, CroySat-2, Jason-3, and ICESat-2) and imagery data from Landsat and Sentinel-2 to produce a comprehensive reservoir dataset on the WSE, SWA, and RWSC during 2010-2021. Validation against gauged measurements of 93 reservoirs demonstrates the relatively high accuracy and reliability of our remotely sensed datasets. (1) Across gauge comparisons of RWSC, the median statistics of the Pearson correlation coefficient (CC), normalized root mean square error (NRMSE), and root mean square error (RMSE) are 0.89, 11%, and 0.021 km3, with a total of 91% validated reservoirs (83 of 91) having good RMSE from 0.002 to 0.31 km3 and NRMSE values smaller than 20%. (2) Comparisons of WSE retracked by six satellite altimeters and gauges show good agreement. Specifically, the percentages of reservoirs having good and moderate RMSE values smaller than 1.0m for CryoSat-2 (validated in 30 reservoirs), SARAL/AltiKa (9), Sentinel-3A (34), Sentinel-3B (25), Jason-3 (11), and ICESat-2 (26) are 77%, 75%, 79%, 87%, 81%, and 82%, respectively. By taking advantages of six satellite altimeters, we are able to densify WSE observations across spatiotemporal scales. Statistically, around 96% o
Published: 2022

20. Estimating Reservoir Release Using Multi‐Source Satellite Datasets and Hydrological Modeling Techniques

Author: Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Tøttrup, Christian, Druce, Daniel, Yin, Jiabo, Nielsen, Karina, Bauer‐gottwein, Peter, Wang, Jun, Zhao, Xin, Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Tøttrup, Christian, Druce, Daniel, Yin, Jiabo, Nielsen, Karina, Bauer‐gottwein, Peter, Wang, Jun, and Zhao, Xin
Abstract: Reservoir release is an essential variable as it affects hydrological processes and water availability downstream. This study aims to estimate reservoir release using a satellite‐based approach, specially focusing on the impacts of inflow simulations and reservoir water storage change (RWSC) on release estimates. Ten inflow simulations based on hydrological models and blending schemes are used in combination with three RWSC estimates based on two satellite‐based approaches. A case study is performed at the Ankang reservoir, China. The results demonstrate that release estimates show high skill, with normalized root‐mean‐square error (NRMSE) less than 0.12 and Kling‐Gupta Efficiency (KGE) over 0.65. The performance of release estimates is varying with and influenced by inflow simulations and RWSC estimates, with NRMSE ranging from 0.09–0.12 and KGE from 0.65–0.74. Based on time‐varying Bayesian Model Averaging (BMA) approaches and synthetic aperture radar (SAR) satellite datasets, more accurate inflow and RWSC estimates can be obtained, thus facilitating substantially release estimates. With multi‐source satellite datasets, temporal scale of reservoir estimates is increased (monthly and bi‐weekly), acting as a key supplement to in situ records. Overall, this study explores the possibility to reconstruct and facilitate reservoir release estimates in poorly gauged dammed basins using hydrological modeling techniques and multi‐source satellite datasets.
Published: 2022

21. Sentinel-3 radar altimetry for river monitoring - A catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B

Author: Kittel, Cecile M.M., Jiang, Liguang, Tøttrup, Christian, Bauer-Gottwein, Peter, Kittel, Cecile M.M., Jiang, Liguang, Tøttrup, Christian, and Bauer-Gottwein, Peter
Abstract: Sentinel-3 is the first satellite altimetry mission to operate both in synthetic aperture radar (SAR) mode and in open-loop tracking mode nearly globally. Both features are expected to improve the ability of the altimeters to observe inland water bodies. Additionally, the two-satellite constellation offers a unique compromise between spatial and temporal resolution with over 65 000 potential water targets sensed globally. In this study, we evaluate the possibility of extracting river water surface elevation (WSE) at catchment level from Sentinel-3A and Sentinel-3B radar altimetry using Level-1b and Level-2 data from two public platforms: the Copernicus Open Access Hub (SciHub) and Grid Processing on Demand (GPOD). The objectives of the study are to demonstrate that by using publicly available processing platforms, such databases can be created to suit specific study areas for any catchment and with a wide range of applications in hydrology. We select the Zambezi River as a study area. In the Zambezi basin, 156 virtual stations (VSs) contain useful WSE information in both datasets. The root-mean-square deviation (RMSD) is between 2.9 and 31.3 cm at six VSs, where in situ data are available, and all VSs reflect the observed WSE climatology throughout the basin. Some VSs are exclusive to either the SciHub or GPOD datasets, highlighting the value of considering multiple processing options beyond global altimetry-based WSE databases. In particular, we show that the processing options available on GPOD affect the number of useful VSs; specifically, extending the size of the receiving window considerably improved data at 13 Sentinel-3 VSs. This was largely related to the implementation of GPOD parameters. While correct on-board elevation information is crucial, the postprocessing options must be adapted to handle the steep changes in the receiving window position. Finally, we extract Sentinel-3 observations over key wetlands in the Zambezi basin. We show that clear seas
Published: 2021

22. Calibrating 1D hydrodynamic river models in the absence of cross-section geometry using satellite observations of water surface elevation and river width

Author: Jiang, Liguang, Westphal Christensen, Silja, Bauer-Gottwein, Peter, Jiang, Liguang, Westphal Christensen, Silja, and Bauer-Gottwein, Peter
Abstract: Hydrodynamic modeling has been increasingly used to simulate water surface elevation which is important for flood prediction and risk assessment. Scarcity and inaccessibility of in situ bathymetric information have hindered hydrodynamic model development at continental-to-global scales. Therefore, river cross-section geometry is commonly approximated by highly simplified generic shapes. Hydrodynamic river models require both bed geometry and roughness as input parameters. Simultaneous calibration of shape parameters and roughness is difficult, because often there are trade-offs between them. Instead of parameterizing cross-section geometry and hydraulic roughness separately, this study introduces a parameterization of 1D hydrodynamic models by combining cross-section geometry and roughness into one conveyance parameter. Flow area and conveyance are expressed as power laws of flow depth, and they are found to be linearly related in log-log space at reach scale. Data from a wide range of river systems show that the linearity approximation is globally applicable. Because the two are expressed as power laws of flow depth, no further assumptions about channel geometry are needed. Therefore, the hydraulic inversion approach allows for calibrating flow area and conveyance curves in the absence of direct observations of bathymetry and hydraulic roughness. The feasibility and performance of the hydraulic inversion workflow are illustrated using satellite observations of river width and water surface elevation in the Songhua river, China. Results show that this approach is able to reproduce water level dynamics with root-mean-square error values of 0.44 and 0.50m at two gauging stations, which is comparable to that achieved using a standard calibration approach. In summary, this study puts forward an alternative method to parameterize and calibrate river models using satellite observations of river width and water surface elevation.
Published: 2021

23. Impacts of water resources management on land water storage in the North China Plain:Insights from multi-mission earth observations

Author: Liu, Jun, Jiang, Liguang, Zhang, Xingxing, Druce, Daniel, Kittel, Cecile M.M., Tøttrup, Christian, Bauer-Gottwein, Peter, Liu, Jun, Jiang, Liguang, Zhang, Xingxing, Druce, Daniel, Kittel, Cecile M.M., Tøttrup, Christian, and Bauer-Gottwein, Peter
Abstract: Natural conditions of surface water bodies and groundwater aquifers in the North China Plain (NCP) have been altered to meet the ever-growing human water demands. Several water resources management measures have been implemented in recent decades to alleviate groundwater depletion, maintain ecological resilience, and sustain agricultural production. This study aims to investigate their impacts on land water storage, and thus obtain a picture of the spatio-temporal variation of water resources over the NCP. Based on multi-mission earth observation datasets, i.e., altimetry (Sentinel-3), synthetic aperture radar (SAR) and spectral imagery (Sentinel-1/2), gravimetry (GRACE/-FO), and microwave sensors (IMERG), as well as reanalysis datasets, we investigate surface water storage (SWS), soil moisture water storage (SMS), and total water storage (TWS) changes. Groundwater storage (GWS) change is subsequently estimated as the residual of the total storage equation. Results show that TWS declined significantly over the past decades (−1.04 ± 0.05 cm/yr in 2004 to 2020), while SMS rebounded after a decreasing trend from 2004 to 2014. The spatial pattern of TWS variations depicts a particularly severe depletion along provincial boundaries. The SWS dynamics reveal that the volumes of three major NCP reservoirs (Guanting, Miyun, and Danjiangkou) increased significantly since around 2014 when the operation of the South-to-North Water Diversion Middle Route project (SNWDP-MR) started. Moreover, GWS maintained a depletion rate of −1.05 ± 0.08 cm/yr during 2004–2014 over the whole NCP, while the depletion rate accelerated during 2015–2020 (−1.88 ± 0.38 cm/yr). We also found that the GWS depletion in Beijing (−1.20 ± 0.10 cm/yr during 2004–2014 and −0.79 ± 0.44 cm/yr during 2015–2020) and its surrounding areas has been lowered possibly because of the SNWDP-MR. This study shows how multi-mission satellite earth observation products can be combined to monitor water resources at a reg
Published: 2021

24. Altimetry for the future: Building on 25 years of progress

Author: Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Ablain, Michael, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barcelo-llull, Barbara, Barlier, Francois, Basu, Sujit, Bauer-gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jerome, Bercher, Nicolas, Berge-nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jerome, Boy, Francois, Boy, Jean-paul, Brachet, Cedric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stephane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-faye, Sophie, Cretaux, Jean-francois, Cyr, Frederic, D'Ovidio, Francesco, Darrozes, Jose, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-damien, Dettmering, Denise, Di Bella, Alessandro, Diaz-barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joel, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cedric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Gabriel Fernandez, Juan, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frederic, Frery, Marie-laure, Garcia, Pablo, Garcia-mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gomez-enri, Jesus, Gomez-navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Daniele, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idzanovic, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M. M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Selene Lago, Loreley, Lambin, Juliette, Lasson, Lea, Laurain, Olivier, Laxenaire, Remi, Lazaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-yves, Lebedev, Sergey, Leger, Fabien, Legresy, Benoit, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cecile, Marin, Frederic, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, Mcmillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Minster, Jean-francois, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Oie, Nino, Fernando, Loddo, Carolina Nogueira, Nous, Camille, Obligis, Estelle, Otosaka, Ines, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Etienne, De Leon, Sonia Ponce, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Rayna, Matthias, Remy, Elisabeth, Remy, Frederique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simon, Ryan, Barbara J., Salaun, Corinne, Sanchez-roman, Antonio, Sorensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C. K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Remi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, Luanne, Tintore, Joaquin, Tison, Celine, Tourain, Cedric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sebastien, Tsamados, Michel, Tseng, Kuo-hsin, Ubelmann, Clement, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, Zlotnicki, Victor, Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Ablain, Michael, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barcelo-llull, Barbara, Barlier, Francois, Basu, Sujit, Bauer-gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jerome, Bercher, Nicolas, Berge-nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jerome, Boy, Francois, Boy, Jean-paul, Brachet, Cedric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stephane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-faye, Sophie, Cretaux, Jean-francois, Cyr, Frederic, D'Ovidio, Francesco, Darrozes, Jose, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-damien, Dettmering, Denise, Di Bella, Alessandro, Diaz-barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joel, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cedric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Gabriel Fernandez, Juan, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frederic, Frery, Marie-laure, Garcia, Pablo, Garcia-mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gomez-enri, Jesus, Gomez-navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Daniele, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idzanovic, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M. M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Selene Lago, Loreley, Lambin, Juliette, Lasson, Lea, Laurain, Olivier, Laxenaire, Remi, Lazaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-yves, Lebedev, Sergey, Leger, Fabien, Legresy, Benoit, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cecile, Marin, Frederic, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, Mcmillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Minster, Jean-francois, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Oie, Nino, Fernando, Loddo, Carolina Nogueira, Nous, Camille, Obligis, Estelle, Otosaka, Ines, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Etienne, De Leon, Sonia Ponce, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Rayna, Matthias, Remy, Elisabeth, Remy, Frederique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simon, Ryan, Barbara J., Salaun, Corinne, Sanchez-roman, Antonio, Sorensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C. K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Remi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, Luanne, Tintore, Joaquin, Tison, Celine, Tourain, Cedric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sebastien, Tsamados, Michel, Tseng, Kuo-hsin, Ubelmann, Clement, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, and Zlotnicki, Victor
Abstract: In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other
Published: 2021
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25. Altimetry for the future: Building on 25 years of progress

Author: Abdalla, Saleh, Abdeh Kolahchi, Abdolnabi, Adusumilli, Susheel, Aich Bhowmick, Suchandra, Alou-Font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barceló-Llull, Bàrbara, Barlier, François, Basu, Sujit, Bauer-Gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jérôme, Bercher, Nicolas, Berge-Nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jérôme, Boy, François, Boy, Jean-Paul, Brachet, Cédric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stéphane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-Faye, Sophie, Crétaux, Jean-François, Cyr, Frederic, d’Ovidio, Francesco, Darrozes, José, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-Damien, Dettmering, Denise, Di Bella, Alessandro, Díaz-Barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joël, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cédric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Fernández, Juan Gabriel, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frédéric, Frery, Marie-laure, Garcia, Pablo, Garcia-Mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gómez-Enri, Jesús, Gómez-Navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Danièle, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idžanović, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M.M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Lago, Loreley Selene, Lambin, Juliette, Lasson, Léa, Laurain, Olivier, Laxenaire, Rémi, Lázaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-Yves, Lebedev, Sergey, Léger, Fabien, Legresy, Benoı̂t, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Makhoul Varona, Eduard, Manfredi, Cécile, Marin, Frédéric, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, McMillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Michaël, Ablain, Minster, Jean-François, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Øie, Niño, Fernando, Nogueira Loddo, Carolina, Noûs, Camille, Obligis, Estelle, Otosaka, Inès, Otten, Michiel, Oztunali Ozbahceci, Berguzar, P. Raj, Roshin, Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Étienne, Ponce de León, Sonia, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-Isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Raynal, Matthias, Remy, Elisabeth, Rémy, Frédérique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simón, Ryan, Barbara J., Salaün, Corinne, Sanchez-Roman, Antonio, Sandberg Sørensen, Louise, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C.K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Rémi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, LuAnne, Tintoré, Joaquín, Tison, Céline, Tourain, Cédric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sébastien, Tsamados, Michel, Tseng, Kuo-Hsin, Ubelmann, Clément, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Vinogradova Shiffer, Nadya, Visser, Pieter, Vivier, Frederic, Volkov, Denis, von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, Zlotnicki, Victor, Abdalla, Saleh, Abdeh Kolahchi, Abdolnabi, Adusumilli, Susheel, Aich Bhowmick, Suchandra, Alou-Font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barceló-Llull, Bàrbara, Barlier, François, Basu, Sujit, Bauer-Gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jérôme, Bercher, Nicolas, Berge-Nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jérôme, Boy, François, Boy, Jean-Paul, Brachet, Cédric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stéphane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-Faye, Sophie, Crétaux, Jean-François, Cyr, Frederic, d’Ovidio, Francesco, Darrozes, José, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-Damien, Dettmering, Denise, Di Bella, Alessandro, Díaz-Barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joël, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cédric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Fernández, Juan Gabriel, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frédéric, Frery, Marie-laure, Garcia, Pablo, Garcia-Mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gómez-Enri, Jesús, Gómez-Navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Danièle, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idžanović, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M.M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Lago, Loreley Selene, Lambin, Juliette, Lasson, Léa, Laurain, Olivier, Laxenaire, Rémi, Lázaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-Yves, Lebedev, Sergey, Léger, Fabien, Legresy, Benoı̂t, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Makhoul Varona, Eduard, Manfredi, Cécile, Marin, Frédéric, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, McMillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Michaël, Ablain, Minster, Jean-François, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Øie, Niño, Fernando, Nogueira Loddo, Carolina, Noûs, Camille, Obligis, Estelle, Otosaka, Inès, Otten, Michiel, Oztunali Ozbahceci, Berguzar, P. Raj, Roshin, Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Étienne, Ponce de León, Sonia, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-Isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Raynal, Matthias, Remy, Elisabeth, Rémy, Frédérique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simón, Ryan, Barbara J., Salaün, Corinne, Sanchez-Roman, Antonio, Sandberg Sørensen, Louise, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C.K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Rémi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, LuAnne, Tintoré, Joaquín, Tison, Céline, Tourain, Cédric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sébastien, Tsamados, Michel, Tseng, Kuo-Hsin, Ubelmann, Clément, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Vinogradova Shiffer, Nadya, Visser, Pieter, Vivier, Frederic, Volkov, Denis, von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, and Zlotnicki, Victor
Published: 2021

26. Altimetry for the future: Building on 25 years of progress

Author: Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Ablain, Michael, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barcelo-llull, Barbara, Barlier, Francois, Basu, Sujit, Bauer-gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jerome, Bercher, Nicolas, Berge-nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jerome, Boy, Francois, Boy, Jean-paul, Brachet, Cedric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stephane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-faye, Sophie, Cretaux, Jean-francois, Cyr, Frederic, D'Ovidio, Francesco, Darrozes, Jose, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-damien, Dettmering, Denise, Di Bella, Alessandro, Diaz-barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joel, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cedric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Gabriel Fernandez, Juan, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frederic, Frery, Marie-laure, Garcia, Pablo, Garcia-mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gomez-enri, Jesus, Gomez-navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Daniele, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idzanovic, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M. M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Selene Lago, Loreley, Lambin, Juliette, Lasson, Lea, Laurain, Olivier, Laxenaire, Remi, Lazaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-yves, Lebedev, Sergey, Leger, Fabien, Legresy, Benoit, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cecile, Marin, Frederic, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, Mcmillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Minster, Jean-francois, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Oie, Nino, Fernando, Loddo, Carolina Nogueira, Obligis, Estelle, Otosaka, Ines, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Etienne, De Leon, Sonia Ponce, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Rayna, Matthias, Remy, Elisabeth, Remy, Frederique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simon, Ryan, Barbara J., Salaun, Corinne, Sanchez-roman, Antonio, Sorensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C. K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Remi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, Luanne, Tintore, Joaquin, Tison, Celine, Tourain, Cedric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sebastien, Tsamados, Michel, Tseng, Kuo-hsin, Ubelmann, Clement, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, Zlotnicki, Victor, Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Ablain, Michael, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barcelo-llull, Barbara, Barlier, Francois, Basu, Sujit, Bauer-gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jerome, Bercher, Nicolas, Berge-nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jerome, Boy, Francois, Boy, Jean-paul, Brachet, Cedric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stephane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-faye, Sophie, Cretaux, Jean-francois, Cyr, Frederic, D'Ovidio, Francesco, Darrozes, Jose, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-damien, Dettmering, Denise, Di Bella, Alessandro, Diaz-barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joel, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cedric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Gabriel Fernandez, Juan, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frederic, Frery, Marie-laure, Garcia, Pablo, Garcia-mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gomez-enri, Jesus, Gomez-navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Daniele, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idzanovic, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M. M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Selene Lago, Loreley, Lambin, Juliette, Lasson, Lea, Laurain, Olivier, Laxenaire, Remi, Lazaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-yves, Lebedev, Sergey, Leger, Fabien, Legresy, Benoit, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cecile, Marin, Frederic, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, Mcmillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Minster, Jean-francois, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Oie, Nino, Fernando, Loddo, Carolina Nogueira, Obligis, Estelle, Otosaka, Ines, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Etienne, De Leon, Sonia Ponce, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Rayna, Matthias, Remy, Elisabeth, Remy, Frederique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simon, Ryan, Barbara J., Salaun, Corinne, Sanchez-roman, Antonio, Sorensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C. K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Remi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, Luanne, Tintore, Joaquin, Tison, Celine, Tourain, Cedric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sebastien, Tsamados, Michel, Tseng, Kuo-hsin, Ubelmann, Clement, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, and Zlotnicki, Victor
Abstract: In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other
Published: 2021
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27. Altimetry for the future: Building on 25 years of progress

Author: Abdalla, Saleh, Abdeh Kolahchi, Abdolnabi, Adusumilli, Susheel, Aich Bhowmick, Suchandra, Alou-Font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barceló-Llull, Bàrbara, Barlier, François, Basu, Sujit, Bauer-Gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jérôme, Bercher, Nicolas, Berge-Nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jérôme, Boy, François, Boy, Jean-Paul, Brachet, Cédric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stéphane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-Faye, Sophie, Crétaux, Jean-François, Cyr, Frederic, d’Ovidio, Francesco, Darrozes, José, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-Damien, Dettmering, Denise, Di Bella, Alessandro, Díaz-Barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joël, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cédric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Fernández, Juan Gabriel, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frédéric, Frery, Marie-laure, Garcia, Pablo, Garcia-Mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gómez-Enri, Jesús, Gómez-Navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Danièle, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idžanović, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M.M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Lago, Loreley Selene, Lambin, Juliette, Lasson, Léa, Laurain, Olivier, Laxenaire, Rémi, Lázaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-Yves, Lebedev, Sergey, Léger, Fabien, Legresy, Benoı̂t, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Makhoul Varona, Eduard, Manfredi, Cécile, Marin, Frédéric, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, McMillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Michaël, Ablain, Minster, Jean-François, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Øie, Niño, Fernando, Nogueira Loddo, Carolina, Noûs, Camille, Obligis, Estelle, Otosaka, Inès, Otten, Michiel, Oztunali Ozbahceci, Berguzar, P. Raj, Roshin, Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Étienne, Ponce de León, Sonia, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-Isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Raynal, Matthias, Remy, Elisabeth, Rémy, Frédérique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simón, Ryan, Barbara J., Salaün, Corinne, Sanchez-Roman, Antonio, Sandberg Sørensen, Louise, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C.K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Rémi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, LuAnne, Tintoré, Joaquín, Tison, Céline, Tourain, Cédric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sébastien, Tsamados, Michel, Tseng, Kuo-Hsin, Ubelmann, Clément, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Vinogradova Shiffer, Nadya, Visser, Pieter, Vivier, Frederic, Volkov, Denis, von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, Zlotnicki, Victor, Abdalla, Saleh, Abdeh Kolahchi, Abdolnabi, Adusumilli, Susheel, Aich Bhowmick, Suchandra, Alou-Font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barceló-Llull, Bàrbara, Barlier, François, Basu, Sujit, Bauer-Gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jérôme, Bercher, Nicolas, Berge-Nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jérôme, Boy, François, Boy, Jean-Paul, Brachet, Cédric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stéphane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-Faye, Sophie, Crétaux, Jean-François, Cyr, Frederic, d’Ovidio, Francesco, Darrozes, José, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-Damien, Dettmering, Denise, Di Bella, Alessandro, Díaz-Barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joël, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cédric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Fernández, Juan Gabriel, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frédéric, Frery, Marie-laure, Garcia, Pablo, Garcia-Mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gómez-Enri, Jesús, Gómez-Navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Danièle, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idžanović, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M.M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Lago, Loreley Selene, Lambin, Juliette, Lasson, Léa, Laurain, Olivier, Laxenaire, Rémi, Lázaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-Yves, Lebedev, Sergey, Léger, Fabien, Legresy, Benoı̂t, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Makhoul Varona, Eduard, Manfredi, Cécile, Marin, Frédéric, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, McMillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Michaël, Ablain, Minster, Jean-François, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Øie, Niño, Fernando, Nogueira Loddo, Carolina, Noûs, Camille, Obligis, Estelle, Otosaka, Inès, Otten, Michiel, Oztunali Ozbahceci, Berguzar, P. Raj, Roshin, Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Étienne, Ponce de León, Sonia, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-Isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Raynal, Matthias, Remy, Elisabeth, Rémy, Frédérique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simón, Ryan, Barbara J., Salaün, Corinne, Sanchez-Roman, Antonio, Sandberg Sørensen, Louise, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C.K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Rémi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, LuAnne, Tintoré, Joaquín, Tison, Céline, Tourain, Cédric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sébastien, Tsamados, Michel, Tseng, Kuo-Hsin, Ubelmann, Clément, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Vinogradova Shiffer, Nadya, Visser, Pieter, Vivier, Frederic, Volkov, Denis, von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, and Zlotnicki, Victor
Published: 2021

28. Altimetry for the future: Building on 25 years of progress

Author: Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Ablain, Michael, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barcelo-llull, Barbara, Barlier, Francois, Basu, Sujit, Bauer-gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jerome, Bercher, Nicolas, Berge-nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jerome, Boy, Francois, Boy, Jean-paul, Brachet, Cedric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stephane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-faye, Sophie, Cretaux, Jean-francois, Cyr, Frederic, D'Ovidio, Francesco, Darrozes, Jose, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-damien, Dettmering, Denise, Di Bella, Alessandro, Diaz-barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joel, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cedric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Gabriel Fernandez, Juan, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frederic, Frery, Marie-laure, Garcia, Pablo, Garcia-mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gomez-enri, Jesus, Gomez-navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Daniele, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idzanovic, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M. M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Selene Lago, Loreley, Lambin, Juliette, Lasson, Lea, Laurain, Olivier, Laxenaire, Remi, Lazaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-yves, Lebedev, Sergey, Leger, Fabien, Legresy, Benoit, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cecile, Marin, Frederic, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, Mcmillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Minster, Jean-francois, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Oie, Nino, Fernando, Loddo, Carolina Nogueira, Obligis, Estelle, Otosaka, Ines, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Etienne, De Leon, Sonia Ponce, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Rayna, Matthias, Remy, Elisabeth, Remy, Frederique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simon, Ryan, Barbara J., Salaun, Corinne, Sanchez-roman, Antonio, Sorensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C. K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Remi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, Luanne, Tintore, Joaquin, Tison, Celine, Tourain, Cedric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sebastien, Tsamados, Michel, Tseng, Kuo-hsin, Ubelmann, Clement, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, Zlotnicki, Victor, Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Ablain, Michael, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barcelo-llull, Barbara, Barlier, Francois, Basu, Sujit, Bauer-gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jerome, Bercher, Nicolas, Berge-nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jerome, Boy, Francois, Boy, Jean-paul, Brachet, Cedric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stephane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-faye, Sophie, Cretaux, Jean-francois, Cyr, Frederic, D'Ovidio, Francesco, Darrozes, Jose, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-damien, Dettmering, Denise, Di Bella, Alessandro, Diaz-barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joel, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cedric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Gabriel Fernandez, Juan, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frederic, Frery, Marie-laure, Garcia, Pablo, Garcia-mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gomez-enri, Jesus, Gomez-navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Daniele, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idzanovic, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M. M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Selene Lago, Loreley, Lambin, Juliette, Lasson, Lea, Laurain, Olivier, Laxenaire, Remi, Lazaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-yves, Lebedev, Sergey, Leger, Fabien, Legresy, Benoit, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cecile, Marin, Frederic, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, Mcmillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Minster, Jean-francois, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Oie, Nino, Fernando, Loddo, Carolina Nogueira, Obligis, Estelle, Otosaka, Ines, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Etienne, De Leon, Sonia Ponce, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Rayna, Matthias, Remy, Elisabeth, Remy, Frederique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simon, Ryan, Barbara J., Salaun, Corinne, Sanchez-roman, Antonio, Sorensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C. K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Remi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, Luanne, Tintore, Joaquin, Tison, Celine, Tourain, Cedric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sebastien, Tsamados, Michel, Tseng, Kuo-hsin, Ubelmann, Clement, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, and Zlotnicki, Victor
Abstract: In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other
Published: 2021
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29. Altimetry for the future: Building on 25 years of progress

Author: Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-Font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barceló-Llull, Bàrbara, Barlier, François, Basu, Sujit, Bauer-Gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jérôme, Bercher, Nicolas, Berge-Nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jérôme, Boy, François, Boy, Jean-Paul, Brachet, Cédric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stéphane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-Faye, Sophie, Crétaux, Jean-François, Cyr, Frederic, d’Ovidio, Francesco, Darrozes, José, David, Cedric, Dayoub, Nadim, Staerke, Danielle De, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-Damien, Dettmering, Denise, Bella, Alessandro Di, Díaz-Barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joël, Drezen, Christine, Drinkwater, Mark, Penhoat, Yves Du, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cédric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Fernández, Juan Gabriel, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frédéric, Frery, Marie-laure, Garcia, Pablo, Garcia-Mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gómez-Enri, Jesús, Gómez-Navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Danièle, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idžanović, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M.M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Lago, Loreley Selene, Lambin, Juliette, Lasson, Léa, Laurain, Olivier, Laxenaire, Rémi, Lázaro, Clara, Gac, Sophie Le, Sommer, Julien Le, Traon, Pierre-Yves Le, Lebedev, Sergey, Léger, Fabien, Legresy, Benoı̂t, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cécile, Marin, Frédéric, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, McMillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Michaël, Ablain, Minster, Jean-François, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Øie, Niño, Fernando, Loddo, Carolina Nogueira, Noûs, Camille, Obligis, Estelle, Otosaka, Inès, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Étienne, León, Sonia Ponce de, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-Isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Raynal, Matthias, Remy, Elisabeth, Rémy, Frédérique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simón, Ryan, Barbara J., Salaün, Corinne, Sanchez-Roman, Antonio, Sørensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin, Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C.K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Rémi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, LuAnne, Tintoré, Joaquín, Tison, Céline, Tourain, Cédric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sébastien, Tsamados, Michel, Tseng, Kuo-Hsin, Ubelmann, Clément, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Schuckmann, Karina von, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, Zlotnicki, Victor, Abdalla, Saleh, Kolahchi, Abdolnabi Abdeh, Adusumilli, Susheel, Bhowmick, Suchandra Aich, Alou-Font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barceló-Llull, Bàrbara, Barlier, François, Basu, Sujit, Bauer-Gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jérôme, Bercher, Nicolas, Berge-Nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jérôme, Boy, François, Boy, Jean-Paul, Brachet, Cédric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stéphane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-Faye, Sophie, Crétaux, Jean-François, Cyr, Frederic, d’Ovidio, Francesco, Darrozes, José, David, Cedric, Dayoub, Nadim, Staerke, Danielle De, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-Damien, Dettmering, Denise, Bella, Alessandro Di, Díaz-Barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joël, Drezen, Christine, Drinkwater, Mark, Penhoat, Yves Du, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cédric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Fernández, Juan Gabriel, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frédéric, Frery, Marie-laure, Garcia, Pablo, Garcia-Mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gómez-Enri, Jesús, Gómez-Navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Danièle, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idžanović, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M.M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Lago, Loreley Selene, Lambin, Juliette, Lasson, Léa, Laurain, Olivier, Laxenaire, Rémi, Lázaro, Clara, Gac, Sophie Le, Sommer, Julien Le, Traon, Pierre-Yves Le, Lebedev, Sergey, Léger, Fabien, Legresy, Benoı̂t, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Varona, Eduard Makhoul, Manfredi, Cécile, Marin, Frédéric, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, McMillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Michaël, Ablain, Minster, Jean-François, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Øie, Niño, Fernando, Loddo, Carolina Nogueira, Noûs, Camille, Obligis, Estelle, Otosaka, Inès, Otten, Michiel, Ozbahceci, Berguzar Oztunali, Raj, Roshin P., Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Étienne, León, Sonia Ponce de, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-Isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Raynal, Matthias, Remy, Elisabeth, Rémy, Frédérique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simón, Ryan, Barbara J., Salaün, Corinne, Sanchez-Roman, Antonio, Sørensen, Louise Sandberg, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin, Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C.K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Rémi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, LuAnne, Tintoré, Joaquín, Tison, Céline, Tourain, Cédric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sébastien, Tsamados, Michel, Tseng, Kuo-Hsin, Ubelmann, Clément, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Shiffer, Nadya Vinogradova, Visser, Pieter, Vivier, Frederic, Volkov, Denis, Schuckmann, Karina von, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, and Zlotnicki, Victor
Abstract: In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other
Published: 2021

30. Calibrating 1D hydrodynamic river models in the absence of cross-section geometry using satellite observations of water surface elevation and river width

Author: Jiang, Liguang, Christensen, Silja Westphal, Bauer-Gottwein, Peter, Jiang, Liguang, Christensen, Silja Westphal, and Bauer-Gottwein, Peter
Abstract: Hydrodynamic modeling has been increasingly used to simulate water surface elevation which is important for flood prediction and risk assessment. Scarcity and inaccessibility of in situ bathymetric information have hindered hydrodynamic model development at continental-to-global scales. Therefore, river cross-section geometry is commonly approximated by highly simplified generic shapes. Hydrodynamic river models require both bed geometry and roughness as input parameters. Simultaneous calibration of shape parameters and roughness is difficult, because often there are trade-offs between them. Instead of parameterizing cross-section geometry and hydraulic roughness separately, this study introduces a parameterization of 1D hydrodynamic models by combining cross-section geometry and roughness into one conveyance parameter. Flow area and conveyance are expressed as power laws of flow depth, and they are found to be linearly related in log-log space at reach scale. Data from a wide range of river systems show that the linearity approximation is globally applicable. Because the two are expressed as power laws of flow depth, no further assumptions about channel geometry are needed. Therefore, the hydraulic inversion approach allows for calibrating flow area and conveyance curves in the absence of direct observations of bathymetry and hydraulic roughness. The feasibility and performance of the hydraulic inversion workflow are illustrated using satellite observations of river width and water surface elevation in the Songhua river, China. Results show that this approach is able to reproduce water level dynamics with root-mean-square error values of 0.44 and 0.50 m at two gauging stations, which is comparable to that achieved using a standard calibration approach. In summary, this study puts forward an alternative method to parameterize and calibrate river models using satellite observations of river width and water surface elevation.
Published: 2021

31. Impacts of water resources management on land water storage in the North China Plain:Insights from multi-mission earth observations

Author: Liu, Jun, Jiang, Liguang, Zhang, Xingxing, Druce, Daniel, Kittel, Cecile M.M., Tøttrup, Christian, Bauer-Gottwein, Peter, Liu, Jun, Jiang, Liguang, Zhang, Xingxing, Druce, Daniel, Kittel, Cecile M.M., Tøttrup, Christian, and Bauer-Gottwein, Peter
Abstract: Natural conditions of surface water bodies and groundwater aquifers in the North China Plain (NCP) have been altered to meet the ever-growing human water demands. Several water resources management measures have been implemented in recent decades to alleviate groundwater depletion, maintain ecological resilience, and sustain agricultural production. This study aims to investigate their impacts on land water storage, and thus obtain a picture of the spatio-temporal variation of water resources over the NCP. Based on multi-mission earth observation datasets, i.e., altimetry (Sentinel-3), synthetic aperture radar (SAR) and spectral imagery (Sentinel-1/2), gravimetry (GRACE/-FO), and microwave sensors (IMERG), as well as reanalysis datasets, we investigate surface water storage (SWS), soil moisture water storage (SMS), and total water storage (TWS) changes. Groundwater storage (GWS) change is subsequently estimated as the residual of the total storage equation.Results show that TWS declined significantly over the past decades (−1.04 ± 0.05 cm/yr in 2004 to 2020), while SMS rebounded after a decreasing trend from 2004 to 2014. The spatial pattern of TWS variations depicts a particularly severe depletion along provincial boundaries. The SWS dynamics reveal that the volumes of three major NCP reservoirs (Guanting, Miyun, and Danjiangkou) increased significantly since around 2014 when the operation of the South-to-North Water Diversion Middle Route project (SNWDP-MR) started. Moreover, GWS maintained a depletion rate of −1.05 ± 0.08 cm/yr during 2004–2014 over the whole NCP, while the depletion rate accelerated during 2015–2020 (−1.88 ± 0.38 cm/yr). We also found that the GWS depletion in Beijing (−1.20 ± 0.10 cm/yr during 2004–2014 and −0.79 ± 0.44 cm/yr during 2015–2020) and its surrounding areas has been lowered possibly because of the SNWDP-MR. This study shows how multi-mission satellite earth observation products can be combined to monitor water resources at
Published: 2021

32. Polar Drift in the 1990s Explained by Terrestrial Water Storage Changes

Author: Deng, S., Liu, Sihang, Mo, X., Jiang, Liguang, Bauer‐Gottwein, Peter, Deng, S., Liu, Sihang, Mo, X., Jiang, Liguang, and Bauer‐Gottwein, Peter
Abstract: Secular polar drift underwent a directional change in the 1990s, but the underlying mechanism remains unclear. In this study, polar motion observations are compared with geophysical excitations from the atmosphere, oceans, solid Earth, and terrestrial water storage (TWS) during the period of 1981–2020 to determine major drivers. When contributions from the atmosphere, oceans, and solid Earth are removed, the residual dominates the change in the 1990s. The contribution of TWS to the residual is quantified by comparing the hydrological excitations from modeled TWS changes in two different scenarios. One scenario assumes that the TWS change is stationary over the entire study period, and another scenario corrects the stationary result with actual glacier mass change. The accelerated ice melting over major glacial areas drives the polar drift toward 26°E for 3.28 mas/yr after the 1990s. The findings offer a clue for studying past climate‐driven polar motion.
Published: 2021

33. Sentinel-3 radar altimetry for river monitoring - A catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B

Author: Kittel, Cecile Marie Margaretha, Jiang, Liguang, Tøttrup, Christian, Bauer-Gottwein, Peter, Kittel, Cecile Marie Margaretha, Jiang, Liguang, Tøttrup, Christian, and Bauer-Gottwein, Peter
Abstract: Sentinel-3 is the first satellite altimetry mission to operate both in synthetic aperture radar (SAR) mode and in open-loop tracking mode nearly globally. Both features are expected to improve the ability of the altimeters to observe inland water bodies. Additionally, the two-satellite constellation offers a unique compromise between spatial and temporal resolution with over 65 000 potential water targets sensed globally. In this study, we evaluate the possibility of extracting river water surface elevation (WSE) at catchment level from Sentinel-3A and Sentinel-3B radar altimetry using Level-1b and Level-2 data from two public platforms: the Copernicus Open Access Hub (SciHub) and Grid Processing on Demand (GPOD). The objectives of the study are to demonstrate that by using publicly available processing platforms, such databases can be created to suit specific study areas for any catchment and with a wide range of applications in hydrology. We select the Zambezi River as a study area. In the Zambezi basin, 156 virtual stations (VSs) contain useful WSE information in both datasets. The root-mean-square deviation (RMSD) is between 2.9 and 31.3 cm at six VSs, where in situ data are available, and all VSs reflect the observed WSE climatology throughout the basin. Some VSs are exclusive to either the SciHub or GPOD datasets, highlighting the value of considering multiple processing options beyond global altimetry-based WSE databases. In particular, we show that the processing options available on GPOD affect the number of useful VSs; specifically, extending the size of the receiving window considerably improved data at 13 Sentinel-3 VSs. This was largely related to the implementation of GPOD parameters. While correct on-board elevation information is crucial, the postprocessing options must be adapted to handle the steep changes in the receiving window position. Finally, we extract Sentinel-3 observations over key wetlands in the Zambezi basin. We show that clear seasona
Published: 2021

34. A Bigger Picture of how the Tibetan Lakes Have Changed Over the Past Decade Revealed by CryoSat-2 Altimetry

Author: Jiang, Liguang, Nielsen, Karina, Andersen, Ole B., Bauer-Gottwein, Peter, Jiang, Liguang, Nielsen, Karina, Andersen, Ole B., and Bauer-Gottwein, Peter
Abstract: Tibetan lakes are an effective indicator of climate change as they are highly sensitive to and directly affected by climate change. The past decade has seen the seven warmest years on record globally. Such observations have prompted questions about lake changes over the Tibetan Plateau. The dense coverage of the CryoSat-2 altimeter reveals large-scale patterns in this climate change signal. We investigate lake level variations of more than 200 lakes using altimetry observations from CryoSat-2 during the period 2010 to 2019. Combined with GRACE/GRACE-FO, we evaluate the water storage change of lakes and terrestrial water storage (TWS). We find that most studied lakes generally went through three phases of change, that is, rising-hiatus/decline-rising, albeit lakes in the north Tibetan Plateau, show higher rising rates. Results also show that lake levels are widely affected by the 2015/16 El Niño event across the entire Inner Plateau via reduced precipitation. Above normal precipitation during 2016–2018, resulted in a sharp rise of ~1.22 m on average, accounting for 56% of the decadal lake level rise (mean/median: 2.19/1.85 m). TWS in the Inner Tibetan Plateau accumulated a net gain of 70.5 km3, which is dominated by the net gain of lake water storage (ca. 63.3 km3). The interannual TWS variation is found to be associated mainly with precipitation. In particular, extreme conditions such as the 2015/16 El Niño, had a profound negative impact on the TWS. The findings in this study shed new light on the response of Tibetan lakes to recent decadal environmental changes.
Published: 2020

35. On the contribution of satellite altimetry-derived water surface elevation to hydrodynamic model calibration in the Han river

Author: Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Yin, Jiabo, Nielsen, Karina, Bauer-Gottwein, Peter, Guo, Shenglian, Wang, Jun, Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Yin, Jiabo, Nielsen, Karina, Bauer-Gottwein, Peter, Guo, Shenglian, and Wang, Jun
Abstract: Satellite altimetry can fill the spatial gaps of in-situ gauging networks especially in poorly gauged regions. Although at a generally low temporal resolution, satellite altimetry has been successfully used for water surface elevation (WSE) estimation and hydrodynamic modeling. This study aims to investigate the contribution of WSE from both short-repeat and geodetic altimetry to hydrodynamic model calibration, and also explore the contribution of the new Sentinel-3 mission. Two types of data sources (i.e., in-situ and satellite altimetry) are investigated together with two roughness cases (i.e., spatially variable and uniform roughness) for calibration of a hydrodynamic model (DHI MIKE 11) with available bathymetry. A 150 km long reach of Han River in China with rich altimetry and in-situ gauging data is selected as a case study. Results show that the performances of the model calibrated by satellite altimetry-derived datasets are acceptable in terms of Root Mean Square Error (RMSE) of simulated WSE. Sentinel-3A can support hydrodynamic model calibration even though it has a relatively low temporal resolution (27-day repeat cycle). The CryoSat-2 data with a higher spatial resolution (7.5 km at the Equator) are proved to be more valuable than the Sentinel-3A altimetry data with a low spatial resolution (104 km at the Equator) for hydrodynamic model calibration in terms of RMSE values of 0.16 and 0.18 m, respectively. Moreover, the spatially variable roughness can also improve the model performance compared to the uniform roughness case, with decreasing RMSE values by 2–14%. Our finding shows the value of satellite altimetry-derived datasets for hydrodynamic model calibration and therefore supports flood risk assessment and water resources management.
Published: 2020

36. The value of distributed high-resolution UAV-borne observations of water surface elevation for river management and hydrodynamic modeling

Author: Jiang, Liguang, Bandini, Filippo, Smith, Ole, Jensen, Inger Klint, Bauer-Gottwein, Peter, Jiang, Liguang, Bandini, Filippo, Smith, Ole, Jensen, Inger Klint, and Bauer-Gottwein, Peter
Abstract: Water level or water surface elevation (WSE) is an important state variable of rivers, lakes, and wetlands. Hydrodynamic models of rivers and streams simulate WSE and can benefit from spatially distributed WSE observations, to increase model reliability and predictive skill. This has been partially addressed by satellite radar altimetry, but satellite altimetry is unable to deliver useful data for small rivers. To overcome such limitations, we deployed a radar altimetry system on an unmanned aerial vehicle (UAV), to map spatially distributed WSE.We showed that UAV altimetry can provide observations of WSE with a very high spatial resolution (ca. 0.5 m) and accuracy (ca. 3 cm), in a time-saving and cost-effective way. Furthermore, we investigated the value of this dataset for the calibration and validation of hydrodynamic models. Specifically, we introduced spatially distributed roughness parameters in a hydrodynamic model and estimated these parameters, using the observed WSE profiles along the stream as input. A case study was conducted in the Åmose stream, Denmark. The results showed that UAV-borne WSE can identify significant variations of the Manning-Strickler coefficients, along this small and highly vegetated stream and over time. Moreover, the model performed extremely well using distributed roughness coefficients, but it could not reproduce WSE satisfactorily using uniform roughness. We concluded that distributed roughness coefficients should be considered, especially for small vegetated rivers, to improve model performance, both locally and globally. Spatially distributed parameterizations of the effective channel roughness could be constrained with UAV-borne WSE. This study demonstrated for the first time that UAV-borne WSE can help to understand the variations of hydraulic roughness, and can support efficient river management and maintenance.
Published: 2020

37. Response of Tibetan Plateau lakes to climate change - Trends, patterns, and mechanisms

Author: Zhang, Guoqing, Yao, Tandong, Xie, Hongjie, Yang, Kun, Zhu, Liping, Shum, C. K., Bolch, Tobias, Yi, Shuang, Allen, Simon, Jiang, Liguang, Chen, Wenfeng, Ke, Changqing, Zhang, Guoqing, Yao, Tandong, Xie, Hongjie, Yang, Kun, Zhu, Liping, Shum, C. K., Bolch, Tobias, Yi, Shuang, Allen, Simon, Jiang, Liguang, Chen, Wenfeng, and Ke, Changqing
Abstract: The wide distribution of natural lakes over the Tibetan Plateau, the highest and largest plateau on Earth, have received extensive attention due to global warming. In this Review, we examine lake evolution, spatial patterns and driving mechanisms over the Tibetan Plateau. The changes in lake area, level and volume show a slight decrease from 1976 to the mid-1990s, followed by a continuous rapid increase. The spatial patterns show an overall lake growth in the north of the inner plateau against a reduction in the south, which are accompanied by most of the lakes cooling in the north against warming in the south, and longer ice cover duration in the north compared with the south. The changes in lake temperature are negatively correlated with water level variations and lake ice duration. Enhanced precipitation is the dominant contributor to increased lake water storage, followed by glacier mass loss and permafrost thawing. The decadal or longer lake expansion since the mid-1990s could have been driven by the positive phase of Atlantic Multidecadal Oscillation, and clear inflection points of lake area/level identified in 1997/1998 and 2015/2016 are attributed to strong El Niño events. In the near-term, the lakes will continue to expand. Future interdisciplinary lake studies are urgently required to improve understanding of climate-cryosphere-hydrosphere interactions and water resources management.
Published: 2020

38. On the contribution of satellite altimetry-derived water surface elevation to hydrodynamic model calibration in the Han river

Author: Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Yin, Jiabo, Nielsen, Karina, Bauer-Gottwein, Peter, Guo, Shenglian, Wang, Jun, Shen, Youjiang, Liu, Dedi, Jiang, Liguang, Yin, Jiabo, Nielsen, Karina, Bauer-Gottwein, Peter, Guo, Shenglian, and Wang, Jun
Abstract: Satellite altimetry can fill the spatial gaps of in-situ gauging networks especially in poorly gauged regions. Although at a generally low temporal resolution, satellite altimetry has been successfully used for water surface elevation (WSE) estimation and hydrodynamic modeling. This study aims to investigate the contribution of WSE from both short-repeat and geodetic altimetry to hydrodynamic model calibration, and also explore the contribution of the new Sentinel-3 mission. Two types of data sources (i.e., in-situ and satellite altimetry) are investigated together with two roughness cases (i.e., spatially variable and uniform roughness) for calibration of a hydrodynamic model (DHI MIKE 11) with available bathymetry. A 150 km long reach of Han River in China with rich altimetry and in-situ gauging data is selected as a case study. Results show that the performances of the model calibrated by satellite altimetry-derived datasets are acceptable in terms of Root Mean Square Error (RMSE) of simulated WSE. Sentinel-3A can support hydrodynamic model calibration even though it has a relatively low temporal resolution (27-day repeat cycle). The CryoSat-2 data with a higher spatial resolution (7.5 km at the Equator) are proved to be more valuable than the Sentinel-3A altimetry data with a low spatial resolution (104 km at the Equator) for hydrodynamic model calibration in terms of RMSE values of 0.16 and 0.18 m, respectively. Moreover, the spatially variable roughness can also improve the model performance compared to the uniform roughness case, with decreasing RMSE values by 2–14%. Our finding shows the value of satellite altimetry-derived datasets for hydrodynamic model calibration and therefore supports flood risk assessment and water resources management.
Published: 2020

39. On the Performance of Sentinel‐3 Altimetry Over New Reservoirs: Approaches to Determine Onboard A Priori Elevation

Author: Zhang, Xingxing, Jiang, Liguang, Kittel, Cecile M. M., Yao, Zhijun, Nielsen, Karina, Liu, Zhaofei, Wang, Rui, Liu, Jun, Andersen, Ole B., Bauer‐Gottwein, Peter, Zhang, Xingxing, Jiang, Liguang, Kittel, Cecile M. M., Yao, Zhijun, Nielsen, Karina, Liu, Zhaofei, Wang, Rui, Liu, Jun, Andersen, Ole B., and Bauer‐Gottwein, Peter
Abstract: Satellite radar altimetry has become an important data source supplementing in situ water level. For practical reasons, a radar altimeter can only record reflected echoes within its range window. Therefore, water surface elevation must fall within the range window. To this end, the Sentinel‐3 radar altimetry mission is configured with a new tracking function (i.e., open loop) to position its range window based on an onboard a priori elevation of ground targets. We found that Sentinel‐3 is unable to observe recently built reservoirs due to the incorrect onboard elevations. To overcome this issue, four approaches are proposed to improve the a priori elevation for inland water bodies, particularly reservoirs. These approaches can significantly increase data availability of Sentinel‐3 over reservoirs and can be used to prepare the onboard elevations of reservoirs and lakes for future missions such as Sentinel‐6, Sentinel‐3C/‐3D, and the Surface Water and Ocean Topography (SWOT) mission.
Published: 2020

40. A bigger picture of how the Tibetan lakes change over the past decade revealed by CryoSat‐2 altimetry

Author: Jiang, Liguang, Nielsen, Karina, Andersen, Ole B., Bauer‐Gottwein, Peter, Jiang, Liguang, Nielsen, Karina, Andersen, Ole B., and Bauer‐Gottwein, Peter
Abstract: Tibetan lakes are an effective indicator of climate change as they are highly sensitive to and directly affected by climate change. The past decade has seen the 7 warmest years on record globally. Such observations have prompted questions about lake changes over the Tibetan Plateau. The dense coverage of the CryoSat‐2 altimeter reveals large‐scale patterns in this climate change signal. We investigate lake level variations of more than 200 lakes using altimetry observations from CryoSat‐2 during the period 2010 to 2019. Combined with GRACE/GRACE‐FO, we evaluate the water storage change of lakes and terrestrial water storage (TWS). We find that most studied lakes generally went through three phases of change, i.e. rising‐hiatus/decline‐rising, albeit lakes in the north Tibetan Plateau show higher rising rates. Results also show that lake levels are widely affected by the 2015/16 El Niño event across the entire inner plateau via reduced precipitation. Above normal precipitation during 2016‐2018, resulted in a sharp rise of ~1.22 m on average, accounting for 56% of the decadal lake level rise (mean/median: 2.19/1.85 m). TWS in the Inner Tibetan Plateau accumulated a net gain of 70.5 km3, which is dominated by the net gain of lake water storage (ca. 63.3 km3). The interannual TWS variation is found to be associated mainly with precipitation. In particular, extreme conditions such as the 2015/16 El Niño, had a profound negative impact on the TWS. The findings in this study shed new light on the response of Tibetan lakes to recent decadal environmental changes.
Published: 2020

41. Evaluation of Sentinel-3 SRAL SAR altimetry over Chinese rivers

Author: Jiang, Liguang, Nielsen, Karina, Dinardo, Salvatore, Andersen, Ole Baltazar, Bauer-Gottwein, Peter, Jiang, Liguang, Nielsen, Karina, Dinardo, Salvatore, Andersen, Ole Baltazar, and Bauer-Gottwein, Peter
Abstract: Satellite radar altimetry observations of water surface elevation (WSE) have become an important data source to supplement river gauge records. Sentinel-3 is the first radar altimetry mission operating with a synthetic aperture radar (SAR) altimeter at global scale and with a new on-board tracking system (i.e. open-loop), which has great potential in terms of delivering reliable observations of inland water bodies for the next two decades (several future missions include an open-loop tracking mode). In this context, it is very important to investigate the data quality at an early stage. In this study, a comprehensive evaluation of Sentinel-3A (S3A) is conducted at 50 virtual stations (VS) located on a wide range of rivers in China. The evaluation of Level 1 data shows that, over mountain rivers, a good prior surface elevation estimate on-board is vital to deliver useful datasets using the S3A open-loop tracking system. The Open-Loop Tracking Command version 5 (OLTC V5) has significantly improved the placement of the range window, which was misplaced and resulted in lack of data over many mountain rivers prior to OLTC V5 (March 2019). However, application of S3A over mountain rivers still requires careful evaluation, especially before March 2019. Four retrackers are evaluated including a physical SAR Altimetry Mode Studies and Applications retracker (SAMOSA+), a traditional Offset Center Of Gravity (OCOG), a Primary Peak Center Of Gravity (PPCOG), and a modified Multiple Waveform Persistent Peak (MWaPP+) retracker. For 26 VSs in plain areas, retracked WSE data achieved a root mean square error (RMSE) ranging from 0.12 m to 0.9 m. The comparison of retracking methods reveals that SAMOSA+, OCOG, and PPCOG are unable to handle multi-peak waveforms. But the MWaPP+ can significantly improve the accuracy of the estimated WSE over large rivers, especially when the waveforms are contaminated. Moreover, our result shows no considerable difference between medium (ca. 300 m
Published: 2020

42. The value of distributed high-resolution UAV-borne observations of water surface elevation for river management and hydrodynamic modeling

Author: Jiang, Liguang, Bandini, Filippo, Smith, Ole, Jensen, Inger Klint, Bauer-Gottwein, Peter, Jiang, Liguang, Bandini, Filippo, Smith, Ole, Jensen, Inger Klint, and Bauer-Gottwein, Peter
Abstract: Water level or water surface elevation (WSE) is an important state variable of rivers, lakes, and wetlands. Hydrodynamic models of rivers and streams simulate WSE and can benefit from spatially distributed WSE observations, to increase model reliability and predictive skill. This has been partially addressed by satellite radar altimetry, but satellite altimetry is unable to deliver useful data for small rivers. To overcome such limitations, we deployed a radar altimetry system on an unmanned aerial vehicle (UAV), to map spatially distributed WSE.We showed that UAV altimetry can provide observations of WSE with a very high spatial resolution (ca. 0.5 m) and accuracy (ca. 3 cm), in a time-saving and cost-effective way. Furthermore, we investigated the value of this dataset for the calibration and validation of hydrodynamic models. Specifically, we introduced spatially distributed roughness parameters in a hydrodynamic model and estimated these parameters, using the observed WSE profiles along the stream as input. A case study was conducted in the Åmose stream, Denmark. The results showed that UAV-borne WSE can identify significant variations of the Manning-Strickler coefficients, along this small and highly vegetated stream and over time. Moreover, the model performed extremely well using distributed roughness coefficients, but it could not reproduce WSE satisfactorily using uniform roughness. We concluded that distributed roughness coefficients should be considered, especially for small vegetated rivers, to improve model performance, both locally and globally. Spatially distributed parameterizations of the effective channel roughness could be constrained with UAV-borne WSE. This study demonstrated for the first time that UAV-borne WSE can help to understand the variations of hydraulic roughness, and can support efficient river management and maintenance.
Published: 2020

43. How do GPM IMERG precipitation estimates perform as hydrological model forcing? Evaluation for 300 catchments across Mainland China

Author: Jiang, Liguang, Bauer-Gottwein, Peter, Jiang, Liguang, and Bauer-Gottwein, Peter
Abstract: Accurate precipitation estimates are essential for reliable hydrological simulations of fluxes and states. Satellite precipitation products have been widely used for hydrological applications, especially for ungauged regions. The Global Precipitation Measurement (GPM) product is starting to provide a new generation of precipitation estimates. This work first evaluates several GPM Integrated Multi-satellite Retrievals (IMERG) against gauge-based precipitation over Mainland China for a two-year period (2016–2017), and then explores the feasibility of using GPM to force a lumped hydrological model over 300 catchments of varying size and climate. The analysis indicates that IMERG Final run estimates (gauge-adjusted) agree well with gauge-based precipitation at daily scale, while IMERG Early run estimates (near-real time without gauge adjustments) are consistently lower than the rain gauge records. Nevertheless, both Final run and Early run estimates are slightly better than TRMM 3B42 estimates in terms of rainfall detection skill. Moreover, all three products show better skill over humid regions than over high elevation zones. When used as hydrological model forcing, IMERG Final and Early estimates provide comparable performances to gauge-based precipitation. However, TRMM 3B42 performs relatively poor in terms of hydrological simulation. Moreover, models generally perform better in humid than in arid areas for all three products. The evaluation sheds light on how IMERG-driven hydrological predictions perform in different regions across China. The findings also indicate the potential of IMERG Early run for flood forecasting and Final run for climatological/hydrological modeling in ungauged or poorly gauged basins.
Published: 2019

44. Simultaneous calibration of multiple hydrodynamic model parameters using satellite altimetry observations of water surface elevation in the Songhua River

Author: Jiang, Liguang, Madsen, Henrik, Bauer-Gottwein, Peter, Jiang, Liguang, Madsen, Henrik, and Bauer-Gottwein, Peter
Abstract: Hydrodynamic modeling is an essential tool to simulate water level for flood forecasting and risk assessment. However, parameterization of hydrodynamic models is challenging due to poor knowledge of bathymetry and lack of gauge data. In this study, we present an approach for calibrating spatially distributed Strickler coefficient and river datum simultaneously by regularized inversion. Calibration was carried out using altimetry derived observations of water surface elevation in the Songhua River (China). Synthetic experiments show that spatial variability of model parameters can be well constrained by geodetic altimetry, e.g., CryoSat-2 and SARAL, and to a lesser extent by Envisat and Jason-1. However, Jason-2 can only recover some of the parameters. We also find that a higher accuracy of observations does not proportionally decrease parameter uncertainty for all cross sections. Instead, high spatial sampling density helps to identify the spatial variability of parameters. Real-world calibrations indicate that CryoSat-2 by far outperforms other altimeters in terms of parameter identification. We conclude that high spatial resolution is more important than temporal resolution and observation accuracy for calibrating parameters of large-scale river models. The findings demonstrate the added value of geodetic satellite altimetry for inversion of spatially resolved parameter fields. This study is timely because the upcoming Surface Water and Ocean Topography mission will significantly improve spatial and temporal resolution of spaceborne observations of water surface elevation, and hydraulic models need to be prepared for the uptake of these data.
Published: 2019

45. Influence of local geoid variation on water surface elevation estimates derived from multi-mission altimetry for Lake Namco

Author: Jiang, Liguang, Andersen, Ole Baltazar, Nielsen, Karina, Zhang, Guoqing, Bauer-Gottwein, Peter, Jiang, Liguang, Andersen, Ole Baltazar, Nielsen, Karina, Zhang, Guoqing, and Bauer-Gottwein, Peter
Abstract: Water surface elevation (WSE) is an essential quantity for water resource monitoring and hydrodynamic modeling. Satellite altimetry has provided data for inland water bodies. The height that is derived from altimetry measurement is ellipsoidal height. In order to convert the ellipsoidal height to orthometric height, which has physical meaning, accurate estimates of the geoid are needed. This paper evaluates the suitability of geodetic altimetric measurements for improvement of global geoid models over a large lake in the Tibetan Plateau. CryoSat-2 and SARAL/AltiKa are used to derive the high-frequency geoid correction. A validation of the local geoid correction is performed with data from in-situ observations, a laser altimetry satellite (ICESat), a Ka-band radar altimetry satellite (SARAL) and a SAR radar altimetry satellite (Sentinel-3). Results indicate that the geodetic altimetric dataset can capture the high-resolution geoid information. By applying local geoid correction, the precision of ICESat, SARAL and Sentinel-3 retrievals are significantly improved. We conclude that using geodetic altimetry to correct for local geoid residual over large lakes significantly decreases the uncertainty of WSE estimates. These results also indicate the potential of geodetic altimetry missions to determine local geoid residual with centimeter-level accuracy, which can be used to improve global and regional geopotential models.
Published: 2019

46. Influence of local geoid variation on water surface elevation estimates derived from multi-mission altimetry for Lake Namco

Author: Jiang, Liguang, Andersen, Ole Baltazar, Nielsen, Karina, Zhang, Guoqing, Bauer-Gottwein, Peter, Jiang, Liguang, Andersen, Ole Baltazar, Nielsen, Karina, Zhang, Guoqing, and Bauer-Gottwein, Peter
Abstract: Water surface elevation (WSE) is an essential quantity for water resource monitoring and hydrodynamic modeling. Satellite altimetry has provided data for inland water bodies. The height that is derived from altimetry measurement is ellipsoidal height. In order to convert the ellipsoidal height to orthometric height, which has physical meaning, accurate estimates of the geoid are needed. This paper evaluates the suitability of geodetic altimetric measurements for improvement of global geoid models over a large lake in the Tibetan Plateau. CryoSat-2 and SARAL/AltiKa are used to derive the high-frequency geoid correction. A validation of the local geoid correction is performed with data from in-situ observations, a laser altimetry satellite (ICESat), a Ka-band radar altimetry satellite (SARAL) and a SAR radar altimetry satellite (Sentinel-3). Results indicate that the geodetic altimetric dataset can capture the high-resolution geoid information. By applying local geoid correction, the precision of ICESat, SARAL and Sentinel-3 retrievals are significantly improved. We conclude that using geodetic altimetry to correct for local geoid residual over large lakes significantly decreases the uncertainty of WSE estimates. These results also indicate the potential of geodetic altimetry missions to determine local geoid residual with centimeter-level accuracy, which can be used to improve global and regional geopotential models.
Published: 2019

47. How do GPM IMERG precipitation estimates perform as hydrological model forcing? Evaluation for 300 catchments across Mainland China

Author: Jiang, Liguang, Bauer-Gottwein, Peter, Jiang, Liguang, and Bauer-Gottwein, Peter
Abstract: Accurate precipitation estimates are essential for reliable hydrological simulations of fluxes and states. Satellite precipitation products have been widely used for hydrological applications, especially for ungauged regions. The Global Precipitation Measurement (GPM) product is starting to provide a new generation of precipitation estimates. This work first evaluates several GPM Integrated Multi-satellite Retrievals (IMERG) against gauge-based precipitation over Mainland China for a two-year period (2016–2017), and then explores the feasibility of using GPM to force a lumped hydrological model over 300 catchments of varying size and climate. The analysis indicates that IMERG Final run estimates (gauge-adjusted) agree well with gauge-based precipitation at daily scale, while IMERG Early run estimates (near-real time without gauge adjustments) are consistently lower than the rain gauge records. Nevertheless, both Final run and Early run estimates are slightly better than TRMM 3B42 estimates in terms of rainfall detection skill. Moreover, all three products show better skill over humid regions than over high elevation zones. When used as hydrological model forcing, IMERG Final and Early estimates provide comparable performances to gauge-based precipitation. However, TRMM 3B42 performs relatively poor in terms of hydrological simulation. Moreover, models generally perform better in humid than in arid areas for all three products. The evaluation sheds light on how IMERG-driven hydrological predictions perform in different regions across China. The findings also indicate the potential of IMERG Early run for flood forecasting and Final run for climatological/hydrological modeling in ungauged or poorly gauged basins.
Published: 2019

48. Simultaneous calibration of multiple hydrodynamic model parameters using satellite altimetry observations of water surface elevation in the Songhua River

Author: Jiang, Liguang, Madsen, Henrik, Bauer-Gottwein, Peter, Jiang, Liguang, Madsen, Henrik, and Bauer-Gottwein, Peter
Abstract: Hydrodynamic modeling is an essential tool to simulate water level for flood forecasting and risk assessment. However, parameterization of hydrodynamic models is challenging due to poor knowledge of bathymetry and lack of gauge data. In this study, we present an approach for calibrating spatially distributed Strickler coefficient and river datum simultaneously by regularized inversion. Calibration was carried out using altimetry derived observations of water surface elevation in the Songhua River (China). Synthetic experiments show that spatial variability of model parameters can be well constrained by geodetic altimetry, e.g., CryoSat-2 and SARAL, and to a lesser extent by Envisat and Jason-1. However, Jason-2 can only recover some of the parameters. We also find that a higher accuracy of observations does not proportionally decrease parameter uncertainty for all cross sections. Instead, high spatial sampling density helps to identify the spatial variability of parameters. Real-world calibrations indicate that CryoSat-2 by far outperforms other altimeters in terms of parameter identification. We conclude that high spatial resolution is more important than temporal resolution and observation accuracy for calibrating parameters of large-scale river models. The findings demonstrate the added value of geodetic satellite altimetry for inversion of spatially resolved parameter fields. This study is timely because the upcoming Surface Water and Ocean Topography mission will significantly improve spatial and temporal resolution of spaceborne observations of water surface elevation, and hydraulic models need to be prepared for the uptake of these data.
Published: 2019

49. Unmanned Airborne Vehicles (UAVs) for monitoring small streams and optimizing river maintenance:UAV-borne observations of water level, surface velocity and discharge

Author: Bandini, Filippo, Luthi, Beat, Smith, Ole, Klint Jensen, Inger, Jiang, Liguang, Pheiffer Sunding, Tanya, Bauer-Gottwein, Peter, Bandini, Filippo, Luthi, Beat, Smith, Ole, Klint Jensen, Inger, Jiang, Liguang, Pheiffer Sunding, Tanya, and Bauer-Gottwein, Peter
Published: 2019

50. Exploiting CryoSat-2 altimetry for surface water monitoring and modeling

Author: Jiang, Liguang and Jiang, Liguang
Abstract: Vandmangel, oversvømmelse og tørke er globale udfordringer. Inden for det sidste årti, findes flere eksempler på alvorlig vandmangel, og den voksende verdensbefolkning samt stigende temperatuer øger presset på vores globale ferskvandsresourcer. Paradoksalt, har vi begrænset kendskab til de spatiotemporale dynamikker, som kontrollerer overfladevandsresourcer i stor skala. Remote sensing har vist sig at være et nyttigt redskab til overvågning af overfladevand samt i hydrologisk og geomorfologisk modellering. Det er hovedmotivationen bag dette studie: overvågning af vandresourcer fra rummet. Altimetrisatellitter gør det muligt at overvåge overfladevandets højde og hældning samt ændringer over tid. Desværre risikerer såkaldte ”short-repeat” altimetri-missioner at misse flere vandområder, da en kortere gentagelsesperiode sker på bekostning af stor afstand imellem satellitens spor. Takket være dens drivende bane, kan CryoSat-2 overvåge et langt større antal vandområder. Desuden opnås en mere detaljeret profil af floder, som ellers har været sparsomt besøgt. Denne fordel medfører dog en meget lang gentagelsesperiode. Dette stiller nye udfordring, i særdeleshed i forhold til at udlede vandhøjdetidsrækker ved bestemte ”virtual stations”, punkter langs floden, som short-repeat missioner besøger gentagne gange. Derfor stilles problematikken: ”Kan vi anvende CryoSat-2s distribuerede data til flodmodeller ud over ”virtual station” konceptet?” I dette PhD projekt anvendes CryoSat-2 til overvågning af overfladevandsresourcer i Kina på national skala og til hydrodynamisk modellering. Formålet er at forstå variationer i ferskvandsresourcer i tid og rum, samt muligheder for hydrodynamicsk modellering uden præcis kundskab til batymetry. Hvordan ændrer søer og reservoirer sig og hvordan kan CryoSat-2 anvendes til at besvare dette spørgsmål? Dette spørgsmål er baggrunden for vores undersøgelse af vandhøjdeændringer i floder og søer. Dette studie viser CryoSat-2s bemærkelse, Water shortages, floods, and droughts pose global challenges. The past decade saw severe water scarcity and flooding. The world’s population continues to soar and temperature is ever rising, meaning that the freshwater we have is under severe pressure. However, we have poor knowledge of the spatial and temporal dynamics of freshwater at large scales. Remote sensing has proven useful in water resources monitoring as well as hydrological and geomorphological modeling. This is the main motivation of this research: monitoring water resources from space. Satellite altimetry allows us to measure water surface elevation, its slope, and temporal variation. Most satellite altimetry missions (Jason series, ERS/Envisat/SARAL, etc.) have a short repeat period, i.e. 10 to 35 days while CryoSat-2 has a 369-day long repeat (geodetic orbit). However, short-repeat altimeters miss too many water bodies due to their coarse ground track spacing. Thanks to its geodetic orbit, CryoSat-2 allows a high number of water bodies to be monitored. This also provides a more highly resolved water surface elevation profile of rivers that have not been well sampled before. In the meantime, these benefits come at the cost of long repeat cycle. This particularly poses challenges to derive time series of water level at virtual stations, which are commonly used for short-repeat altimeters. Therefore, one research question is “Can we use distributed CryoSat-2 data for river modeling beyond the ‘virtual station’ concept?” The contributions of this PhD project are to exploit CryoSat-2 for surface water resources monitoring in China at national scale and for hydrodynamic modeling. The aim is to understand spatiotemporal variations of freshwater resources as well as hydrodynamic modeling without precise knowledge of bathymetry. How do lakes and reservoirs change and how can CryoSat-2 help to understand these variations? This motivates the study of water level variation of water bodies. This wo
Published: 2018

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