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Maritime surveillance of the Arctic region is of growing importance as shipping, fishing and tourism are increasing due to the sea ice retreat caused by global warming. Ships that do not identify themselves with a transponder system, so-called dark ships, pose a security risk. They can be detected by SAR satellites, which can monitor the vast Arctic region through clouds, day and night, with the caveat that the abundant icebergs in the Arctic cause false alarms. We collect and analyze 200 Sentinel-1 horizontally polarized SAR scenes from areas with high maritime traffic and from the Arctic region with a high density of icebergs. Ships and icebergs are detected using a continuous wavelet transform, which is optimized by correlating ships to known AIS positions. Globally, we are able to assign 72% of the AIS signals to a SAR ship and 32% of the SAR ships to an AIS signal. The ships are used to construct an annotated dataset of more than 9000 ships and ten times as many icebergs. The dataset is used for training several convolutional neural networks, and we propose a new network which achieves state of the art performance compared to previous ship–iceberg discrimination networks, reaching 93% validation accuracy. Furthermore, we collect a smaller test dataset consisting of 424 ships from 100 Arctic scenes which are correlated to AIS positions. This dataset constitutes an operational Arctic test scenario. We find these ships harder to classify with a lower test accuracy of 83%, because some of the ships sail near icebergs and ice floes, which confuses the classification algorithms. [ABSTRACT FROM AUTHOR]

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. Key Points: More than 200 lakes have been monitored by CryoSat‐2 over the last decade (2010–2019)CryoSat‐2 reveals three phases (rising‐hiatus/decline‐rising) of lake level change; hiatus/decline is widely observed during 2015/16 El NiñoMean change of lake level over the last decade is 2.19 m, of which 56% occurs in the three most recent years [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: Satellite radar altimetry is increasingly being used for hydrological studies. However, it is still challenging to deliver high‐quality data over inland water bodies, that is, lakes, rivers, and reservoirs. One of the reasons is that the altimeter cannot easily identify the water surface elevation due to highly variable terrain elevation along the satellite flight path. In other words, the data delivered may not contain valid information for water bodies. To address this issue, Sentinel‐3 is configured with a new function, which informs the altimeter about the expected elevation of the water surface. However, this function demands a priori knowledge of the altitude of the ground targets. We present four approaches to improve the a priori information to increase data availability over inland water bodies, specifically reservoirs. Key Points: The Sentinel‐3A altimeter cannot deliver useful data over many reservoirs (constructed after 2005) in open‐loop tracking mode with OLTC V5Defining correct a priori elevation information is the key to increasing data availability over reservoirsFour approaches are proposed to define the most accurate onboard a priori elevation [ABSTRACT FROM AUTHOR]

Abstract. Sea level is an essential climate variable (ECV) that has a direct effect on many people through inundations of coastal areas, and it is also a clear indicator of climate changes due to external forcing factors and internal climate variability. Regional patterns of sea level change inform us on ocean circulation variations in response to natural climate modes such as El Niño and the Pacific Decadal Oscillation, and anthropogenic forcing. Comparing numerical climate models to a consistent set of observations enables us to assess the performance of these models and help us to understand and predict these phenomena, and thereby alleviate some of the environmental conditions associated with them. All such studies rely on the existence of long-term consistent high-accuracy datasets of sea level. The Climate Change Initiative (CCI) of the European Space Agency was established in 2010 to provide improved time series of some ECVs, including sea level, with the purpose of providing such data openly to all to enable the widest possible utilisation of such data. Now in its second phase, the Sea Level CCI project (SL_cci) merges data from nine different altimeter missions in a clear, consistent and well-documented manner, selecting the most appropriate satellite orbits and geophysical corrections in order to further reduce the error budget. This paper summarises the corrections required, the provenance of corrections and the evaluation of options that have been adopted for the recently released v2.0 dataset (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). This information enables scientists and other users to clearly understand which corrections have been applied and their effects on the sea level dataset. The overall result of these changes is that the rate of rise of global mean sea level (GMSL) still equates to ∼ 3.2 mm yr−1 during 1992–2015, but there is now greater confidence in this result as the errors associated with several of the corrections have been reduced. Compared with v1.1 of the SL_cci dataset, the new rate of change is 0.2 mm yr−1 less during 1993 to 2001 and 0.2 mm yr−1 higher during 2002 to 2014. Application of new correction models brought a reduction of altimeter crossover variances for most corrections. [ABSTRACT FROM AUTHOR]

In this study we use CryoSat-2 SAR (Delay-Doppler Synthetic Aperture Radar) data over the Mekong River Basin to estimate water levels. Smaller inland waters can be observed with CryoSat-2 data with a higher accuracy compared to the classical radar altimeters due to the increased along track resolution of SAR and the smaller footprint. However, even with this SAR data the estimation of water levels over smaller (width less than 500m) is still challenging as only very few consecutive observations over the water body are present. The usage of land-water-masks for target identification tends to fail as the river becomes smaller. Therefore, we developed a classification to divide the observations into water and land observations based solely on the observations. he classification is done with an unsupervised classification algorithm, and it is based on features derived from the SAR and RIP (Range Integrated Power) waveforms. After the classification, classes representing water and land are identified. The measurements classified as water are used in a next step to estimate water levels for each crossing over the Mekong River. The resulting water levels are validated and compared to gauge data, Envisat data and CryoSat-2 water levels derived with a land-water mask. The CryoSat-2 classified water levels perform better than results based on the land-water-mask and Envisat. Especially, in the smaller upstream regions the improvements of the classification approach for CryoSat-2 are evident. [ABSTRACT FROM AUTHOR]

Monitoring the variation of rivers and lakes is of great importance. Satellite radar altimetry is a promising technology to do this on a regional to global scale. Satellite radar altimetry data has been used successfully to observe water levels in lakes and (large) rivers, and has also been combined with hydrologic/hydrodynamic models. Except CryoSat-2, all radar altimetry missions have been operated in conventional low resolution mode with a short repeat orbit (35 days or less). CryoSat-2, carrying a Synthetic Aperture Radar (SAR) altimeter, has a 369-day repeat and a drifting ground track pattern and provides new opportunities for hydrologic research. The narrow inter-track distance (7.5 km at the equator) makes it possible to monitor many lakes and rivers and SAR mode provides a finer along-track resolution, higher return power and speckle reduction through multi-looks. However, CryoSat-2 challenges conventional ways of dealing with satellite inland water altimetry data because virtual station time series cannot be directly derived for rivers. We review the CryoSat-2 mission characteristics, data products, and its use and perspectives for inland water applications. We discuss all the important steps in the workflow for hydrologic analysis with CryoSat-2, and conclude with a discussion of promising future research directions. [ABSTRACT FROM AUTHOR]

A new approach for improving the accuracy of altimetry-derived sea level anomalies (SLAs) near the coast is presented. Estimation of SLAs is optimized using optimal waveform retracking through a fuzzy multiple retracking system and the most appropriate detiding method. With the retracking system, fuzzy-retracked SLAs become available within 5 km of the coast; meanwhile it becomes more important to use pointwise tide modelling rather than state-of-the-art global tidal models, as the latter leave residual ocean tide signals in retracked SLAs. These improvements are demonstrated for Jason-2 waveforms in the area of the Great Barrier Reef, Australia. Comparing the retrieved SLAs withinsitutide gauge data from Townsville and Bundaberg stations showed that the SLAs from this study generally outperform those from conventional methods, demonstrating that adequate waveform retracking and detiding are equally important in bringing altimetry SLAs closer to the coast. [ABSTRACT FROM AUTHOR]

Abstract: The differences between coastal altimetry and sea level time series of tide gauges in between March 1993 and December 2009 are used to estimate the rates of vertical land motion at three tide gauge locations along the southwestern coasts of Turkey. The CTOH/LEGOS along-track coastal altimetry retrieves altimetric sea level anomalies closer to the coast than the standard along-track altimetry products. However, the use of altimetry very close to the coast is not found to improve the results. On the contrary, the gridded and interpolated AVISO merged product exhibits the best agreement with tide gauge data as it provides the smoothest variability both in space and time compared with along track altimetry data. The Antalya gauge to the south (in the Mediterranean Sea) and the Mentes/Izmir gauge to the west (in the Aegean Sea) both show subsidence while the Bodrum tide gauge to the south (in the Aegean Sea) shows no significant vertical land motion. The results are compared and assessed with three independent geophysical vertical land motion estimates like from GPS. The GIA effect in the region is negligible. The VLM estimates from altimetry and tide gauge data are in good agreement both with GPS derived vertical velocity estimates and those inferred from geological and archaeological investigations. [Copyright &y& Elsevier]

The article presents a study of trend patterns in sea surface temperature (SST) environment. It mentions that a systematic decrease in SST during 25-year period in the equatorial pacific and the increase in global ocean are reflected in the first derived trend pattern. It also notes that the trend-emperical orthogonal function (EOF) is considered as the alternative technique towards the traditional EOF analysis and is used as a method in the extraction of trend patterns.

Studies of global sea level often exclude Tide Gauges (TGs) in glaciated regions due to vertical land movement. Recent studies show that geodetic GNSS stations can be used to estimate sea level by taking advantage of the reflections from the ocean surface using GNSS Interferometric Reflectometry (GNSS-IR). This method has the immediate benefit that one can directly correct for bedrock movements as measured by the GNSS station. Here we test whether GNSS-IR can be used for measurements of inter annual sea level variations in Thule, Greenland, which is affected by sea ice and icebergs during much of the year. We do this by comparing annual average sea level variations using the two methods from 2008–2019. Comparing the individual sea level measurements over short timescales we find a root mean square deviation (RMSD) of 13 cm, which is similar to other studies using spectral methods. The RMSD for the annual average sea level variations between TG and GNSS-IR is large (18 mm) compared to the estimated uncertainties concerning the measurements. We expect that this is in part due to the TG not being datum controlled. We find sea level trends from GNSS-IR and TG of −4 and −7 mm/year, respectively. The negative trend can be partly explained by a gravimetric decrease in sea level as a result of ice mass changes. We model the gravimetric sea level from 2008–2017 and find a trend of −3 mm/year. [ABSTRACT FROM AUTHOR]

Sea level change is an important indicator of climate change. Our study focuses on the sea level budget assessment of the Arctic Ocean using: (1) the newly reprocessed satellite altimeter data with major changes in the processing techniques; (2) ocean mass change data derived from GRACE satellite gravimetry; (3) and steric height estimated from gridded hydrographic data for the GRACE/Argo time period (2003–2016). The Beaufort Gyre (BG) and the Nordic Seas (NS) regions exhibit the largest positive trend in sea level during the study period. Halosteric sea level change is found to dominate the area averaged sea level trend of BG, while the trend in NS is found to be influenced by halosteric and ocean mass change effects. Temporal variability of sea level in these two regions reveals a significant shift in the trend pattern centered around 2009–2011. Analysis suggests that this shift can be explained by a change in large-scale atmospheric circulation patterns over the Arctic. The sea level budget assessment of the Arctic found a residual trend of more than 1.0 mm/yr. This nonclosure of the sea level budget is further attributed to the limitations of the three above mentioned datasets in the Arctic region. [ABSTRACT FROM AUTHOR]

Spaceborne radar altimeters record echo waveforms over all Earth surfaces, but their interpretation and quantitative exploitation over the Arctic Ocean is particularly challenging. Radar returns may be from all ocean, all sea ice, or a mixture of the two, so the first task is the determination of which surface and then an interpretation of the signal to give range. Subsequently, corrections have to be applied for various surface and atmospheric effects before making a comparison with a reference level. This paper discusses the drivers for improved altimetry in the Arctic and then reviews the various approaches that have been used to achieve the initial classification and subsequent retracking over these diverse surfaces, showing examples from both LRM (low resolution mode) and SAR (synthetic aperture radar) altimeters. The review then discusses the issues concerning corrections, including the choices between using other remote-sensing measurements and using those from models or climatology. The paper finishes with some perspectives on future developments, incorporating secondary frequency, interferometric SAR and opportunities for fusion with measurements from laser altimetry or from the SMOS salinity sensor, and provides a full list of relevant abbreviations. [ABSTRACT FROM AUTHOR]

The vadose zone plays an important role in the hydrologic cycle. Various geophysical methods can determine soil water content variations in time and space in volumes ranging from a few cubic centimeters to several cubic meters. In contrast to the established methods, time-lapse gravity measurements of changes in soil water content do not rely on a petrophysical relationship between the measured quantity and the water content but give a direct measure of the mass change in the soil. Only recently has the vadose zone been systematically incorporated when ground-based gravity data are used to infer hydrologic information. In this study, changes in the soil water content gave rise to a measurable signal in a forced infiltration experiment on a 107-m² grassland area. Time-lapse gravity data were able to constrain the van Genuchten soil hydraulic parameters in both a synthetic example and a field experiment with forced infiltration. The most significant reduction in parameter uncertainty was achieved for the saturated water content, while gravity data had some ability to constrain the saturated hydraulic conductivity and the van Genuchten n Cross-borehole ground penetrating radar data were used to support the interpretation and control of the gravity data. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this work has been to examine the relationship of steep bathymetry in the coastal areas around the permanent Cal/Val facility of Gavdos, and their influence on the produced calibration values for the Jason-2 satellite altimeter. The paper describes how changes in seafloor topography (from 200 to 3500m depth over a distance of 10km) are reflected on the determined altimeter parameters using different reference surfaces for satellite calibration. Finally, it describes the relation between these parameter trends and the region’s local characteristics. Using 3.5years of Jason-2 calibration data and careful data analysis, certain features and variations, with permanent signatures at some locations south of Gavdos, have been found in the altimeter bias values. Causes of these variations have been interpreted. Some of these features, for example, at 12km south of the Cal/Val site seem to be related to the general oceanographic circulation, but others of short wavelength (in the order of 1km) are because of the insufficient geoid model resolution. Along Pass No. 109, the concealed effect of bathymetry on the geoid has produced a slope of 3.1cm over 14–21km from Gavdos. Along the other Pass No.18 and in the range 12–21km, a slope in the geoid model, caused again by the sharp changes in the topography of seafloor (from 300 to 3200m depth over a distance of 10km), have been discovered. Those geoid model imperfections of short wavelength do not change the previously reported bias values. Finally, boat campaigns that took place for verifying the previous features, were also used to determine an altimeter bias of B=+19.6±4.5cm, for cycle=80, at 15:14:58 UTC, on 7-Sept-2010, along Pass No. 109. Calibration took place at a distance of about 19km south of Gavdos, in the open sea while Jason-2 was flying over. [Copyright &y& Elsevier]