Search

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.

We study the role of airborne gravimetry for seamless bathymetry modeling over the Paracel Islands in the northern South China Sea (SCS) and investigate the possibility of using Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data and Satellite-derived bathymetry (SDB) to evaluate bathymetry models over shallow waters. We use ICESat-2 data for training Sentinel-2 imagery and derive the SDB data with a root-mean-squared error (RMSE) of 0.29–0.50 m, which is lower than 10% of the maximum depths. The local bathymetry is modeled by using a modified version of the S&S bandpass filter, and a partition-wise scheme is applied for determining the scaling factors. Numerical experiments verify the feasibility of using ICESat-2 and SDB data to assess bathymetry models. By utilizing the airborne gravity data, the fit between the computed bathymetry and the SDB data is significantly improved, by 18.7%–58.0% over different shallow waters compared with recently released bathymetry models. The bathymetry predicted from the airborne data has also higher performance in deep water areas, which performs best in all these depth ranges from 500 to 3000 m. In comparison with the existing models, the RMSEs of the misfits between the computed bathymetry and the National Oceanic and Atmospheric Administration depths are reduced by tens to hundreds of meters in different depth ranges. Our study highlights that using airborne gravimetry for bathymetry modeling over island areas is advantageous, in both shallow and deep waters, and that ICESat-2 and SDB data can largely alleviate the lack of in situ depths over shallow waters.

A new mean sea surface (MSS) from the Technical University of Denmark (DTU) called DTU21MSS for referencing sea-level anomalies from satellite altimetry is introduced in this paper, and a suite of evaluations are performed. One of the reasons for updating the existing mean sea surface is the fact that during the last 6 years, nearly 3 times as many data have been made available by space agencies, resulting in more than 15 years of altimetry from long-repeat orbits (LROs) or geodetic missions. This includes the two interleaved long-repeat cycles of Jason-2 with a systematic cross-track distance as low as 4ĝ€¯km. A new processing chain with updated filtering and editing has been implemented for the DTU21MSS. This way, the DTU21MSS has been computed from 2ĝ€¯Hz altimetry in contrast to the former DTU15MSS and DTU18MSS which were computed from 1ĝ€¯Hz altimetry. The new DTU21MSS is computed over the same 20-year averaging time from 1 January 1993 to 31 December 2012 with a well-specified central time of 1 January 2003 and is available from 10.11583/DTU.19383221.v1 (Andersen, 2022). Cryosat-2 employs synthetic aperture radar (SAR) and SAR interferometric (SARin) modes in a large part of the Arctic Ocean due to the presence of sea ice. For SAR- and SARin-mode data we applied the SAMOSA+ physical retracking to make it compatible with the physical retracker used for conventional low-resolution-mode data in other parts of the ocean.

With the availability of more than 9 years of Cryosat-2, it is possible to revisit polar ocean tides, which have traditionally been difficult to determine from satellite altimetry. The SAMOSA+ physical retracker is a stable retracker developed particularly for Cryosat-2. Being a physical retracker, it enables the determination of the sea state bias. Correcting for the sea state bias enables more reliable sea level estimates compared with traditional empirical retrackers used before. Cryosat-2 data have been analyzed for residual ocean tides to the FES2014 ocean tide model in the Arctic Ocean and Antarctic Ocean using the response formalism. We utilize data from the sub-cycle of Cryosat-2, which follows a repeating pattern of approximately 28.33 days. This sub-repeat period makes it an advantageous alias period for the majority of significant constituents. This allowed for the estimation and mapping of the major tidal constituents in the open ocean and also in floating ice shelves from data extracted from leads in the sea ice. A novel empirical ocean tide model designed specifically for the polar region, DTU22, is introduced. Our findings reveal substantial enhancements in semi-diurnal tides within the Arctic Ocean and improvement in diurnal constituents within the Southern Ocean. In the Southern Ocean, the diurnal constituents are particularly improved using the empirical model by more than a factor of two to around 3 cm for both constituents compared with FES2014b. These outcomes underscore the significance of incorporating the reprocessed and retracted Cryosat-2 data into tidal modeling, highlighting its pivotal role in advancing the field.

The Copernicus Sentinel-3 Surface Topography Mission (STM) Land Altimetry provides valuable surface elevation information over inland waters, sea ice, and land ice, thanks to its synthetic aperture radar (SAR) altimeter and its orbit that covers high-latitude polar regions. To ensure that these measurements are reliable and to maximise the return on investment, adequate validation of the geophysical retrieval methods, processing algorithms, and corrections must be performed using independent observations. The EU-ESA project St3TART (started July 2021) aims to generalise the concept of Fiducial Reference Measurements (FRMs) for the Copernicus Sentinel-3 STM. This work has gathered existing data, made new observations during field campaigns, and ensured that these observations meet the criteria of FRM standards so that they can be used to validate Sentinel-3 STM Land Altimetry products operationally. A roadmap for the operational provision of the FRM, including the definition, consolidation, and identification of the most relevant and cost-effective methods and protocols to be maintained, supported, or implemented, has been developed. The roadmap includes guidelines for SI traceability, definitions of FRM measurement procedures, processing methods, and uncertainty budget estimations.

Seastar is one of four mission candidates to the ESA Earth Explorer 11 call, an innovative mission concept dedicated to observing fast-evolving small-scale ocean surface dynamics in all coastal seas, shelf seas and marginal ice zones. Seastar would measure fast-evolving small-scale ocean dynamics with critical 1 day revisit time and 1 km resolution to study exchanges of heat, carbon and nutrients at boundaries between land, the cryosphere, the atmosphere and the deep ocean. It would deliver the first comprehensive high- resolution description of currents, winds and waves in the global coastal, shelf and marginal ice zones to improve their representation in models and identify coastal hazards, pollution pathways and impacts on marine energy, food and ecosystems. Seastar would carry a high-squint three-azimuth along-track radar interferometer, enabling the simultaneous observation and separation of ocean surface total currents and vector winds with unmatched revisit, coverage, and sensitivity.

Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way of increasing the understanding of “black box” models and building trust. In this work, we applied transfer learning to develop a deep neural network to predict sex from electrocardiograms. Using the visual explanation method Grad-CAM, heat maps were generated from the model in order to understand how it makes predictions. To evaluate the usefulness of the heat maps and determine if the heat maps identified electrocardiogram features that could be recognized to discriminate sex, medical doctors provided feedback. Based on the feedback, we concluded that, in our setting, this mode of explainable artificial intelligence does not provide meaningful information to medical doctors and is not useful in the clinic. Our results indicate that improved explanation techniques that are tailored to medical data should be developed before deep neural networks can be applied in the clinic for diagnostic purposes.

Radar satellite altimeters enable the determination of the mean sea surface to centimeter accuracy, which can be degraded in coastal areas because of the lack of valid altimetry observations due to land contamination and the altimeter footprint size. In 2018, the National Aeronautics and Space Administration launched ICESat-2, a laser altimetry mission equipped with the Advanced Topographic Laser Altimeter System, providing measurements every 0.7 m in the along-track direction. Taking into account the complexity of the Norwegian coastline, this study aims to evaluate coastal observations from ICESat-2 in order to use it to update the existing mean sea surface for Norway, NMBU18. We, therefore, determined the mean sea surface using only ICESat-2 observations and compared it with mean sea level observations from 23 permanent tide gauges along the entire coast and 21 temporary tide gauges in Norway’s largest and deepest fjord, Sognefjorden. We also included two global mean sea surface models and NMBU18 for comparison. The results have shown that ICESat-2 is indeed able to provide more valid observations in the coastal zone, which can be used to improve the mean sea surface model, especially along the coast.

Performance in short-duration sports is highly dependent on muscle glycogen, but the total degradation is only moderate and considering the water-binding property of glycogen, unnecessary storing of glycogen may cause an unfavorable increase in body mass. To investigate this, we determined the effect of manipulating dietary carbohydrates (CHO) on muscle glycogen content, body mass and short-term exercise performance. In a cross-over design twenty-two men completed two maximal cycle tests of either 1-min (n = 10) or 15-min (n = 12) duration with different pre-exercise muscle glycogen levels. Glycogen manipulation was initiated three days prior to the tests by exercise-induced glycogen-depletion followed by ingestion of a moderate (M-CHO) or high (H-CHO) CHO-diet. Subjects were weighed before each test, and muscle glycogen content was determined in biopsies from m. vastus lateralis before and after each test. Pre-exercise muscle glycogen content was lower following M-CHO than H-CHO (367 mmol · kg-1 DW vs. 525 mmol · kg-1 DW, p < 0.00001), accompanied by a 0.7 kg lower body mass (p < 0.00001). No differences were observed in performance between diets in neither the 1-min (p = 0.33) nor the 15-min (P = 0.99) test. In conclusion, pre-exercise muscle glycogen content and body mass was lower after ingesting moderate compared with high amounts of CHO, while short-term exercise performance was unaffected. This demonstrates that adjusting pre-exercise glycogen levels to the requirements of competition may provide an attractive weight management strategy in weight-bearing sports, particularly in athletes with high resting glycogen levels.