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The article discusses the Coastal Flood Hazard Workshop held by the Scripps Institution of Oceanography in San Diego, California, focusing on advancements in predicting and evaluating coastal flood hazards in a changing climate. The workshop aimed to assess state-of-the-art methods, identify knowledge gaps, and determine future research pathways to inform community-level flood risk and adaptation planning. It highlighted advancements in both long-term flood projection models and operational forecast models, emphasizing the need to bridge scales and integrate various sources of data for accurate flood predictions. The article also addresses identified knowledge gaps and future research avenues, emphasizing the importance of sustained observations, satellite monitoring, community engagement, and interdisciplinary collaboration in improving coastal flood forecasting and mitigation efforts. [Extracted from the article]

The 2024 "Hacking Limnology" Workshop Series and Virtual Summit aimed to increase inclusion, participation, and representation in the aquatic sciences. The event brought together over 100 aquatic science practitioners and enthusiasts from around the world, with an emphasis on global accessibility. The workshops focused on big data, open science, modeling, remote sensing, and ecological modeling, while the virtual summit covered topics such as data science, climate change, and open science applications. The event showcased a diverse range of presenters, panelists, and organizational team members, reflecting the growing interest in data-intensive aquatic science and the importance of diverse representation in the field. [Extracted from the article]

Rivers play a crucial role in maintaining ecosystems and regional climates, while also providing essential water for irrigation and drinking. With the increasing impacts of climate change and human activities, rivers are becoming more prone to extreme events (droughts and floods) and induced erosion/deposition processes, making water-related risk management more challenging. The recent launch of the Surface Water and Ocean Topography (SWOT) mission, which focuses on continental surfaces with a spatial resolution of 100 m, has opened new avenues for applications in hydrology, hydrodynamics, and geomorphology. This study examines the initial results of the SWOT mission for sixteen rivers (ranging in width from 50 to 2,000 m) in the Cuvette Centrale of the Congo Basin, obtained in April 2023 during the fast sampling phase. The study assesses water surface elevations (WSE) and backscatter coefficient (s0) measured from SWOT. Comparisons of WSE with data from other radar altimetry missions (Sentinel-3A and 3B, Jason-3, and Sentinel-6A) and GEDI data show high correlation coefficients of 0.977 (with a bias of 0.538 m) and 0.992 (with a bias of 1.011 m), respectively. The first maps of WSE slopes show realistic values, even in rivers less than 100mwide, with steeper slopes upstream. Various WSE longitudinal profiles are retrieved with unprecedented spatial resolution, surpassing what other nadir altimetry missions have achieved. The s0 values, between -10 and 20 dB on average, also appear consistent with other studies. These promising initial results pave the way for future studies on fluvial geomorphology dynamics and erosion/deposition processes from the new SWOT observations. [ABSTRACT FROM AUTHOR]

Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant. [ABSTRACT FROM AUTHOR]

Atmospheric circulation has significant impacts on sea ice drifting patterns and mass balance, as wind drag induces pressure ridges and leads on the sea ice surface. In this study, the spatiotemporal distributions of these dynamic sea ice deformation features in the Ross Sea are examined using ICESat‐2 (IS2) ATL10 freeboard data (2019–2022). The temporal variation of the modal sea ice thickness (SIT), caused by thermodynamic ice growth and sea ice advection, varies from 0.7–1.0 m in April to 1.0–1.6 m in July–September and decreases thereafter in the northwest (NW) and northeast (NE) sectors. This temporal variation of modal SIT agrees with the air temperature (correlation coefficients >0.5). The southwest (SW) sector shows a consistently low modal SIT (<1.0 m) because of the production of new ice in polynyas and continuous northward sea ice drift. Meanwhile, the southeast (SE) sector shows the thickest ice in Octobers 2019 and 2020 because of the advection of thick ice from the Amundsen Sea, which was reduced in 2021 and 2022. In terms of dynamic sea ice deformation, the SE sector shows the largest deformation because of the wind‐driven convergence of sea ice movement. However, such intense deformation in the SE sector diminished in 2021 and 2022 due to the dominance of strong southerly wind associated with the Amundsen Sea Low (ASL). This study emphasizes the potential of IS2 sea ice products to assess the role of atmospheric driving forces on thermodynamic and dynamic sea ice changes. Plain Language Summary: The movement of sea ice is primarily driven by wind speed and direction. Furthermore, wind changes sea ice surface topography by forming sea ice deformation features. When sea ice floes collide with each other, the piled‐up sea ice fragments form thicker ice, namely, pressure ridges. Observation of such pressure ridges in the Southern Ocean has been limited to specific seasons or regions because of the lack of high‐resolution remote sensing data. However, high‐resolution observation of pressure ridges is now available regularly through NASA's satellite altimeter ICESat‐2. We investigate the spatiotemporal variations of sea ice topography in the Ross Sea, especially the distribution of pressure ridges, by using ICESat‐2 data. The observation from ICESat‐2 shows that the areal fraction of pressure ridges in the Ross Sea decreased in 2021 and 2022, particularly in the southeast Ross Sea. The comparison with weather data indicates that this decrease might be caused by strong southerly winds associated with the deep Amundsen Sea Low in these 2 years. This study demonstrates that ICESat‐2 can play an important role in understanding the influence of wind on sea ice drift and the formation of pressure ridges. Key Points: Variation of modal ice thickness is characterized by thermodynamic ice growth in the north Ross Sea and ice advection in the south Ross SeaSea ice in the southeast Ross Sea was significantly deformed in 2019–2020 due to the inflow of thick ice and convergent ice driftStrong southerly wind associated with the Amundsen Sea Low decreased sea ice deformation in the southeast Ross Sea in 2021 and 2022 [ABSTRACT FROM AUTHOR]

Conventional altimetry has greatly advanced our understanding of mesoscale eddies but falls short in studying fine-scale eddies (<150 km). The newly launched Surface Water and Ocean Topography (SWOT) altimeter, however, with its unprecedented high-resolution capabilities, offers new opportunities to observe these fine-scale eddies. In this study, we use SWOT data to explore these previously elusive fine-scale eddies in the Kuroshio Extension. During SWOT's fast sampling phase from 29 May 2023 to 10 July 2023, we identified an average of 4.5 fine-scale eddies within each 120 km wide swath. Cyclonic eddies, which are slightly more frequent than the anticyclonic ones (ratio of 1.16), have a similar mean radius of 23.4 km. However, cyclonic eddies exhibit higher amplitudes, averaging 3.5 cm compared to 2.8 cm for anticyclonic eddies. In contrast to the mesoscale eddies detected by conventional altimeters, the fine-scale eddies revealed by SWOT are characterized by smaller sizes and weaker amplitudes. This study offers a preliminary view of fine-scale eddy characteristics from space, highlighting SWOT's potential to advance our understanding of these dynamic processes. Nonetheless, it also emphasizes the necessity for comprehensive analysis to fully exploit the satellite's capabilities in monitoring and interpreting complex eddy behaviors. [ABSTRACT FROM AUTHOR]

Mesoscale currents account for 80% of the ocean's kinetic energy, whereas submesoscale currents capture 50% of the vertical velocity variance. SWOT's first sea surface height (SSH) observations have a spatial resolution an order of magnitude greater than traditional nadir‐looking altimeters and capture mesoscale and submesoscale features. This enables the derivation of submesoscale vertical velocities, crucial for the vertical transport of heat, carbon and nutrients between the ocean interior and the surface. This work focuses on a mesoscale energetic region south of Tasmania using a coupled ocean‐atmosphere simulation at km‐scale resolution and preliminary SWOT SSH observations. Vertical velocities (w), temperature anomalies and vertical heat fluxes (VHF) from the surface down to 1,000 m are reconstructed using effective surface Quasi‐Geostrophic (sQG) theory. An independent method for reconstructing temperature anomalies, mimicking an operational gridded product, is also developed. Results show that sQG reconstructs 90% of the modeled w and VHF rms at scales down to 30 km just below the mixed layer and 50%–70% of the rms for scales larger than 70 km at greater depth, with a spatial correlation of ∼ ${\sim} $ 0.6. The reconstruction is spectrally coherent (>0.65) $(> 0.65)$ for scales larger than 30–40 km at the surface, slightly degrading (∼ ${\sim} $ 0.55) at depth. Two temperature anomaly data sets yield similar results, indicating the dominance of w on VHF. The RMS of sQG w $w$ and VHF derived from SWOT are twice as large as those derived from conventional altimetry, highlighting the potential of SWOT for reconstructing energetic meso and submesoscale dynamics in the ocean interior. Plain Language Summary: This work focuses on vertical ocean dynamics induced by small‐scale ocean surface currents, especially those at the mesoscale and submesoscale (20–100 km in diameter). These ocean vertical velocities pump heat and carbon from the surface to depth and carry nutrients important for biomass development. Our motivation is the first data from the new satellite SWOT (Surface Water and Ocean Topography), which provides observations of surface geostrophic currents at much higher resolution compared to traditional satellites. We study a Southern Ocean area near Tasmania using a realistic coupled ocean‐atmosphere simulation at a km‐scale resolution and initial SWOT data and reconstruct vertical velocities, temperature, and heat fluxes using a vertical projection theory. Results show that the vertical reconstruction coherently represents ocean vertical velocities and heat fluxes below the surface mixed layer larger than 30–40 km and that smaller scales are not well reconstructed. In the computation of vertical heat fluxes, we compare two different ways of measuring temperature anomalies, finding that, overall, the difference is not significant because vertical velocities dominate the heat fluxes. This study highlights the potential of SWOT for studying small‐scale ocean dynamics at the surface and reconstructed at depth. Key Points: Vertical velocities can be coherently reconstructed in the Southern Ocean at scales down to 30–40 kmVertical heat fluxes can be retrieved using effective surface quasi‐geostrophic reconstruction and are dominated by vertical velocitiesVertical velocities reconstructed from SWOT observations have 50% more variance than those derived from traditional altimetry [ABSTRACT FROM AUTHOR]

Accurate streamflow prediction in human‐regulated catchments remains a formidable challenge due to the complex disturbance of hydrological processes. To consider human disturbance in hydrological modeling, this study introduces a novel static attribute collection that combines river‐reach attributes with catchment attributes, referred to as multiscale attributes. The attribute collection is assembled into two deep learning (DL) methods, that is, the Long Short‐Term Memory (named as Multiscale LSTM) and the Differentiable Parameter Learning (DPL) model, and the performance is evaluated across 95 human‐regulated catchments in the United States (USA) and 24 catchments in the Yellow River Basin in China. In the USA, the Multiscale LSTM and the DPL models achieve similar performance with median Kling‐Gupta Efficiency (KGE) of 0.78 and 0.71, respectively. However, in the Yellow River Basin, the KGE values are 0.58 for Multiscale LSTM and 0.24 for DPL. These results highlight the DL models' ability to leverage multiscale attributes for improved performance compared to traditional catchment attributes. The performance of Multiscale LSTM and DPL models is predominantly influenced by river‐scale attributes, encompassing factors such as connectivity status index (CSI), degree of regulation (DOR), sediment trapping (SED), and number of dams. Additionally, satellite‐derived attributes such as mean and maximum river width (Width), slope and mean water surface elevation (WSE) from the Surface Water and Ocean Topography River Database (SWORD) contribute valuable insights into anthropogenic influences. Moreover, our study highlights the significance of selecting the appropriate training data period, which emerges as the most dominant factor affecting model performance across human‐regulated catchments. The diversity of data during the training period enables the model to capture a broad spectrum of hydrological signatures within these catchments. Consequently, this study emphasizes the advantages of Multiscale LSTM and underscores the significance of considering both natural and anthropogenic signatures to enhance hydrological predictions within human‐regulated environments. Plain Language Summary: Understanding how water flows in rivers is crucial for managing reservoirs, preventing floods, and making smart decisions about water use in human‐regulated catchments. Previous research using data‐driven models has predominantly focused on long short‐term memory (LSTM) and differentiable parameter learning (DPL) models in natural catchments with minimal human influences. Identifying the effectiveness of these models in human‐regulated catchments has posed a significant challenge. To address this gap, we intentionally compared the performance of LSTM and DPL models, incorporating multiscale attributes as inputs. The results underscore the significant superiority of the LSTM model over the DPL model in human‐regulated catchments, emphasizing the crucial role of river attributes in enhancing model performance. Additionally, we observed that the DPL model exhibited higher sensitivity to the dynamics of human activities, and struggles to provide accurate simulations during periods of elevated human impacts. These findings elucidate the divergent capabilities of these models in representing hydrological processes in human‐regulated catchments. Key Points: Long Short‐Term Memory is able to capture irregular streamflow patterns by utilizing a novel collection of multiscale attributes as inputThe performance of the model is extremely sensitive to the training data period across human‐regulated catchmentsDifferentiable Parameter Learning may be susceptible to the dynamics of human activities, and struggles to provide accurate simulations [ABSTRACT FROM AUTHOR]

Severe storms produce ocean waves with periods of 18–26 s, corresponding to wavelengths 500–1,055 m. These waves radiate globally as swell, generating microseisms and affecting coastal areas. Despite their significance, long waves often elude detection by existing remote sensing systems when their height is below 0.2 m. The new Surface Water Ocean Topography (SWOT) satellite offers a breakthrough by resolving these waves in global sea level measurements. Here we show that SWOT can detect 25‐s waves with heights as low as 3 cm, and resolves period and direction better than in situ buoys. SWOT provides detailed maps of wave height, wavelength, and direction across ocean basins. These measurements unveil intricate spatial patterns, shedding light on wave generation in storms, currents that influence propagation, and refraction, diffraction and reflection in shallow regions. Notably, the magnitude of reflections exceeds previous expectations, illustrating SWOT's transformative impact. Plain Language Summary: Wind storms at sea make waves that increase in size with wind speed, and with the distance over which the high winds have been able to amplify the waves. Once generated these waves propagate as swell around the world ocean: in that stage the wave period remains constant while the wave height decay away from the source. Waves with periods longer than 18 s are relatively infrequent, but they are an important source of seismic waves and coastal impacts. However, current remote sensing techniques miss long waves under 0.2 m high. The Surface Water Ocean Topography (SWOT) satellite mission changes this, spotting 25‐s waves with heights as low as 3 cm. SWOT maps wave height, wavelength, and direction worldwide, revealing the influence of winds, currents and water depth. For example, We found stronger than expected coastal reflection, which will help revise wave forecasting models and their application in seismology. Key Points: Surface Water Ocean Topography (SWOT) data provide the first open ocean spatial measurements of phase‐resolved swells with wavelength 500–1,050 mSwells with heights as low as 3 cm are well detected by SWOT, allowing tracking across oceansSwell reflection off the coast can be separated from incident waves [ABSTRACT FROM AUTHOR]

In this study, wind speed sensitivity and calibration bias were first determined for Surface Water and Ocean Topography (SWOT) satellite Ka-band Radar Interferometer (KaRIn) Normalized Radar Backscatter Cross Section (NRCS) data at VV and HH polarizations. Here, the calibration bias was estimated by comparing the KaRIn NRCS with collocated simulations from a model developed using Global Precipitation Measurement (GPM) satellite Dual-frequency Precipitation Radar (DPR) data. To recalibrate the bias, the correlation coefficient between the KaRIn data and the simulations was estimated, and the data with the corresponding top 10% correlation coefficients were used to estimate the recalibration coefficients. After recalibration, a Ka-band NRCS model was developed from the KaRIn data to retrieve ocean surface wind speeds. Finally, wind speed retrievals were evaluated using the collocated European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis winds, Haiyang-2C scatterometer (HY2C-SCAT) winds and National Data Buoy Center (NDBC) and Tropical Atmosphere Ocean (TAO) buoy winds. Evaluation results show that the Root Mean Square Error (RMSE) at both polarizations is less than 1.52 m/s, 1.34 m/s and 1.57 m/s, respectively, when compared to ECMWF, HY2C-SCAT and buoy collocated winds. Moreover, both the bias and RMSE were constant with the incidence angles and polarizations. This indicates that the winds from the SWOT KaRIn data are capable of correcting the sea state bias for sea surface height products. [ABSTRACT FROM AUTHOR]

The Surface Water and Ocean Topography (SWOT) mission provides a good opportunity to study fine‐scale processes in the global ocean but whether it can detect balanced submesoscale eddies is uncertain due to the "contamination" by unbalanced inertial gravity waves. Here, based on concurrent observations from SWOT and a mooring array in the northwestern Pacific, we successfully captured two submesoscale cyclonic eddies with negative sea level anomalies (SLAs) in spring 2023. We find that the SLA amplitude and equivalent radius of the first (second) eddy are 2.5 cm and 16.0 km (2.0 cm and 18.8 km), respectively. For both eddies, their vertical scales are around 150 m and their horizontal velocities and Rossby numbers exceed 15.0 cm/s and 0.4, respectively. Further analysis suggests that similar submesoscale eddies can commonly occur in the northwestern Pacific and that SWOT is capable to detect larger submesoscale eddies with scales greater than ∼10 km. Plain Language Summary: The Surface Water and Ocean Topography (SWOT) mission measures sea surface heights with a spatial resolution an order of magnitude higher than the prior nadir altimetry missions. However, whether SWOT can detect oceanic submesoscale eddies that play key roles in oceanic energy cycle and vertical material transports, is uncertain. To investigate this issue, we deployed a mooring array beneath a SWOT orbital swath in the northwestern Pacific. Based on the concurrent SWOT and mooring data, we successfully captured two submesoscale cyclonic eddies in spring 2023. Radii of the submesoscale eddies are found to be between 10 and 20 km and their horizontal velocities exceed 15.0 cm/s. The ratio between their vertical relative vorticity and the planetary vorticity exceeds 0.4. Further analysis suggests that similar submesoscale eddies can commonly occur in the northwestern Pacific. This study demonstrates the capability of SWOT to detect submesoscale eddies in the global ocean. Key Points: Two submesoscale cyclonic eddies (SCEs) were observed by SWOT and moorings in the northwestern PacificKinematic and dynamic features of the SCEs were revealedIt is feasible to use SWOT data to detect larger submesoscale eddies in the ocean [ABSTRACT FROM AUTHOR]

We present a preliminary study on using the Surface Water and Ocean Topography (SWOT) mission to extend water surface elevation (WSE) measurements from a sparsely distributed in situ gauge network along a one-dimensional (1D) study reach within the Mahanadi River basin in India. We use the Centre National d'Etudes Spatiales (CNES) simulator to simulate 3 years of synthetic measurements of SWOT WSE, which are assimilated into a 1D stochastic model based on six independent configurations. For each configuration, the model is derived using historical measurements of in situ WSE to simulate daily WSE estimates every 200 m along the study reach. Assimilated outputs showed high Nash-Sutcliffe efficiency (0.697–0.811), high correlation (0.838–0.901) and low root mean square error (0.242–0.513 m) with respect to in situ validation data. Results indicate consistent performance of the SWOT-assimilated model framework and are relevant considering the declining availability of in situ monitoring stations. [ABSTRACT FROM AUTHOR]

Bering Strait is the only ocean gateway connecting the Pacific and Arctic oceans. The ∼1 Sv northward flow of Pacific water through the strait to the Arctic Ocean has been increasing by ∼0.01 Sv/yr since 1990. Monthly dynamic ocean topography (DOT), wind, and sea‐ice data at Bering Strait are analyzed in context with the long‐term record of flow through the strait to investigate local drivers. Ocean transport is found to be proportional to the across‐strait slope in DOT, suggesting some component of the flow is in geostrophic balance. Along‐strait ocean surface stresses, which modulate the across‐strait DOT slope via Ekman transport, are analyzed in the presence of a seasonally varying ice cover. It is shown that northward interior ocean flow under sea ice in winter results in southward surface stresses, and westward Ekman transport that slows the geostrophic component of the northward ocean flow. As the number of open water days local to Bering Strait increase each year, we find no trend in the annual mean surface stress, that is, the loss of sea ice is not leading to increased northward wind stress input that would enhance northward ocean flow. This analysis is consistent with the theory that changes in both the atmosphere and ocean non‐local to Bering Strait are likely driving the increased transport from the Pacific into the Arctic via Bering Strait. Plain Language Summary: Bering Strait is a narrow waterway, 50 m deep and 85 km wide, between Alaska and Russia that allows relatively warmer and fresher Pacific water to flow into the Arctic Ocean. The volume of water entering the Arctic through Bering Strait has increased approximately 30% since 1990. It is unclear what processes are responsible for this observed increase. We determine that part of Bering Strait throughflow is driven by the difference in pressure across the strait, or an across‐strait slope in sea surface, which can be caused by a stress applied parallel to the strait. When winds blow to the north, water piles up on the Alaskan side creating a pressure difference that is proportional to the flow. When sea ice is absent, winds act directly on the ocean. When sea ice is present, sea ice applies a stress onto the ocean. We find that as the Arctic loses sea ice, there are no changes in stress due to fewer days of sea ice cover. This suggests that local winds and sea ice are not driving the increase in transport, and that large‐scale changes in the Pacific and Arctic Oceans are driving the increase in transport through Bering Strait. Key Points: Monthly dynamic ocean topography (DOT) supports that some component of flow through Bering Strait is in geostrophic balanceLocal surface stress in Bering Strait increases to the south as the interior flow increases to the north when sea ice is presentThe increasing number of open water days each year is not contributing to enhanced northward transport via increased wind stress input [ABSTRACT FROM AUTHOR]

Two moorings deployed for 75 days in 2019 and long‐term satellite altimetry data reveal a spatially complex and temporally variable internal tidal field at the Surface Water and Ocean Topography (SWOT) Cal/Val site off central California due to the interference of multiple seasonally‐variable sources. These two data sets offer complementary insights into the variability of internal tides in various time scales. The in situ measurements capture variations occurring from days to months, revealing ∼45% coherent tides. The north mooring displays stronger mode‐1 M2 with an amplitude of ∼5.1 mm and exhibits distinct time‐varying energy and modal partitioning compared to the south mooring, which is only 30‐km away. The 27‐year altimetry data unveils the mean and seasonal variations of internal tides. The results indicate that the complex internal tidal field is attributed to multiple sources and seasonality. Mode‐1 tides primarily originate from the Mendocino Ridge and the 36.5–37.5°N California continental slope, while mode‐2 tides are generated by local seamounts and Monterey Bay. Seasonality is evident for mode‐1 waves from three directions. The highest variability of energy flux is found in the westward waves (±22%), while the lowest is in the southward waves (±13%). The large variability observed from the moorings cannot be solely explained by seasonality; additional factors like mesoscale eddies also play a role. This study emphasizes the importance of incorporating the seasonality and spatial variability of internal tides for the SWOT internal tidal correction, particularly in regions characterized by multiple tidal sources. Plain Language Summary: This study explores the variations of internal tides, which are waves at tidal frequencies beneath the ocean surface. They play a crucial role in deep‐ocean mixing, ocean circulation, and the overall climate system by transporting nutrients, heat, and carbon within the ocean. Our research area is off central California. We use both in situ measurement and satellite observation to understand how internal tides change over time and space. Our discoveries suggest that four main sources, changing ocean currents, and seasonal variations of internal tides, contribute to these tidal changes and create the complicated tidal field off central California. Key Points: Temporal and spatial variations of semidiurnal internal tides are observed using in situ moorings and satellite altimetryComplex internal tide field is caused by multiple generation sources, seasonal stratification, and likely mesoscale eddiesThe three generation sources of mode‐1 M2 internal tides are subject to strong but different seasonalities [ABSTRACT FROM AUTHOR]

Flow–duration curves (FDCs) provide a compact view of the historical variability of river flows, reflecting climate conditions and the main hydrologic features of river basins. The Surface Water and Ocean Topography (SWOT) satellite mission will enable the estimation of river flows globally, by sensing rivers wider than 100 m with a sampling recurrence from 3 to 21 days. This study investigated the lifetime mission potential for FDC estimation through the comparison between remotely-sensed and empirical FDCs. We employed the Global Runoff Data Center dataset and derived SWOT-like river flows by selecting gauging stations of rivers wider than 100 m with more than 10-year long daily river flow time series. Overall, 1200 gauged river cross-sections were examined. For each site, we created a set of 24 SWOT-simulated FDCs (i.e., based on different sampling recurrences, mean biases, and random errors) to be compared against their empirical counterparts through the Nash–Sutcliffe efficiency and the mean relative error. Our results show that climate and the sampling recurrence play a key role on the performance of SWOT-based FDCs. Tropical and temperate climates performed the best, whereas arid climates mostly revealed higher uncertainties, especially for high- and low-flows. [ABSTRACT FROM AUTHOR]

Using the wide‐swath sea surface height (SSH) data from the 1‐day repeat calibration/validation phase of the Surface Water and Ocean Topography (SWOT) mission, we explored fine‐scale evolution of nonlinear internal solitary waves (ISWs) in the Banda/Molucca Seas in the Indonesian Archipelagos. Generated in the Ombai Strait and Lifamatola Passage through semidiurnal tide‐topography interaction, respectively, ISWs in the Banda/Molucca Seas have a SSH amplitude of 10–20 cm and exhibit multiple wave packets with the leading wave crest followed by a series of rank‐ordered secondary wave crests. Due to nonlinearity, the ISWs are observed to propagate northward at a speed faster than the regional mode‐1 internal gravity waves and their amplitudes are modulated fortnightly following the regional spring‐neap tidal cycle. On longer timescale, the observed ISW amplitudes are controlled by seasonal upper ocean stratification changes with a weaker stratification favoring a larger amplitude. By converting the SWOT‐measured SSH data to the interior ocean pressure signals, we quantified the depth‐integrated energy flux associated with the northward‐propagating ISWs to be 5 and 2 kW m−1 in the central Banda and Molucca Seas, respectively. Comparisons with past studies indicate that the ISWs contribute to close to 100% and 40% of the tidally‐induced, northward energy fluxes, respectively, across the Banda and Molucca Seas. Plain Language Summary: The Indonesian Archipelago is known to have complex bathymetry with numerous islands and straits. Being in the tropics, it is also where upper ocean is well stratified. As the tidal currents pass through the constricted straits, they enhance the through‐strait flows and form a breeding ground for internal solitary waves (ISWs). ISWs commonly appear as wave packets that contain multiple wave crests in surface ocean with a sea surface height (SSH) amplitude of 10–20 cm and an inter‐crest separation of 10–20 km. In this study, we used the daily, wide‐swath SSH measurements from the recently‐launched Surface Water and Ocean Topography satellite to investigate the ISW's dynamical properties and evolution in the Banda and Molucca Sea. We found that the observed ISW signals modulated not only by the regional spring‐neap tidal cycle, but also by the seasonally‐varying upper ocean stratification. Unlike other remote‐sensing technologies, the measurement of SSH allowed us to further quantify the energetics of the ISWs. It is important to explore the ISWs because their propagation carries with them substantial velocity shear that can lead to oceanic turbulence and mixing. In addition, the flow divergence/convergence along the ISW pathways can exert impact on upper ocean biogeochemical properties and variability. Key Points: Sea surface height (SSH) measurements from 1‐day repeat Surface Water and Ocean Topography mission captured evolution of internal solitary waves (ISWs) in Banda/Molucca SeasISWs are found to move faster than mode‐1 gravity waves and their amplitudes are modulated by spring‐neap cycle and seasonal stratificationBeing a dynamical property, SSH measurements allow us to evaluate ISW energy fluxes and be compared to those associated with internal tides [ABSTRACT FROM AUTHOR]

Over 9 years of hourly surface current data from high‐frequency radar (HFR) off the US West Coast are analyzed using a Bayesian least‐squares fit for tidal components. The spatial resolution and geographic extent of HFR data allow us to assess the spatial structure of the non‐phase‐locked component of the tide. In the frequency domain, the record length and sampling rate allow resolution of discrete tidal lines corresponding to well‐known constituents and the near‐tidal broadband elevated continuum resulting from amplitude and phase modulation of the tides, known as cusps. The FES2014 tide model is used to remove the barotropic component of tidal surface currents in order to evaluate its contribution to the phase‐locked variance and spatial structure. The mean time scale of modulation is 243 days for the M2 constituent and 181 days for S2, with overlap in their range of values. These constituents' modulated amplitudes are significantly correlated in several regions, suggesting shared forcing mechanisms. Within the frequency band M2 ± 5 cycles per year, an average of 48% of energy is not at the phase‐locked frequency. When we remove the barotropic model, this increases to 64%. In both cases there is substantial regional variability. This indicates that a large fraction of tidal energy is not easily predicted (e.g., for satellite altimeter applications). The spatial autocorrelation of the non‐phase‐locked variance fraction drops to zero over a distance of 150 km, a scale that is comparable to the swath width of the Surface Water and Ocean Topography altimeter. Plain Language Summary: Tides in the ocean encompass both the highly predictable daily changes in sea level seen from the shore as well as a less predictable component that changes over time depending on seasonal conditions and wind. Tidal signals are detectable at the ocean surface, for example, via satellite or land‐based radar antenna. The time‐evolving tide signals interact with other processes in the ocean, like currents, and can become harder to predict and describe. Many studies have examined this aspect of tides. In this work, we use land‐based radar observations of ocean currents off the US West Coast to examine this process with high detail, using mathematical techniques to separate the tides from everything else and then evaluating how much the tide has been altered by other processes. This is useful because ocean‐observing satellites can observe a single part of the ocean only when the satellite passes overhead, approximately every 10–20 days, while the data we analyze are sampled hourly and thus more easily allow us to draw conclusions about how tides behave. Key Points: In the California Current System, High‐Frequency Radar resolves stationary and non‐stationary tidesBroadband cusps occur at tidal constituent frequencies, with M2 exhibiting annual modulationWe analyze the tidal modulation to assess physics governing non‐stationary tidal variability [ABSTRACT FROM AUTHOR]

The recently deployed Surface Water and Ocean Topography (SWOT) mission for the first time has observed the ocean surface at a spatial resolution of 1 km, thus giving an opportunity to directly monitor submesoscale sea surface height (SSH) variations that have a typical magnitude of a few centimeters. This progress comes at the expense of the necessity to take into account numerous uncertainties in calibration of the quality-controlled altimeter data. Of particular importance is the proper filtering of spatially correlated errors caused by the uncertainties in geometry and orientation of the on-board interferometer. These "systematic" errors dominate the SWOT error budget and are likely to have a notable signature in the SSH products available to the oceanographic community. In this study, we explore the utility of the block-circulant (BC) approximation of the SWOT precision matrix developed by the Jet Propulsion Laboratory for assessment of a mission's accuracy, including the possible impact of the systematic errors on the assimilation of the wide-swath altimeter data into numerical models. It is found that BC approximation of the precision matrix has sufficient (90–99%) accuracy for a wide range of significant wave heights of the ocean surface, and, therefore, could potentially serve as an efficient preconditioner for data assimilation problems involving altimetry observations by space-borne interferometers. An extensive set of variational data assimilation (DA) experiments demonstrates that BC approximation provides more accurate SSH retrievals compared to approximations, assuming a spatially uncorrelated observation error field as is currently adopted in operational DA systems. [ABSTRACT FROM AUTHOR]

This study evaluates the feasibility of applying the Estimating the Circulation and Climate of the Ocean (ECCO) data assimilation (DA) framework to a submesoscale-resolving model [Massachusetts Institute of Technology General Circulation Model (MITgcm), at 1-km grid resolution]. This is in preparation for future studies to understand and assimilate the novel swath measurements of sea surface height from the Surface Water and Ocean Topography (SWOT) satellite mission. The model domain is centered at the SWOT calibration/validation (CalVal) site, located 300 km offshore of Monterey Bay, California. We assimilate vertical profiles of temperature and salinity from a linear array of three SWOT prelaunch CalVal moorings, between September and December 2019. Two model solutions are analyzed: 1) a nonassimilating forward simulation termed "first-guess" and 2) an optimized solution that assimilates the in situ observations. Both runs are nested within the global 1/12° Hybrid Coordinate Ocean Model that uses Navy Coupled Ocean Data Assimilation (HYCOM/NCODA) analysis. We evaluate the performance by comparing the two model solutions against assimilated and withheld in situ observations. We show that by assimilating hydrographic data, the model performance over the first-guess solution is improved with an error-to-observation reduction of 30%–45% for temperature, 14%–41% for salinity, and 44%–56% for steric height. Over the study period, the average steric height error at the three assimilated moorings was 1.27 cm for the optimized solution versus 2.6 cm for the first-guess solution. A comparison to withheld glider observations shows that the optimized solution outperforms the first-guess solution with an error-to-observation reduction of approximately 38% in steric height (1.5 versus 2.4 cm). This study indicates, for the first time, that the MITgcm–ECCO framework can be successfully applied to the reconstruction of submesoscale ocean variability, via the nesting of a high-resolution regional domain into a global outer domain. [ABSTRACT FROM AUTHOR]

Launched on 2022 December 16, the Surface Water and Ocean Topography (SWOT) satellite, using synthetic aperture radar interferometric techniques, measures sea surface heights (SSHs) across two 50-km-wide swaths, offering high-resolution and accurate 2-D SSH observations. This study explores the efficiency of SWOT in seamount detection employing the vertical gravity gradient (VGG) derived from simulated SWOT SSH data. Simulated circular and elliptical seamounts (height: 900–1500 m) are integrated within the South China Sea's 4000 m background depths. Geoid perturbations induced by these seamounts are extracted through the residual depth model principle, subsequently merged with the DTU21MSS model for simulating SWOT SSH observations. For comparative assessment, SSH data from Jason-2 and Cryosat-2 are included. An automatic algorithm (AIFS) is presented to identify seamount centres and base polygons using VGG derived from simulated altimeter SSH data. The analysis reveals SWOT-derived VGGs precisely locate all seamount centres, base polygons and elliptical seamount azimuths. The merged Jason-2 and Cryosat-2 data face challenges with identifying small circular and elliptical seamounts. Detecting long narrow elliptical seamounts remains arduous; however, SWOT-derived VGGs successfully elucidate the approximate shapes and major axis azimuths of the elliptical seamounts. Validated against 'true values' of VGG, the root-mean-squared deviation (RMSD) of SWOT-derived VGG stands at 1.33 Eötvös, whereas the merged Jason-2 and Cryosat-2 data exhibit an RMSD of 1.93 Eötvös. This study shows the enhanced capability of SWOT from its high-resolution 2-D SSH observations in advancing seamount detection via satellite-derived VGG. We identify challenges and recommend improved detections using data integration and machine learning. [ABSTRACT FROM AUTHOR]

We assess the accuracy and spatial resolution of the surface water and ocean topography (SWOT) swath altimeter for deriving marine gravity anomalies. The analysis is performed at the Foundation Seamounts in the South Pacific where we developed a highly accurate gravity field by combining the long‐wavelength (>40 km) gravity field derived from previous nadir altimeters with the shorter wavelength gravity field from the seafloor topography as constrained by the ship gravity. In this region, the sea surface slope (SSS) of the ocean variability is 50–100 times smaller than the slope signal of the seamounts so can be ignored in the analysis. Each SWOT cycle can deliver SSS accurately with a standard deviation of 2.6 µrad and a spatial resolution of 14 km at typical sea state (significant wave height 4 m), with accuracy diminishing at high significant wave heights (e.g., exceeds 6 m). Averaging repeated SWOT measurements improves the accuracy and resolution. For example, we expect that averaging just 10 repeats (7 months) results in accuracy/resolution that matches the best marine gravity maps based on 230 months of nadir altimetry. With a mission lasting over a year, SWOT promises a substantial leap in marine gravity accuracy and resolution, uncovering previously uncharted details of the seafloor, including thousands of uncharted seamounts. Plain Language Summary: The surface water and ocean topography (SWOT) is a satellite mission designed to measure Earth's water body heights in wide‐swath, offering opportunities to measure the ocean surface in unprecedented details. This capability brings valuable high‐resolution information about the gravity field and seafloor underneath the ocean. This study aims to evaluate SWOT's performance and our test area is in the South Pacific Ocean where we already know the ocean topography and gravity field well. Results show that with SWOT global measurements lasting over 1 year, it promises a significant improvement in uncharted details of the seafloor. Key Points: A single cycle of surface water and ocean topography (SWOT) at a typical significant wave height of 4 m, has an accuracy of 2.6 μrad and a spatial resolution of 14 kmA stack of ∼60 cycles of SWOT data provides a significant improvement in accuracy to ∼1.2 μrad and spatial resolution ∼8 kmThe accuracy and resolution of the marine gravity field derived from SWOT will exceed current models after 8 months [ABSTRACT FROM AUTHOR]

Satellite altimetry offers a unique approach for direct sea surface current observation, but it is limited to measuring the surface‐constrained geostrophic component. Ageostrophic dynamics, prevalent at horizontal scales below 100 km and time scales below 10 days, are often underestimated by ocean reanalyzes employing data assimilation schemes. To address this limitation, we introduce a novel deep learning scheme, rooted in a variational data assimilation formulation with trainable observations and a priori terms, that harnesses the synergies between satellite‐derived sea surface observations, namely sea surface height (SSH) and sea surface temperature (SST), to enhance sea surface current reconstruction. Numerical experiments, conducted using realistic simulations, in a case study area of the Gulf Stream, demonstrate the potential of the proposed scheme to capture ageostrophic dynamics at time scales of 2.5–3.0 days and horizontal scales of 0.5°–0.7°. The analysis of diverse observation configurations, encompassing nadir along‐track altimetry, wide‐swath SWOT (Surface Water and Ocean Topography) altimetry, and SST data, highlights the pivotal role of SST features in retrieving a significant portion of the ageostrophic dynamics (approximately 47%). These findings underscore the potential of deep learning and 4DVarNet schemes in improving ocean reanalyzes and enhancing our understanding of ocean dynamics. Plain Language Summary: Satellite altimetry provides a unique means for direct observation of sea surface currents, but it is confined to the geostrophic component, limiting the recovery of a substantial portion of mesoscale sea surface currents in operational products. To address this limitation, we present a novel deep learning framework, rooted in a variational data assimilation paradigm, that unlocks new avenues for leveraging the synergistic relationships between satellite‐derived sea surface observations, namely sea surface height and sea surface temperature. This innovative scheme demonstrates its remarkable potential to enhance sea surface current reconstruction and recover a substantial portion of the elusive ageostrophic dynamics. Numerical experiments, employing realistic simulations, in a case study area along the Gulf Stream, underscore the efficacy of our proposed approach. These findings support the pivotal role of physics‐informed deep learning in maximizing the utilization of available multimodal observation data sets and numerical simulations to elucidate partially observed sea surface dynamics. Key Points: We present end‐to‐end deep learning schemes to improve the reconstruction of total sea surface currents from satellite‐derived observationsExperiments in a region of the Gulf Stream support the synergistic analysis of sea surface temperature and sea surface height dataThe strain of sea surface dynamics is a proxy of the uncertainty of the retrieved estimation [ABSTRACT FROM AUTHOR]

This paper examines spectra of horizontal kinetic energy (HKE) in the surface and sub‐surface ocean, with an emphasis on internal gravity wave (IGW) motions, in global high‐resolution ocean simulations. Horizontal wavenumber‐frequency spectra of surface HKE are computed over seven oceanic regions from two global simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three global simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). In regions with high IGW activity, high surface HKE variance in the horizontal wavenumber‐frequency spectra is aligned along IGW linear dispersion curves. For both HYCOM and MITgcm, and in almost all regions, finer horizontal resolution yields more energetic supertidal IGW continuum spectra. The ratio of high‐horizontal‐wavenumber variance in semi‐diurnal and supertidal motions relative to lower‐frequency motions, a quantity of great interest for swath altimetry, depends on the model employed and the horizontal resolution within the model, implying that quantitative predictions of the partition between low‐ and high‐frequency motions taken from particular simulations should be treated with care. The frequency‐vertical wavenumber spectra, frequency spectra, and vertical wavenumber spectra from the models are compared to spectra computed from McLane profilers at nine locations. In general, MITgcm spectra match the McLane profiler spectra more closely at high frequencies (|ω| > 4.5 cpd). In both models, vertical wavenumber spectra roll off more steeply than observations at high vertical wavenumbers (m > 10−2 cpm). The vertical wavenumber spectra in such models is an important target for improvement, due to turbulence production and dissipation that takes place at high vertical wavenumbers. Plain Language Summary: Recently, a small but growing number of global ocean models have begun to employ simultaneous tidal and atmospheric forcing. At the same time, increasing supercomputer power has allowed for simulations of oceanic motions with increasing accuracy, increasing feature (spatial) resolution, and more frequent time slices. Global ocean models with fine grid spacing, and simultaneous tidal and atmospheric forcing, host a vigorous spectrum of high‐frequency waves that control mixing over most of the ocean water column, and are important for many operational oceanography challenges. As an example of the latter, high‐resolution global internal wave models have been used to study the relative partition of high‐frequency versus low‐frequency motions at the small horizontal scales that will be measured by the new Surface Water Ocean Topography mission. The partition described above depends on the model employed and the grid spacing employed within that model, meaning that conclusions about the partition are dependent on the model used to estimate it. Comparisons between the models and vertically profiling instruments indicate that resolving fine scale motions in the vertical direction, where ocean mixing takes place, is not yet handled well by the models. Modeling of fine‐vertical scale motions is therefore an important future research direction. Key Points: Vertical wavenumber spectra of internal gravity wave kinetic energy in two high‐resolution global models are compared to observed spectraModels under‐estimate motions at high vertical wavenumbers (small vertical scales), flagging this as a target for model improvementThe ratio of high‐ versus low‐frequency surface kinetic energy at small horizontal scales is dependent on the model and grid spacings employed [ABSTRACT FROM AUTHOR]

The wide-swath altimeter satellite Surface Water and Ocean Topography (SWOT) will provide high spatiotemporal resolution sea surface heights (SSHs), which is crucial for studying the impact of observation errors on marine gravity recovery. This study uses simulated SWOT data to derive deflection of the vertical (DOV) and gravity anomalies in the northern South China Sea. We quantified the impact of SWOT errors on DOV and gravity anomalies, and analysed the contributions from different directions of geoid gradient. The results show that the geoid gradient in the cross-track direction significantly improves gravity field recovery by enhancing the precision of east component of DOV. For one-cycle SWOT observations, phase errors emerge as the most impactful error affecting both DOV and gravity anomalies, followed by random errors. 2-D Gaussian filtering and the tilt correction proposed in this study could effectively mitigate their impact. Using the corrected data for DOV computation, the precision in the east and north components improves by 75.32 and 46.80 per cent, respectively, while enhancing the accuracy of the gravity field by 70.23 per cent. For 17-cycle data, phase errors and random errors remain the predominant factors affecting DOV and gravity anomalies, but their impact diminishes with an increase in SWOT observations. Our results indicate that marine gravity accuracy improves by approximately 70 per cent compared to a single cycle. Whether for single-cycle or multicycle data, the impact of phase errors is roughly twice that of random errors. These data processing strategies can serve as valuable references for wide-swath altimeter data processing, aiming to advance the precision and resolution of marine gravity field recovery. [ABSTRACT FROM AUTHOR]

The Surface Water and Ocean Topography (SWOT) mission, launched in December 2022, aims to address the crucial environmental goal of water monitoring to support preparedness for extreme events and facilitate adaptation to climate change on global and local scales. This mission will provide a comprehensive inventory of worldwide water resources, lakes, reservoir storage, and river dynamics. In this work, we carried out a preliminary assessment of SWOT's Lake product Level 2 version 1.1, also known as "L2_HR_LakeSP". The analysis was performed across six diverse lakes on three continents, revealing an average median bias of 0.08 m with respect to the considered reference, after suitable outlier removal. An overall precision of 0.22 m was found, combined with an average correlation of 68% between SWOT and reference time series. Moreover, the accuracy varied in the considered six lakes, since biases up to some decimeters were found for some of them; they could be due to residual inconsistencies between the vertical reference frame of SWOT and that of the considered reference. In summary, the first analysis of the "L2_HR_LakeSP" product, Version 1.1, demonstrated the promising potential of SWOT for monitoring seasonal variations in water levels. Nevertheless, notable anomalies were found in the water masks, particularly in higher latitudes, suggesting potential difficulties in accurately delineating water bodies in those regions. Additionally, a discernible reduction in accuracy was observed towards the end of the monitoring period. These preliminary findings indicate some issues that should be addressed in future investigations about the quality and potential of SWOT's lake products for advancing our understanding of global water dynamics. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach to enhance the assimilation of high-resolution simulated observations, specifically targeting Surface Water Ocean Topography (SWOT) Ka-band Radar Interferometer Sea Surface Height (SSH) products, within the Regional Ocean Modeling System (ROMS). Responding to the demand for improved assimilation techniques, we developed a multi-scale Four-Dimensional Variational Data Assimilation (4DVAR) system, building upon validated fine-scale correction capabilities from prior studies. The multi-scale strategy was extended to the ROMS-4DVAR system, providing a comprehensive solution for assimilating high-resolution observations. Leveraging the Observing System Simulation Experiment (OSSE) framework, we conducted a twin experiment comprising a nature run and a free run case. Subsequently, synthetic SWOT SSH measurements were decomposed, considering the model configuration resolution. These components, derived from dense SSH observations, were integrated into a two-step 4DVAR assimilation scheme. The first cycle targets large-scale features for model field correction, and the updated analysis serves as the background for the second assimilation step, addressing fine-scale observation components. Comparisons with the primitive ROMS-4DVAR using a single-scale scheme highlight the superiority of the multi-scale strategy in reducing gaps between the model and the SSH observations. The Root Mean Squared Error (RMSE) is halved, and the Mean Absolute Percentage Error (MAPE) decreases from 2.237% to 0.93%. The two-step assimilation procedure ensures comprehensive multi-scale updates in the SSH field simulation, enhancing fine-scale features in the analysis fields. The quantification of three-dimensional-model dynamic fields further validates the efficiency and superiority of the multi-scale 4DVAR approach, offering a robust methodology for assimilating high-resolution observations within the ROMS. [ABSTRACT FROM AUTHOR]

The elevations of water surfaces hold important information on the earth's oceans and land surface waters. Ocean sea surface height is related to the internal change of the ocean's density and mass associated with ocean circulation and its response to climate change. The flow rates of rivers and volume changes of lakes are crucial to freshwater supplies and the hazards of floods and drought resulting from extreme weather and climate events. The Surface Water and Ocean Topography (SWOT) Mission is a new satellite using advanced radar technology to make headway in observing the variability of the elevation of water surfaces globally, providing fundamentally new information previously not available to the study of earth's waters. Here, we provide the first results of SWOT over oceans, rivers, and lakes. We demonstrate the potential of the mission to address science questions in oceanography and hydrology. Plain Language Summary: Earth is a water planet. The vast amount of ocean water has stored most of the heat released to the atmosphere since the Industrial Revolution through burning fossil fuels. Climate change is thus moderated by the ocean. Over land the freshwater in lakes, rivers, and reservoirs, a critical natural resource, is affected by the warming climate and direct human modifications. Processes of oceanic uptake of heat and carbon from the atmosphere and cycling of freshwater on land take place at spatial scales too small to have been adequately quantified from space. A new satellite, the Surface Water and Ocean Topography (SWOT) mission, was launched in December 2022. Using advanced radar technology, SWOT provides unprecedented global observations for understanding the ocean's role in climate change and how freshwater resources respond to human influence. SWOT observations near coasts will also advance understanding of how rising sea levels impact those coasts. Key Points: The first space observations of submesoscale ocean surface topography for understanding ocean's role in heat uptake from the atmosphereThe first space observations of the change of water storage of lakes and flow rates of rivers for understanding the freshwater cycleThe first space observations of the details of the change of coastal water levels to assess the impact of local sea level rise [ABSTRACT FROM AUTHOR]

Observing System Simulation Experiments (OSSEs) with the Mercator Ocean/Copernicus Marine global 1/12° data assimilation system has been carried out to compare and quantify the expected performance of two high resolution altimetry mission concepts envisioned for the long-term evolution (post-2032) of the Copernicus Sentinel-3 topography mission. The two mission concepts are a constellation of two wide-swath altimeters and a constellation of 12 nadir altimeters. These two configurations greatly improve ocean forecasting and monitoring capabilities. Compared to a constellation of three nadir altimeters (the present configuration), analysis and forecast errors are reduced by a factor of 2. Our results also show that a constellation of two wide-swath altimeters has better performance than a constellation of 12 nadirs. Compared to a constellation of 12 nadirs, the error of the Sea Surface Height (SSH) forecast of a two wide swath constellation will be reduced by 14% overall. Improvements are also observed when analyzing surface currents and Lagrangian diagnostics. A constellation of two wide-swath altimeters thus seems to be a very promising concept for the long-term evolution of the Sentinel-3 topography mission. [ABSTRACT FROM AUTHOR]

Full tensor of gravity gradients contains extremely large amounts of information, which is one of the most important sources for research on recovery seafloor topography and underwater matching navigation. The calculation and accuracy of the full tensor of gravity gradients are worth studying. The Ka-band interferometric radar altimeter (KaRIn) of surface water and ocean topography (SWOT) mission enables high spatial resolution of sea surface height (SSH), which would be beneficial for the calculation of gravity gradients. However, there are no clear accuracy results for the gravity gradients (the gravity gradient tensor represents the second-order derivative of the gravity potential) recovered based on SWOT data. This study evaluated the possible precision of gravity gradients using the discretization method based on simulated SWOT wide-swath data and investigated the impact of instrument errors. The data are simulated based on the sea level anomaly data provided by the European Space Agency. The instrument errors are simulated based on the power spectrum data provided in the SWOT error budget document. Firstly, the full tensor of gravity gradients (SWOT_GGT) is calculated based on deflections of the vertical and gravity anomaly. The distinctions of instrument errors on the ascending and descending orbits are also taken into account in the calculation. The precision of the Tzz component is evaluated by the vertical gravity gradient model provided by the Scripps Institution of Oceanography. All components of SWOT_GGT are validated by the gravity gradients model, which is calculated by the open-source software GrafLab based on spherical harmonic. The Tzz component has the poorest precision among all the components. The reason for the worst accuracy of the Tzz component may be that it is derived by Txx and Tyy, Tzz would have a larger error than Txx and Tyy. The precision of all components is better than 6 E. Among the various errors, the effect of phase error and KaRIn error (random error caused by interferometric radar) on the results is greater than 2 E. The effect of the other four errors on the results is about 0.5 E. Utilizing multi-cycle data for the full tensor of gravity gradients recovery can suppress the effect of errors. [ABSTRACT FROM AUTHOR]

Lakes are valuable water resources that support aquatic and terrestrial ecosystems and supply fresh water for the agricultural, industrial, and urban sectors worldwide. Although water levels should be tracked to monitor these services, conventional gauging is unfeasible in most lakes. This study applies Differential Interferometric Synthetic Aperture Radar (D‐InSAR) to estimate small water level changes, less than 2 cm, in Swedish lakes over 6‐day intervals. We validated the method across the shores of 30 Swedish lakes with gauged observations in 2019. We used Sentinel‐1A/B images with a 6‐day temporal separation to construct consecutive interferograms and accumulated the phase changes in pixels of high coherence to build a time series of water levels. We find that the accumulated phase change obtained by D‐InSAR replicates the magnitude of water levels in seven lakes in Southern Sweden, where water levels change slowly, less than 2 cm per 6‐day period, as validated by in‐situ gauges. In addition, this study demonstrates the application of D‐InSAR to estimate the long‐term direction of water level change (i.e., increase or decrease) in all 30 lakes. This work reveals the utility of high temporal resolution water level observations in support of other satellite water level instruments such as conventional altimeters and the recently launched Surface Water and Ocean Topography Mission. Key Points: Small water level changes in seven lakes in South Sweden revealed by D‐InSARReplicating the seasonal timing of high and low lake water levels by D‐InSAR [ABSTRACT FROM AUTHOR]

Satellite altimetry sea surface height measurements from 1993 to 2022 are used to show the strengthened mode‐1 M2 internal tides in the past 30 years. Two mode‐1 M2 internal tide models M9509 and M1019 are constructed using the data in 1995–2009 and 2010–2019, respectively. The results show that the global mean M2 internal tides strengthened by 6% in energy. However, the internal tide strengthening is spatially inhomogeneous. Significantly strengthened internal tides are observed in a number of regions including the Aleutian Ridge and the Madagascar‐Mascarene region. Weakened internal tides are observed in the central Pacific. On global average, M1019 leads M9509 by about 10° (20 min in time), suggesting that the propagation speed of M2 internal tides increased. M9509 and M1019 are evaluated using independent altimetry data. The results show that M9509 and M1019 perform better for the data in 1993–1994 and 2020–2022, respectively. Plain Language Summary: It is not surprising that ocean stratification increases with global ocean warming, because the upper ocean stores more extra heat and becomes lighter. Given that ocean stratification becomes stronger, it is naturally expected that internal tides should strengthen with global ocean warming as well. However, it is extremely difficult to quantify internal tide strengthening on a global scale. Here we show for the first time that mode‐1 M2 internal tides strengthened in the past 30 years using satellite altimetry data from 1993 to 2022. We further show that the internal tide strengthening is spatially inhomogeneous, which has important implications on the downward heat transport. The strengthened internal tides and eventual ocean mixing may facilitate the vertical transport of tracers and nutrients, compensating partly for the reduction caused by strengthened ocean stratification. The results suggest that the long‐term changes should be taken into account in making internal tide correction for the Surface Water and Ocean Topography (SWOT) mission. Key Points: Mode‐1 M2 internal tide models M9509 and M1019 are constructed using satellite altimetry data in 1995–2009 and 2010–2019, respectivelyMode‐1 M2 internal tides strengthened and their speeds increased; however, the internal tide strengthening is spatially inhomogeneousM9509 (M1019) performs better in making internal tide correction to independent satellite altimetry data in 1993–1994 (2020–2022) [ABSTRACT FROM AUTHOR]

In late 2023 the Surface Water and Ocean Topography (SWOT) satellite mission will release unprecedented high-resolution measurements of water surface elevation (WSE) and water surface slope (WSS) globally. SWOT's exciting Ka-band near-nadir wide-swath interferometric radar (InSAR) technology could transform studies of surface water hydrology, but remains highly experimental. We examine Airborne SWOT (AirSWOT) data acquired twice over Canada's Peace-Athabasca Delta (PAD), a large, low-gradient, ecologically important riverine wetland complex. While noisy and susceptible to "dark water" (low-return) data losses, spatially averaged AirSWOT WSE observations reveal a broad-scale water-level decline of ~44 cmn (σ =271 cm) between 9 July and 13 August 2017, similar to a ~56 cm decline (σ=33 cm) recorded by four in situ gauging stations. River flow directions and WSS are correctly inferred following filtering and reach-averaging of AirSWOT data, but ~10 km reaches are essential to retrieve them. July AirSWOT observations suggest steeper WSS down an alternate flow course (Embarras River–Mamawi Creek distributary) of the Athabasca River, consistent with field surveys conducted the following year. This signifies potential for the Athabasca River to avulse northward into Mamawi Lake, with transformative impacts on flooding, sedimentation, ecology, and human activities in the PAD. Although AirSWOT differs from SWOT, we conclude SWOT Ka-band InSAR observations may detect water level changes and avulsion potentials in other low-gradient deltas globally. [ABSTRACT FROM AUTHOR]

This document is an editorial published in the journal Frontiers in Marine Science. It discusses the importance of understanding and predicting the ocean dynamics in the Gulf of Mexico. The Gulf of Mexico has been a focus of research due to its significance in maritime transportation, the petroleum industry, and its impact on regional ecosystems, weather, and climate. The editorial highlights recent research efforts to improve understanding and forecasting capabilities of the Gulf of Mexico circulation, particularly the Loop Current and its associated eddies. The document also mentions collaborative research programs and initiatives aimed at reducing risks to offshore energy exploration, forecasting hurricane intensification, and managing fisheries. The editorial concludes by summarizing the articles included in the research topic, which provide new insights into the Gulf of Mexico circulation and its impacts on ecosystems, climate, and weather. The authors express their hope that these articles will contribute to a greater understanding and skillful prediction of the Gulf of Mexico system. [Extracted from the article]

The wide-swath altimetry mission, Surface Water and Ocean Topography (SWOT), makes it possible to further break through the accuracy and resolution of marine gravity field recovery. However, as its main payload, the Ka-band radar interferometer (KaRIN) is easy to be affected by the spacecraft attitude, mechanical deformations and dual antenna signal reception status, which generates instrumental errors including roll errors, phase errors, baseline dilation errors, timing errors, and KaRIN noise. Together with ocean temporal variations, the instrumental errors have large effects on the SWOT Sea Surface Height (SSH) observations and hence the marine gravity field recovery. Here, taking the sea area around Japan as an example, we investigated the calibrations of instrumental errors and ocean temporal variations on the recovery of the marine gravity field. The SSH observations of SWOT are first simulated by Mean Sea Surface (MSS), Absolute Dynamic Topography (ADT), Mean Dynamic Topography (MDT) and instrumental errors. Next, the influence of instrumental errors on determining vertical deflection within single-cycle data was analyzed. Then, three calibration methods (KaRIN/KaRIN cross-calibration, Representative KaRIN/KaRIN cross-calibration, and KaRIN/Nadir cross-calibration) are used to reduce the instrumental errors; the experimental results show KaRIN/KaRIN cross-calibration is the optimal one. Last, for the multi-cycle observations containing ocean temporal variations, crossover calibration is done in single cycle and then followed by collinear adjustment in multi-cycles. This approach is verified by considering 18 simulated cycles that cover almost 1 year. Our result indicates an improvement in the accuracy of marine gravity anomaly by about 45% compared to that of one cycle. The calibration strategy of instrumental errors and ocean temporal variations can be used for high-precision marine gravity field recovery with abundant SWOT observations in the near future. [ABSTRACT FROM AUTHOR]

With the success of the Sentinel‐6 Michael Freilich satellite, the satellite radar altimetry record of sea level has now surpassed 30 years in length. This reference satellite mission has continued uninterrupted alongside a significant expansion of the satellite sea‐level observing network in the past decade. This expansion was punctuated by the launch of the Surface Water and Ocean Topography mission in December 2022, which will bring higher resolution measurements of sea level closer to the shore than ever before. Here, we take stock of where we are now in terms of using satellites to measure sea level, and what is still needed to address the growing need of those living along the coast for information to support planning and adaptation efforts. Key Points: With the launch of the Sentinel‐6 MF satellite, the satellite radar altimetry record of sea level has now surpassed 30 years in lengthOther satellites have been launched—including the Surface Water and Ocean Topography mission—that complement the altimeter missionFuture missions should be targeted to provide the information that coastal communities need to prepare for rising sea levels [ABSTRACT FROM AUTHOR]

Ocean vertical velocity (w) plays a key role in regulating the exchanges of mass, heat and nutrients between the surface and deep ocean. However, direct observation remains difficult due to its small magnitude and large spatiotemporal variability. Therefore, w fields are generally diagnosed using dynamic‐based methods. In this study, we developed a deep neural network (DNN) to reconstruct three‐dimensional fields of ocean vertical velocity based on sea surface height (SSH) fields. Compared to dynamic‐based methods, the DNN shows improved performance in the w reconstruction within upper 500 m in terms of higher correlation and less error. Remarkably, the DNN requires only a ∼45 × 45 km size SSH image as input to estimate w at the center. This suggests that the DNN has great potential for w reconstruction in the future combined with high‐resolution observations such as the Surface Water and Ocean Topography mission. Plain Language Summary: Direct measurement of ocean vertical motion is challenging because it is too weak and unstable. However, understanding this vertical motion is important to study the heat/material transports in the oceans and even climate variability. Here, we propose a deep learning‐based method that uses only the sea surface height (SSH) fields to reconstruct ocean vertical velocity. Our results indicate that this new reconstruction method outperforms the conventional method, particularly in the upper ocean. Moreover, the less data input makes it possible to be an effective tool for reconstructing oceanic vertical velocity with high‐resolution SSH observations in the future. This demonstrates the promise of using deep learning to estimate hard‐to‐measure ocean features, improving our knowledge of ocean processes related to climate. Key Points: A deep learning (DL) based approach is developed to reconstruct the ocean vertical velocityUsing the modeled sea surface height (SSH) as input, the DL approach outperforms the dynamic‐based methodThe DL approach has the potential to improve the retrieval of real‐time vertical velocity field along the SWOT swaths [ABSTRACT FROM AUTHOR]

The interferometric imaging radar altimeter (InIRA), mounted on the Tiangong-2 space laboratory, utilizes a small incidence and a short interferometric baseline to achieve altimetry for wide swathes of ocean surface topography and inland water surface elevation. To obtain a high-precision digital elevation model (DEM), calibration of the interferometric system parameters is necessary. Because InIRA utilizes the small-incidence interference system design, serious coupling occurs between the interferometric parameters. Commonly used interferometric calibration methods tend to fall into the local optimal solution for InIRA. Because evolutionary algorithms have a stronger robustness and global search ability, they are better suited to handling the solution space structure under the coupling of complex interferometric parameters. This article establishes an interferometric calibration optimization model for InIRA by utilizing the relative flatness of the lake surface as an inequality constraint. Furthermore, an adaptive penalty coefficient constraint evolutionary algorithm is designed to solve the model. The proposed method was tested on actual InIRA data, and the results indicate that it efficiently adjusts interferometric parameters, enhancing the precision of measurements for Qinghai Lake elevation. [ABSTRACT FROM AUTHOR]

This paper reviews the recent progress in our estimation of ocean dynamic topography and the derived surface geostrophic currents, mainly based on multiple nadir radar altimeter missions. These altimetric observations provide the cornerstone of our ocean circulation observing system from space. The largest signal in sea surface topography is from the mean surface dominated by the marine geoid, and we will discuss recent progress in observing the mean ocean circulation from altimetry, once the geoid and other corrections have been estimated and removed. We then address the recent advances in our observations of the large-scale and mesoscale ocean circulation from space, and the particular challenges and opportunities for new observations in the polar regions. The active research in the ocean barotropic tides and internal tidal circulation is also presented. The paper also addresses how our networks of global multi-satellite and in situ observations are being combined and assimilated to characterize the four-dimensional ocean circulation, for climate research and ocean forecasting systems. For the future of ocean circulation from space, the need for continuity of our current observing system is crucial, and we discuss the exciting enhancement to come with global wide-swath altimetry, the extension into the coastal and high-latitude regions, and proposals for direct total surface current satellites in the 2030 period. [ABSTRACT FROM AUTHOR]

The Surface Water & Ocean Topography (SWOT) mission is a joint NASA/CNES mission launched on December 16th, 2022 dedicated to oceanography and continental hydrology. Once the scientific mission is over, SWOT will have to perform a controlled re-entry to comply with the French Space Operation Act (FSOA). Indeed, the launch authorization is subject to the respect of the FSOA, fully applicable since 2020. The main requirement applying to the end-of-life of the satellite consists in limiting the casualty area and then the probability of having a victim on ground under the threshold of 10−4 in case of a natural re-entry. With a mass over two tons and a casualty area of about 47 m2, SWOT cannot comply with this requirement. Thus, the platform has been designed with a specific propulsion system to carry out end-of-life maneuvers leading to an atmospheric re-entry and impact in the South Pacific Ocean Uninhabited Area (SPOUA). CNES is in charge of defining the re-entry maneuvers strategy, performing end-of-life operations and evaluating the risk of casualties in case of failure during nominal strategy. This paper addresses these topics. The computation of the ten maneuvers used to decrease the perigee altitude and finally target the SPOUA is performed using the DOORS tool. Before describing the maneuvers strategy, this paper presents an overview of the current functionalities of this tool, which has been already used during the five ATV missions and ASTRA-1K de-orbit twenty years ago. DOORS is mainly used for mission analysis purposes, but for end-of-life operations it can be activated by the operational Flight Dynamics System (FDS). Finally, the casualty risk estimation relies on the use of two other CNES tools, DEBRISK and ELECTRA, whose methods are presented. The list of surviving fragments has been computed using the new DEBRISK-V3 methodology in case of controlled and uncontrolled re-entry. The risk of human casualty is evaluated using ELECTRA and its Monte Carlo simulations. This tool generates numerous trajectories of the satellite and its fragments with various dispersed variables. The impact locations compared to an up-to-date grid of the World population lead to the probability of victims. The complete risk of SWOT controlled re-entry encompasses both the risk related to a failure during the last re-entry maneuver and the risk associated with the natural re-entry in case a failure occurs before this last burn (during the mission or during the first re-entry maneuvers). Both of them are weighted by their probability of occurrence. • SWOT controlled re-entry strategy to fulfill French regulation. • Robustness test of the nominal strategy made of 10 maneuvers. • Latest aerothermodynamic models used to build the list of surviving fragments. • Probability of victims considers contingencies during the whole re-entry operation. • Combination of several CNES softwares: DOORS, PSIMU, DEBRISK, ELECTRA. [ABSTRACT FROM AUTHOR]

While satellite altimeters have revolutionized ocean science, validation measurements in high wave environments are rare. Using geodetic Global Navigation Satellite System (GNSS) data collected from the Southern Ocean Flux Station (SOFS; −47°S, 142°E) since 2019, as part of the Southern Ocean Time Series (SOTS), we present a validation of satellite missions in this energetic region. Here we show that high rate GNSS observations at SOFS can successfully measure waves in the extreme conditions of the Southern Ocean and obtain robust measurements in all wave regimes [significant wave height (SWH) ranging from 1.5 to 12.6 m]. We find good agreement between the in situ and nadir altimetry SWH (RMSE = 0.16 m, mean bias = 0.04 m, and n = 60). Directional comparisons with the Chinese–French Ocean Satellite (CFOSAT) Surface Waves Investigation and Monitoring (SWIM) instrument also show good agreement, with dominant directions having an RMSE of 9.1° (n = 22), and correlation coefficients between the directional spectra ranging between 0.57 and 0.79. Initial sea level anomaly (SLA) estimates capture eddies propagating through the region. Comparisons show good agreement with daily gridded SLA products (RMSE = 0.03 m, and n = 205), with scope for future improvement. These results demonstrate the utility of high rate geodetic GNSS observations on moored surface platforms in highly energetic regions of the ocean. Such observations are important to maximize the geophysical interpretation from altimeter missions. In particular, the ability to provide collocated directional wave observations and SLA estimates will be useful for the validation of the recently launched Surface Water and Ocean Topography (SWOT) mission where understanding the interactions between sea state and sea surface height poses a major challenge. [ABSTRACT FROM AUTHOR]

The Surface Water and Ocean Topography (SWOT) satellite is expected to observe sea surface height (SSH) down to scales approaching ∼15 km, revealing submesoscale patterns that have never before been observed on global scales. Features at these soon‐to‐be‐observed scales, however, are expected to be significantly influenced by internal gravity waves, fronts, and other ageostrophic processes, presenting a serious challenge for estimating surface velocities from SWOT observations. Here we show that a data‐driven approach can be used to estimate the surface flow, particularly the kinematic signatures of smaller scale flows, from SSH observations, and that it performs significantly better than using the geostrophic relationship. We use a Convolutional Neural Network (CNN) trained on submesoscale‐permitting high‐resolution simulations to test the possibility of reconstructing surface vorticity, strain, and divergence from snapshots of SSH. By evaluating success using pointwise accuracy and vorticity‐strain‐divergence joint distributions, we show that the CNN works well when inertial gravity wave amplitudes are relatively weak. When the wave amplitudes are strong, reconstructions of vorticity and strain are less accurate; however, we find that the CNN naturally filters the wave‐divergence, making divergence a surprisingly reliable field to reconstruct. We also show that when applied to realistic simulations, a CNN model pretrained with simpler simulation data performs well, indicating a possible path forward for estimating real flow statistics with limited observations. Plain Language Summary: Satellite measurements of sea surface height (SSH) have for the past few decades provided weekly global estimates of upper ocean currents at scales larger than approximately 100 km. The new Surface Water and Ocean Topography satellite promises to improve the resolution of these SSH observations. However, these new observations will introduce a new challenge, since a simple physics‐based diagnostic relationship does not exist between the SSH and upper ocean currents for the finer scales that will now be visible. Here we show that a neural network can be used to estimate the surface flow from SSH observations. In particular, our trained neural networks are able to use SSH to predict aspects of upper‐ocean currents that may be particularly useful for improving estimates of oceanic transport of heat and other tracers. Key Points: Neural networks reasonably reconstruct surface vorticity, strain and divergence, from sea surface heightNeural networks naturally filter wave divergence, leaving only the desired divergence associated with frontsTransfer learning shows promise when task‐specific data is limited but data from reasonably close simulations is available [ABSTRACT FROM AUTHOR]

Ocean salinity is an important variable that affects the ocean stratification. We compared the salinity and ocean stratification in the tropical Pacific derived from the Argo (Array for Real-time Geostrophic Oceanography data), EN4 (Ensemble 4 analysis), SODA (the Simple Ocean Data Assimilation reanalysis), IAP (Institute of Atmospheric Physics data), and ORAS4 (Ocean Reanalysis System 4) over 2005–2017. Results show that the spatial distribution of climatological mean of sea surface salinity (SSS) in all the products is consistent, and the low salinity region showed large deviation and strong dispersion. The Argo has the smallest RMSE and the highest correlation with the ensemble mean, while the IAP shows a high-salinity deviations relative to other datasets. All the products show high positive correlations between the sea surface density (SSD) and SSS with respect to the deviations of climatological mean from ensemble mean, suggesting that the SSD deviation may be mainly influenced by the SSS deviation. In the aspect of the ocean stratification, the mixed layer depth (MLD) climatological mean in the Argo shows the highest correlation with the ensemble mean, followed by EN4, IAP, ORAS4, and SODA. The Argo and EN4 show thicker barrier layer (BL) relative to the ensemble mean while the SODA displays the largest negative deviation in the tropical western Pacific. Furthermore, the EN4, ORAS4, and IAP underestimate the stability in the upper ocean at the depths of 20–140 m, while Argo overestimates ocean stability. The salinity fronts in the western-central equatorial Pacific from Argo, EN4, and ORAS4 are consistent, while those from SODA and IAP show large deviations with a westward position in amplitude of 0°–6° and 0°–10°, respectively. The SSS trend patterns from all the products are consistent in having ensemble mean with high spatial correlations of 0.95–0.97. [ABSTRACT FROM AUTHOR]

Accurate species identification is a key component of biodiversity research. DNA barcoding is an effective molecular method used for fish species identification. We aimed to study the DNA barcoding of fish in Zhoushan coastal waters, explore the differences and applicability of two gene fragments (12S rRNA and COI) of DNA barcoding in fish species identification, and established a comprehensive fish barcoding reference database. Two hundred and eighty-seven captured fish samples from Zhoushan coastal waters were identified using morphological characteristics and DNA barcoding. A total of 264 12S rRNA sequences (belonging to eight orders, 31 families, 55 genera, and 66 species) and 188 COI sequences (belonging to seven orders, 30 families, 48 genera, and 58 species) were obtained. The lengths of the 12S rRNA sequences ranged from 165 to 178 bp, and the guanine-cytosine (GC) content was 45.37%. The average 12S rRNA interspecific and intraspecific genetic distances (K2P) were 0.10% and 26.66%, respectively. The length of the COI sequence ranged 574–655 bp, and the content of GC was 45.97%. The average 12S rRNA interspecific and intraspecific genetic distances (K2P) were 0.16% and 27.45%, respectively. The minimum interspecific genetic distances of 12S rRNA and COI (1.23% and 1.86%) were both greater than their maximum intraspecific genetic distances (2.42% and 8.66%). Three molecular analyses (NJ tree, ABGD, and GMYC) were performed to accurately identify and delineate species. Clustering errors occurred when the 12S rRNA sequences were delimited using the NJ tree method, and the delimitation results of ABGD and GMYC are consistent with the final species identification results. Our results demonstrate that DNA barcoding based on 12S rRNA and COI can be used as an effective tool for fish species identification, and 12S rRNA has good application prospects in the environmental DNA (eDNA) metabarcoding of marine fish. [ABSTRACT FROM AUTHOR]

Benthodytes tetrapapillata sp. nov. was collected from a seamount located on the Caroline Ridge at a depth of 2 289 m, during the cruise of R/V Kexue in June 2019. We provided detailed descriptions of external and deposits morphology. The phylogenetic analyses based on cytochrome c oxidase I (COI) and a concatenated dataset of 16S and COI genes showed that the new species belonged to Benthodytes that is not monophyletic. Both details of morphological comparisons and molecular analyses confirmed that Benthodytes tetrapapillata sp. nov. is a new psychropotid species. A state of main morphological characters in valid species of Benthodytes is also provided in this study. [ABSTRACT FROM AUTHOR]

Accurate measurements of upwelling irradiance just beneath the ocean surface, Eu(λ, 0−), can be used to calculate ocean optical parameters, and further develop retrieval algorithms for remotely sensing water component concentrations. Due to the effects of sea surface waves, perturbation from instrument platform (ship), and instrument self-shading, Eu(λ, 0−) is often difficult to be accurately measured. This study presents a procedure for extrapolating the Eu(λ, 0−) from the in-water radiometric profile measurements. Using the optical profile data from 13 bands (ranging from 381 to 779 nm) measured by 45 casts in the Ligurian Sea during 2003–2009, the Eu(λ, 0−) was extrapolated from in-water upwelling irradiance measurements between the initial shallow depth, Z0, and an optimal bottom depth, Z1, by three linear models (linear, 2-degree polynomial, and exponential) and two nonlinear models (LOESS and spline). The accumulated errors of extrapolated Eu(λ, 0−) at each wavelength for the five models were calculated. It was found that the optimal Z1 depth for the linear and exponential models was at the depth of 80% of Eu(λ, Z0), 50% of Eu(λ, Z0) for the 2-degree polynomial model, 40% of Eu(λ, Z0) for the LOESS model, and 15% of Eu(λ, Z0) for the spline model. The extrapolated Eu(λ, 0−) derived from the five models was in good agreement with the calculated true Eu(λ, 0−). In all bands, the 2-degree polynomial model achieved the highest accuracy, followed by the LOESS model. In the short band of 381–559 nm, the linear and exponential models had the third-best performance, and the spline model performed worst within this range. For the red band of 619–779 nm, the accuracies of the exponential and spline models had the third highest performance, and the linear model produced lowest accuracy. Hence, the 2-degree polynomial model was an optimal procedure for extrapolation of Eu(λ, 0−) from the in-water radiometric profile measurements. [ABSTRACT FROM AUTHOR]

We investigate ocean dynamics at different scales in the Agulhas Current system, a region of important interocean exchange of heat and energy. While ocean observations and some of the most advanced climate models capture the larger mesoscale dynamics (> 100 km), the smaller-scale fronts and eddies are underrepresented. The recently launched NASA–CNES Surface Water and Ocean Topography (SWOT) wide-swath altimeter mission observes the smaller ocean geostrophic scales down to 15 km in wavelength globally. Here we will analyse different eddy diagnostics in the Agulhas Current region and quantify the contributions from the larger mesoscales observable today and the smaller scales to be observed with SWOT. Surface geostrophic diagnostics of eddy kinetic energy, strain, and energy cascades are estimated from modelled sea surface height (SSH) fields of the Massachusetts Institute of Technology general circulation model (MITgcm) latitude–longitude polar cap (LLC4320) simulation subsampled at 1/10 ∘. In this region, the smaller scales (<150 km) have a strong signature on the horizontal geostrophic strain rate and for all eddy diagnostics in the Western Boundary Current and along the meandering Agulhas Extension. We investigate the horizontal cascade of energy using a coarse-graining technique, and we observe that the wavelength range where the inverse cascade occurs is biased towards larger mesoscale wavelengths with today's altimetric sampling. We also calculate the projected sampling of the eddy diagnostics under the SWOT swaths built with the NASA–CNES simulator to include the satellite position and realistic noise. For the swaths, a neural network noise mitigation method is implemented to reduce the residual SWOT random error before calculating eddy diagnostics. In terms of SSH, observable wavelengths of 15 to 20 km are retrieved after neural network noise mitigation, as opposed to wavelengths larger than 40 km before the noise reduction. [ABSTRACT FROM AUTHOR]

More than 30 years of observations from an international suite of satellite altimeter missions continue to provide key data enabling research discoveries and a broad spectrum of operational and user-driven applications. These missions were designed to advance technologies and to answer scientific questions about ocean circulation, ocean heat content, and the impact of climate change on these Earth systems. They are also a valuable resource for the operational needs of oceanographic and weather forecasting agencies that provide information to shipping and fishing vessels and offshore operations for route optimization and safety, as well as for other decision makers in coastal, water resources, and disaster management fields. This time series of precise measurements of ocean surface topography (OST)—the "hills and valleys" of the ocean surface—reveals changes in ocean dynamic topography, tracks sea level variations at global to regional scales, and provides key information about ocean trends reflecting climate change in our warming world. Advancing technologies in new satellite systems allows measurements at higher spatial resolution ever closer to coastlines, where the impacts of storms, waves, and sea level rise on coastal communities and infrastructure are manifest. We review some collaborative efforts of international space agencies, including NASA, CNES, NOAA, ESA, and EUMETSAT, which have contributed to a collection of use cases of satellite altimetry in operational and decision-support contexts. The extended time series of ocean surface topography measurements obtained from these satellite altimeter missions, along with advances in satellite technology that have allowed for higher resolution measurements nearer to coasts, has enabled a range of such applications. The resulting body of knowledge and data enables better assessments of storms, waves, and sea level rise impacts on coastal communities and infrastructure amongst other key contributions for societal benefit. Although not exhaustive, this review provides a broad overview with specific examples of the important role of satellite altimetry in ocean and coastal applications, thus justifying the significant resource contributions made by international space agencies in the development of these missions. [ABSTRACT FROM AUTHOR]

Global lake/reservoir surface water extent is the basic input data for many studies. Although there are some datasets at present, there are problems such as incomplete or spatial inconsistency exist among them due to various reasons like different data sources and dynamic change characteristics of the surface water. In this paper, a new Global 10 Lake/Reservoir Surface Extent Dataset (GLRSED) that contains spatial extent and basic attributes (e.g., name, area, lake type and source) of 2.17 million lakes/reservoirs was produced based on HydroLAKES, GRanD and OpenStreetMap. In addition, by overlaying with mountain data, we identified the lakes/reservoirs located in mountain areas. By overlaying with the Global geReferenced Database of Dams (GOODD) and Georeferenced Global Dams and Reserves (GeoDAR) dataset, we partitioned human-managed reservoirs from natural lakes. Lakes/reservoirs on the rivers were identified by overlaying 15 with the SWOT Mission River Database (SWORD). Using the same method, we identified endorheic, glacier-fed and permafrost-fed lakes. Furthermore, the coverage of Surface Water and Ocean Topography (SWOT) ground track to each lake/reservoir in GLRSED was calculated to explore the potential of SWOT for monitoring lakes. The dataset could provide basic data for global lake/reservoir monitoring, enabling the study on the impact of human actions and climate changes on lake/reservoir freshwater availability. The GLRSED database is available at https://doi.org/10.5281/zenodo.8121174 (Bai et 20 al., under review, 2023). [ABSTRACT FROM AUTHOR]

While many studies have been conducted regarding wind-driven Ka-band scattering on the ocean and sea surfaces, few have identified the impacts of Ka-band scattering on small inland water bodies, and fewer have identified the influence of wind on coherence over water. These previous studies have been limited in spatial scale, covering only large water bodies >25 km2. The recently launched Surface Water and Ocean Topography (SWOT) mission is the first Ka-band InSAR satellite designed for mapping water surface elevations and open water areas for rivers as narrow as 100 m and lakes as small as 0.0625 km2. Because measurements of these types are novel, there remains some uncertainty about expected backscatter amplitudes given wind-driven water surface roughness variability. A previous study using the airborne complement to SWOT, AirSWOT, found that low backscatter and low coherence values were indicative of higher errors in the water surface elevation products, recommending minimum thresholds for backscatter and coherence for filtering the data to increase the accuracy of averaged data for lakes and rivers. We determined that the global average wind speed over lakes is 4 m/s, and after comparing AirSWOT backscatter and coherence data with ERA-5 wind speeds, we found that the minimum required speed to retrieve high backscatter and coherence is 3 m/s. We examined 11,072 lakes across Canada and Alaska, with sizes ranging from 350 m2 to 156 km2, significantly smaller than what could be measured with previous Ka-band instruments in orbit. We found that small lakes (0.0625–0.25 km2) have significantly lower backscatter (3–5 dB) and 0.20–0.25 lower coherence than larger lakes (>1 km2). These results suggest that approximately 75% of SWOT observable lake areas around the globe will have consistently high-accuracy water surface elevations, though seasonal wind variability should remain an important consideration. Despite very small lakes presenting lower average backscatter and coherence, this study asserts that SWOT will be able to accurately resolve the water surface elevations and water surface extents for significantly smaller water bodies than have been previously recorded from satellite altimeters. This study additionally lays the foundation for future high-resolution inland water wind speed studies using SWOT data, when the data become available, as the relationships between wind speed and Ka-band backscatter reflect those of traditional scatterometers designed for oceanic studies. [ABSTRACT FROM AUTHOR]

Surface wind speed measurements from a satellite radar altimeter are used to adjust altimeter sea level measurements via sea state bias range correction. We focus here on previously neglected ocean radar backscatter and subsequent wind speed variations due to sea surface temperature (SST) change that may impact these sea level estimates. The expected error depends on the radar operating frequency and may be significant at the Ka band (36 GHz) frequency chosen for the new Surface Water and Ocean Topography (SWOT) satellite launched in December 2022. SWOT is expected to revolutionize oceanography by providing wide-swath Ka band observations and enhanced spatial resolution compared to conventional Ku band (14 GHz) altimetry. The change to the Ka band suggests a reconsideration of SST impact on wind and sea level estimates, and we investigate this in advance of SWOT using existing long-term Ku and Ka band satellite altimeter datasets. This study finds errors up to 1.5 m/s in wind speed estimation and 1.0 cm in sea level for AltiKa altimeter data. Future SWOT data analyses may require consideration of this dependence prior to using its radar backscatter data in its sea level estimation. [ABSTRACT FROM AUTHOR]