Satellite Altimetry Data Research Articles

Leveraging synthetic data to improve regional sea level predictions

The rapid increase in sea levels driven by climate change presents serious risks to coastal communities around the globe. Traditional prediction models frequently concentrate on developed regions with extensive tide gauge networks, leaving a significant gap in data and forecasts for developing countries where the tide gauges are sparse. This study presents a novel deep learning approach that combines TimesGAN with ConvLSTM to enhance regional sea level predictions using the more widely available satellite altimetry data. By generating synthetic training data with TimesGAN, we can significantly improve the predictive accuracy of the ConvLSTM model. Our method is tested across three developed regions—Shanghai, New York, and Lisbon—and three developing regions—Liberia, Gabon, and Somalia. The results reveal that integrating TimesGAN reduces the average mean squared error of the ConvLSTM prediction by approximately 66.1%, 76.6%, 64.5%, 78.2%, 81.7% and 85.1% for Shanghai, New York, Lisbon, Liberia, Gabon, and Somalia, respectively. This underscores the effectiveness of synthetic data in enhancing sea level prediction accuracy, across all regions studied.

Hydro-geodetic approach for predicting river runoff in ungauged basins using gravity and altimetry satellite data

A novel satellite-based approach is proposed for predicting river runoff in ungauged basins using gravity and altimetry data. This hydro-geodetic approach integrates the Gravity Recovery And Climate Experiment (GRACE) observations in the global monthly hydrological model, as an alternative input data to in-situ runoff. By combination with water-budget equation and by using an efficient innovative multi-objective-optimization algorithm, the problem is solved and validated by three strategies, considering various basins. The results have outlined a 3-months time-shift to be considered for Amazon basin for transiting from storage to runoff, while other basins as Cheliff, Congo and Daly require runoff bias correction. Basin area and climatic characteristics have demonstrated its effect on parameter calibration performance, while the relationship between runoff and space-based river-level needs an appropriate mathematical model to each basin. An agreement was found between the predicted runoff and those reported elsewhere, highlighting the effectiveness and feasibility of the proposed approach.

Coastal sea level rise at altimetry-based virtual stations in the Gulf of Mexico

A dedicated reprocessing of satellite altimetry data from the Jason-1/2/3 missions in the world coastal zones provides a large set of virtual coastal stations where sea level time series and associated trends over 2002-2021 can be estimated. In the Gulf of Mexico, we obtain a set of 32 virtual coastal sites, well distributed along the Gulf coastlines, completing the tide gauge network with long-term data that is currently limited to the northern part of the Gulf. Altimetry-based coastal sea level time series and associated sea level trends confirm previous published results that report a strong acceleration in tide-gauge based sea level rise along the US coast of the Gulf of Mexico since the early 2010s. In addition, our study shows that this acceleration also takes place along the western and southern coasts of the Gulf of Mexico. The coastal sea level trends estimated over 2012-2021 amounts to ∼10 mm/yr at most virtual stations. We note a slightly smaller rise on the western coast of Florida and at two sites of the Cuba Island. Good agreement in terms of sea level trends over 2002-2021 is found between coastal altimetry data and tide-gauge record corrected for vertical land motion. Good correlation is also found between coastal altimetry and tide gauge sea level time series at low-frequency time scales, with interannual fluctuations in sea level being indirectly linked to natural climate modes, in particular the El Nino Southern Oscillation (ENSO).

Behavior and Energy of the M2 Internal Tide in the Madagascar–Mascarene Region

Internal tides serve as essential intermediate steps in the cascading of oceanic energy, playing a crucial role in oceanic mixing. M2 internal tides are the dominant tidal constituent in many oceanic regions, significantly influencing ocean dynamics. The Madagascar–Mascarene Region has high-energy internal tides, but due to a lack of observational studies, their propagation remains underexplored and warrants further investigation. In this study, we used satellite altimetry data to capture the sea surface manifestation of the first-mode M2 internal tides in the region. The results show that the Mascarene Plateau plays a key role in shaping the region’s uneven internal tide distribution. The Mascarene Strait is the most intense generation area, with an east-west energy flux of 1.42 GW. Using the internal tidal energy concentration index, we decomposed the internal tidal beams, finding the primary beam oriented at 148°. These beams propagate outward for over 800 km, with a maximum distance exceeding 1000 km. Geostrophic currents intensify the northward refraction of westward-propagating internal tides in the Mascarene Basin, particularly between 15°S and 20°S.

Automated Estimation of Building Heights with ICESat-2 and GEDI LiDAR Altimeter and Building Footprints: The Case of New York City and Los Angeles

Accurate estimation of building height is crucial for urban aesthetics and urban planning as it enables an accurate calculation of the shadow period, the effective management of urban energy consumption, and thorough investigation of regional climatic patterns and human-environment interactions. Although three-dimensional (3D) cadastral data, ground measurements (total station, Global Positioning System (GPS), ground laser scanning) and air-based (such as Unmanned Aerial Vehicle—UAV) measurement methods are used to determine building heights, more comprehensive and advanced techniques need to be used in large-scale studies, such as in cities or countries. Although satellite-based altimetry data, such as Ice, Cloud and land Elevation Satellite (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI), provide important information on building heights due to their high vertical accuracy, it is often difficult to distinguish between building photons and other objects. To overcome this challenge, a self-adaptive method with minimal data is proposed. Using building photons from ICESat-2 and GEDI data and building footprints from the New York City (NYC) and Los Angeles (LA) open data platform, the heights of 50,654 buildings in NYC and 84,045 buildings in LA were estimated. As a result of the study, root mean square error (RMSE) 8.28 m and mean absolute error (MAE) 6.24 m were obtained for NYC. In addition, 46% of the buildings had an RMSE of less than 5 m and 7% less than 1 m. In LA data, the RMSE and MAE were 6.42 m and 4.66 m, respectively. It was less than 5 m in 67% of the buildings and less than 1 m in 7%. However, ICESat-2 data had a better RMSE than GEDI data. Nevertheless, combining the two data provided the advantage of detecting more building heights. This study highlights the importance of using minimum data for determining urban-scale building heights. Moreover, continuous monitoring of urban alterations using satellite altimetry data would provide more effective energy consumption assessment and management.

Assimilation of Surface Geostrophic Currents in the East Sea Using the Ensemble Kalman Filter

The conventional ocean data assimilation process typically involves assimilating hydrographic data, such as temperature and salinity measurements, obtained from both satellites and in-situ observations. This study introduces a novel approach to enhance ocean circulation modeling by assimilating surface geostrophic currents derived from satellite altimetry data using the ensemble Kalman filter. To match the time scales for the variability in the observed surface geostrophic currents and the model currents, the current velocities from the model were low-pass filtered. The optimal cut-off period for the low-pass filter was determined to be 31 days in the East Sea. Eight sensitivity experiments were then conducted to examine the effects of observation error and low-pass filtering during the assimilation of surface geostrophic current data. Assimilation experiments with surface geostrophic current data improved surface currents but had minor negative impacts on the temperature and salinity when compared with assimilation experiments without surface geostrophic current data. Notably, the experiment with an observation error of 10 cm/s for the geostrophic current outperformed the other experiments. Surface geostrophic current assimilation improved the sea surface temperature during winter and effectively modified surface current patterns during autumn in the East Sea. Assimilating satellite-derived surface geostrophic currents in the ocean circulation model thus enhanced the accuracy of surface circulation simulation. This improvement in ocean analysis data offers significant benefits for understanding ocean climate change and for developing marine management strategies.

Regional Mean Sea Level Variability Due to Tropical Cyclones: Insights from August Typhoons

This study investigates the interannual variations in regional mean sea levels (MSLs) of the northeast Asian marginal seas (NEAMS) during August, focusing on the role of typhoon activity from 1993 to 2019. The NEAMS are connected to the Pacific through the East China Sea (ECS) and narrow, shallow straits in the east, where inflow from the southern boundary (ECS), unless balanced by eastern outflow, leads to significant convergence or divergence, as well as subsequent changes in regional MSLs. Satellite altimetry and tide-gauge data reveal that typhoon-induced Ekman transport plays a key role in MSL variability, with increased inflow raising MSLs during active typhoon seasons. In contrast, weak typhoon activity reduces inflow, resulting in lower MSLs. This study’s findings have significant implications for coastal management, as the projected changes in tropical cyclone frequency and intensity due to climate change could exacerbate sea level rise and flooding risks. Coastal communities in the NEAMS region will need to prioritize enhanced flood defenses, early warning systems, and adaptive land use strategies to mitigate these risks. This is the first study to link typhoon frequency directly to NEAMS MSL variability, highlighting the critical role of wind-driven processes in regional sea level changes.

Lake water storage changes and their cause analysis in Mongolia

Lake is an important water resources in Mongolia, which has undergone a large variation in past decades. However, it is still challenging to monitor long-term changes in lake water storage (LWS) due to the lack of lake level monitoring and long-term satellite altimetry data for Mongolian lakes. According to the Advanced Land Observing Satellite Digital Elevation Model (ALOS DEM) and the Joint Research Centre (JRC) dataset, we estimated the LWS changes of 55 Mongolian lakes (> 10 km2) from 1991 to 2020. The results showed that the LWS increased by 40.24 km3 from 1991 to 1997, especially for northwestern Mongolia with 31.47 km3. However, the LWS decreased by 32.44 km3 from 1998 to 2010, and the lakes in the northwestern and southern decreased by 20.24 km3 (62%) and 7.38 km3 (23%), respectively, and then the LWS continued to decrease by 10.22 km3 from 2011 to 2020. The precipitation was the primary cause of lake change, which could explain 45.13% of LWS change based on Generalized Linear Model, followed by temperature (26.33%) and irrigated area (16.72%). Analyzing the changing characteristic and driving mechanisms of LWS can provide a scientific basis for local water resources management and planning.

Two-Dimensional Legendre Polynomial Method for Internal Tide Signal Extraction

This study employs the two-dimensional Legendre polynomial fitting (2-D LPF) method to fit M2 tidal harmonic constants from satellite altimetry data within the region of 53°E–131°E, 34°S–6°N, extracting internal tide signals acting on the sea surface. The M2 tidal harmonic constants are derived from the sea surface height (SSH) data of the TOPEX/Poseidon (T/P), Jason-1, Jason-2, and Jason-3 satellites via t-tide analysis. We validate the 2-D LPF method against the 300 km moving average (300 km smooth) method and the one-dimensional Legendre polynomial fitting (1-D LPF) method. Through cross-validation across 42 orbits, the optimal polynomial orders are determined to be seven for 1-D LPF, and eight and seven for the longitudinal and latitudinal directions in 2-D LPF, respectively. The 2-D LPF method demonstrated superior spatial continuity and smoothness of internal tide signals. Further single-orbit correlation analysis confirmed generally higher correlation with topographic and density perturbations (correlation coefficients: 0.502, 0.620, 0.245; 0.420, 0.273, −0.101), underscoring its accuracy. Overall, the 2-D LPF method can use all regional data points, overcoming the limitations of single-orbit approaches and proving its effectiveness in extracting internal tide signals acting on the sea surface.

Hydrological model calibration in data-deficient basins using satellite altimetry and a hydrodynamic model

Large basins with insufficient hydrological station distribution and lacking sufficient meteorological data, such as water level and discharge, pose significant challenges in developing reliable hydrological models. These models are crucial for addressing water resource-related challenges such as climate change (e.g., floods and droughts) and human-induced activities (e.g., dams) impacts. Recent advancements in satellite altimetry offer an efficient alternative by providing water level data; however, integrating this data into hydrological models remains an ongoing challenge. Here we demonstrate that a properly developed hydrodynamic model can effectively translate the satellite-observed water levels at various river cross-sections (hereafter referred to as virtual stations (VSs)) into the required discharge data, facilitating reliable hydrological modeling for data-deficient basins. Our results, based on the assessment of water level data derived from a hydrodynamic model and satellite altimetry, showed high consistency (NSE > 0.96) in the Lancang-Mekong River (LMR) basin as a case study. We found that the distribution of stations along the mainstream, in terms of their number and distance from each other, can significantly impact the performance of hydrological modeling processes. The results revealed that when a large stretch of the river is not monitored by a station, a large uncertainty occurs in runoff generation, at least for that segment of the river. However, the inclusion of virtual stations in the modeling process improved the overall performance, indicating the advantages of satellite altimetry data in better modeling of data-deficient basins. Our findings revealed that virtual stations can be effectively utilized in physically based and spatially distributed hydrological models to develop a sub-basin modeling approach that addresses the regional contribution of sub-basins to downstream river flow. The integrated modeling framework holds potential for hydrological analysis and water resources management for basins lacking sufficient gauging data and provides insight into how the distribution of stations can influence the calibration of hydrological models.

Сравнительное влияние гидрометеорологических процессов на межгодовую изменчивость сезонных колебаний уровня Балтийского моря

With the help of long-term average daily tide gauge observations of sea level, satellite altimetry measurements and data from reanalyses of meteorological and hydrophysical fields, the features and physical mechanisms of interannual variability of seasonal fluctuations in the level of the Baltic Sea are investigated. It is shown that for the period 1889-2022 in Stockholm, in interannual changes in the amplitudes of harmonics Sa, Ssa, Sta, Sqa, there are statistically insignificant positive linear trends, against the background of which long-term cycles with time scales approximately from 20–35 to 55 years and very significant changes in amplitudes from 0.5–1.0 to 25–27 centimeters are observed. In recent decades, the harmonics Sa, Ssa, and Sta have seen a noticeable decrease in the amplitudes and dispersion of oscillations. The results of mutual correlation and multiple regression analyses of anomalies of seasonal fluctuations in sea level and various hydrometeorological processes indicate that the largest contribution to the interannual variability of seasonal fluctuations in sea level is made by changes in the tangential friction of the wind. The second most important processes are changes in atmospheric pressure over the sea and water exchange between the Baltic and North Seas. Changes in freshwater balance and density have the smallest impact on interannual variability in seasonal sea-level patterns.

Coincident Lake Drainage and Grounding Line Retreat at Engelhardt Subglacial Lake, West Antarctica

AbstractAntarctica has an active subglacial hydrological system, with interconnected subglacial lakes fed by subglacial meltwater. Subglacial hydrology can influence basal sliding, inject freshwater into the sub‐ice‐shelf cavity, and impact sediment transport and deposition which can affect the stability of grounding lines (GLs). We used satellite altimetry data from the ICESat, ICESat‐2, and CryoSat‐2 missions to document the second recorded drainage of Engelhardt Subglacial Lake (SLE), which began in July 2021 and discharged more than 2.3 km3 of subglacial water into the Ross Ice Shelf cavity. We used differential synthetic aperture radar interferometry from RADARSAT‐2 and TerraSAR‐X alongside ICESat‐2 repeat‐track laser altimetry (RTLA) and REMA digital elevation model strips to detect 2–13 km of GL retreat since the previous drainage event in 2003–06. Combining these satellite observations, we evaluated the mechanism triggering SLE drainage, the cause of the observed GL retreat, and the interplay between subglacial hydrology and GL dynamics. We find that: (a) SLE drainage was initiated by influx from a newly identified upstream lake; (b) the observed GL retreat is mainly driven by the continued retreat of Engelhardt Ice Ridge and long‐term dynamic thinning that caused a grounded ice plain to reach flotation; and (c) SLE drainage and GL retreat were largely independent. We also discuss the possible origins and influence of a 27 km grounded promontory found to protrude seaward from the GL. Our observations demonstrate the importance of high‐resolution satellite data for improving the process‐based understanding of dynamic and complex regions around the Antarctic Ice Sheet margins.

Seasonal Patterns, Inter‐Annual Variability, and Long‐Term Trends of Mean Sea Level Along the Western Iberian Coast and the North Atlantic Islands

AbstractSea level rise is challenging for coastal communities and land management decision makers. Understanding the patterns of regional variations at different temporal and spatial scales is key to implement adaptation plans that mitigate the local impacts of sea level rise. In this study, in situ observations from 14 tide gauges were complemented with satellite altimetry data to assess seasonality, multidecadal variability and long‐term trends in mean sea level around the Western Iberian Coast (WIC) and the Portuguese archipelagos (Azores and Madeira). Results show varying spatial seasonal patterns between regions, with minimum (maximum) sea level observed in April (September) at the islands and minimum (maximum) observed in July (November) at the WIC. The influence of coastal upwelling on the seasonal mean sea level variations was detected over mainland. Although the influence of atmospheric patterns was observed on sea level inter‐annual variability, the Atlantic Multidecadal Oscillation (AMO) showed a greater correlation with the sea level inter‐decadal patterns. Finally, the trend analysis confirmed widespread sea level rise along the mainland and around the islands, which has intensified in recent decades. The regions of La Coruña and Cascais showed trends that were similar to the global average sea level rise since 1993, but the mainland regional average pointed to lower rates of rise (2.00 ± 0.06 mm/year). This work reinforces the need for long‐term monitoring networks of sea level, ensuring the vertical stability of instruments and platforms. The implementation of regional adaptation plans to sea level rise is deeply dependent on high quality information.

Differences among the total electron content derived by radio occultation, global ionospheric maps and satellite altimetry

In recent years, significant progress has been in ionospheric modeling research through data ingestion and data assimilation from a variety of sources, including ground-based global navigation satellite systems, space-based radio occultation and satellite altimetry (SA). Given the diverse observing geometries, vertical data coverages and intermission biases among different measurements, it is imperative to evaluate their absolute accuracies and estimate systematic biases to determine reasonable weights and error covariances when constructing ionospheric models. This study specifically investigates the disparities among the vertical total electron content (VTEC) derived from SA data of the Jason and Sentinel missions, the integrated VTEC from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and global ionospheric maps (GIMs). To mitigate the systematic bias resulting from differences in satellite altitudes, the vertical ranges of various VTECs are mapped to a standardized height. The results indicate that the intermission bias of SA-derived VTEC remains relatively stable, with Jason-1 serving as a benchmark for mapping other datasets. The mean bias between COSMIC and SA-derived VTEC is minimal, suggesting good agreement between these two space-based techniques. However, COSMIC and GIM VTEC exhibit remarkable seasonal discrepancies, influenced by the solar activity variations. Moreover, GIMs demonstrate noticeable hemispheric asymmetry and a degradation in accuracy ranging from 0.7 to 1.7 TECU in the ocean-dominant Southern Hemisphere. While space-based observations effectively illustrate phenomena such as the Weddell Sea anomaly and longitudinal ionospheric characteristics, GIMs tend to exhibit a more pronounced mid-latitude electron density enhancement structure.

Scalable interpolation of satellite altimetry data with probabilistic machine learning

We present GPSat; an open-source Python programming library for performing efficient interpolation of non-stationary satellite altimetry data, using scalable Gaussian process techniques. We use GPSat to generate complete maps of daily 50 km-gridded Arctic sea ice radar freeboard, and find that, relative to a previous interpolation scheme, GPSat offers a 504 × computational speedup, with less than 4 mm difference on the derived freeboards on average. We then demonstrate the scalability of GPSat through freeboard interpolation at 5 km resolution, and Sea-Level Anomalies (SLA) at the resolution of the altimeter footprint. Interpolated 5 km radar freeboards show strong agreement with airborne data (linear correlation of 0.66). Footprint-level SLA interpolation also shows improvements in predictive skill over linear regression. In this work, we suggest that GPSat could overcome the computational bottlenecks faced in many altimetry-based interpolation routines, and hence advance critical understanding of ocean and sea ice variability over short spatio-temporal scales.

Программный комплекс обработки данных спутниковой альтиметрии космической геодезической системы «ГЕО-ИК-2»

The Central Research Institute for Machine Building JSC has created a software package for processing primary satellite altimetry data of the “GEO-IK-2” space geodetic system, adapted for high-performance computing systems. The software package performs step-by-step multi-level processing of measuring and auxiliary information with sequential recording of intermediate and final results in a database. The technology of processing level 0 data received from the spacecraft up to and including level 2 has been implemented. The article provides information about the input data used at different levels of processing, about the algorithms and functionality of the software package. In the process of debugging the software package on high-performance computing systems all the valid data of the “GEO-IK-2” space geodetic system from 2018 to 2022 were processed for the first time. The developed software package should serve as a prototype of the satellite altimetry data processing subsystem of the ground-based special complex of the promising new generation space geodetic system

Optimized estimation of marine deflection of the vertical from multibeam laser altimeter data of ICESat-2

SUMMARY Satellite altimetry data, with its increasing density and quality, has become the primary source for marine deflection of the vertical (DOV) and gravity anomaly modelling. Limited by orbital inclinations, the precision of the meridian component of the gridded deflection of the vertical (GDOV) calculated by traditional altimetry satellites is significantly better than that of the prime vertical component, and the excessive precision difference between these two components restricts the inversion precision of marine gravity anomaly model. The study of cross-track deflection of the vertical (CTDOV) is enabled by the multibeam synchronous observation mode of the new laser altimetry satellite, Ice, Cloud and Land Elevation Satellite-2 (ICESat-2). Based on the remove-restore method, residual geoid gradients are first calculated in this paper using three approaches: along-track (A-T), cross-track (C-T) and an integration of along-track and cross-track. Vertical deflections are then computed on a 1′ × 1′ grid using the least squares collocation (LSC) method, and the precision is verified against the SIO V32.1_DOV model. An optimized combination is proposed to address the issue of precision differences between the meridian and prime vertical components, and to enhance the precision of DOV inversion. A new DOV combination is formed by combining the meridian component from along-track deflection of the vertical (ATDOV) with the prime vertical component from cross-track deflection of the vertical (CTDOV) based on the remove-restore method. The Philippine Sea (0°–35°N, 120°–150°E) is selected as the test area to verify the feasibility of the optimized combination. The results indicate that the optimized combination of the meridian and prime vertical components achieved test precision of 2.63 and 3.33 μrad, respectively, when compared against the SIO V32.1_DOV model. The precision gap between the components is effectively narrowed by this approach, which maintains the precision of the meridian component and enhances that of the prime vertical component, thereby achieving optimal inversion precision for gravity anomalies.

Regional tidal modeling on the European coast using tide gauges and satellite altimetry

The study investigates sea-level measurements along the coastal area of Europe for the 60-year (1961–2020) time span. Linear and quadratic modeling of tide gauge measurements showed an almost positive rate of trend of sea-level rise (0.09 to 3.6 mm/yr) and low acceleration (−0.05 to 0.40 mm/yr2). A least-squares harmonic estimation tidal modeling was carried out to estimate frequency (cycles per day) for a certain period. The smaller and higher tidal frequencies of these stations indicate their stability in terms of their surface variation. We used the 1993–2020 satellite altimetry data from the nearest grid points of the tide gauge station. The correlation coefficient between observed and satellite altimetry (lowest 0.53 and highest 0.93) varies at each station. This happens because of many factors that can affect the large difference in the sea-level trend between the satellite-derived and tide gauge results. Finally, to implement a global reference system for physical heights, the offshore topographic slope direction and slope range with contour spacing from the sea to the associated coastline were analyzed using bathymetry data. The abrupt change in slope from the coastline toward the sea can be seen toward the east, west, and southeast on the European coast. This is also an important factor that affects the variation of sea level.

A Mechanism for Ice Layer Formation in Glacial Firn

AbstractThere is ample evidence for ice layers and lenses within glacial firn. The standard model for ice layer formation localizes the refreezing by perching of meltwater on pre‐existing discontinuities. Here we argue that even extreme melting events provide insufficient flux for this mechanism. Using a thermomechanical model we demonstrate a different mechanism of ice layer formation. After a melting event when the drying front catches up with the wetting front and arrests melt percolation, conductive heat loss freezes the remaining melt in place to form an ice layer. This model reproduces the depth of a new ice layer at the Dye‐2 site in Greenland. It provides a deeper insight into the interpretation of firn stratigraphy and past climate variability. It also improves the simulation of firn densification processes, a key source of uncertainty in assessing and attributing ice sheet mass balance based on satellite altimetry and gravimetry data.

Internal Tide Variability Off Central California: Multiple Sources, Seasonality, and Eddying Background

AbstractTwo 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.