Felix Lucian Müller

Satellite radar altimetry provides basin-wide observations of sea surface height in the rapidly changing Arctic Ocean, where harsh weather, sea ice, and remoteness limit in situ measurements. In this study, we created and analyzed a dataset of absolute dynamic topography (ADT) and geostrophic currents in the Pacific Arctic, based on cross-calibrated altimetry data from Envisat, SARAL, and CryoSat-2. The use of advanced lead-detection algorithms and a tailored approach for sea surface height retrieval in ice-covered regions enabled improved temporal and spatial resolution (10 d/8 km) over 2002-2024. Validation against tide-gauge, mooring, and model data shows that the dataset captures interannual, seasonal, and synoptic ADT variability in the Chukchi and Beaufort Seas. We use this dataset to examine eastward surface geostrophic flow along the Beaufort shelfbreak and its relationship to the regional geostrophic system. Although the Beaufort Gyre (BG) supports predominantly westward geostrophic flow along the Beaufort coast, we identify recurrent eastward along-coast flow events, mainly in summer and fall. Empirical orthogonal function analysis links these events primarily to the BG-shelf ADT dipole, with secondary contributions from shelf-intensified modes associated with Chukchi-Beaufort exchange; the relative importance of these pathways varies over time under different atmospheric conditions. The results indicate that eastward geostrophic flow along the Beaufort shelfbreak is not an isolated coastal feature, but part of a coupled Chukchi-Beaufort geostrophic system shaped by BG variability and shelf sea level.

Gridded geostrophic currents derived from satellite altimetry are a cornerstone for investigating ocean surface circulation. However, their effective spatial resolution and dynamical fidelity are highly sensitive to processing choices. Here, we present a comprehensive global intercomparison of several daily, gridded (Level-4) freely available altimetry-based datasets that employ distinct gridding strategies.Dataset performance is evaluated using a suite of complementary metrics. Spectral diagnostics, including power spectral density and eddy kinetic energy, are employed to quantify the representation of mesoscale variability across a range of spatial scales, dynamical regimes, and energy levels. In addition, a Lagrangian framework is adopted in which virtual drifters are deployed and advected along observed drifter trajectories, enabling robust statistical comparisons of transport and dispersion characteristics among the datasets. The results are consistent across metrics and highlight the strong performance of recently developed products, including neural network–based approaches such as NeurOST, and advanced multi-mission datasets, such as those provided by the Copernicus Marine Environment Monitoring Service (CMEMS) data store.This intercomparison is conducted within the framework of ESA’s Climate Change Initiative, which aims to expand ESA’s portfolio of Essential Climate Variables. It supports the development of a novel Ocean Surface Heat Flux (OSHF) product, generated to address the observational gaps and limitations inherent in existing OSHF estimates.

Accurate estimates of ocean surface heat fluxes (OSHF) are essential for assessing and improving climate projections and supporting adaptation strategies, yet direct measurements are challenging, costly, and not feasible at global scales. The GCOS Implementation Plan 2022 emphasizes the urgent need to enhance estimates of latent and sensible heat fluxes, recommends greater use of satellite data, and highlights that current in-situ observing systems, such as Argo, are insufficient to provide the high-resolution data required for climate modeling and model validation. The CCI OSHF project addresses this gap by generating a new satellite-based OSHF product aiming at meeting the climate community requirements for spatial and temporal resolution, timeliness, uncertainty, and long-term stability. By relying on fundamental physical principles rather than parameterizations and leveraging multiple satellite missions and in-situ observing networks, the product aims at reducing uncertainties. After one year of the project, we will present the user requirements outcomes from the dedicated user consultation action, describe the methodology used to generate the product, and show preliminary results on the performance of the first 15-year version of the new satellite-derived OSHF dataset.

A consistent monitoring of the sea ice freeboard is crucial for observing changes in sea ice thickness and for improving sea ice forecasts. Mainly, area-wide freeboard heights are determined by using surface elevations from satellite altimetry missions like ESA's Earth Explorer Cryosat-2 and NASA's ICESat-2. A sudden failure or interruption of these altimeter missions would lead to significant data gaps in the central Arctic Ocean. Therefore, additional ways to determine sea level and freeboard based on remote sensing techniques are of great importance.One of these additional techniques is grazing angle GNSS reflectometry (GA GNSS-R), which uses surface reflections from Global Navigation Satellite System (GNSS) signals to capture elevation information and characterize surface roughness. Here, we utilize reflections collected by up to 15 Spire Global nanosatellites. These nanosatellites record both the directly transmitted signal (line of sight) and the signal reflected from the surface , The signals are used to determine the delays in the measured phase compared to a modelled phase, from which the elevation of a reflecting surface is then derived. Accurate height estimation is feasible when the reflected signal remains phase‑coherent and retains right‑hand circular polarization at grazing incidence angles between approximately 5° and 30°. Under these conditions, smooth surfaces such as sea ice or calm water produce strong coherent reflections, whereas rougher ocean surfaces induce decorrelation and significantly weaker reflected signatures.As part of the ESA Earthnet Data Assessment Project (EDAP+), a new approach is developed to derive sea ice freeboard from GA GNSS-R observations providing complementary information to satellite altimetry. One key advantage of Spire’ GA GNSS-R constellation is the high geographic density over the poles and thus continuous coverage of high latitudes without a systematic polar observation gap, as is the case with altimetry missions. Geolocated surface reflections and elevation data provided by Spire Global are used to classify surfaces, to detect water openings within the sea-ice cover (e.g., leads), to retrieve local sea-surface elevations, and subsequently to derive along-track sectional freeboard heights from GA GNSS-R observations.This study presents first monthly Arctic-wide freeboard maps for a complete winter season (2023/2024) and comparisons with upward-looking sonar measurements and CryoSat-2 freeboard products. Initial comparisons demonstrate that GNSS-R-derived freeboard provides valuable complementary information, particularly in regions with a dense data coverage, and achieves accuracy comparable to altimetry during autumn and early winter.

This study presents an Arctic-wide assessment of the Surface Water and Ocean Topography (SWOT) mission's swath observations of sea surface height (SSH). SWOT provides measurements in two-dimensional swaths and enables pixel-based height information with a resolution of 250 m up to a latitudinal limit of 78° N. Although SWOT doesn’t cover the central Arctic, it provides insights into SSH at an unprecedented spatial and temporal resolution. The quality of these innovative observations in such a challenging environment is evaluated through comparison with data from ICESat-2. Approximately one year of surface elevation data, collected between March 2023 and April 2024, is used at around 550 regionally distributed crossover locations, with measurements taken within 30 min. Sentinel-1 SAR imagery supports the comparisons if available. Visual comparisons of SWOT and ICESat-2 with Sentinel-1 backscatter (i.e. σ₀), converted to 8-bit grey-scale values, reveal clear coherence. However, small-scale surface features aren’t captured by SWOT as equally as by ICESat-2. The data shows absolute water level differences of about 5 cm, despite prior harmonisation of references and corrections. Differences of up to 50 cm can occur when comparing left- and right-hand SWOT swaths, mainly during winter and in areas with long sea ice coverage. This may be due to issues with the height correction from the crossover calibration. Quantitative point-by-point comparisons show mean standard deviations of about 8 cm for all surface types and 6 cm if restricted to ICESat-2-detected leads. Higher deviations are found during the early melting period between May and June, in the Canadian Archipelago and the Greenland Sea.

For over 30 years, satellite altimetry has been a vital tool for monitoring ocean and inland water surfaces. Since 1992, at least two missions have operated concurrently, beginning with TOPEX/Poseidon and ERS-1, and now including around 10 active satellites such as ICESat-2, Sentinel-6A, and SWOT. While most mission data are freely available, they differ in format, processing level, and reference systems (e.g., ellipsoid or time), complicating multi-mission applications. Additionally, generating high-quality, ready-to-use scientific products often requires specialized expertise. To address these challenges, DGFI-TUM has developed the Open Altimeter Database (OpenADB), which enables consistent data management and integration. OpenADB comprises the internal Multi-Version Altimetry (MVA) repository and a user-friendly web portal. It offers access to along-track products such as sea surface heights and ocean tides, along with detailed information on satellite missions, configurations, and data characteristics. All products are freely accessible via https://openadb.dgfi.tum.de after registration. A key focus of OpenADB is the coastal zone. Over two decades of data have been reprocessed using algorithms and geophysical corrections tailored to enhance sea level retrievals near coasts without compromising open-ocean standards. The coastal dataset, based on ALES and ALES+SAR retrackers, is the largest of its kind. It also underpins the EOT20 tidal model, which delivers superior performance in shelf and coastal regions, which are typically challenging for tidal estimation. The EOT20 model is also available as an independent product. Furthermore, all missions are cross-calibrated, allowing users to seamlessly combine data from different satellites for regional-scale sea level analysis.

This study presents an Arctic-wide assessment of the Surface Water and Ocean Topography (SWOT) mission's swath observations of sea surface height. SWOT provides measurements in two-dimensional swaths and enables pixel-based height information with a resolution of 250 metres up to a latitudinal limit of 78° N. Although SWOT doesn’t cover the central Arctic, it provides insights into SSH at an unprecedented spatial and temporal resolution. The quality of these innovative observations in such a challenging environment is evaluated through comparison with data from ICESat-2. Approximately one year of sea level anomaly data, collected between March 2023 and April 2024, is used at around 550 regionally distributed crossover locations, with measurements taken within 30 minutes. Sentinel-1 SAR imagery supports the comparisons if available. Visual comparisons of SWOT and ICESat-2 with Sentinel-1 grey-scale values reveal clear coherence. However, small-scale surface features aren’t captured by SWOT as equally as by ICESat-2. The data shows absolute water level differences of about 5 cm, despite prior harmonisation of references and corrections. Differences of up to 50 cm can occur when comparing left- and right-hand SWOT swaths, mainly during winter and in areas with long sea ice coverage. This may be due to issues with the height correction from the crossover calibration. Quantitative point-by-point comparisons show mean standard deviations of about 8 cm for all surface types and 6 cm if restricted to ICESat-2-detected leads. Higher deviations are found during the early melting period between May and June, in the Canadian Archipelago and the Greenland Sea.

This study presents an Arctic-wide assessment of the Surface Water and Ocean Topography (SWOT) mission's swath observations of sea surface height. SWOT provides measurements in two-dimensional swaths and enables pixel-based height information with a resolution of 250 metres up to a latitudinal limit of 78° N. Although SWOT doesn’t cover the central Arctic, it provides insights into SSH at an unprecedented spatial and temporal resolution. The quality of these innovative observations in such a challenging environment is evaluated through comparison with data from ICESat-2. Approximately one year of sea level anomaly data, collected between March 2023 and April 2024, is used at around 550 regionally distributed crossover locations, with measurements taken within 30 minutes. Sentinel-1 SAR imagery supports the comparisons if available. Visual comparisons of SWOT and ICESat-2 with Sentinel-1 grey-scale values reveal clear coherence. However, small-scale surface features aren’t captured by SWOT as equally as by ICESat-2. The data shows absolute water level differences of about 5 cm, despite prior harmonisation of references and corrections. Differences of up to 50 cm can occur when comparing left- and right-hand SWOT swaths, mainly during winter and in areas with long sea ice coverage. This may be due to issues with the height correction from the crossover calibration. Quantitative point-by-point comparisons show mean standard deviations of about 8 cm for all surface types and 6 cm if restricted to ICESat-2-detected leads. Higher deviations are found during the early melting period between May and June, in the Canadian Archipelago and the Greenland Sea.

This study presents an Arctic-wide assessment of the Surface Water and Ocean Topography (SWOT) mission's swath observations of sea surface height. SWOT provides measurements in two-dimensional swaths and enables pixel-based height information with a resolution of 250 metres up to a latitudinal limit of 78° N. Although SWOT doesn’t cover the central Arctic, it provides insights into SSH at an unprecedented spatial and temporal resolution. The quality of these innovative observations in such a challenging environment is evaluated through comparison with data from ICESat-2. Approximately one year of sea level anomaly data, collected between March 2023 and April 2024, is used at around 550 regionally distributed crossover locations, with measurements taken within 30 minutes. Sentinel-1 SAR imagery supports the comparisons if available. Visual comparisons of SWOT and ICESat-2 with Sentinel-1 grey-scale values reveal clear coherence. However, small-scale surface features aren’t captured by SWOT as equally as by ICESat-2. The data shows absolute water level differences of about 5 cm, despite prior harmonisation of references and corrections. Differences of up to 50 cm can occur when comparing left- and right-hand SWOT swaths, mainly during winter and in areas with long sea ice coverage. This may be due to issues with the height correction from the crossover calibration. Quantitative point-by-point comparisons show mean standard deviations of about 8 cm for all surface types and 6 cm if restricted to ICESat-2-detected leads. Higher deviations are found during the early melting period between May and June, in the Canadian Archipelago and the Greenland Sea.

This study presents an Arctic-wide assessment of the Surface Water and Ocean Topography (SWOT) mission's swath observations of sea surface height. SWOT provides measurements in two-dimensional swaths and enables pixel-based height information with a resolution of 250 metres up to a latitudinal limit of 78° N. Although SWOT doesn’t cover the central Arctic, it provides insights into SSH at an unprecedented spatial and temporal resolution. The quality of these innovative observations in such a challenging environment is evaluated through comparison with data from ICESat-2. Approximately one year of sea level anomaly data, collected between March 2023 and April 2024, is used at around 550 regionally distributed crossover locations, with measurements taken within 30 minutes. Sentinel-1 SAR imagery supports the comparisons if available. Visual comparisons of SWOT and ICESat-2 with Sentinel-1 grey-scale values reveal clear coherence. However, small-scale surface features aren’t captured by SWOT as equally as by ICESat-2. The data shows absolute water level differences of about 5 cm, despite prior harmonisation of references and corrections. Differences of up to 50 cm can occur when comparing left- and right-hand SWOT swaths, mainly during winter and in areas with long sea ice coverage. This may be due to issues with the height correction from the crossover calibration. Quantitative point-by-point comparisons show mean standard deviations of about 8 cm for all surface types and 6 cm if restricted to ICESat-2-detected leads. Higher deviations are found during the early melting period between May and June, in the Canadian Archipelago and the Greenland Sea.