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Christian Schwatke
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM), Arcisstraße 21, 80333 München, Germany

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Journal article
Published: 21 August 2021 in Remote Sensing
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Satellite altimetry observations have provided a significant contribution to the understanding of global sea surface processes, particularly allowing for advances in the accuracy of ocean tide estimations. Currently, almost three decades of satellite altimetry are available which can be used to improve the understanding of ocean tides by allowing for the estimation of an increased number of minor tidal constituents. As ocean tide models continue to improve, especially in the coastal region, these minor tides become increasingly important. Generally, admittance theory is used by most global ocean tide models to infer several minor tides from the major tides when creating the tidal correction for satellite altimetry. In this paper, regional studies are conducted to compare the use of admittance theory to direct estimations of minor tides from the EOT20 model to identify which minor tides should be directly estimated and which should be inferred. The results of these two approaches are compared to two global tide models (TiME and FES2014) and in situ tide gauge observations. The analysis showed that of the eight tidal constituents studied, half should be inferred (2N2, ϵ2, MSF and T2), while the remaining four tides (J1, L2, μ2 and ν2) should be directly estimated to optimise the ocean tidal correction. Furthermore, for certain minor tides, the other two tide models produced better results than the EOT model, suggesting that improvements can be made to the tidal correction made by EOT when incorporating tides from the two other tide models. Following on from this, a new approach of merging tidal constituents from different tide models to produce the ocean tidal correction for satellite altimetry that benefits from the strengths of the respective models is presented. This analysis showed that the tidal correction created based on the recommendations of the tide gauge analysis provided the highest reduction of sea-level variance. Additionally, the combination of the EOT20 model with the minor tides of the TiME and FES2014 model did not significantly increase the sea-level variance. As several additional minor tidal constituents are available from the TiME model, this opens the door for further investigations into including these minor tides and optimising the tidal correction for improved studies of the sea surface from satellite altimetry and in other applications, such as gravity field modelling.

ACS Style

Michael G. Hart-Davis; Denise Dettmering; Roman Sulzbach; Maik Thomas; Christian Schwatke; Florian Seitz. Regional Evaluation of Minor Tidal Constituents for Improved Estimation of Ocean Tides. Remote Sensing 2021, 13, 3310 .

AMA Style

Michael G. Hart-Davis, Denise Dettmering, Roman Sulzbach, Maik Thomas, Christian Schwatke, Florian Seitz. Regional Evaluation of Minor Tidal Constituents for Improved Estimation of Ocean Tides. Remote Sensing. 2021; 13 (16):3310.

Chicago/Turabian Style

Michael G. Hart-Davis; Denise Dettmering; Roman Sulzbach; Maik Thomas; Christian Schwatke; Florian Seitz. 2021. "Regional Evaluation of Minor Tidal Constituents for Improved Estimation of Ocean Tides." Remote Sensing 13, no. 16: 3310.

Data description paper
Published: 02 August 2021 in Earth System Science Data
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Information on sea level and its temporal and spatial variability is of great importance for various scientific, societal, and economic issues. This article reports about a new sea level dataset for the North Sea (named North SEAL) of monthly sea level anomalies (SLAs), absolute sea level trends, and amplitudes of the mean annual sea level cycle over the period 1995–2019. Uncertainties and quality flags are provided together with the data. The dataset has been created from multi-mission cross-calibrated altimetry data preprocessed with coastal dedicated approaches and gridded with an innovative least-squares procedure including an advanced outlier detection to a 6–8 km wide triangular mesh. The comparison of SLAs and tide gauge time series shows good consistency, with average correlations of 0.85 and maximum correlations of 0.93. The improvement with respect to existing global gridded altimetry solutions amounts to 8 %–10 %, and it is most pronounced in complicated coastal environments such as river mouths or regions sheltered by islands. The differences in trends at tide gauge locations depend on the vertical land motion model used to correct relative sea level trends. The best consistency with a median difference of 0.04±1.15 mm yr−1 is reached by applying a recent glacial isostatic adjustment (GIA) model. With the presented sea level dataset, for the first time, a regionally optimized product for the entire North Sea is made available. It will enable further investigations of ocean processes, sea level projections, and studies on coastal adaptation measures. The North SEAL data are available at https://doi.org/10.17882/79673 (Müller et al., 2021).

ACS Style

Denise Dettmering; Felix L. Müller; Julius Oelsmann; Marcello Passaro; Christian Schwatke; Marco Restano; Jérôme Benveniste; Florian Seitz. North SEAL: a new dataset of sea level changes in the North Sea from satellite altimetry. Earth System Science Data 2021, 13, 3733 -3753.

AMA Style

Denise Dettmering, Felix L. Müller, Julius Oelsmann, Marcello Passaro, Christian Schwatke, Marco Restano, Jérôme Benveniste, Florian Seitz. North SEAL: a new dataset of sea level changes in the North Sea from satellite altimetry. Earth System Science Data. 2021; 13 (8):3733-3753.

Chicago/Turabian Style

Denise Dettmering; Felix L. Müller; Julius Oelsmann; Marcello Passaro; Christian Schwatke; Marco Restano; Jérôme Benveniste; Florian Seitz. 2021. "North SEAL: a new dataset of sea level changes in the North Sea from satellite altimetry." Earth System Science Data 13, no. 8: 3733-3753.

Journal article
Published: 26 June 2021 in Journal of Hydrology: Regional Studies
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The Great Rift Valley lakes of Kenya have recently experienced significant increases in their water levels, negatively impacting the local communities. This has provoked renewed concerns about the causations, with various geological, anthropogenic and hydro-climatic influences hypothesized as potential causes of the water level rises. This study analyses and documents water level fluctuations in Lakes Baringo, Bogoria, Nakuru, Solai, Elementaita and Naivasha. Hydrometeorological analyses are undertaken to understand potential causes and lake volume data is used to derive the “Integrated Catchment Response” (ICR), a magnitude which allows to relate changes in water balance components to signals observed in the lake volume changes. Compared to 1984−2009, the recent increases in lake areas range from 21 % for Lake Naivasha to an extraordinary 123 % for Lake Solai. Mean annual rainfall for 2010−2020 increased by up to 30 %. Actual evapotranspiration also increased, but to lesser extent compared to rainfall. The results illustrate that changes in catchment properties due to anthropogenic influences or changes in underground permeability are not necessary to explain the lake level rises. Based on the ICR only surprisingly minor changes in the water balance are necessary to explain the lake level rises, since an increase of only 0.4–2 % of mean annual effective rainfall leads to the observed phenomena.

ACS Style

Mathew Herrnegger; Gabriel Stecher; Christian Schwatke; Luke Olang. Hydroclimatic analysis of rising water levels in the Great rift Valley Lakes of Kenya. Journal of Hydrology: Regional Studies 2021, 36, 100857 .

AMA Style

Mathew Herrnegger, Gabriel Stecher, Christian Schwatke, Luke Olang. Hydroclimatic analysis of rising water levels in the Great rift Valley Lakes of Kenya. Journal of Hydrology: Regional Studies. 2021; 36 ():100857.

Chicago/Turabian Style

Mathew Herrnegger; Gabriel Stecher; Christian Schwatke; Luke Olang. 2021. "Hydroclimatic analysis of rising water levels in the Great rift Valley Lakes of Kenya." Journal of Hydrology: Regional Studies 36, no. : 100857.

Journal article
Published: 21 June 2021 in Nature Communications
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Coastal studies of wave climate and evaluations of wave energy resources are mainly regional and based on the use of computationally very expensive models or a network of in-situ data. Considering the significant wave height, satellite radar altimetry provides an established global and relatively long-term source, whose coastal data are nevertheless typically flagged as unreliable within 30 km of the coast. This study exploits the reprocessing of the radar altimetry signals with a dedicated fitting algorithm to retrieve several years of significant wave height records in the coastal zone. We show significant variations in annual cycle amplitudes and mean state in the last 30 km from the coastline compared to offshore, in areas that were up to now not observable with standard radar altimetry. Consequently, a decrease in the average wave energy flux is observed. Globally, we found that the mean significant wave height at 3 km off the coast is on average 22% smaller than offshore, the amplitude of the annual cycle is reduced on average by 14% and the mean energy flux loses 38% of its offshore value.

ACS Style

Marcello Passaro; Mark A. Hemer; Graham D. Quartly; Christian Schwatke; Denise Dettmering; Florian Seitz. Global coastal attenuation of wind-waves observed with radar altimetry. Nature Communications 2021, 12, 1 -13.

AMA Style

Marcello Passaro, Mark A. Hemer, Graham D. Quartly, Christian Schwatke, Denise Dettmering, Florian Seitz. Global coastal attenuation of wind-waves observed with radar altimetry. Nature Communications. 2021; 12 (1):1-13.

Chicago/Turabian Style

Marcello Passaro; Mark A. Hemer; Graham D. Quartly; Christian Schwatke; Denise Dettmering; Florian Seitz. 2021. "Global coastal attenuation of wind-waves observed with radar altimetry." Nature Communications 12, no. 1: 1-13.

Data description paper
Published: 21 May 2021 in Earth System Science Data
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Observations of changes in terrestrial water storage (TWS) obtained from the satellite mission GRACE (Gravity Recovery and Climate Experiment) have frequently been used for water cycle studies and for the improvement of hydrological models by means of calibration and data assimilation. However, due to a low spatial resolution of the gravity field models, spatially localized water storage changes, such as those occurring in lakes and reservoirs, cannot properly be represented in the GRACE estimates. As surface storage changes can represent a large part of total water storage, this leads to leakage effects and results in surface water signals becoming erroneously assimilated into other water storage compartments of neighbouring model grid cells. As a consequence, a simple mass balance at grid/regional scale is not sufficient to deconvolve the impact of surface water on TWS. Furthermore, non-hydrology-related phenomena contained in the GRACE time series, such as the mass redistribution caused by major earthquakes, hamper the use of GRACE for hydrological studies in affected regions. In this paper, we present the first release (RL01) of the global correction product RECOG (REgional COrrections for GRACE), which accounts for both the surface water (lakes and reservoirs, RECOG-LR) and earthquake effects (RECOG-EQ). RECOG-LR is computed from forward-modelling surface water volume estimates derived from satellite altimetry and (optical) remote sensing and allows both a removal of these signals from GRACE and a relocation of the mass change to its origin within the outline of the lakes/reservoirs. The earthquake correction, RECOG-EQ, includes both the co-seismic and post-seismic signals of two major earthquakes with magnitudes above Mw9. We discuss that applying the correction dataset (1) reduces the GRACE signal variability by up to 75 % around major lakes and explains a large part of GRACE seasonal variations and trends, (2) avoids the introduction of spurious trends caused by leakage signals of nearby lakes when calibrating/assimilating hydrological models with GRACE, and (3) enables a clearer detection of hydrological droughts in areas affected by earthquakes. A first validation of the corrected GRACE time series using GPS-derived vertical station displacements shows a consistent improvement of the fit between GRACE and GNSS after applying the correction. Data are made available on an open-access basis via the Pangaea database (RECOG-LR: Deggim et al., 2020a, https://doi.org/10.1594/PANGAEA.921851; RECOG-EQ: Gerdener et al., 2020b, https://doi.org/10.1594/PANGAEA.921923).

ACS Style

Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. Earth System Science Data 2021, 13, 2227 -2244.

AMA Style

Simon Deggim, Annette Eicker, Lennart Schawohl, Helena Gerdener, Kerstin Schulze, Olga Engels, Jürgen Kusche, Anita T. Saraswati, Tonie van Dam, Laura Ellenbeck, Denise Dettmering, Christian Schwatke, Stefan Mayr, Igor Klein, Laurent Longuevergne. RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. Earth System Science Data. 2021; 13 (5):2227-2244.

Chicago/Turabian Style

Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. 2021. "RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes." Earth System Science Data 13, no. 5: 2227-2244.

Preprint content
Published: 05 May 2021
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The Central Rift Valley lakes of Kenya have recently experienced significant increases in their water levels, negatively impacting the local communities. This has provoked renewed concerns about the causations, with various geological, anthropogenic and hydro-climatic influences hypothesized as potential causes of the water level rises. This study systematically analyses and documents water level fluctuations in Lakes Baringo, Bogoria, Nakuru, Solai, Elementaita and Naivasha. Long-term hydrometeorological analyses are undertaken to understand potential causes. Satellite-based lake volume variation data is used to derive the “Integrated Catchment Response” (ICR), a magnitude which allows to relate the changes in water balance components to the signal observed in the lake volume changes. Compared to 1984-2009, the increases in lake areas range from 21% for Lake Naivasha to an extraordinary 123% for Lake Solai. Fluctuation between minimum and maximum water level range between 8.53 m and 2.38 m. Mean annual rainfall for 2010-2020 increased by up to 30%. Actual evapotranspiration also increased, but to lesser extent compared to rainfall. The results clearly show the connection between changes in (effective) rainfall and observed lake level rises and that changes in catchment properties due to anthropogenic influences or changes in underground permeability are not necessary to explain the lake level rises. The ICR highlights that only small changes in the water balance are necessary to explain the increases in the lake level rises.

ACS Style

Mathew Herrnegger; Gabriel Stecher; Christian Schwatke; Luke Olang. Hydroclimatic Analysis of Rising Water Levels in the Great Rift Valley Lakes of Kenya. 2021, 1 .

AMA Style

Mathew Herrnegger, Gabriel Stecher, Christian Schwatke, Luke Olang. Hydroclimatic Analysis of Rising Water Levels in the Great Rift Valley Lakes of Kenya. . 2021; ():1.

Chicago/Turabian Style

Mathew Herrnegger; Gabriel Stecher; Christian Schwatke; Luke Olang. 2021. "Hydroclimatic Analysis of Rising Water Levels in the Great Rift Valley Lakes of Kenya." , no. : 1.

Preprint content
Published: 29 March 2021
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Information on sea level and its temporal and spatial variability is of great importance for various scientific, societal and economic issues. This article reports about a new sea level dataset for the North Sea (named NorthSEAL) of monthly sea level anomalies (SLA), absolute sea level trends and sea level mean annual amplitudes over the period 1995–2019. Uncertainties and quality flags are provided together with the data. The dataset has been created from multi-mission cross-calibrated altimetry data, preprocessed 5 with coastal dedicated approaches and gridded with innovative methods to a 6–8 km wide triangular mesh. The comparison of SLA and tide gauge time series shows a good consistency with average correlations of 0.85 and maximum correlations of 0.93. The improvement with respect to existing global gridded altimetry solutions amounts to 8–10 %, and it is most pronounced in complicated coastal environments such as river mouths or regions sheltered by islands. The differences in trends at tide gauge locations depend on the vertical land motion model used to correct relative sea level trends. The best 10 consistency with a median difference of 0.04 ± 1.15 mm/year is reached by applying a recent glacial isostatic adjustment (GIA) model. With the presented sea level dataset, for the first time, a regionally optimized product for the entire North Sea is made available. It will enable further investigations of ocean processes, sea level projections and studies on coastal adaptation measures. The NorthSEAL data is available at https://doi.org/10.17882/79673 (Müller et al., 2021).

ACS Style

Denise Dettmering; Felix L. Müller; Julius Oelsmann; Marcello Passaro; Christian Schwatke; Marco Restano; Jérôme Benveniste; Florian Seitz. NorthSEAL: A new Dataset of Sea Level Changes in the North Sea from Satellite Altimetry. 2021, 2021, 1 -28.

AMA Style

Denise Dettmering, Felix L. Müller, Julius Oelsmann, Marcello Passaro, Christian Schwatke, Marco Restano, Jérôme Benveniste, Florian Seitz. NorthSEAL: A new Dataset of Sea Level Changes in the North Sea from Satellite Altimetry. . 2021; 2021 ():1-28.

Chicago/Turabian Style

Denise Dettmering; Felix L. Müller; Julius Oelsmann; Marcello Passaro; Christian Schwatke; Marco Restano; Jérôme Benveniste; Florian Seitz. 2021. "NorthSEAL: A new Dataset of Sea Level Changes in the North Sea from Satellite Altimetry." 2021, no. : 1-28.

Preprint content
Published: 26 March 2021
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EOT20 is the latest in a series of empirical ocean tide (EOT) models derived using residual tidal analysis of multi-mission satellite altimetry at DGFI-TUM. The amplitudes and phases of seventeen tidal constituents are provided on a global 0.125-degree grid based on empirical analysis of seven satellite altimetry missions and four extended missions. The EOT20 model shows significant improvements compared to the previous iteration of the global model (EOT11a) throughout the ocean, particularly in the coastal and shelf regions, due to the inclusion of more recent satellite altimetry data as well as more missions, the use of the updated FES2014 tidal model as a reference to estimated residual signals, the inclusion of the ALES retracker and improved coastal representation. In the validation of EOT20 using tide gauges and ocean bottom pressure data, these improvements in the model compared to EOT11a are highlighted with the root-square sum (RSS) of the eight major tidal constituents improving by ~3 cm for the entire global ocean with the major improvement in RSS (~3.5 cm) occurring in the coastal region. Concerning the other global ocean tidal models, EOT20 shows an improvement of ~0.2 cm in RSS compared to the closest model (FES2014) in the global ocean. Variance reduction analysis was conducted comparing the results of EOT20 with FES2014 and EOT11a using the Jason-2, Jason-3 and SARAL satellite altimetry missions. From this analysis, EOT20 showed a variance reduction for all three satellite altimetry missions with the biggest improvement in variance occurring in the coastal region. These significant improvements, particularly in the coastal region, provides encouragement for the use of the EOT20 model as a tidal correction for satellite altimetry in sea-level research. All ocean and load tide data from the model can be freely accessed at https://doi.org/10.17882/79489 (Hart-Davis et al., 2021).

ACS Style

Michael Geoffrey Hart-Davis; Gaia Piccioni; Denise Dettmering; Christian Schwatke; Marcello Passaro; Florian Seitz. EOT20: A global ocean tide model from multi-mission satellite altimetry. 2021, 2021, 1 -23.

AMA Style

Michael Geoffrey Hart-Davis, Gaia Piccioni, Denise Dettmering, Christian Schwatke, Marcello Passaro, Florian Seitz. EOT20: A global ocean tide model from multi-mission satellite altimetry. . 2021; 2021 ():1-23.

Chicago/Turabian Style

Michael Geoffrey Hart-Davis; Gaia Piccioni; Denise Dettmering; Christian Schwatke; Marcello Passaro; Florian Seitz. 2021. "EOT20: A global ocean tide model from multi-mission satellite altimetry." 2021, no. : 1-23.

Correction
Published: 19 March 2021 in Remote Sensing
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Our earlier work on assessment of altimeter significant wave height (SWH) algorithms

ACS Style

Florian Schlembach; Marcello Passaro; Graham Quartly; Andrey Kurekin; Francesco Nencioli; Guillaume Dodet; Jean-François Piollé; Fabrice Ardhuin; Jean Bidlot; Christian Schwatke; Florian Seitz; Paolo Cipollini; Craig Donlon. Correction: Schlembach, F., et al. Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height. Remote Sens. 2020, 12, 1254. Remote Sensing 2021, 13, 1182 .

AMA Style

Florian Schlembach, Marcello Passaro, Graham Quartly, Andrey Kurekin, Francesco Nencioli, Guillaume Dodet, Jean-François Piollé, Fabrice Ardhuin, Jean Bidlot, Christian Schwatke, Florian Seitz, Paolo Cipollini, Craig Donlon. Correction: Schlembach, F., et al. Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height. Remote Sens. 2020, 12, 1254. Remote Sensing. 2021; 13 (6):1182.

Chicago/Turabian Style

Florian Schlembach; Marcello Passaro; Graham Quartly; Andrey Kurekin; Francesco Nencioli; Guillaume Dodet; Jean-François Piollé; Fabrice Ardhuin; Jean Bidlot; Christian Schwatke; Florian Seitz; Paolo Cipollini; Craig Donlon. 2021. "Correction: Schlembach, F., et al. Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height. Remote Sens. 2020, 12, 1254." Remote Sensing 13, no. 6: 1182.

Preprint content
Published: 03 March 2021
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EOT20 is the latest in a series of empirical ocean tide (EOT) models derived using residual tidal analysis of multi-mission satellite altimetry at DGFI-TUM. The amplitudes and phases of seventeen tidal constituents are provided on a global 0.125-degree grid based on empirical analysis of eleven satellite altimetry missions. The EOT20 model shows significant improvements compared to the previous iteration of the global model (EOT11a) throughout the ocean, particularly in the coastal and shelf regions, due to the inclusion of more recent satellite altimetry data as well as more missions, the use of the updated FES2014 tidal model as a reference to estimated residual signals, the inclusion of the ALES retracker and improved coastal representation. In the validation of EOT20 using tide gauges and ocean bottom pressure data, these improvements in the model compared to EOT11a are highlighted with the root-square sum (RSS) of the eight major tidal constituents improving by ~3 cm for the entire global ocean with the major improvement in RSS (~3.5 cm) occurring in coastal regions (<1 km to the coast). Compared to the other global ocean tidal models, EOT20 shows a clear improvement of ~0.4 cm in RSS compared to the closest model (FES2014) in the global ocean. Compared to the FES2014 model, the RSS improvement in EOT20 is mainly seen in the coastal region (~0.45 cm) while in the shelf and open ocean regions these two models only vary in terms of RSS by ~0.005 cm. The significant improvement of EOT20, particularly in the coastal region, provides encouragement for the use of the EOT20 model as a tidal correction of satellite altimetry in coastal sea level research. 

ACS Style

Michael Hart-Davis; Denise Dettmering; Gaia Piccioni; Christian Schwatke; Marcello Passaro; Florian Seitz. EOT20: A new global empirical ocean tide model derived from multi-mission satellite altimetry. 2021, 1 .

AMA Style

Michael Hart-Davis, Denise Dettmering, Gaia Piccioni, Christian Schwatke, Marcello Passaro, Florian Seitz. EOT20: A new global empirical ocean tide model derived from multi-mission satellite altimetry. . 2021; ():1.

Chicago/Turabian Style

Michael Hart-Davis; Denise Dettmering; Gaia Piccioni; Christian Schwatke; Marcello Passaro; Florian Seitz. 2021. "EOT20: A new global empirical ocean tide model derived from multi-mission satellite altimetry." , no. : 1.

Journal article
Published: 18 February 2021 in Advances in Space Research
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In the context of the ESA Climate Change Initiative project, a new coastal sea level altimetry product has been developed in order to support advances in coastal sea level variability studies. Measurements from Jason-1,2&3 missions have been retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker and then ingested in the X-TRACK software with the best possible set of altimetry corrections. These two coastal altimetry processing approaches, previously successfully validated and applied to coastal sea level research, are combined here for the first time in order to derive a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset in six regions: Northeast Atlantic, Mediterranean Sea, West Africa, North Indian Ocean, Southeast Asia and Australia. The study demonstrates that this new coastal sea level product called X-TRACK/ALES is able to extend the spatial coverage of sea level altimetry data ~3.5 km in the land direction, when compared to the X-TRACK 1-Hz dataset. We also observe a large improvement in coastal sea level data availability from Jason-1 to Jason-3, with data at 3.6 km, 1.9 km and 0.9 km to the coast on average, for Jason-1, Jason-2 and Jason-3, respectively. When combining measurements from Jason-1 to Jason-3, we reach a distance of 1.2–4 km to the coast. When compared to tide gauge data, the accuracy of the new altimetry near-shore sea level estimations also improves. In terms of correlations with a large set of independent tide gauge observations selected in the six regions, we obtain an average value of 0.77. We also show that it is now possible to derive from the X-TRACK/ALES product an estimation of the ocean current variability up to 5 km to the coast. This new altimetry dataset, freely available, will provide a valuable contribution of altimetry in coastal marine research community.

ACS Style

Florence Birol; Fabien Léger; Marcello Passaro; Anny Cazenave; Fernando Niño; Francisco M. Calafat; Andrew Shaw; Jean-François Legeais; Yvan Gouzenes; Christian Schwatke; Jérôme Benveniste. The X-TRACK/ALES multi-mission processing system: New advances in altimetry towards the coast. Advances in Space Research 2021, 67, 2398 -2415.

AMA Style

Florence Birol, Fabien Léger, Marcello Passaro, Anny Cazenave, Fernando Niño, Francisco M. Calafat, Andrew Shaw, Jean-François Legeais, Yvan Gouzenes, Christian Schwatke, Jérôme Benveniste. The X-TRACK/ALES multi-mission processing system: New advances in altimetry towards the coast. Advances in Space Research. 2021; 67 (8):2398-2415.

Chicago/Turabian Style

Florence Birol; Fabien Léger; Marcello Passaro; Anny Cazenave; Fernando Niño; Francisco M. Calafat; Andrew Shaw; Jean-François Legeais; Yvan Gouzenes; Christian Schwatke; Jérôme Benveniste. 2021. "The X-TRACK/ALES multi-mission processing system: New advances in altimetry towards the coast." Advances in Space Research 67, no. 8: 2398-2415.

Journal article
Published: 12 January 2021 in Ocean Science
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Vertical land motion (VLM) at the coast is a substantial contributor to relative sea level change. In this work, we present a refined method for its determination, which is based on the combination of absolute satellite altimetry (SAT) sea level measurements and relative sea level changes recorded by tide gauges (TGs). These measurements complement VLM estimates from the GNSS (Global Navigation Satellite System) by increasing their spatial coverage. Trend estimates from the SAT and TG combination are particularly sensitive to the quality and resolution of applied altimetry data as well as to the coupling procedure of altimetry and TGs. Hence, a multi-mission, dedicated coastal along-track altimetry dataset is coupled with high-frequency TG measurements at 58 stations. To improve the coupling procedure, a so-called “zone of influence” (ZOI) is defined, which confines coherent zones of sea level variability on the basis of relative levels of comparability between TG and altimetry observations. Selecting 20 % of the most representative absolute sea level observations in a 300 km radius around the TGs results in the best VLM estimates in terms of accuracy and uncertainty. At this threshold, VLMSAT-TG estimates have median formal uncertainties of 0.58 mm yr−1. Validation against GNSS VLM estimates yields a root mean square (rmsΔVLM) of VLMSAT-TG and VLMGNSS differences of 1.28 mm yr−1, demonstrating the level of accuracy of our approach. Compared to a reference 250 km radius selection, the 300 km zone of influence improves trend accuracies by 15 % and uncertainties by 35 %. With increasing record lengths, the spatial scales of the coherency in coastal sea level trends increase. Therefore, the relevance of the ZOI for improving VLMSAT-TG accuracy decreases. Further individual zone of influence adaptations offer the prospect of bringing the accuracy of the estimates below 1 mm yr−1.

ACS Style

Julius Oelsmann; Marcello Passaro; Denise Dettmering; Christian Schwatke; Laura Sánchez; Florian Seitz. The zone of influence: matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation. Ocean Science 2021, 17, 35 -57.

AMA Style

Julius Oelsmann, Marcello Passaro, Denise Dettmering, Christian Schwatke, Laura Sánchez, Florian Seitz. The zone of influence: matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation. Ocean Science. 2021; 17 (1):35-57.

Chicago/Turabian Style

Julius Oelsmann; Marcello Passaro; Denise Dettmering; Christian Schwatke; Laura Sánchez; Florian Seitz. 2021. "The zone of influence: matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation." Ocean Science 17, no. 1: 35-57.

Preprint content
Published: 22 October 2020
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Observations of changes in terrestrial water storage obtained from the satellite mission GRACE (Gravity Recovery and Climate Experiment) have frequently been used for water cycle studies and for the improvement of hydrological models by means of calibration and data assimilation. However, due to a low spatial resolution of the gravity field models spatially localized water storage changes, such as those occurring in lakes and reservoirs, cannot properly be represented in the GRACE estimates. As surface storage changes can represent a large part of total water storage, this leads to leakage effects and results in surface water signals becoming erroneously assimilated into other water storage compartments of neighboring model grid cells. As a consequence, a simple mass balance at grid/regional scale is not sufficient to deconvolve the impact of surface water on TWS. Furthermore, non-hydrology related phenomena contained in the GRACE time series, such as the mass redistribution caused by major earthquakes, hamper the use of GRACE for hydrological studies in affected regions. In this paper, we present the first release (RL01) of the global correction product RECOG (REgional COrrections for GRACE), which accounts for both the surface water (lakes & reservoirs, RECOG-LR) and earthquake effects (RECOG-EQ). RECOG-LR is computed from forward-modelling surface water volume estimates derived from satellite altimetry and (optical) remote sensing and allows both a removal of these signals from GRACE and a re-location of the mass change to its origin within the outline of the lakes/reservoirs. The earthquake correction RECOG-EQ includes both the co-seismic and post-seismic signals of two major earthquakes with magnitudes above 9 Mw. We can show that applying the correction dataset (1) reduces the GRACE signal variability by up to 75 % around major lakes and explains a large part of GRACE seasonal variations and trends, (2) avoids the introduction of spurious trends caused by leakage signals of nearby lakes when calibrating/assimilating hydrological models with GRACE, even in neighboring river basins, and (3) enables a clearer detection of hydrological droughts in areas affected by earthquakes. A first validation of the corrected GRACE time series using GPS-derived vertical station displacements shows a consistent improvement of the fit between GRACE and GNSS after applying the correction. Data are made available as open access via the Pangea database (RECOG-LR: Deggim et al. (2020a) https://doi.org/10.1594/PANGAEA.921851; RECOG-EQ: Gerdener et al. (2020b, under revision), https://doi.pangaea.de/10.1594/PANGAEA.921923).

ACS Style

Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. 2020, 1 -30.

AMA Style

Simon Deggim, Annette Eicker, Lennart Schawohl, Helena Gerdener, Kerstin Schulze, Olga Engels, Jürgen Kusche, Anita T. Saraswati, Tonie van Dam, Laura Ellenbeck, Denise Dettmering, Christian Schwatke, Stefan Mayr, Igor Klein, Laurent Longuevergne. RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. . 2020; ():1-30.

Chicago/Turabian Style

Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. 2020. "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes." , no. : 1-30.

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Published: 22 October 2020
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Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. Supplementary material to "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes". 2020, 1 .

AMA Style

Simon Deggim, Annette Eicker, Lennart Schawohl, Helena Gerdener, Kerstin Schulze, Olga Engels, Jürgen Kusche, Anita T. Saraswati, Tonie van Dam, Laura Ellenbeck, Denise Dettmering, Christian Schwatke, Stefan Mayr, Igor Klein, Laurent Longuevergne. Supplementary material to "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes". . 2020; ():1.

Chicago/Turabian Style

Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. 2020. "Supplementary material to "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes"." , no. : 1.

Journal article
Published: 12 October 2020 in Remote Sensing
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Remote sensing data are essential for monitoring the Earth’s surface waters, especially since the amount of publicly available in-situ data is declining. Satellite altimetry provides valuable information on the water levels and variations of lakes, reservoirs and rivers. In combination with satellite imagery, the derived time series allow the monitoring of lake storage changes and river discharge. However, satellite altimetry is limited in terms of its spatial resolution due to its measurement geometry, only providing information in the nadir direction beneath the satellite’s orbit. In a case study in the Mississippi River Basin (MRB), this study investigates the potential and limitations of past and current satellite missions for the monitoring of basin-wide storage changes. For that purpose, an automated target detection is developed and the extracted lake surfaces are merged with the satellites’ tracks. This reveals that the current altimeter configuration misses about 80% of all lakes larger than 0.1 km2 in the MRB and 20% of lakes larger than 10 km2, corresponding to 30% and 7% of the total water area, respectively. Past altimetry configurations perform even more poorly. From the larger water bodies represented by a global hydrology model, at least 91% of targets and 98% of storage changes are captured by the current altimeter configuration. This will improve significantly with the launch of the planned Surface Water and Ocean Topography (SWOT) mission.

ACS Style

Denise Dettmering; Laura Ellenbeck; Daniel Scherer; Christian Schwatke; Christoph Niemann. Potential and Limitations of Satellite Altimetry Constellations for Monitoring Surface Water Storage Changes—A Case Study in the Mississippi Basin. Remote Sensing 2020, 12, 3320 .

AMA Style

Denise Dettmering, Laura Ellenbeck, Daniel Scherer, Christian Schwatke, Christoph Niemann. Potential and Limitations of Satellite Altimetry Constellations for Monitoring Surface Water Storage Changes—A Case Study in the Mississippi Basin. Remote Sensing. 2020; 12 (20):3320.

Chicago/Turabian Style

Denise Dettmering; Laura Ellenbeck; Daniel Scherer; Christian Schwatke; Christoph Niemann. 2020. "Potential and Limitations of Satellite Altimetry Constellations for Monitoring Surface Water Storage Changes—A Case Study in the Mississippi Basin." Remote Sensing 12, no. 20: 3320.

Journal article
Published: 07 October 2020 in Ocean Science
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In the context of the ESA Climate Change Initiative project, we are engaged in a regional reprocessing of high-resolution (20 Hz) altimetry data of the classical missions in a number of the world's coastal zones. It is done using the ALES (Adaptive Leading Edge Subwaveform) retracker combined with the X-TRACK system dedicated to improve geophysical corrections at the coast. Using the Jason-1 and Jason-2 satellite data, high-resolution, along-track sea level time series have been generated, and coastal sea level trends have been computed over a 14-year time span (from July 2002 to June 2016). In this paper, we focus on a particular coastal site where the Jason track crosses land, Senetosa, located south of Corsica in the Mediterranean Sea, for two reasons: (1) the rate of sea level rise estimated in this project increases significantly in the last 4–5 km to the coast compared to what is observed further offshore, and (2) Senetosa is the calibration site for the TOPEX/Poseidon and Jason altimetry missions, which are equipped for that purpose with in situ instrumentation, in particular tide gauges and a Global Navigation Satellite System (GNSS) antenna. A careful examination of all the potential errors that could explain the increased rate of sea level rise close to the coast (e.g., spurious trends in the geophysical corrections, imperfect inter-mission bias estimate, decrease of valid data close to the coast and errors in waveform retracking) has been carried out, but none of these effects appear able to explain the trend increase. We further explored the possibility that it results from real physical processes. Change in wave conditions was investigated, but wave setup was excluded as a potential contributor because the magnitude was too low and too localized in the immediate vicinity of the shoreline. A preliminary model-based investigation about the contribution of coastal currents indicates that it could be a plausible explanation of the observed change in sea level trend close to the coast.

ACS Style

Yvan Gouzenes; Fabien Léger; Anny Cazenave; Florence Birol; Pascal Bonnefond; Marcello Passaro; Fernando Nino; Rafael Almar; Olivier Laurain; Christian Schwatke; Jean-François Legeais; Jérôme Benveniste. Coastal sea level rise at Senetosa (Corsica) during the Jason altimetry missions. Ocean Science 2020, 16, 1165 -1182.

AMA Style

Yvan Gouzenes, Fabien Léger, Anny Cazenave, Florence Birol, Pascal Bonnefond, Marcello Passaro, Fernando Nino, Rafael Almar, Olivier Laurain, Christian Schwatke, Jean-François Legeais, Jérôme Benveniste. Coastal sea level rise at Senetosa (Corsica) during the Jason altimetry missions. Ocean Science. 2020; 16 (5):1165-1182.

Chicago/Turabian Style

Yvan Gouzenes; Fabien Léger; Anny Cazenave; Florence Birol; Pascal Bonnefond; Marcello Passaro; Fernando Nino; Rafael Almar; Olivier Laurain; Christian Schwatke; Jean-François Legeais; Jérôme Benveniste. 2020. "Coastal sea level rise at Senetosa (Corsica) during the Jason altimetry missions." Ocean Science 16, no. 5: 1165-1182.

Journal article
Published: 20 August 2020 in Remote Sensing
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Despite increasing interest in monitoring the global water cycle, the availability of in situ gauging and discharge time series is decreasing. However, this lack of ground data can partly be compensated for by using remote sensing techniques to observe river stages and discharge. In this paper, a new approach for estimating discharge by combining water levels from multi-mission satellite altimetry and surface area extents from optical imagery with physical flow equations at a single cross-section is presented and tested at the Lower Mississippi River. The datasets are combined by fitting a hypsometric curve, which is then used to derive the water level for each acquisition epoch of the long-term multi-spectral remote sensing missions. In this way, the chance of detecting water level extremes is increased and a bathymetry can be estimated from water surface extent observations. Below the minimum hypsometric water level, the river bed elevation is estimated using an empirical width-to-depth relationship in order to determine the final cross-sectional geometry. The required flow gradient is derived from the differences between virtual station elevations, which are computed in a least square adjustment from the height differences of all multi-mission satellite altimetry data that are close in time. Using the virtual station elevations, satellite altimetry data from multiple virtual stations and missions are combined to one long-term water level time series. All required parameters are estimated purely based on remote sensing data, without using any ground data or calibration. The validation at three gauging stations of the Lower Mississippi River shows large deviations primarily caused by the below average width of the predefined cross-sections. At 13 additional cross-sections situated in wide, uniform, and straight river sections nearby the gauges the Normalized Root Mean Square Error (NRMSE) varies between 10.95% and 28.43%. The Nash-Sutcliffe Efficiency (NSE) for these targets is in a range from 0.658 to 0.946.

ACS Style

Daniel Scherer; Christian Schwatke; Denise Dettmering; Florian Seitz. Long-Term Discharge Estimation for the Lower Mississippi River Using Satellite Altimetry and Remote Sensing Images. Remote Sensing 2020, 12, 2693 .

AMA Style

Daniel Scherer, Christian Schwatke, Denise Dettmering, Florian Seitz. Long-Term Discharge Estimation for the Lower Mississippi River Using Satellite Altimetry and Remote Sensing Images. Remote Sensing. 2020; 12 (17):2693.

Chicago/Turabian Style

Daniel Scherer; Christian Schwatke; Denise Dettmering; Florian Seitz. 2020. "Long-Term Discharge Estimation for the Lower Mississippi River Using Satellite Altimetry and Remote Sensing Images." Remote Sensing 12, no. 17: 2693.

Preprint content
Published: 27 May 2020
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Vertical land motion (VLM) at the coast is a substantial contributor to relative sea level change. In this work, we present a refined method for its determination, which is based on the combination of absolute satellite alimetry (SAT) sea level measurements and relative sea level changes recorded by tide gauges (TG). These measurements complement VLM estimates based on GNSS (Global Navigation Satellite System) by increasing their spatial coverage. Trend estimates from SAT and TG combination are particularly sensitive to the quality and resolution of applied altimetry data as well as to the coupling procedure of altimetry and tide gauges. Hence, a multi-mission, dedicated coastal along-track altimetry dataset is coupled with highfrequent tide gauge measurements at 58 stations. To improve the coupling-procedure, a so-called `Zone of Influence’ is defined to identify coherent zones of sea level variability on the basis of relative levels of comparability between tide gauge and altimetry observations. Selecting 20 % of the most representative absolute sea level observations in a 300 km radius around the tide gauges results in the best VLM-estimates in terms of accuracies and uncertainties. At this threshold, VLM_SAT-TG estimates have median formal uncertainties of 0.59 mm/year. Validation against GNSS VLM estimates yields a root-mean-square (RMS_VLM) of VLM_SAT-TG and VLM_GNSS differences of 1.28 mm/year, demonstrating the level of accuracy of our approach. Compared to a reference 250 km radius selection of sea level anomalies, the 300 km Zone of Influence improves trend accuracies by 12 % and uncertainties by 28 %. With progressing record lengths, the spatial scales of coastal sea level trend coherency increase. Therefore the relevance of the ZOI for improving VLM_SAT-TG accuracies decreases. Further individual Zone of Influence adaptations offer the prospect of bringing the accuracy of the estimates below 1 mm/year.

ACS Style

Julius Oelsmann; Marcello Passaro; Denise Dettmering; Christian Schwatke; Laura Sanchez; Florian Seitz. The Zone of Influence: Matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation. 2020, 2020, 1 -32.

AMA Style

Julius Oelsmann, Marcello Passaro, Denise Dettmering, Christian Schwatke, Laura Sanchez, Florian Seitz. The Zone of Influence: Matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation. . 2020; 2020 ():1-32.

Chicago/Turabian Style

Julius Oelsmann; Marcello Passaro; Denise Dettmering; Christian Schwatke; Laura Sanchez; Florian Seitz. 2020. "The Zone of Influence: Matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation." 2020, no. : 1-32.

Journal article
Published: 18 May 2020 in Remote Sensing
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In this study, a new approach for estimating volume variations of lakes and reservoirs using water levels from satellite altimetry and surface areas from optical imagery is presented. Both input data sets, namely water level time series and surface area time series, are provided by the Database of Hydrological Time Series of Inland Waters (DAHITI), developed and maintained by the Deutsches Geodätisches Forschungsinsitut der Technischen Universität München (DGFI-TUM). The approach is divided into three parts. In the first part, a hypsometry model based on the new modified Strahler approach is computed by combining water levels and surface areas. The hypsometry model describes the dependency between water levels and surface areas of lakes and reservoirs. In the second part, a bathymetry between minimum and maximum surface area is computed. For this purpose, DAHITI land-water masks are stacked using water levels derived from the hypsometry model. Finally, water levels and surface areas are intersected with the bathymetry to estimate a time series of volume variations in relation to the minimum observed surface area. The results are validated with volume time series derived from in-situ water levels in combination with bathymetric surveys. In this study, 28 lakes and reservoirs located in Texas are investigated. The absolute volumes of the investigated lakes and reservoirs vary between 0.062 km 3 and 6.041 km 3 . The correlation coefficients of the resulting volume variation time series with validation data vary between 0.80 and 0.99. Overall, the relative errors with respect to volume variations vary between 2.8% and 14.9% with an average of 8.3% for all 28 investigated lakes and reservoirs. When comparing the resulting RMSE with absolute volumes, the absolute errors vary between 1.5% and 6.4% with an average of 3.1%. This study shows that volume variations can be calculated with a high accuracy which depends essentially on the quality of the used water levels and surface areas. In addition, this study provides a hypsometry model, high-resolution bathymetry and water level time series derived from surface areas based on the hypsometry model. All data sets are publicly available on the Database of Hydrological Time Series of Inland Waters.

ACS Style

Christian Schwatke; Denise Dettmering; Florian Seitz. Volume Variations of Small Inland Water Bodies from a Combination of Satellite Altimetry and Optical Imagery. Remote Sensing 2020, 12, 1606 .

AMA Style

Christian Schwatke, Denise Dettmering, Florian Seitz. Volume Variations of Small Inland Water Bodies from a Combination of Satellite Altimetry and Optical Imagery. Remote Sensing. 2020; 12 (10):1606.

Chicago/Turabian Style

Christian Schwatke; Denise Dettmering; Florian Seitz. 2020. "Volume Variations of Small Inland Water Bodies from a Combination of Satellite Altimetry and Optical Imagery." Remote Sensing 12, no. 10: 1606.

Journal article
Published: 16 April 2020 in Remote Sensing
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Radar altimeters have been measuring ocean significant wave height for more than three decades, with their data used to record the severity of storms, the mixing of surface waters and the potential threats to offshore structures and low-lying land, and to improve operational wave forecasting. Understanding climate change and long-term planning for enhanced storm and flooding hazards are imposing more stringent requirements on the robustness, precision, and accuracy of the estimates than have hitherto been needed. Taking advantage of novel retracking algorithms, particularly developed for the coastal zone, the present work aims at establishing an objective baseline processing chain for wave height retrieval that can be adapted to all satellite missions. In order to determine the best performing retracking algorithm for both Low Resolution Mode and Delay-Doppler altimetry, an objective assessment is conducted in the framework of the European Space Agency Sea State Climate Change Initiative project. All algorithms process the same Level-1 input dataset covering a time-period of up to two years. As a reference for validation, an ERA5-based hindcast wave model as well as an in-situ buoy dataset from the Copernicus Marine Environment Monitoring Service In Situ Thematic Centre database are used. Five different metrics are evaluated: percentage and types of outliers, level of measurement noise, wave spectral variability, comparison against wave models, and comparison against in-situ data. The metrics are evaluated as a function of the distance to the nearest coast and the sea state. The results of the assessment show that all novel retracking algorithms perform better in the majority of the metrics than the baseline algorithms currently used for operational generation of the products. Nevertheless, the performance of the retrackers strongly differ depending on the coastal proximity and the sea state. Some retrackers show high correlations with the wave models and in-situ data but significantly under- or overestimate large-scale spectral variability. We propose a weighting scheme to select the most suitable retrackers for the Sea State Climate Change Initiative programme.

ACS Style

Florian Schlembach; Marcello Passaro; Graham D. Quartly; Andrey Kurekin; Francesco Nencioli; Guillaume Dodet; Jean-François Piollé; Fabrice Ardhuin; Jean Bidlot; Christian Schwatke; Florian Seitz; Paolo Cipollini; Craig Donlon. Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height. Remote Sensing 2020, 12, 1254 .

AMA Style

Florian Schlembach, Marcello Passaro, Graham D. Quartly, Andrey Kurekin, Francesco Nencioli, Guillaume Dodet, Jean-François Piollé, Fabrice Ardhuin, Jean Bidlot, Christian Schwatke, Florian Seitz, Paolo Cipollini, Craig Donlon. Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height. Remote Sensing. 2020; 12 (8):1254.

Chicago/Turabian Style

Florian Schlembach; Marcello Passaro; Graham D. Quartly; Andrey Kurekin; Francesco Nencioli; Guillaume Dodet; Jean-François Piollé; Fabrice Ardhuin; Jean Bidlot; Christian Schwatke; Florian Seitz; Paolo Cipollini; Craig Donlon. 2020. "Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height." Remote Sensing 12, no. 8: 1254.