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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,
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 StyleMichael 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 StyleMichael 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.
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).
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 StyleDenise 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 StyleDenise 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.
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.
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 StyleMarcello 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 StyleMarcello 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.
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).
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 StyleSimon 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 StyleSimon 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.
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).
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 StyleDenise 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 StyleDenise 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.
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).
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 StyleMichael 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 StyleMichael 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.
Precise orbits of altimetry satellites are a prerequisite for the investigation of global, regional, and coastal sea levels together with their changes, since accurate orbit information is required for the reliable determination of the water surface height (distance between the altimeter position in space and the water surface). Orbits of altimetry satellites are nowadays usually computed using DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite), SLR (Satellite Laser Ranging), and, of some satellites, GPS (Global Positioning System) observations of a global network of tracking stations. Significant progress in the improvement of altimetry satellite orbit quality has been achieved in the last 30 years. However, the differences of the sea level and its trend computed using up-to-date orbit solutions derived at various institutions using different software packages, types of observations (DORIS+SLR as compared to GPS+DORIS) and different up-to-date models still exceed the requirements of the Global Climate Observing System for the uncertainties of the regional sea level (< 1 cm) and its trend (< 1 mm/year).
In this study, we evaluate the current accuracy of orbits of altimetry satellites derived by various institutions in the state-of-the-art reference frames using up-to-date background models for precise orbit determination by using various observation types. We present some results of our analysis of geographically correlated errors and radial orbit differences for various orbit solutions. We also discuss possible reasons causing the orbit differences and potential ways to reduce them.
Sergei Rudenko; Denise Dettmering; Mathis Bloßfeld; Julian Zeitlhöfler; Riva Alkahal. On the current accuracy of altimetry satellite orbits. 2021, 1 .
AMA StyleSergei Rudenko, Denise Dettmering, Mathis Bloßfeld, Julian Zeitlhöfler, Riva Alkahal. On the current accuracy of altimetry satellite orbits. . 2021; ():1.
Chicago/Turabian StyleSergei Rudenko; Denise Dettmering; Mathis Bloßfeld; Julian Zeitlhöfler; Riva Alkahal. 2021. "On the current accuracy of altimetry satellite orbits." , no. : 1.
The project OPTIMAP is at the current stage a joint initiative of BGIC, GSSAC and DGFI-TUM. The development of an operational tool for ionospheric mapping and prediction is the main goal of the project.
The ionosphere is a dispersive medium. Therefore, GNSS signals are refracted while they pass through the ionosphere. The magnitude of the refraction rate depends on the frequencies of the transmitted GNSS signals. The ionospheric disturbance on the GNSS signals paves the way of extracting Vertical Total Electron Content (VTEC) information of the ionosphere.
In OPTIMAP, the representation of the global and regional VTEC signal is based on localizing B-spline basis functions. For global VTEC modeling, polynomial B-splines are employed to represent the latitudinal variations, whereas trigonometric B-splines are used for the longitudinal variations. The regional modeling in OPTIMAP relies on a polynomial B-spline representation for both latitude and longitude.
The VTEC modeling in this study relies on both a global and a regional sequential estimator (Kalman filter) running in a parallel mode. The global VTEC estimator produces VTEC maps based on data from GNSS receiver stations which are mainly part of the global real-time IGS network. The global estimator relies on additional VTEC information obtained from a forecast procedure using ultra-rapid VTEC products. The regional estimator makes use of the VTEC product of the real-time global estimator as background information and generates high-resolution VTEC maps using real-time data from the EUREF Permanent GNSS Network. EUREF provides a network of very dense GNSS receivers distributed alongside Europe.
Carrier phase observations acquired from GPS and GLONASS, which are transmitted in accordance with RTCM standard, are used for real-time regional VTEC modeling. After the acquisition of GNSS data, cycle slips for each satellite-receiver pair are detected, and ionosphere observations are constructed via the linear combination of carrier-phase observations in the data pre-processing step. The unknown B-spline coefficients, as well as the biases for each phase-continuous arc belonging to each receiver-satellite pair, are simultaneously estimated in the Kalman filter.
Within this study, we compare the performance of regional and global VTEC products generated in real-time using the well-known dSTEC analysis.
Eren Erdogan; Andreas Goss; Michael Schmidt; Denise Dettmering; Florian Seitz; Jennifer Müller; Ernst Lexen; Barbara Görres; Wilhelm F. Kersten. Real-time regional VTEC modeling based on B-splines using real-time GPS and GLONASS observations. 2021, 1 .
AMA StyleEren Erdogan, Andreas Goss, Michael Schmidt, Denise Dettmering, Florian Seitz, Jennifer Müller, Ernst Lexen, Barbara Görres, Wilhelm F. Kersten. Real-time regional VTEC modeling based on B-splines using real-time GPS and GLONASS observations. . 2021; ():1.
Chicago/Turabian StyleEren Erdogan; Andreas Goss; Michael Schmidt; Denise Dettmering; Florian Seitz; Jennifer Müller; Ernst Lexen; Barbara Görres; Wilhelm F. Kersten. 2021. "Real-time regional VTEC modeling based on B-splines using real-time GPS and GLONASS observations." , no. : 1.
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.
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 StyleMichael 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 StyleMichael 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.
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.
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 StyleJulius 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 StyleJulius 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.
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 StyleSimon 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 StyleSimon 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.
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).
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 StyleSimon 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 StyleSimon 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.
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.
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 StyleDenise 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 StyleDenise 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.
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.
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 StyleDaniel 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 StyleDaniel 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.
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.
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 StyleJulius 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 StyleJulius 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.
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.
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 StyleChristian 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 StyleChristian 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.
Despite increasing interest in monitoring the global water cycle, the availability of in-situ discharge time series is decreasing. However, this lack of ground data can be compensated by using remote sensing techniques to observe river discharge.
In this contribution, a new approach for estimating the discharge of large rivers by combining various long-term remote sensing data with physical flow equations is presented. For this purpose, water levels derived from multi-mission satellite altimetry and water surface extents extracted from optical satellite images are used, both provided by DGFI-TUM’s “Database of Hydrological Time series of Inland Waters” (DAHITI, https://dahiti.dgfi.tum.de). The datasets are combined by fitting a hypsometric curve in order to describe the stage-width relation, 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 computed based on a linear adjustment of river surface slope using all altimetry-observed water level differences between synchronous measurements at various virtual stations along the river. The roughness coefficient is set based on geomorphological features quantified by adjustment factors. These are chosen using remote sensing data and a literature decision guide.
Within this study, all parameters are estimated purely based on remote sensing data, without using any ground data. In-situ data is only used for the validation of the method at the Lower Mississippi River. It shows that the presented approach yields best results for uniform and straight river sections. The resulting normalized root mean square error for those targets varies between 10% to 35% and is comparable with other studies.
Daniel Scherer; Christian Schwatke; Denise Dettmering. Estimation of River Discharge using Multi-Mission Satellite Altimetry and Optical Remote Sensing Imagery. 2020, 1 .
AMA StyleDaniel Scherer, Christian Schwatke, Denise Dettmering. Estimation of River Discharge using Multi-Mission Satellite Altimetry and Optical Remote Sensing Imagery. . 2020; ():1.
Chicago/Turabian StyleDaniel Scherer; Christian Schwatke; Denise Dettmering. 2020. "Estimation of River Discharge using Multi-Mission Satellite Altimetry and Optical Remote Sensing Imagery." , no. : 1.
The use of satellite altimetry at high latitudes and coastal regions is currently limited by the presence of seasonal sea ice coverage, and the proximity to the coast. The semi-enclosed Baltic Sea features seasonal coverage of sea-ice in the northern and coastal regions, and complex jagged coastlines with a huge number of small islands. However, as a semi-enclosed sea with a considerable extent, the Baltic Sea features a much-reduced tidal signal, both open- and coastal- waters, and an extensive multi-national network of tide-gauges. These factors maximise opportunities to drive improvements in sea-level estimations for coastal, and seasonal-ice regions.
The ESA Baltic SEAL project, launched in April 2019, aims to exploit these opportunities. It is generating and validating a suite of enhanced multi-mission sea level products. Processing is developed specifically for coastal regions, with the objective of achieving a consistent description of the sea-level variability in terms of long-term trends, seasonal variations and a mean sea-surface. These will advance knowledge on adapting processing algorithms, to account for seasonal ice, and complex coastlines. Best practice approaches will be available to update current state-of-the-art datasets.
In order to fulfill these goals, a novel altimeter re-tracking strategy has been developed. This enables the homogeneous determination of sea-surface heights for open-ocean, coastal and sea-ice conditions (ALES+). An unsupervised classification algorithm based on artificial intelligence routines has been developed and tailored to ingest data from all current and past satellite altimetry missions. This identifies radar echoes, reflected by narrow cracks within the sea-ice domain. Finally, the improved altimetry observations are gridded onto a triangulated surface mesh, featuring a spatial resolution greater than 1/4 degree. This is more suitable for utility for coastal areas, and use by coastal stakeholders.
In addition to utilizing a wide range of altimetry data (Delay-Doppler and Pulse-Limited systems), the Baltic SEAL initiative harnesses the Baltic Seas unique characteristics to test novel geophysical corrections (e.g. wet troposphere correction), use the latest generation of regional altimetry datasets, and evaluate the benefits of the newest satellite altimetry missions. This presentation outlines the methodology and results achieved to date. These include estimations of a new regional mean sea surface, and insights into the trends of the sea level along the altimetry tracks with the longest records. The transfer of advances to other regions and sea-level initiatives are also highlighted.
Marcello Passaro; Felix L. Müller; Adili Abulaitijiang; Ole B. Andersen; Denise Dettmering; Jacob L. Høyer; Milla Johansson; Julius Oelsmann; Laura Rautiainen; Ida M. Ringgaard; Eero Rinne; Jani Särkkä; Rory Scarrott; Christian Schwatke; Florian Seitz; Kristine Skovgaard Madsen; Laura Tuomi; Americo Ambrozio; Marco Restano; Jérôme Benveniste. Using the Baltic Sea to advance algorithms to extract altimetry-derived sea-level data from complex coastal areas, featuring seasonal sea-ice. 2020, 1 .
AMA StyleMarcello Passaro, Felix L. Müller, Adili Abulaitijiang, Ole B. Andersen, Denise Dettmering, Jacob L. Høyer, Milla Johansson, Julius Oelsmann, Laura Rautiainen, Ida M. Ringgaard, Eero Rinne, Jani Särkkä, Rory Scarrott, Christian Schwatke, Florian Seitz, Kristine Skovgaard Madsen, Laura Tuomi, Americo Ambrozio, Marco Restano, Jérôme Benveniste. Using the Baltic Sea to advance algorithms to extract altimetry-derived sea-level data from complex coastal areas, featuring seasonal sea-ice. . 2020; ():1.
Chicago/Turabian StyleMarcello Passaro; Felix L. Müller; Adili Abulaitijiang; Ole B. Andersen; Denise Dettmering; Jacob L. Høyer; Milla Johansson; Julius Oelsmann; Laura Rautiainen; Ida M. Ringgaard; Eero Rinne; Jani Särkkä; Rory Scarrott; Christian Schwatke; Florian Seitz; Kristine Skovgaard Madsen; Laura Tuomi; Americo Ambrozio; Marco Restano; Jérôme Benveniste. 2020. "Using the Baltic Sea to advance algorithms to extract altimetry-derived sea-level data from complex coastal areas, featuring seasonal sea-ice." , no. : 1.
The project OPTIMAP is at the current stage a joint initiative of BGIC, GSSAC and DGFI-TUM. The development of an operational tool for ionospheric mapping and prediction is the main goal of the project.
The ionosphere is a dispersive medium. Therefore, GNSS signals are refracted while they pass through the ionosphere. The magnitude of the refraction rate depends on the frequencies of the transmitted GNSS signals. The ionospheric disturbance on the GNSS signals paves the way of extracting Vertical Total Electron Content (VTEC) information of the ionosphere.
In OPTIMAP, the representation of the global and regional VTEC signal is based on localizing B-spline basis functions. For global VTEC modeling, polynomial B-splines are employed to represent the latitudinal variations, whereas trigonometric B-splines are used for the longitudinal variations. The regional modeling in OPTIMAP relies on a polynomial B-spline representation for both latitude and longitude.
The VTEC modeling in this study relies on both a global and a regional sequential estimator (Kalman filter) running in a parallel mode. The global VTEC estimator produces VTEC maps based on data from GNSS receiver stations which are mainly part of the global real-time IGS network. The global estimator relies on additional VTEC information obtained from a forecast procedure using ultra-rapid VTEC products. The regional estimator makes use of the VTEC product of the real-time global estimator as background information and generates high-resolution VTEC maps using real-time data from the EUREF Permanent GNSS Network. EUREF provides a network of very dense GNSS receivers distributed alongside Europe.
Carrier phase observations acquired from GPS, GLONASS and GALILEO constellations, which are transmitted in accordance with RTCM standard, are used for real-time regional VTEC modeling. After the acquisition of GNSS data, cycle slips for each satellite-receiver pair are detected, and ionosphere observations are constructed via the linear combination of carrier-phase observations in the data pre-processing step. The unknown B-spline coefficients, as well as the biases for each phase-continuous arc belonging to each receiver-satellite pair, are simultaneously estimated in the Kalman filter.
Within this study, we compare the performance of regional and global VTEC products generated in real-time using the well-known dSTEC analysis.
Eren Erdogan; Andreas Goss; Michael Schmidt; Denise Dettmering; Florian Seitz; Jennifer Müller; Barbara Görres; Wilhelm F. Kersten. Real-time regional VTEC modeling based on B-splines using real-time GPS, GLONASS and GALILEO observations. 2020, 1 .
AMA StyleEren Erdogan, Andreas Goss, Michael Schmidt, Denise Dettmering, Florian Seitz, Jennifer Müller, Barbara Görres, Wilhelm F. Kersten. Real-time regional VTEC modeling based on B-splines using real-time GPS, GLONASS and GALILEO observations. . 2020; ():1.
Chicago/Turabian StyleEren Erdogan; Andreas Goss; Michael Schmidt; Denise Dettmering; Florian Seitz; Jennifer Müller; Barbara Görres; Wilhelm F. Kersten. 2020. "Real-time regional VTEC modeling based on B-splines using real-time GPS, GLONASS and GALILEO observations." , no. : 1.
Satellite altimetry is an important part of the Global Geodetic Observing System providing precise information on sea level on different spatial and temporal scales. Moreover, satellite altimetry-derived dynamic ocean topography heights enable the computation of ocean surface currents by applying the well-known geostrophic equations. However, in polar regions, altimetry observations are affected by seasonally changing sea-ice cover leading to a fragmentary data sampling.
In order to overcome this problem, an ocean model is used to fill in data gaps. The aim is to obtain a homogeneous ocean topography representation that enables consistent investigations of ocean surface current changes. For that purpose, the global Finite Element Sea-ice Ocean Model (FESOM) is used. It is based on an unstructured grid and provides daily water elevations with high spatial resolution.
The combination is done based on a Principal Component Analysis (PCA) after reducing both quantities by their constant and seasonal signals. In the main step, the most dominant spatial patterns of the modeled water heights as provided by the PCA are linked with the temporal variability of the estimated dynamic ocean topography elevations from altimetry. At the end, the seasonal signal as well as the absolute reference from altimetry is added back to the data set.
This contribution describes the combination process as well as the generated final product: a daily, more than 17 years covering dataset of geostrophic ocean currents. The combination is done for the marine regions Greenland Sea, Barents Sea and the Fram Strait and includes sea surface height observations of the ESA altimeter satellites ERS-2 and Envisat. In order to evaluate the combination results, independent surface drifter observations, corrected fora-geostrophic velocity components, are used.
Felix L. Müller; Denise Dettmering; Claudia Wekerle; Christian Schwatke; Marcello Passaro; Wolfgang Bosch; Florian Seitz. Ocean Surface Currents in the northern Nordic Seas from a combination of multi-mission satellite altimetry and numerical modeling. 2020, 1 .
AMA StyleFelix L. Müller, Denise Dettmering, Claudia Wekerle, Christian Schwatke, Marcello Passaro, Wolfgang Bosch, Florian Seitz. Ocean Surface Currents in the northern Nordic Seas from a combination of multi-mission satellite altimetry and numerical modeling. . 2020; ():1.
Chicago/Turabian StyleFelix L. Müller; Denise Dettmering; Claudia Wekerle; Christian Schwatke; Marcello Passaro; Wolfgang Bosch; Florian Seitz. 2020. "Ocean Surface Currents in the northern Nordic Seas from a combination of multi-mission satellite altimetry and numerical modeling." , no. : 1.