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Ole Baltazar Andersen - One of the best experts on this subject based on the ideXlab platform.
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mean sea surface and mean dynamic topography determination from CryoSat 2 data around australia
Advances in Space Research, 2020Co-Authors: Armin Agha Karimi, Ole Baltazar Andersen, Xiaoli DengAbstract:Abstract In this study, we use seven years of CryoSat-2 data to improve Mean Sea Surface (MSS) and also to estimate Mean Dynamic Topography (MDT) around Australia. Sea Level Anomaly (SLA) map, obtained from CryoSat-2 data, shows substantial spatial striping effects in the areas where annual signal has considerable amplitudes. This signal causes shifts among the SLAs acquired from adjacent tracks since they have collected at different times of the year. In order to mitigate these effects, we used Topex/Poseidon and follow on missions to estimate the seasonal signals in the CryoSat-2 data points. MSSC2 is then estimated by (1) removing these signals from SLAs, (2) averaging in a 0.1° × 0.1° grid cells, and (3) finally adding them to the DTUMSS13. The resultant surface shows good agreement with the MSS estimated by Jason-1 and Jason-2 data in altimetry nominal points. MDTC2 is also estimated in the study area using the MSSC2 and the geoid. It is in good agreement with two widely used global MDT models although showing higher values due to the effect of sea-level rise. When compared to the estimated MDT in tide gauge stations using geodetic data, MDTC2 statistically performs better than the global models.
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river levels derived with CryoSat 2 sar data classification a case study in the mekong river basin
Remote Sensing, 2017Co-Authors: Eva Boergens, Ole Baltazar Andersen, Karina Nielsen, D Dettmering, F SeitzAbstract:In this study we use CryoSat-2 SAR (delay-Doppler synthetic-aperture radar) data in the Mekong River Basin to estimate water levels. Compared to classical pulse limited radar altimetry, medium- and small-sized inland waters can be observed with CryoSat-2 SAR data with a higher accuracy due to the smaller along track footprint. However, even with this SAR data the estimation of water levels over a medium-sized river (width less than 500 m) is still challenging with only very few consecutive observations over the water. The target identification with land–water masks tends to fail as the river becomes smaller. Therefore, we developed a classification approach to divide the observations into water and land returns based solely on the data. The classification is done with an unsupervised classification algorithm, and it is based on features derived from the SAR and range-integrated power (RIP) waveforms. After the classification, classes representing water and land are identified. Better results are obtained when the Mekong River Basin is divided into different geographical regions: upstream, middle stream, and downstream. The measurements classified as water are used in a next step to estimate water levels for each crossing over a river in the Mekong River network. The resulting water levels are validated and compared to gauge data, Envisat data, and CryoSat-2 water levels derived with a land–water mask. The CryoSat-2 water levels derived with the classification lead to more valid observations with fewer outliers in the upstream region than with a land–water mask (1700 with 2% outliers vs. 1500 with 7% outliers). The median of the annual differences that is used in the validation is in all test regions smaller for the CryoSat-2 classification results than for Envisat or CryoSat-2 land–water mask results (for the entire study area: 0.76 m vs. 0.96 m vs. 0.83 m, respectively). Overall, in the upstream region with small- and medium-sized rivers the classification approach is more effective for deriving reliable water level observations than in the middle stream region with wider rivers.
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coastal sea level from CryoSat 2 sarin altimetry in norway
Advances in Space Research, 2017Co-Authors: Martina Idžanovic, Vegard Ophaug, Ole Baltazar AndersenAbstract:Abstract Conventional (pulse-limited) altimeters determine the sea surface height with an accuracy of a few centimeters over the open ocean. Sea surface heights and tide-gauge sea level serve as each other’s buddy check. However, in coastal areas, altimetry suffers from numerous effects, which degrade its quality. The Norwegian coast adds further challenges due to its complex coastline with many islands, mountains, and deep, narrow fjords. The European Space Agency CryoSat-2 satellite carries a synthetic aperture interferometric radar altimeter, which is able to observe sea level closer to the coast than conventional altimeters. In this study, we explore the potential of CryoSat-2 to provide valid observations in the Norwegian coastal zone. We do this by comparing time series of CryoSat-2 sea level anomalies with time series of in situ sea level at 22 tide gauges, where the CryoSat-2 sea level anomalies are averaged in a 45-km area around each tide gauge. For all tide gauges, CryoSat-2 shows standard deviations of differences and correlations of 16 cm and 61%, respectively. We further identify the ocean tide and inverted barometer geophysical corrections as the most crucial, and note that a large amount of observations at land-confined tide gauges are not assigned an ocean tide value. With the availability of local air pressure observations and ocean tide predictions, we substitute the standard inverted barometric and ocean tide corrections with local corrections. This gives an improvement of 24% (to 12.2 cm) and 12% (to 68%) in terms of standard deviations of differences and correlations, respectively. Finally, we perform the same in situ analysis using data from three conventional altimetry missions, Envisat, SARAL/AltiKa, and Jason-2. For all tide gauges, the conventional altimetry missions show an average agreement of 11 cm and 60% in terms of standard deviations of differences and correlations, respectively. There is a tendency that results improve with decreasing distance to the tide gauge and a smaller footprint, underlining the potential of SAR altimetry in coastal zones.
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the coastal mean dynamic topography in norway observed by CryoSat 2 and goce
Geophysical Research Letters, 2017Co-Authors: Martina Idžanovic, Vegard Ophaug, Ole Baltazar AndersenAbstract:New-generation synthetic aperture radar altimetry, as implemented on CryoSat-2, observes sea surface heights in coastal areas that were previously not monitored by conventional altimetry. Therefore, CryoSat-2 is expected to improve the coastal mean dynamic topography (MDT). However, the MDT remains highly reliant on the geoid. Using new regional geoid models as well as CryoSat-2 data, we determine three geodetic coastal MDT models in Norway and validate them against independent tide-gauge observations and the operational coastal ocean model NorKyst800. The CryoSat-2 MDTs agree on the ∼3–5 cm level with both tide-gauge geodetic and ocean MDTs along the Norwegian coast. In addition, we compute geostrophic surface currents to help identifying errors in the geoid models. We find that even though the regional geoid models are all based on the latest satellite gravity data as provided by GOCE, the resulting circulation patterns differ. We demonstrate that some of these differences are due to erroneous or lack of marine gravity data. This suggests that there is significant MDT signal at spatial scales beyond GOCE, and that the geodetic approach to MDT determination benefits from the additional terrestrial gravity information provided by a regional geoid model. We also find that the border of the geographical mode mask of CryoSat-2 coincides with the Norwegian Coastal Current, making it challenging to distinguish between artifacts in the CryoSat-2 observations during mode switch and ocean signal.
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the performance and potentials of the CryoSat 2 sar and sarin modes for lake level estimation
Water, 2017Co-Authors: Karina Nielsen, Ole Baltazar Andersen, Lars Stenseng, Per KnudsenAbstract:Over the last few decades, satellite altimetry has proven to be valuable for monitoring lake levels. With the new generation of altimetry missions, CryoSat-2 and Sentinel-3, which operate in Synthetic Aperture Radar (SAR) and SAR Interferometric (SARIn) modes, the footprint size is reduced to approximately 300 m in the along-track direction. Here, the performance of these new modes is investigated in terms of uncertainty of the estimated water level from CryoSat-2 data and the agreement with in situ data. The data quality is compared to conventional low resolution mode (LRM) altimetry products from Envisat, and the performance as a function of the lake area is tested. Based on a sample of 145 lakes with areas ranging from a few to several thousand km 2 , the CryoSat-2 results show an overall superior performance. For lakes with an area below 100 km 2 , the uncertainty of the lake levels is only half of that of the Envisat results. Generally, the CryoSat-2 lake levels also show a better agreement with the in situ data. The lower uncertainty of the CryoSat-2 results entails a more detailed description of water level variations.
Peter Bauergottwein - One of the best experts on this subject based on the ideXlab platform.
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evaluation of multi mode CryoSat 2 altimetry data over the po river against in situ data and a hydrodynamic model
Advances in Water Resources, 2018Co-Authors: Raphael Schneider, Angelica Tarpanelli, Karina Nielsen, Henrik Madsen, Peter BauergottweinAbstract:Abstract Coverage of in situ observations to monitor surface waters is insufficient on the global scale, and decreasing across the globe. Satellite altimetry has become an increasingly important monitoring technology for continental surface waters. The ESA CryoSat-2 altimetry mission, launched in 2010, has two novel features. (i) The radar altimeter instrument on board of CryoSat-2 is operated in three modes; two of them reduce the altimeter footprint by using Delay-Doppler processing. (ii) CryoSat-2 is placed on a distinct orbit with a repeat cycle of 369 days, leading to a drifting ground track pattern. The drifting ground track pattern challenges many common methods of processing satellite altimetry data over rivers. This study evaluates the observation error of CryoSat-2 water level observations over the Po River, Italy, against in situ observations. The average RMSE between CryoSat-2 and in situ observations was found to be 0.38 meters. CryoSat-2 was also shown to be useful for channel roughness calibration in a hydrodynamic model of the Po River. The small across-track distance of CryoSat-2 means that observations are distributed almost continuously along the river. This allowed resolving channel roughness with higher spatial resolution than possible with in situ or virtual station altimetry data. Despite the Po River being extensively monitored, CryoSat-2 still provides added value thanks to its unique spatio-temporal sampling pattern.
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a data assimilation system combining CryoSat 2 data and hydrodynamic river models
Journal of Hydrology, 2018Co-Authors: Raphael Schneider, Henrik Madsen, Marcetienne Ridler, Peter Nygaard Godiksen, Peter BauergottweinAbstract:Abstract There are numerous hydrologic studies using satellite altimetry data from repeat-orbit missions such as Envisat or Jason over rivers. This study is one of the first examples for the combination of altimetry from drifting-ground track satellite missions, namely CryoSat-2, with a river model. CryoSat-2 SARIn Level 2 data is used to improve a 1D hydrodynamic model of the Brahmaputra River in South Asia, which is based on the Saint-Venant equations for unsteady flow and set up in the MIKE HYDRO River software. After calibration of discharge and water level the hydrodynamic model can accurately and bias-free represent the spatio-temporal variations of water levels. A data assimilation framework has been developed and linked with the model. It is a flexible framework that can assimilate water level data which are arbitrarily distributed in time and space. The setup has been used to assimilate CryoSat-2 water level observations over the Assam valley for the years 2010–2015, using an Ensemble Transform Kalman Filter (ETKF). Performance improvement in terms of discharge forecasting skill was then evaluated. For experiments with synthetic CryoSat-2 data the continuous ranked probability score (CRPS) was improved by up to 32%, whilst for experiments assimilating real data it could be improved by up to 10%. The developed methods are expected to be transferable to other rivers and altimeter missions. The model setup and calibration is based almost entirely on globally available remote sensing data.
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application of CryoSat 2 altimetry data for river analysis and modelling
Hydrology and Earth System Sciences, 2016Co-Authors: Raphael Schneider, Henrik Madsen, Heidi Villadsen, Peter Nygaard Godiksen, Peter BauergottweinAbstract:Abstract. Availability of in situ river monitoring data, especially of data shared across boundaries, is decreasing, despite growing challenges for water resource management across the entire globe. This is especially valid for the case study of this work, the Brahmaputra Basin in South Asia. Commonly, satellite altimeters are used in various ways to provide information about such river basins. Most missions provide virtual station time series of water levels at locations where their repeat orbits cross rivers. CryoSat-2 is equipped with a new type of altimeter, providing estimates of the actual ground location seen in the reflected signal. It also uses a drifting orbit, challenging conventional ways of processing altimetry data to river water levels and their incorporation in hydrologic–hydrodynamic models. However, CryoSat-2 altimetry data provides an unprecedentedly high spatial resolution. This paper suggests a procedure to (i) filter CryoSat-2 observations over rivers to extract water-level profiles along the river, and (ii) use this information in combination with a hydrologic–hydrodynamic model to fit the simulated water levels with an accuracy that cannot be reached using information from globally available digital elevation models (DEMs) such as from the Shuttle Radar Topography Mission (SRTM) only. The filtering was done based on dynamic river masks extracted from Landsat imagery, providing spatial and temporal resolutions high enough to map the braided river channels and their dynamic morphology. This allowed extraction of river water levels over previously unmonitored narrow stretches of the river. In the Assam Valley section of the Brahmaputra River, CryoSat-2 data and Envisat virtual station data were combined to calibrate cross sections in a 1-D hydrodynamic model of the river. The hydrologic–hydrodynamic model setup and calibration are almost exclusively based on openly available remote sensing data and other global data sources, ensuring transferability of the developed methods. They provide an opportunity to achieve forecasts of both discharge and water levels in a poorly gauged river system.
Raphael Schneider - One of the best experts on this subject based on the ideXlab platform.
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evaluation of multi mode CryoSat 2 altimetry data over the po river against in situ data and a hydrodynamic model
Advances in Water Resources, 2018Co-Authors: Raphael Schneider, Angelica Tarpanelli, Karina Nielsen, Henrik Madsen, Peter BauergottweinAbstract:Abstract Coverage of in situ observations to monitor surface waters is insufficient on the global scale, and decreasing across the globe. Satellite altimetry has become an increasingly important monitoring technology for continental surface waters. The ESA CryoSat-2 altimetry mission, launched in 2010, has two novel features. (i) The radar altimeter instrument on board of CryoSat-2 is operated in three modes; two of them reduce the altimeter footprint by using Delay-Doppler processing. (ii) CryoSat-2 is placed on a distinct orbit with a repeat cycle of 369 days, leading to a drifting ground track pattern. The drifting ground track pattern challenges many common methods of processing satellite altimetry data over rivers. This study evaluates the observation error of CryoSat-2 water level observations over the Po River, Italy, against in situ observations. The average RMSE between CryoSat-2 and in situ observations was found to be 0.38 meters. CryoSat-2 was also shown to be useful for channel roughness calibration in a hydrodynamic model of the Po River. The small across-track distance of CryoSat-2 means that observations are distributed almost continuously along the river. This allowed resolving channel roughness with higher spatial resolution than possible with in situ or virtual station altimetry data. Despite the Po River being extensively monitored, CryoSat-2 still provides added value thanks to its unique spatio-temporal sampling pattern.
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a data assimilation system combining CryoSat 2 data and hydrodynamic river models
Journal of Hydrology, 2018Co-Authors: Raphael Schneider, Henrik Madsen, Marcetienne Ridler, Peter Nygaard Godiksen, Peter BauergottweinAbstract:Abstract There are numerous hydrologic studies using satellite altimetry data from repeat-orbit missions such as Envisat or Jason over rivers. This study is one of the first examples for the combination of altimetry from drifting-ground track satellite missions, namely CryoSat-2, with a river model. CryoSat-2 SARIn Level 2 data is used to improve a 1D hydrodynamic model of the Brahmaputra River in South Asia, which is based on the Saint-Venant equations for unsteady flow and set up in the MIKE HYDRO River software. After calibration of discharge and water level the hydrodynamic model can accurately and bias-free represent the spatio-temporal variations of water levels. A data assimilation framework has been developed and linked with the model. It is a flexible framework that can assimilate water level data which are arbitrarily distributed in time and space. The setup has been used to assimilate CryoSat-2 water level observations over the Assam valley for the years 2010–2015, using an Ensemble Transform Kalman Filter (ETKF). Performance improvement in terms of discharge forecasting skill was then evaluated. For experiments with synthetic CryoSat-2 data the continuous ranked probability score (CRPS) was improved by up to 32%, whilst for experiments assimilating real data it could be improved by up to 10%. The developed methods are expected to be transferable to other rivers and altimeter missions. The model setup and calibration is based almost entirely on globally available remote sensing data.
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CryoSat-2 Altimetry Applications over Rivers and Lakes
Water, 2017Co-Authors: Liguang Jiang, Ole Baltazar Andersen, Raphael Schneider, Peter Bauer-gottweinAbstract:Monitoring the variation of rivers and lakes is of great importance. Satellite radar altimetry is a promising technology to do this on a regional to global scale. Satellite radar altimetry data has been used successfully to observe water levels in lakes and (large) rivers, and has also been combined with hydrologic/hydrodynamic models. Except CryoSat-2, all radar altimetry missions have been operated in conventional low resolution mode with a short repeat orbit (35 days or less). CryoSat-2, carrying a Synthetic Aperture Radar (SAR) altimeter, has a 369-day repeat and a drifting ground track pattern and provides new opportunities for hydrologic research. The narrow inter-track distance (7.5 km at the equator) makes it possible to monitor many lakes and rivers and SAR mode provides a finer along-track resolution, higher return power and speckle reduction through multi-looks. However, CryoSat-2 challenges conventional ways of dealing with satellite inland water altimetry data because virtual station time series cannot be directly derived for rivers. We review the CryoSat-2 mission characteristics, data products, and its use and perspectives for inland water applications. We discuss all the important steps in the workflow for hydrologic analysis with CryoSat-2, and conclude with a discussion of promising future research directions.
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application of CryoSat 2 altimetry data for river analysis and modelling
Hydrology and Earth System Sciences, 2016Co-Authors: Raphael Schneider, Henrik Madsen, Heidi Villadsen, Peter Nygaard Godiksen, Peter BauergottweinAbstract:Abstract. Availability of in situ river monitoring data, especially of data shared across boundaries, is decreasing, despite growing challenges for water resource management across the entire globe. This is especially valid for the case study of this work, the Brahmaputra Basin in South Asia. Commonly, satellite altimeters are used in various ways to provide information about such river basins. Most missions provide virtual station time series of water levels at locations where their repeat orbits cross rivers. CryoSat-2 is equipped with a new type of altimeter, providing estimates of the actual ground location seen in the reflected signal. It also uses a drifting orbit, challenging conventional ways of processing altimetry data to river water levels and their incorporation in hydrologic–hydrodynamic models. However, CryoSat-2 altimetry data provides an unprecedentedly high spatial resolution. This paper suggests a procedure to (i) filter CryoSat-2 observations over rivers to extract water-level profiles along the river, and (ii) use this information in combination with a hydrologic–hydrodynamic model to fit the simulated water levels with an accuracy that cannot be reached using information from globally available digital elevation models (DEMs) such as from the Shuttle Radar Topography Mission (SRTM) only. The filtering was done based on dynamic river masks extracted from Landsat imagery, providing spatial and temporal resolutions high enough to map the braided river channels and their dynamic morphology. This allowed extraction of river water levels over previously unmonitored narrow stretches of the river. In the Assam Valley section of the Brahmaputra River, CryoSat-2 data and Envisat virtual station data were combined to calibrate cross sections in a 1-D hydrodynamic model of the river. The hydrologic–hydrodynamic model setup and calibration are almost exclusively based on openly available remote sensing data and other global data sources, ensuring transferability of the developed methods. They provide an opportunity to achieve forecasts of both discharge and water levels in a poorly gauged river system.
Michael Studinger - One of the best experts on this subject based on the ideXlab platform.
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an improved CryoSat 2 sea ice freeboard retrieval algorithm through the use of waveform fitting
The Cryosphere, 2014Co-Authors: Nathan Kurtz, N Galin, Michael StudingerAbstract:We develop a physical model capable of simulating the mean echo power of CryoSat-2 SAR- and SARIn-mode waveforms over sea-ice-covered regions. The model simulations are used to show the importance of variations in the radar backscatter coefficient with incidence angle and surface roughness for the retrieval of surface elevation of both sea ice floes and leads. The physical model is used to fit CryoSat-2 waveforms to enable retrieval of surface elevation through the use of lookup tables and a bounded trust region Newton least-squares fitting approach. The use of a model to fit returns from sea ice regions offers advantages over currently used threshold retracking methods, which are here shown to be sensitive to the combined effect of bandwidth-limited range resolution and surface roughness variations. Laxon et al. (2013) have compared ice thickness results from CryoSat-2 and IceBridge, and found good agreement; however consistent assumptions about the snow depth and density of sea ice were not used in the comparisons. To address this issue, we directly compare ice freeboard and thickness retrievals from the waveform-fitting and threshold tracker methods of CryoSat-2 to Operation IceBridge data using a consistent set of parameterizations. The purpose of the comparison is to highlight the physical basis between differences in the retracking methods. For three IceBridge campaign periods from March 2011 to March 2013, mean differences (CryoSat-2 – IceBridge) of 0.144 and 1.351 m are found between the freeboard and thickness retrievals, respectively, using a 50% sea ice floe threshold retracker, while mean differences of 0.019 and 0.182 m are found when using the waveform-fitting method. This suggests the waveform-fitting technique is capable of better reconciling the sea ice thickness data record from laser and radar altimetry data sets through the usage of consistent physical assumptions.
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an improved CryoSat 2 sea ice freeboard retrieval algorithm through the use of waveform fitting
The Cryosphere, 2014Co-Authors: N T Kurtz, N Galin, Michael StudingerAbstract:We develop an empirical model capable of simulating the mean echo power cross product of CryoSat-2 SAR and SAR In mode waveforms over sea ice covered regions. The model simulations are used to show the importance of variations in the radar backscatter coefficient with incidence angle and surface roughness for the retrieval of surfaceelevation of both sea ice floes and leads. The numerical model is used to fit CryoSat-2 waveforms to enable retrieval of surface elevation through the use of look-up tables and a bounded trust region Newton least squares fitting approach. The use of a model to fit returns from sea ice regions offers advantages over currently used threshold retrackingmethods which are here shown to be sensitive to the combined effect of bandwidth limited range resolution and surface roughness variations. Laxon et al. (2013) have compared ice thickness results from CryoSat-2 and IceBridge, and found good agreement, however consistent assumptions about the snow depth and density of sea ice werenot used in the comparisons. To address this issue, we directly compare ice freeboard and thickness retrievals from the waveform fitting and threshold tracker methods of CryoSat-2 to Operation IceBridge data using a consistent set of parameterizations. For three IceBridge campaign periods from March 20112013, mean differences (CryoSat-2 IceBridge) of 0.144m and 1.351m are respectively found between the freeboard and thickness retrievals using a 50 sea ice floe threshold retracker, while mean differences of 0.019m and 0.182m are found when using the waveform fitting method. This suggests the waveform fitting technique is capable of better reconciling the seaice thickness data record from laser and radar altimetry data sets through the usage of consistent physical assumptions.
Karina Nielsen - One of the best experts on this subject based on the ideXlab platform.
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evaluation of multi mode CryoSat 2 altimetry data over the po river against in situ data and a hydrodynamic model
Advances in Water Resources, 2018Co-Authors: Raphael Schneider, Angelica Tarpanelli, Karina Nielsen, Henrik Madsen, Peter BauergottweinAbstract:Abstract Coverage of in situ observations to monitor surface waters is insufficient on the global scale, and decreasing across the globe. Satellite altimetry has become an increasingly important monitoring technology for continental surface waters. The ESA CryoSat-2 altimetry mission, launched in 2010, has two novel features. (i) The radar altimeter instrument on board of CryoSat-2 is operated in three modes; two of them reduce the altimeter footprint by using Delay-Doppler processing. (ii) CryoSat-2 is placed on a distinct orbit with a repeat cycle of 369 days, leading to a drifting ground track pattern. The drifting ground track pattern challenges many common methods of processing satellite altimetry data over rivers. This study evaluates the observation error of CryoSat-2 water level observations over the Po River, Italy, against in situ observations. The average RMSE between CryoSat-2 and in situ observations was found to be 0.38 meters. CryoSat-2 was also shown to be useful for channel roughness calibration in a hydrodynamic model of the Po River. The small across-track distance of CryoSat-2 means that observations are distributed almost continuously along the river. This allowed resolving channel roughness with higher spatial resolution than possible with in situ or virtual station altimetry data. Despite the Po River being extensively monitored, CryoSat-2 still provides added value thanks to its unique spatio-temporal sampling pattern.
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river levels derived with CryoSat 2 sar data classification a case study in the mekong river basin
Remote Sensing, 2017Co-Authors: Eva Boergens, Ole Baltazar Andersen, Karina Nielsen, D Dettmering, F SeitzAbstract:In this study we use CryoSat-2 SAR (delay-Doppler synthetic-aperture radar) data in the Mekong River Basin to estimate water levels. Compared to classical pulse limited radar altimetry, medium- and small-sized inland waters can be observed with CryoSat-2 SAR data with a higher accuracy due to the smaller along track footprint. However, even with this SAR data the estimation of water levels over a medium-sized river (width less than 500 m) is still challenging with only very few consecutive observations over the water. The target identification with land–water masks tends to fail as the river becomes smaller. Therefore, we developed a classification approach to divide the observations into water and land returns based solely on the data. The classification is done with an unsupervised classification algorithm, and it is based on features derived from the SAR and range-integrated power (RIP) waveforms. After the classification, classes representing water and land are identified. Better results are obtained when the Mekong River Basin is divided into different geographical regions: upstream, middle stream, and downstream. The measurements classified as water are used in a next step to estimate water levels for each crossing over a river in the Mekong River network. The resulting water levels are validated and compared to gauge data, Envisat data, and CryoSat-2 water levels derived with a land–water mask. The CryoSat-2 water levels derived with the classification lead to more valid observations with fewer outliers in the upstream region than with a land–water mask (1700 with 2% outliers vs. 1500 with 7% outliers). The median of the annual differences that is used in the validation is in all test regions smaller for the CryoSat-2 classification results than for Envisat or CryoSat-2 land–water mask results (for the entire study area: 0.76 m vs. 0.96 m vs. 0.83 m, respectively). Overall, in the upstream region with small- and medium-sized rivers the classification approach is more effective for deriving reliable water level observations than in the middle stream region with wider rivers.
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the performance and potentials of the CryoSat 2 sar and sarin modes for lake level estimation
Water, 2017Co-Authors: Karina Nielsen, Ole Baltazar Andersen, Lars Stenseng, Per KnudsenAbstract:Over the last few decades, satellite altimetry has proven to be valuable for monitoring lake levels. With the new generation of altimetry missions, CryoSat-2 and Sentinel-3, which operate in Synthetic Aperture Radar (SAR) and SAR Interferometric (SARIn) modes, the footprint size is reduced to approximately 300 m in the along-track direction. Here, the performance of these new modes is investigated in terms of uncertainty of the estimated water level from CryoSat-2 data and the agreement with in situ data. The data quality is compared to conventional low resolution mode (LRM) altimetry products from Envisat, and the performance as a function of the lake area is tested. Based on a sample of 145 lakes with areas ranging from a few to several thousand km 2 , the CryoSat-2 results show an overall superior performance. For lakes with an area below 100 km 2 , the uncertainty of the lake levels is only half of that of the Envisat results. Generally, the CryoSat-2 lake levels also show a better agreement with the in situ data. The lower uncertainty of the CryoSat-2 results entails a more detailed description of water level variations.
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CryoSat 2 altimetry for river level monitoring evaluation in the ganges brahmaputra river basin
Remote Sensing of Environment, 2015Co-Authors: Heidi Villadsen, Ole Baltazar Andersen, Karina Nielsen, Lars Stenseng, Per KnudsenAbstract:Abstract The performance of CryoSat-2/SIRAL altimetry for river level monitoring is investigated by using river levels retrieved from Ganges and Brahmaputra. A key concern for the CryoSat-2 orbit has been its long repeat period of 369 days, which is usually undesirable for river and lake monitoring. However, the results from the method developed in this study involving virtual stations show that the CryoSat-2 data can indeed be used for such monitoring by utilizing the high spatial coverage and the sub-cycle period of 30 days. The results show that it is possible to capture the peak flow occurring during late summer due to monsoonal precipitation and the melting of snow in the Himalayas. The evaluation of CryoSat-2 river levels is performed by comparing with Envisat data in terms of annual signals and amplitudes. The obtained annual amplitudes agree well with the Envisat data, although CryoSat-2 exhibit larger differences. For five virtual stations in the Brahmaputra River, the mean difference between the obtained amplitudes is ~ 10 cm, whereas the mean phase difference is less than 2.7 days. A virtual station in the Ganges River shows a phase difference of around 5 days and a difference in amplitude of 2 cm.