Radar Altimetry

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C. K. Shum - One of the best experts on this subject based on the ideXlab platform.

  • global river Radar Altimetry time series grrats new river elevation earth science data records for the hydrologic community
    Earth System Science Data, 2020
    Co-Authors: Stephen Paul Coss, C. K. Shum, Michael Durand, Yuanyuan Jia, Qi Guo, Stephen Tuozzolo, George H Allen, S. Calmant
    Abstract:

    Abstract. The capabilities of Radar Altimetry to measure inland water bodies are well established, and several river Altimetry datasets are available. Here we produced a globally distributed dataset, the Global River Radar Altimeter Time Series (GRRATS), using Envisat and Ocean Surface Topography Mission (OSTM)/Jason-2 Radar altimeter data spanning the time period 2002–2016. We developed a method that runs unsupervised, without requiring parameterization at the measurement location, dubbed virtual station (VS) level, and applied it to all altimeter crossings of ocean-draining rivers with widths >900  m ( >34  % of the global drainage area). We evaluated every VS, either quantitatively for VS locations where in situ gages are available or qualitatively using a grade system. We processed nearly 1.5 million altimeter measurements from 1478 VSs. After quality control, the final product contained 810 403 measurements distributed over 932 VSs located on 39 rivers. Available in situ data allowed quantitative evaluation of 389 VSs on 12 rivers. The median standard deviation of river elevation error is 0.93 m, Nash–Sutcliffe efficiency is 0.75, and correlation coefficient is 0.9. GRRATS is a consistent, well-documented dataset with a user-friendly data visualization portal, freely available for use by the global scientific community. Data are available at https://doi.org/10.5067/PSGRA-SA2V1 (Coss et al., 2016).

  • time varying land subsidence detected by Radar Altimetry california taiwan and north china
    Scientific Reports, 2016
    Co-Authors: Cheinway Hwang, C. K. Shum, Yuande Yang, Ricky Kao, Jiancheng Han, Devin L Galloway, Michelle Sneed, Wei Chia Hung, Yung Sheng Cheng
    Abstract:

    Contemporary applications of Radar Altimetry include sea-level rise, ocean circulation, marine gravity and icesheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, Altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission Radar Altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT and JASON-2 during 1992–2015 show time-varying trends with respect to displacement over time in California’s San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm yr−1 with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm yr−1. Radar Altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm yr−1 and cumulative subsidence as much as 155 cm.

  • assessment of the impact of reservoirs in the upper mekong river using satellite Radar Altimetry and remote sensing imageries
    Remote Sensing, 2016
    Co-Authors: Kuan Ting Liu, C. K. Shum, Kuo-hsin Tseng, Yuanyuan Jia, Chianyi Liu, Chungyen Kuo, Ganming Liu, Kun Shang
    Abstract:

    Water level (WL) and water volume (WV) of surface-water bodies are among the most crucial variables used in water-resources assessment and management. They fluctuate as a result of climatic forcing, and they are considered as indicators of climatic impacts on water resources. Quantifying riverine WL and WV, however, usually requires the availability of timely and continuous in situ data, which could be a challenge for rivers in remote regions, including the Mekong River basin. As one of the most developed rivers in the world, with more than 20 dams built or under construction, Mekong River is in need of a monitoring system that could facilitate basin-scale management of water resources facing future climate change. This study used spaceborne sensors to investigate two dams in the upper Mekong River, Xiaowan and Jinghong Dams within China, to examine river flow dynamics after these dams became operational. We integrated multi-mission satellite Radar Altimetry (RA, Envisat and Jason-2) and Landsat-5/-7/-8 Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+)/Operational Land Imager (OLI) optical remote sensing (RS) imageries to construct composite WL time series with enhanced spatial resolutions and substantially extended WL data records. An empirical relationship between WL variation and water extent was first established for each dam, and then the combined long-term WL time series from Landsat images are reconstructed for the dams. The R2 between Altimetry WL and Landsat water area measurements is >0.95. Next, the Tropical Rainfall Measuring Mission (TRMM) data were used to diagnose and determine water variation caused by the precipitation anomaly within the basin. Finally, the impact of hydrologic dynamics caused by the impoundment of the dams is assessed. The discrepancy between satellite-derived WL and available in situ gauge data, in term of root-mean-square error (RMSE) is at 2–5 m level. The estimated WV variations derived from combined RA/RS imageries and digital elevation model (DEM) are consistent with results from in situ data with a difference at about 3%. We concluded that the river level downstream is affected by a combined operation of these two dams after 2009, which has decreased WL by 0.20 m·year−1 in wet seasons and increased WL by 0.35 m·year−1 in dry seasons.

  • Satellite Radar Altimetry for monitoring small rivers and lakes in Indonesia
    Hydrology and Earth System Sciences, 2015
    Co-Authors: Yohanes Budi Sulistioadi, C. K. Shum, Kuo-hsin Tseng, H. Hidayat, Muhammad Sumaryono, A. Suhardiman, Fajar Setiawan, Sunarso Sunarso
    Abstract:

    Remote sensing and satellite geodetic observations are capable of hydrologic monitoring of freshwater resources. Although satellite Radar Altimetry has been used in monitoring water level or discharge, its use is often limited to monitoring large rivers (>1 km) with longer interval periods (>1 week) because of its low temporal and spatial resolutions (i.e., satellite revisit period). Several studies have reported successful retrieval of water levels for small rivers as narrow as 40 m. However, processing current satellite Altimetry signals for such small water bodies to retrieve water levels accurately remains challenging. Physically, the Radar signal returned by water bodies smaller than the satellite footprint is most likely contaminated by non-water surfaces, which may degrade the measurement quality. In order to address this scientific challenge, we carefully selected the waveform shapes corresponding to the range measurement resulting from standard retrackers for the European Space Agency's (ESA's) Envisat (Environmental Satellite) Radar Altimetry. We applied this approach to small (40–200 m in width) and medium-sized (200–800 m in width) rivers and small lakes (extent 2 ) in the humid tropics of Southeast Asia, specifically in Indonesia. This is the first study that explored the ability of satellite Altimetry to monitor small water bodies in Indonesia. The major challenges in this study include the size of the water bodies that are much smaller than the nominal extent of the Envisat satellite footprint (e.g., ~250 m compared to ~1.7 km, respectively) and slightly smaller than the along-track distance (i.e., ~370 m). We addressed this challenge by optimally using geospatial information and optical remote sensing data to define the water bodies accurately, thus minimizing the probability of non-water contamination in the Altimetry measurement. Considering that satellite Altimetry processing may vary with different geographical regions, meteorological conditions, or hydrologic dynamic, we further evaluated the performance of all four Envisat standard retracking procedures. We found that satellite Altimetry provided a good alternative or the only means in some regions of measuring the water level of medium-sized rivers and small lakes with high accuracy (root mean square error (RMSE) of 0.21–0.69 m and a correlation coefficient of 0.94–0.97). In contrast to previous studies, we found that the commonly used Ice-1 retracking algorithm was not necessarily the best retracker among the four standard waveform retracking algorithms for Envisat Radar Altimetry observing inland water bodies. As a recommendation, we propose to include the identification and selection of standard waveform shapes to complete the use of standard waveform retracking algorithms for Envisat Radar Altimetry data over small and medium-sized rivers and small lakes.

  • envisat Altimetry Radar waveform retracking of quasi specular echoes over the ice covered qinghai lake
    Terrestrial Atmospheric and Oceanic Sciences, 2013
    Co-Authors: Kuo-hsin Tseng, C. K. Shum, Hyongki Lee, Chungyen Kuo, Hok Sum Fok, Xiao Cheng, Xianwei Wang
    Abstract:

    The use of satellite Radar Altimetry has long been extended to areas other than the deep-ocean primarily because of the advances in Radar waveform retracking methodologies. However, the retracking algorithms are limited to a handful shapes of return echoes over assumed known surfaces, while numerous unknown waveforms exist due to the complexity of real-world land cover and other surfaces. Measurements over a surface with seasonal or ephemeral patterns could thus degrade in accuracy due to varying characteristics from the corresponding Radar backscatters. In this study, we demonstrate that the Qinghai Lake, an alpine water body with distinct seasonal variation between water and ice causes inaccurate surface-height estimates when using Envisat Radar Altimetry and conventional retracking techniques. Following the characterization of the lake surface using EO-1 and Landsat multispectral analysis, we hypothesize that the overestimation of the lake level during winter and early spring is not from the snow accumulation; rather it is due to an error of the onboard retracker (ICE-1) which is unable to properly model the quasi-specular waveforms. Hence, we first build a classification algorithm to identify the anomalous waveforms, and then use an empirical retracking gate correction to mitigate the ice contamination. The accuracy of the 20% threshold retracker (TR) after applying suggested gate correction has a significant improvement with a root-mean-square error (RMSE) of 6 ± 7 cm and a correlation of 0.98 compared with the in situ gauge data. The improvement in accuracy is 54% better than the ICE-1 and 85% than the OCEAN retrackers, respectively.

Peter Bauergottwein - One of the best experts on this subject based on the ideXlab platform.

  • sentinel 3 Radar Altimetry for river monitoring a catchment scale evaluation of satellite water surface elevation from sentinel 3a and sentinel 3b
    Hydrology and Earth System Sciences, 2021
    Co-Authors: Cecile Marie Margaretha Kittel, Liguang Jiang, Christian Tottrup, Peter Bauergottwein
    Abstract:

    Abstract. Sentinel-3 is the first satellite Altimetry mission to operate both in synthetic aperture Radar (SAR) mode and in open-loop tracking mode nearly globally. Both features are expected to improve the ability of the altimeters to observe inland water bodies. Additionally, the two-satellite constellation offers a unique compromise between spatial and temporal resolution with over 65 000 potential water targets sensed globally. In this study, we evaluate the possibility of extracting river water surface elevation (WSE) at catchment level from Sentinel-3A and Sentinel-3B Radar Altimetry using Level-1b and Level-2 data from two public platforms: the Copernicus Open Access Hub (SciHub) and Grid Processing on Demand (GPOD). The objectives of the study are to demonstrate that by using publicly available processing platforms, such databases can be created to suit specific study areas for any catchment and with a wide range of applications in hydrology. We select the Zambezi River as a study area. In the Zambezi basin, 156 virtual stations (VSs) contain useful WSE information in both datasets. The root-mean-square deviation (RMSD) is between 2.9 and 31.3 cm at six VSs, where in situ data are available, and all VSs reflect the observed WSE climatology throughout the basin. Some VSs are exclusive to either the SciHub or GPOD datasets, highlighting the value of considering multiple processing options beyond global Altimetry-based WSE databases. In particular, we show that the processing options available on GPOD affect the number of useful VSs; specifically, extending the size of the receiving window considerably improved data at 13 Sentinel-3 VSs. This was largely related to the implementation of GPOD parameters. While correct on-board elevation information is crucial, the postprocessing options must be adapted to handle the steep changes in the receiving window position. Finally, we extract Sentinel-3 observations over key wetlands in the Zambezi basin. We show that clear seasonal patterns are captured in the Sentinel-3 WSE, reflecting flooding events in the floodplains. These results highlight the benefit of the high spatiotemporal resolution of the dual-satellite constellation.

  • unmanned aerial system uas observations of water surface elevation in a small stream comparison of Radar Altimetry lidar and photogrammetry techniques
    Remote Sensing of Environment, 2020
    Co-Authors: Filippo Bandini, Tanya Pheiffer Sunding, Johannes Linde, Ole Smith, Inger Klint Jensen, Christian Josef Koppl, Michael Brian Butts, Peter Bauergottwein
    Abstract:

    Abstract Water Surface Elevation (WSE) is an important hydrometric observation, useful to calibrate hydrological models, predict floods, and assess climate change. However, the number of in-situ gauging stations is in decline worldwide. Satellite Altimetry, including the recently launched satellite missions (e.g. the Radar Altimetry missions Cryosat 2, Jason 3, Sentinel 3A/B and the LIDAR mission ICESat-2), can determine WSE only in rivers which are more than ca. 100 m wide. WSE measurements in small streams currently remain limited to the few existing in-situ stations or to time-consuming in-situ surveys. Unmanned Aerial Systems (UAS) can acquire real-time WSE observations during periods of hydrological interest (but with flight limitations in extreme weather conditions), within short survey times and with automatic or semi-automatic flight operations. UAS-borne photogrammetry is a well-known technique that can estimate land elevation with an accuracy as high as a few cm, similarly UAS-borne LIDAR can estimate land elevation but without requiring Ground Control Points (GCPs). However, both techniques face limitations in estimating WSE: water transparency and lack of stable visual key points on the Water Surface (WS) complicate the UAS-borne photogrammetric estimates of WSE, while the LIDAR reflection from the water surface is generally not strong enough to be captured by most of the UAS-borne LIDAR systems currently available on the market. Thus, LIDAR and photogrammetry generally require extraction of the elevation of the “water-edge” points, i.e. points at the interface between land and water, for identifying the WSE. We demonstrate highly accurate WSE observations with a new Radar Altimetry solution, which comprises a 77 GHz Radar chip with full waveform analysis and an accurate dual frequency differential Global Navigation Satellite System (GNSS) system. The Radar Altimetry solution shows the lowest standard deviation (σ) and RMSE on WSE estimates, ca. 1.5 cm and ca. 3 cm respectively, whilst photogrammetry and LIDAR show a σ and an RMSE at decimetre level. Radar Altimetry also requires a significantly shorter survey and processing time compared to LIDAR and especially to photogrammetry.

  • influence of local geoid variation on water surface elevation estimates derived from multi mission Altimetry for lake namco
    Remote Sensing of Environment, 2019
    Co-Authors: Liguang Jiang, Karina Nielsen, Ole Baltazar Andersen, Guoqing Zhang, Peter Bauergottwein
    Abstract:

    Abstract Water surface elevation (WSE) is an essential quantity for water resource monitoring and hydrodynamic modeling. Satellite Altimetry has provided data for inland water bodies. The height that is derived from Altimetry measurement is ellipsoidal height. In order to convert the ellipsoidal height to orthometric height, which has physical meaning, accurate estimates of the geoid are needed. This paper evaluates the suitability of geodetic altimetric measurements for improvement of global geoid models over a large lake in the Tibetan Plateau. CryoSat-2 and SARAL/AltiKa are used to derive the high-frequency geoid correction. A validation of the local geoid correction is performed with data from in-situ observations, a laser Altimetry satellite (ICESat), a Ka-band Radar Altimetry satellite (SARAL) and a SAR Radar Altimetry satellite (Sentinel-3). Results indicate that the geodetic altimetric dataset can capture the high-resolution geoid information. By applying local geoid correction, the precision of ICESat, SARAL and Sentinel-3 retrievals are significantly improved. We conclude that using geodetic Altimetry to correct for local geoid residual over large lakes significantly decreases the uncertainty of WSE estimates. These results also indicate the potential of geodetic Altimetry missions to determine local geoid residual with centimeter-level accuracy, which can be used to improve global and regional geopotential models.

  • cryosat 2 Radar Altimetry for monitoring freshwater resources of china
    Remote Sensing of Environment, 2017
    Co-Authors: Liguang Jiang, Karina Nielsen, Ole Baltazar Andersen, Peter Bauergottwein
    Abstract:

    Abstract Surface water bodies (lakes, reservoirs, and rivers) are key components of the water cycle and are important water resources. Water level and storage vary greatly under the impacts of climate change and human activities. Due to sparse in-situ monitoring networks, a comprehensive national-scale monitoring dataset of surface water bodies in China is not available. Over the last two decades, satellite Altimetry has been used successfully for inland water monitoring. Here, we use CryoSat-2 Radar Altimetry to monitor water level variations of large lakes, reservoirs and rivers across China and demonstrate its potential to complement available in-situ monitoring datasets for the country. In this study, over 1000 lakes and reservoirs, and 6 large rivers are investigated. The results show that surface water varied greatly over the past 6 years, e.g. in the Tibetan Plateau, the Junggar Basin, the Northeast China Plain, and the central Yangtze River basin. Estimated changes in volume indicate that surface water variation contributes significantly to terrestrial storage variation, especially in the Qaidam Basin and the Tibetan Plateau. CryoSat-2 is capable of measuring regional-scale river level at high spatial resolution and competitive accuracy as demonstrated by comparison with available in-situ gauging data. The results are encouraging with RMSE values ranging from 0.24 to 0.35 m for the Heilongjiang-Amur River, 0.22 to 0.6 m for the Yellow River and 0.22 to 0.5 m for the Songhua River. Comparatively, accuracy is much lower over the Yangtze and Pearl Rivers (RMSE ~ 2.6 m and ~ 3.3 m), probably due to intensive inland waterway navigation. CryoSat-2 shows great potential for monitoring surface water at national scale in China.

  • operational reservoir inflow forecasting with Radar Altimetry the zambezi case study
    Hydrology and Earth System Sciences, 2014
    Co-Authors: Claire Irene B Michailovsky, Peter Bauergottwein
    Abstract:

    Abstract. River basin management can greatly benefit from short-term river discharge predictions. In order to improve model produced discharge forecasts, data assimilation allows for the integration of current observations of the hydrological system to produce improved forecasts and reduce prediction uncertainty. Data assimilation is widely used in operational applications to update hydrological models with in situ discharge or level measurements. In areas where timely access to in situ data is not possible, remote sensing data products can be used in assimilation schemes. While river discharge itself cannot be measured from space, Radar Altimetry can track surface water level variations at crossing locations between the satellite ground track and the river system called virtual stations (VS). Use of Radar Altimetry versus traditional monitoring in operational settings is complicated by the low temporal resolution of the data (between 10 and 35 days revisit time at a VS depending on the satellite) as well as the fact that the location of the measurements is not necessarily at the point of interest. However, combining Radar Altimetry from multiple VS with hydrological models can help overcome these limitations. In this study, a rainfall runoff model of the Zambezi River basin is built using remote sensing data sets and used to drive a routing scheme coupled to a simple floodplain model. The extended Kalman filter is used to update the states in the routing model with data from 9 Envisat VS. Model fit was improved through assimilation with the Nash–Sutcliffe model efficiencies increasing from 0.19 to 0.62 and from 0.82 to 0.88 at the outlets of two distinct watersheds, the initial NSE (Nash–Sutcliffe efficiency) being low at one outlet due to large errors in the precipitation data set. However, model reliability was poor in one watershed with only 58 and 44% of observations falling in the 90% confidence bounds, for the open loop and assimilation runs respectively, pointing to problems with the simple approach used to represent model error.

Jonathan L. Bamber - One of the best experts on this subject based on the ideXlab platform.

  • antarctic ice shelf thickness from cryosat 2 Radar Altimetry
    EGUGA, 2016
    Co-Authors: Stephen Chuter, Jonathan L. Bamber
    Abstract:

    Ice shelf thickness for the whole of Antarctica is derived from 4 years (2011–2014) of CryoSat-2 (CS2) Radar Altimetry measurements using the assumption that the shelves are in hydrostatic equilibrium. The satellite orbit and novel synthetic aperture Radar interferometric mode of CS2 results in 92.3% data coverage over the ice shelves, with particular improvements around the grounding zone. When compared to ICESat data, surface elevations have a mean bias of less than 1 m and a fourfold reduction in standard deviation compared with the previous data set. Over the Amery Ice Shelf there is a mean thickness difference of 3.3% between radio echo sounding measurements and the CS2-derived thicknesses, rising to 4.7% within 10 km of the grounding line. Our new data set provides key improvements in accuracy and coverage, especially in the grounding zone, allowing for reduced uncertainties in mass budget calculations, subshelf ocean and ice sheet-shelf modeling.

  • accuracy and performance of cryosat 2 sarin mode data over antarctica
    IEEE Geoscience and Remote Sensing Letters, 2015
    Co-Authors: Fang Wang, Jonathan L. Bamber, Xiao Cheng
    Abstract:

    The instrument onboard CryoSat-2 has a new measurement mode to improve performance on the steeper margins of the ice sheets where conventional Radar Altimetry has been limited in accuracy and coverage. We assess the accuracy of CryoSat-2 synthetic aperture Radar interferometric (SARIn) mode data using data from Geoscience Laser Altimeter System onboard ICESat and also compare coverage with conventional Altimetry. Biases, exceeding 4 m, were ubiquitous in areas with surface slopes above about 0.9°. Over the ice shelves and the interior of the ice sheet, the bias was less than 50 cm but appeared to be sensitive to snowpack density. We find that the accuracy and coverage of CryoSat-2 SARIn mode data is significantly better than for previous satellite Radar altimeter missions for slopes up to 1°.

  • time evolving mass loss of the greenland ice sheet from satellite Altimetry
    The Cryosphere, 2014
    Co-Authors: R T W L Hurkmans, Jonathan L. Bamber, C H Davis, Ian Joughin, K S Khvorostovsky, B S Smith, Nana Schoen
    Abstract:

    Abstract. Mass changes of the Greenland Ice Sheet may be estimated by the input–output method (IOM), satellite gravimetry, or via surface elevation change rates (dH/dt). Whereas the first two have been shown to agree well in reconstructing ice-sheet wide mass changes over the last decade, there are few decadal estimates from satellite Altimetry and none that provide a time-evolving trend that can be readily compared with the other methods. Here, we interpolate Radar and laser Altimetry data between 1995 and 2009 in both space and time to reconstruct the evolving volume changes. A firn densification model forced by the output of a regional climate model is used to convert volume to mass. We consider and investigate the potential sources of error in our reconstruction of mass trends, including geophysical biases in the Altimetry, and the resulting mass change rates are compared to other published estimates. We find that mass changes are dominated by surface mass balance (SMB) until about 2001, when mass loss rapidly accelerates. The onset of this acceleration is somewhat later, and less gradual, compared to the IOM. Our time-averaged mass changes agree well with recently published estimates based on gravimetry, IOM, laser Altimetry, and with Radar Altimetry when merged with airborne data over outlet glaciers. We demonstrate that, with appropriate treatment, satellite Radar Altimetry can provide reliable estimates of mass trends for the Greenland Ice Sheet. With the inclusion of data from CryoSat-2, this provides the possibility of producing a continuous time series of regional mass trends from 1992 onward.

  • brief communication importance of slope induced error correction in volume change estimates from Radar Altimetry
    The Cryosphere, 2012
    Co-Authors: R T W L Hurkmans, Jonathan L. Bamber, J A Griggs
    Abstract:

    In deriving elevation change rates (d H /d t ) from Radar Altimetry, the slope-induced error is usually assumed to cancel out in repeat measurements. These measurements, however, represent a location that can be significantly further upslope than assumed, causing an underestimate of the basin-integrated volume change. In a case-study for the fast-flowing part of Jakobshavn Isbrae, we show that a relatively straightforward correction for slope-induced error increases elevation change rates by up to several metres per year and significantly reduces the volume change error with respect to laser Altimetry for the area of interest.

  • antarctic ice shelf thickness from satellite Radar Altimetry
    Journal of Glaciology, 2011
    Co-Authors: J A Griggs, Jonathan L. Bamber
    Abstract:

    Ice-shelf thickness is an important boundary condition for ice-sheet and sub-ice-shelf cavity modelling. It is required near the grounding line to calculate the ice flux used to determine ice-sheet mass balance by comparison with the upstream accumulation. In this mass budget approach, the accuracy of the ice thickness is one of the limiting factors in the calculation. We present a satellite retrieval of the ice thickness for all Antarctic ice shelves using satellite Radar altimeter data from the geodetic phases of the European Remote-sensing Satellite (ERS-1) during 1994-95 supplemented by ICESat data for regions south of the ERS-1 latitudinal limit. Surface elevations derived from these instruments are interpolated on to regular grids using kriging, and converted to ice thicknesses using a modelled firn-density correction. The availability of a new spatial variable firn-density correction significantly reduces the error in ice thickness as this was previously the dominant error source. Comparison to airborne data shows good agreement, particularly when compared to SOAR CASERTZ data on the largest ice shelves. Biases range from -13.0 m for areas where the assumption of hydrostatic equilibrium breaks down, to 53.4 m in regions where marine ice may be present.

Frédéric Frappart - One of the best experts on this subject based on the ideXlab platform.

  • backscattering signatures at ka ku c and s bands from low resolution Radar Altimetry over land
    Advances in Space Research, 2021
    Co-Authors: Frédéric Frappart, Fabrice Papa, Eric Mougin, Catherine Prigent, Fabien Blarel, Philippe Paillou, Frederic Baup, Pierre Zeiger, Edward Salameh
    Abstract:

    Abstract Radar backscattering coefficients from synthetic aperture Radars and scatterometers are commonly used to characterize the land surface properties and monitor their temporal evolution. Radar Altimetry is mostly used, over land, to provide time series of water stage of lakes, rivers and wetlands and the topography of the ice sheets. Very few studies used the Radar Altimetry backscattering coefficients for geophysical applications except to determine changes in Arctic lakes state surface, surface soil moisture in semi-arid environments or flood extent at high latitude. As Radar Altimetry missions acquired data in four frequency bands (mostly C and Ku but also S and Ka), this study proposes the first thorough analysis of the backscattering signatures of land surfaces using observations from ERS-2, Jason-1, ENVISAT, Jason-2 and SARAL Radar Altimetry missions The spatial and temporal variations of several altimetric information (backscattering coefficient, waveform peakiness, leading edge width and trailing edge slope) are examined at global scale, for each frequency band separately, as well as for their differences. Their relationship with related variations in the surface characteristics (i.e., soil type, soil moisture, presence of water and snow) are evidenced. Finally, spatial patterns and temporal variations computed over selected regions, representative of the major bioclimatic areas, are related to their surface properties and changes.

  • evaluation of historic and operational satellite Radar Altimetry missions for constructing consistent long term lake water level records
    Hydrology and Earth System Sciences, 2021
    Co-Authors: Song Shu, Frédéric Frappart, Hongxing Liu, Richard A Beck, Johanna Korhonen, Minxuan Lan, Bo Yang, Yan Huang
    Abstract:

    Abstract. A total of 13 satellite missions have been launched since 1985, with different types of Radar altimeters on board. This study intends to make a comprehensive evaluation of historic and currently operational satellite Radar Altimetry missions for lake water level retrieval over the same set of lakes and to develop a strategy for constructing consistent long-term water level records for inland lakes at global scale. The lake water level estimates produced by different retracking algorithms (retrackers) of the satellite missions were compared with the gauge measurements over 12 lakes in four countries. The performance of each retracker was assessed in terms of the data missing rate, the correlation coefficient  r , the bias, and the root mean square error (RMSE) between the Altimetry-derived lake water level estimates and the concurrent gauge measurements. The results show that the model-free retrackers (e.g., OCOG/Ice-1/Ice) outperform the model-based retrackers for most of the missions, particularly over small lakes. Among the satellite Altimetry missions, Sentinel-3 gave the best results, followed by SARAL. ENVISAT has slightly better lake water level estimates than Jason-1 and Jason-2, but its data missing rate is higher. For small lakes, ERS-1 and ERS-2 missions provided more accurate lake water level estimates than the TOPEX/Poseidon mission. In contrast, for large lakes, TOPEX/Poseidon is a better option due to its lower data missing rate and shorter repeat cycle. GeoSat and GeoSat Follow-On (GFO) both have an extremely high data missing rate of lake water level estimates. Although several contemporary Radar Altimetry missions provide more accurate lake level estimates than GFO, GeoSat was the sole Radar Altimetry mission, between 1985 and 1990, that provided the lake water level estimates. With a full consideration of the performance and the operational duration, the best strategy for constructing long-term lake water level records should be a two-step bias correction and normalization procedure. In the first step, use Jason-2 as the initial reference to estimate the systematic biases with TOPEX/Poseidon, Jason-1, and Jason-3 and then normalize them to form a consistent TOPEX/Poseidon–Jason series. Then, use the TOPEX/Poseidon–Jason series as the reference to estimate and remove systematic biases with other Radar Altimetry missions to construct consistent long-term lake water level series for ungauged lakes.

  • Evaluation of the Performances of Radar and Lidar Altimetry Missions for Water Level Retrievals in Mountainous Environment: The Case of the Swiss Lakes
    'MDPI AG', 2021
    Co-Authors: Frédéric Frappart, Song Shu, Fabien Blarel, Jeanfrancois Cretaux, Ibrahim Fayad, Muriel Bergé-nguyen, Joël Schregenberger, Nicolas Baghdadi
    Abstract:

    Radar Altimetry is now commonly used to provide long-term monitoring of inland water levels in complement to or for replacing disappearing in situ networks of gauge stations. Recent improvements in tracking and acquisition modes improved the quality the water retrievals. The newly implemented Open Loop mode is likely to increase the number of monitored water bodies owing to the use of an a priori elevation, especially in hilly and mountainous areas. The novelty of this study is to provide a comprehensive evaluation of the performances of the past and current Radar Altimetry missions according to their acquisition (Low Resolution Mode or Synthetic Aperture Radar) and tracking (close or open loop) modes, and acquisition frequency (Ku or Ka) in a mountainous area where tracking losses of the signal are likely to occur, as well as of the recently launched ICESat-2 and GEDI lidar missions. To do so, we evaluate the quality of water level retrievals from most Radar Altimetry missions launched after 1995 over eight lakes in Switzerland, using the recently developed Altimetry Time Series software, to compare the performances of the new tracking and acquisition modes and also the impact of the frequency used. The combination of the Open Loop tracking mode with the Synthetic Aperture Radar acquisition mode on SENTINEL-3A and B missions outperforms the classical Low Resolution Mode of the other missions with a lake observability greater than 95%, an almost constant bias of (−0.17 ± 0.04) m, a RMSE generally lower than 0.07 m and a R most of the times higher than 0.85 when compared to in situ gauge records. To increase the number of lakes that can be monitored and the temporal sampling of the water level retrievals, data acquired by lidar Altimetry missions were also considered. Very accurate results were also obtained with ICESat-2 data with RMSE lower than 0.06 and R higher than 0.95 when compared to in situ water levels. An almost constant bias (0.42 ± 0.03) m was also observed. More contrasted results were obtained using GEDI. As these data were available on a shorter time period, more analyses are necessary to determine their potential for retrieving water levels

  • Evolution of the Performances of Radar Altimetry Missions from ERS-2 to Sentinel-3A over the Inner Niger Delta
    Remote Sensing, 2018
    Co-Authors: Cassandra Normandin, Frédéric Frappart, Eric Mougin, Fabien Blarel, Vincent Marieu, Adama Telly Diepkilé, Bertrand Lubac, Nadine Braquet
    Abstract:

    Radar Altimetry provides unique information on water stages of inland hydro-systems. In this study, the performance of seven Altimetry missions, among the most commonly used in land hydrology (i.e., European Remote-Sensing Satellite-2 (ERS-2), ENVIronment SATellite (ENVISAT), Satellite with Argos and ALtika (SARAL), Jason-1, Jason-2, Jason-3 and Sentinel-3A), are assessed using records from a dense in situ network composed of 19 gauge stations in the Inner Niger Delta (IND) from 1995 to 2017. Results show an overall very good agreement between Altimetry-based and in situ water levels with correlation coefficient (R) greater than 0.8 in 80% of the cases and Root Mean Square Error (RMSE) lower than 0.4 m in 48% of cases. Better agreement is found for the recently launched missions such as SARAL, Jason-3 and Sentinel-3A than for former missions, indicating the advance of the use of the Ka-band for SARAL and of the Synthetic-aperture Radar (SAR) mode for Sentinel-3A. Cross-correlation analysis performed between water levels from the same Altimetry mission leads to time-lags between the upstream and the downstream part of the Inner Niger Delta of around two months that can be related to the time residence of water in the drainage area.

  • Impact of Surface Soil Moisture Variations on Radar Altimetry Echoes at Ku and Ka Bands in Semi-Arid Areas
    Remote Sensing, 2018
    Co-Authors: Christophe Fatras, Pierre Borderies, Frédéric Frappart, Eric Mougin, Denis Blumstein, Fernando Nino
    Abstract:

    Radar Altimetry provides information on the topography of the Earth surface. It is commonly used for the monitoring not only sea surface height but also ice sheets topography and inland water levels. The Radar Altimetry backscattering coefficient, which depends on surface roughness and water content, can be related to surface properties such as surface soil moisture content. In this study, the influence of surface soil moisture on the Radar Altimetry echo and backscattering coefficient is analyzed over semi-arid areas. A semi-empirical model of the soil's complex dielectric permittivity that takes into account that small-scale roughness and large-scale topography was developed to simulate the Radar echoes. It was validated using waveforms acquired at Ku and Ka-bands by ENVISAT RA-2 and SARAL AltiKa respectively over several sites in Mali. Correlation coefficients ranging from 0.66 to 0.94 at Ku-band and from 0.27 to 0.96 at Ka-band were found. The increase in surface soil moisture from 0.02 to 0.4 (i.e., the typical range of variations in semi-arid areas) increase the backscattering from 10 to 15 dB between the core of the dry and the maximum of the rainy seasons.

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  • 25 years of elevation changes of the greenland ice sheet from ers envisat and cryosat 2 Radar Altimetry
    Earth and Planetary Science Letters, 2018
    Co-Authors: Louise Sandberg Sørensen, K. Khvorostovsky, Sebastian B Simonsen, Rene Forsberg, Rakia Meister, M Engdahl
    Abstract:

    Abstract The shape of the large ice sheets responds rapidly to climate change, making the elevation changes of these ice-covered regions an essential climate variable. Consistent, long time series of these elevation changes are of great scientific value. Here, we present a newly-developed data product of 25 years of elevation changes of the Greenland Ice Sheet, derived from satellite Radar Altimetry. The data product is made publicly available within the Greenland Ice Sheets project as part of the ESA Climate Change Initiative programme. Analyzing repeated elevation measurements from Radar Altimetry is widely used for monitoring changes of ice-covered regions. The Greenland Ice Sheet has been mapped by conventional Radar Altimetry since the launch of ERS-1 in 1991, which was followed by ERS-2, Envisat and currently CryoSat-2. The recently launched Sentinel-3A will provide a continuation of the Radar Altimetry time series. Since 2010, CryoSat-2 has for the first time measured the changes in the coastal regions of the ice sheet with Radar Altimetry, with its novel SAR Interferometric (SARIn) mode, which provides improved measurement over regions with steep slopes. Here, we apply a mission-specific combination of cross-over, along-track and plane-fit elevation change algorithms to Radar data from the ERS-1, ERS-2, Envisat and CryoSat-2 Radar missions, resulting in 25 years of nearly continuous elevation change estimates (1992–2016) of the Greenland Ice Sheet. This analysis has been made possible through the recent reprocessing in the REAPER project, of data from the ERS-1 and ERS-2 Radar missions, making them consistent with Envisat data. The 25 years of elevation changes are evaluated as 5-year running means, shifted almost continuously by one year. A clear acceleration in thinning is evident in the 5-year maps of elevation following 2003, while only small elevation changes observed in the maps from the 1990s.

  • Implications of changing scattering properties on Greenland ice sheet volume change from Cryosat-2 Altimetry
    Remote Sensing of Environment, 2017
    Co-Authors: Sebastian Bjerregaard Simonsen, Louise Sandberg Sørensen
    Abstract:

    Long-term observations of surface elevation change of the Greenland ice sheet (GrIS) is of utmost importance when assessing the state of the ice sheet. Satellite Radar Altimetry offers a long time series of data over the GrIS, starting with ERS-1 in 1991. ESA's Cryosat-2 mission, launched in 2010, provides an invaluable Radar Altimetry dataset for monitoring the current changes of the ice sheets due to its dense spatial and temporal coverage of these areas. Here, we investigate the effects of including different parameters which describe the shape of the return Radar waveform (waveform parameters) in the elevation change algorithm, to correct for temporal changes in the ratio between surface- and volume-scatter in Cryosat-2 observations. We present elevation and volume changes for the Greenland ice sheet in the period from 2010 until 2014. The waveform parameters considered here are the backscatter coefficient, and the leading edge width, which are both available in the ESA Cryosat-2 Level-2i data product. Investigations into relocation of Radar reflection points are also included. Inter-comparison of the Cryosat-2 derived elevation changes with those derived from Operation IceBridge laser data suggests waveform parameters to be applicable for correcting for changes in volume scattering. The best results in the Synthetic Aperture Radar Interferometric mode area of the GrIS are found when applying only the backscatter correction, whereas the best result in the Low Resolution Mode area is obtained by only applying a leading edge width correction. Using this approach to correct for the scattering properties, a volume loss of −292±38 km3 yr −1 is found for the GrIS for the time span November 2010 until November 2014. The inclusion of waveform parameter corrections and improved relocation for the GrIS, helps to reconcile the satellite-derived elevation changes with those observed by Operation IceBridge. However, the bias of temporal changes in the scattering horizons of Cryosat-2 is not entirely removed and suggests that future improvements could be made by including climate data and/or additional waveform parameters to make additional corrections in the Cryosat-2 Radar Altimetry.

  • the impact of dem resolution on relocating Radar Altimetry data over ice sheets
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
    Co-Authors: Joanna Fredenslund Levinsen, Louise Sandberg Sørensen, Sebastian B Simonsen, Rene Forsberg
    Abstract:

    Beam-limited footprints from conventional satellite Radar altimeters have diameters of up to tens of kilometers. Topography within the footprint results in a displacement of the reflecting point from Nadir to the point of closest approach relative to the satellite. Several methods exist for correcting for such mispointing errors. Here, two techniques are applied to observations near Jakobshavn Isbrae, acquired with Envisat's Radar Altimeter (RA-2). The a priori knowledge on the surface topography is obtained from a digital elevation model. The methods relocate the measurement location horizontally to agree with the measured range. One method assumes a constant surface slope within the footprint and uses this and the surface aspect to estimate the displacement parameter; the other locates the optimal relocation point using local topography. The results of the two methods are evaluated against airborne laser-scanner data from the airborne topographic mapper. We find that the accuracy of the relocation depends on both the technique and the spatial resolution of the digital elevation model, and that this dependency varies with surface roughness. Thus, the relocation may be associated with significant errors, which will lower the accuracy of cryospheric studies based on Radar Altimetry data. We find that the most accurate results are obtained when assessing the full local topography. Furthermore, errors in data over the steep margin are minimized the most when using a spatial resolution of $2$  km; the effect of the resolution over regions with a smoother topography is minor.

  • greenland 2012 melt event effects on cryosat 2 Radar Altimetry
    Geophysical Research Letters, 2015
    Co-Authors: Johan Nilsson, Louise Sandberg Sørensen, Sebastian B Simonsen, Rene Forsberg, Paul Vallelonga, Dorthe Dahljensen, Motohiro Hirabayashi, Kumiko Gotoazuma, C S Hvidberg, Helle Astrid Kjaer
    Abstract:

    CryoSat-2 data are used to study elevation changes over an area in the interior part of the Greenland Ice Sheet during the extreme melt event in July 2012. The penetration of the Radar signal into dry snow depends heavily on the snow stratigraphy, and the rapid formation of refrozen ice layers can bias the surface elevations obtained from Radar Altimetry. We investigate the change in CryoSat-2 waveforms and elevation estimates over the melt event and interpret the findings by comparing in situ surface and snow pit observations from the North Greenland Eemian Ice Drilling Project camp. The investigation shows a major transition of scattering properties around the area, and an apparent elevation increase of 56 ± 26 cm is observed in reprocessed CryoSat-2 data. We suggest that this jump in elevation can be explained by the formation of a refrozen melt layer that raised the reflective surface, introducing a positive elevation bias.

  • esa s ice sheets cci validation and inter comparison of surface elevation changes derived from laser and Radar Altimetry over jakobshavn isbrae greenland round robin results
    The Cryosphere Discussions, 2013
    Co-Authors: Joanna Fredenslund Levinsen, Louise Sandberg Sørensen, K. Khvorostovsky, Rene Forsberg, Andrew Shepherd, Francesca Ticconi, Alan Muir, Nadege Pie, Denis Felikson
    Abstract:

    In order to increase the understanding of the changing climate, the European Space Agency has launched the Climate Change Initiative (ESA CCI), a program which joins scientists and space agencies into 13 projects either affecting or affected by the concurrent changes. 5 This work is part of the Ice Sheets CCI and four parameters are to be determined for the Greenland Ice Sheet (GrIS), each resulting in a dataset made available to the public: Surface Elevation Changes (SEC), surface velocities, grounding line locations, and calving front locations. All CCI projects have completed a so-called Round Robin exercise in which the scientific community was asked to provide their 10 best estimate of the sought parameters as well as a feedback sheet describing their work. By inter-comparing and validating the results, obtained from research institutions world-wide, it is possible to develop the most optimal method for determining each parameter. This work describes the SEC Round Robin and the subsequent conclusions leading to the creation of a method for determining GrIS SEC values. The participants 15 used either Envisat Radar or ICESat laser Altimetry over Jakobshavn Isbrae drainage basin, and the submissions led to inter-comparisons of Radar vs. Altimetry as well as cross-over vs. repeat-track analyses. Due to the high accuracy of the former and the high spatial resolution of the latter, a method, which combines the two techniques will provide the most accurate SEC estimates. The data supporting the final GrIS analysis 20 stem from the Radar altimeters on-board Envisat, ERS-1 and ERS-2. The accuracy of laser data exceeds that of Radar Altimetry; the Round Robin analysis has, however, proven the latter equally capable of dealing with surface topography thereby making such data applicable in SEC analyses extending all the way from the interior ice sheet to margin regions. This shows good potential for a future inclusion of ESA CryoSat-2 25 and Sentinel-3 Radar data in the analysis, and thus for obtaining reliable SEC estimates throughout the entire GrIS.

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