scholarly journals Using airborne Ku-band altimeter waveforms to investigate winter accumulation and glacier facies on Austfonna, Svalbard

2013 ◽  
Vol 59 (217) ◽  
pp. 893-899 ◽  
Author(s):  
Robert L. Hawley ◽  
Ola Brandt ◽  
Thorben Dunse ◽  
Jon Ove Hagen ◽  
Veit Helm ◽  
...  
Keyword(s):  
Snow Depth ◽  
European Space Agency ◽  
Synthetic Aperture Radar Image ◽  
Altimeter Data ◽  
Radar Altimeter ◽  
Ice Caps ◽  
Ice Cap ◽  
Space Agency ◽  
Wet Snow ◽  
Airborne Sar

AbstractWinter balance is an important metric for assessing the change on glaciers and ice caps, yet measuring it using ground-based techniques can be challenging. We use the European Space Agency prototype Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) to extract snow depths from the received altimeter waveforms over Austfonna ice cap, Svalbard. Additionally, we attempt to distinguish the long-term firn area from other glacier facies. We validate our results using snow depth and glacier facies characterizations determined from ground-based radar profiles, snow pits and a multi-look satellite synthetic aperture radar image. We show that the depth of the winter snowpack can be extracted from the altimeter data over most of the accumulation zone, comprising wet snow zone and a superimposed ice zone. The method struggles at lower elevations where internal reflections within the winter snowpack are strong and the winter snow depth is less than ∼1 m. We use the abruptness of the reflection from the last summer surface (LSS) to attempt to distinguish glacier facies. While there is a general correlation between LSS abruptness and glacier facies, we do not find a relationship that warrants a distinct classification based on ASIRAS waveforms alone.

scholarly journals A New Retracking Algorithm for Retrieving Sea Ice Freeboard from CryoSat-2 Radar Altimeter Data during Winter–Spring Transition

2019 ◽  
Vol 11 (10) ◽  
pp. 1194 ◽  
Author(s):  
Xiaoyi Shen ◽  
Markku Similä ◽  
Wolfgang Dierking ◽  
Xi Zhang ◽  
Changqing Ke ◽  
...  
Keyword(s):  
Sea Ice ◽  
European Space Agency ◽  
Early Spring ◽  
Bézier Curve ◽  
Altimeter Data ◽  
Bezier Curve ◽  
Late Winter ◽  
Radar Altimeter ◽  
Depth Level ◽  
Space Agency

A new method called Bézier curve fitting (BCF) for approximating CryoSat-2 (CS-2) SAR-mode waveform is developed to optimize the retrieval of surface elevation of both sea ice and leads for the period of late winter/early spring. We found that the best results are achieved when the retracking points are fixed on positions at which the rise of the fitted Bézier curve reaches 70% of its peak in case of leads, and 50% in case of sea ice. In order to evaluate the proposed retracking algorithm, we compare it to other empirically-based methods currently reported in the literature, namely the threshold first-maximum retracker algorithm (TFMRA) and the European Space Agency (ESA) CS-2 in-depth Level-2 algorithm (L2I). The results of the retracking procedure for the different algorithms are validated using data of the Operation Ice Bridge (OIB) airborne mission. For two OIB campaign periods in March 2015 and April 2016, the mean absolute differences between freeboard values retrieved from CS-2 and OIB data were 9.22 and 7.79 cm when using the BCF method, 10.41 cm and 8.16 cm for TFMRA, and 10.01 cm and 8.42 cm for L2I. This suggests that the sea ice freeboard data can be obtained with a higher accuracy when using the proposed BCF method instead of the TFMRA or the CS-2 L2I algorithm.

scholarly journals Comparison of airborne radar altimeter and ground-based Ku-band radar measurements on the ice cap Austfonna, Svalbard

2008 ◽  
Vol 2 (5) ◽  
pp. 777-810 ◽  
Author(s):  
O. Brandt ◽  
R. L. Hawley ◽  
J. Kohler ◽  
J. O. Hagen ◽  
E. M. Morris ◽  
...  
Keyword(s):  
Peak Position ◽  
Center Frequency ◽  
Radar Altimeter ◽  
Ice Cap ◽  
Wet Snow ◽  
Radar Measurements ◽  
Good Proxy ◽  
Airborne Sar ◽  
Thin Crust ◽  
Ku Band

Abstract. We compare coincident data from the European Space Agency's Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) with ground-based Very High Bandwidth (VHB) stepped-frequency radar measurements in the Ku-band. The ASIRAS instrument obtained data from ~700 m above the surface, using a 13.5 GHz center frequency and a 1 GHz bandwidth. The ground-based VHB radar measurements were acquired using the same center frequency, but with a variable bandwidth of either 1 or 8 GHz. Four sites were visited with the VHB radar; two sites within the transition region from superimposed ice to firn, and two sites in the long-term firn area (wet-snow zone). The greater bandwidth VHB measurements show that the first peak in the airborne data is a composite of the return from the surface (i.e. air-snow interface) and returns of similar or stronger amplitude from reflectors in the upper ~30 cm of the subsurface. The peak position in the airborne data is thus not necessarily a good proxy for the surface since the maximum and width of the first return depend on the degree of interference between surface and subsurface reflectors. The major response from the winter snowpack was found to be caused by units of thin crust/ice layers (0.5–2 mm) surrounded by large crystals (>3 mm). In the airborne data, it is possible to track such layers for tens of kilometers. The winter snowpack lacked thicker ice layers. The last year's summer surface, characterized by a low density large crystal layer overlaying a harder denser layer, gives a strong radar response, frequently the strongest. The clear relationship observed between the VHB and ASIRAS waveforms, justifies the use of ground-based radar measurements in the validation of air- or spaceborne radars.

scholarly journals Discrimination of glacier facies using multi-temporal SAR data

1998 ◽  
Vol 44 (146) ◽  
pp. 42-53 ◽  
Author(s):  
K. C. Partington
Keyword(s):  
European Space Agency ◽  
Greenland Ice Sheet ◽  
Sensor Calibration ◽  
Lower Altitude ◽  
Mount Pinatubo ◽  
South Central ◽  
Space Agency ◽  
Wet Snow ◽  
Multi Temporal ◽  
Sar Data

AbstractGlacier facies from the Greenland ice sheet and the Wrangell-St Elias Mountains, Alaska, are analyzed using multi-temporal synthetic aperture radar (SAR) data from the European Space Agency ERS-1 satellite. Distinct zones and facies are visible in multi-temporal SAR data, including the dry-snow facies, the combined percolation and wet-snow facies, the ice facies, transient melt areas and moraine. In Greenland and south-central Alaska, very similar multi-temporal signatures are evident for the same facies, although these facies are found at lower altitude in West Greenland where the equilibrium line appears to be found at sea level at 71°30?N during the year analyzed (1992-93), probably because of the cooling effect of the eruption of Mount Pinatubo. In Greenland, both the percolation and dry-snow facies are excellent distributed targets for sensor calibration, with backscatter coefficients stable to within 0.2 dB. However, the percolation facies near the top of Mount Wrangell are more complex and less easily delineated than in Greenland, and at high altitude the glacier facies have a multi-temporal signature which depends sensitively on slope orientation.

scholarly journals CryoSat-2 delivers monthly and inter-annual surface elevation change for Arctic ice caps

2015 ◽  
Vol 9 (3) ◽  
pp. 2821-2865 ◽  
Author(s):  
L. Gray ◽  
D. Burgess ◽  
L. Copland ◽  
M. N. Demuth ◽  
T. Dunse ◽  
...  
Keyword(s):  
Snow Accumulation ◽  
Surface Elevation ◽  
Radar Altimeter ◽  
Elevation Change ◽  
Ice Caps ◽  
Ice Cap ◽  
Winter Snow ◽  
Surface Elevation Change ◽  
Devon Ice Cap ◽  
Arctic Ice

Abstract. We show that the CryoSat-2 radar altimeter can provide useful estimates of surface elevation change on a variety of Arctic ice caps, on both monthly and yearly time scales. Changing conditions, however, can lead to a varying bias between the elevation estimated from the radar altimeter and the physical surface due to changes in the contribution of subsurface to surface backscatter. Under melting conditions the radar returns are predominantly from the surface so that if surface melt is extensive across the ice cap estimates of summer elevation loss can be made with the frequent coverage provided by CryoSat-2. For example, the average summer elevation decreases on the Barnes Ice Cap, Baffin Island, Canada were 2.05 ± 0.36 m (2011), 2.55 ± 0.32 m (2012), 1.38 ± 0.40 m (2013) and 1.44 ± 0.37 m (2014), losses which were not balanced by the winter snow accumulation. As winter-to-winter conditions were similar, the net elevation losses were 1.0 ± 0.2 m (winter 2010/2011 to winter 2011/2012), 1.39 ± 0.2 m (2011/2012 to 2012/2013) and 0.36 ± 0.2 m (2012/2013 to 2013/2014); for a total surface elevation loss of 2.75 ± 0.2 m over this 3 year period. In contrast, the uncertainty in height change results from Devon Ice Cap, Canada, and Austfonna, Svalbard, can be up to twice as large because of the presence of firn and the possibility of a varying bias between the true surface and the detected elevation due to changing year-to-year conditions. Nevertheless, the surface elevation change estimates from CryoSat for both ice caps are consistent with field and meteorological measurements. For example, the average 3 year elevation difference for footprints within 100 m of a repeated surface GPS track on Austfonna differed from the GPS change by 0.18 m.

scholarly journals Interferometric swath processing of Cryosat data for glacial ice topography

2013 ◽  
Vol 7 (6) ◽  
pp. 1857-1867 ◽  
Author(s):  
L. Gray ◽  
D. Burgess ◽  
L. Copland ◽  
R. Cullen ◽  
N. Galin ◽  
...  
Keyword(s):  
European Space Agency ◽  
Main Beam ◽  
Synthetic Aperture Radar Interferometry ◽  
Ice Cap ◽  
Space Agency ◽  
Digital Elevation ◽  
Interferometric Phase ◽  
Elevation Data ◽  
Devon Ice Cap ◽  
Cross Track

Abstract. We have derived digital elevation models (DEMs) over the western part of the Devon Ice Cap in Nunavut, Canada, using "swath processing" of interferometric data collected by Cryosat between February 2011 and January 2012. With the standard ESA (European Space Agency) SARIn (synthetic aperture radar interferometry) level 2 (L2) data product, the interferometric mode is used to map the cross-track position and elevation of the "point-of-closest-approach" (POCA) in sloping glacial terrain. However, in this work we explore the extent to which the phase of the returns in the intermediate L1b product can also be used to map the heights of time-delayed footprints beyond the POCA. We show that there is a range of average cross-track slopes (~ 0.5 to ~ 2°) for which the returns will be dominated by those beneath the satellite in the main beam of the antenna so that the resulting interferometric phase allows mapping of heights in the delayed range window beyond the POCA. In this way a swath of elevation data is mapped, allowing the creation of DEMs from a sequence of L1b SARIn Cryosat data takes. Comparison of the Devon results with airborne scanning laser data showed a mean difference of order 1 m with a standard deviation of about 1 m. The limitations of swath processing, which generates almost 2 orders of magnitude more data than traditional radar altimetry, are explored through simulation, and the strengths and weaknesses of the technique are discussed.

scholarly journals The European Space Agency’s Earth Explorer Mission CryoSat: measuring variability in the cryosphere

2004 ◽  
Vol 39 ◽  
pp. 313-320 ◽  
Author(s):  
Mark R. Drinkwater ◽  
Richard Francis ◽  
Guy Ratier ◽  
Duncan J. Wingham
Keyword(s):  
European Space Agency ◽  
Ice Sheets ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Radar Altimeter ◽  
Operating Characteristics ◽  
Space Agency ◽  
Explorer Mission ◽  
Arctic Sea ◽  
Ku Band

AbstractCryoSat is currently being prepared for a 2005 launch as the first European Space Agency Earth Explorer Opportunity mission. It is a dedicated cryospheric mission equipped with a Ku-band SIRAL (SAR/Interferometric Radar ALtimeter), whose primary objectives are to measure the variability and trends in the mass of the Arctic sea-ice cover and large terrestrial ice sheets. In this paper, an overview is provided of the mission and of the measurement characteristics of the new SIRAL instrument. Examples of data acquired on recent preparatory campaigns are presented, illustrating the operating characteristics of the key SIRAL modes. Preparatory plans for calibration and validation of CryoSat data are described.

scholarly journals A Multi-Sensor Approach to the Interpretation of Radar Altimeter Wave Forms from Two Arctic Ice Caps

1987 ◽  
Vol 9 ◽  
pp. 60-68 ◽  
Author(s):  
Mark R. Drinkwater ◽  
Julian A. Dowdeswell
Keyword(s):  
Surface Roughness ◽  
Leading Edge ◽  
High Amplitude ◽  
Wave Form ◽  
Radar Altimeter ◽  
Ice Caps ◽  
Lower Amplitude ◽  
Wet Snow ◽  
Radio Echo Sounding ◽  
Wave Forms

Data collected over Svalbard on 28 June 1984 by a 13.81 GHz airborne radar altimeter enabled analysis of signals returned from two relatively large ice masses. Wave forms received over the ice caps of Austfonna and Vestfonna are analysed with the aid of existing aerial photography, radio echo-sounding data, and Landsat MSS images acquired close to the date of the altimeter flight. Results indicate that altimeter wave forms are controlled mainly by surface roughness and scattering characteristics. Wet snow surfaces have narrow 3 dB back-scatter half-angles and cause high-amplitude signals, in contrast to relatively dry snow surfaces with lower-amplitude diffuse signals. Metre-scale surface roughness primarily affects wave-form amplitude and leading-edge slope, this becoming apparent over ice streams on Vestfonna.

Quality Status of the CryoSat Data Products

2020 ◽  
Author(s):  
Erica Webb ◽  
Ben Wright ◽  
Marco Meloni ◽  
Jerome Bouffard ◽  
Tommaso Parrinello ◽  
...  
Keyword(s):  
Sea Ice ◽  
Data Quality ◽  
Positive Impact ◽  
European Space Agency ◽  
Performance Standards ◽  
Radar Altimeter ◽  
Mountain Glaciers ◽  
Space Agency ◽  
And Performance ◽  
Quality Status

<p>Launched in 2010, the European Space Agency’s (ESA) polar-orbiting CryoSat satellite was specifically designed to measure changes in the thickness of polar sea ice and the elevation of the ice sheets and mountain glaciers. Beyond the primary mission objectives, CryoSat is also valuable source of data for the oceanographic community and CryoSat’s sophisticated SAR Interferometric Radar Altimeter (SIRAL) can measure high-resolution geophysical parameters from the open ocean to the coast.</p><p>CryoSat data is processed operationally using two independent processing chains: Ice and Ocean. To ensure that the CryoSat products meet the highest data quality and performance standards, the CryoSat Instrument Processing Facilities (IPFs) are periodically updated. Processing algorithms are improved based on feedback and recommendations from Quality Control (QC) activities, Calibration and Validation campaigns, the CryoSat Expert Support Laboratory (ESL), and the Scientific Community. </p><p>Since May 2019, the CryoSat ice products are generated with Baseline-D, which represented a major processor upgrade and implemented several improvements, including the optimisation of freeboard computation in SARIn mode, improvements to sea ice and land ice retracking and the migration from Earth Explorer Format (EEF) to Network Common Data Form (NetCDF). A reprocessing campaign is currently underway to reprocess the full mission dataset (July 2010 – May 2019) to Baseline-D.</p><p>The CryoSat ocean products are also generated in NetCDF, following a processor upgrade in November 2017 (Baseline-C). Improvements implemented in this new Baseline include the generation of ocean products for all data acquisition modes, therefore providing complete data coverage for ocean users. This upgrade also implemented innovative algorithms, refined existing ones and added new parameters and corrections to the products. Following the completion of a successful reprocessing campaign, Baseline-C ocean products are now available for the full mission dataset (July 2010 – present).</p><p>Since launch, the CryoSat ice and ocean products have been routinely monitored as part of QC activities by the ESA/ESRIN Sensor Performance, Products and Algorithms (SPPA) office with the support of the Quality Assurance for Earth Observation (QA4EO) service (formerly IDEAS+) led by Telespazio VEGA UK. The latest processor updates have brought significant improvements to the quality of CryoSat ice and ocean products, which in turn are expected to have a positive impact on the scientific exploitation of CryoSat measurements over all surface types.</p><p>This poster provides an overview of the CryoSat data quality status and the QC activities performed by the QA4EO consortium, including both operational and reprocessing QC. Also presented are the main evolutions and improvements that have implemented to the processors, and anticipated evolutions for the future.</p>

Quality Status of the CryoSat Data Products

2021 ◽  
Author(s):  
Erica Webb ◽  
Jenny Marsh ◽  
Laura Benzan Valette ◽  
Jerome Bouffard ◽  
Tommaso Parrinello ◽  
...  
Keyword(s):  
Sea Ice ◽  
Data Quality ◽  
Positive Impact ◽  
European Space Agency ◽  
Performance Standards ◽  
Radar Altimeter ◽  
Mountain Glaciers ◽  
Space Agency ◽  
And Performance ◽  
Quality Status

<p>Launched in 2010, the European Space Agency’s (ESA) polar-orbiting CryoSat satellite was specifically designed to measure changes in the thickness of polar sea ice and the elevation of the ice sheets and mountain glaciers. Beyond the primary mission objectives, CryoSat is also valuable source of data for the oceanographic community and CryoSat’s sophisticated SAR Interferometric Radar Altimeter (SIRAL) can measure high-resolution geophysical parameters from the open ocean to the coast.</p><p>CryoSat data is processed operationally using two independent processing chains: Ice and Ocean. To ensure that the CryoSat products meet the highest data quality and performance standards, the CryoSat Instrument Processing Facilities (IPFs) are periodically updated. Processing algorithms are improved based on feedback and recommendations from Quality Control (QC) activities, Calibration and Validation campaigns, the CryoSat Expert Support Laboratory (ESL), and the Scientific Community.</p><p>Since May 2019, the CryoSat ice products have been generated with Baseline-D, which represented a major processor upgrade and implemented several improvements, including the optimisation of freeboard computation in SARIn mode, improvements to sea ice and land ice retracking and the migration from Earth Explorer Format (EEF) to Network Common Data Form (NetCDF). The Baseline-D reprocessing campaign completed in May 2020, and the full mission Baseline-D dataset is now available to users (July 2010 – present). The next major processor upgrade, Baseline-E, is already under development and following testing and refinement is anticipated to be operational in Q3 2021.</p><p>The CryoSat ocean products are also generated in NetCDF, following a processor upgrade in November 2017 (Baseline-C). Improvements implemented in this baseline include the generation of ocean products for all data acquisition modes, therefore providing complete data coverage for ocean users. This upgrade also implemented innovative algorithms, refined existing ones and added new parameters and corrections to the products. Following the completion of a successful reprocessing campaign, Baseline-C ocean products are now available for the full mission dataset (July 2010 – present). Preparations are underway for the next major processor upgrade, Baseline-D.</p><p>Since launch, the CryoSat ice and ocean products have been routinely monitored as part of QC activities by the ESA/ESRIN Sensor Performance, Products and Algorithms (SPPA) office with the support of the Quality Assurance for Earth Observation (QA4EO) service (formerly IDEAS+) led by Telespazio UK. The latest processor updates have brought significant improvements to the quality of CryoSat ice and ocean products, which in turn are expected to have a positive impact on the scientific exploitation of CryoSat measurements over all surface types.</p><p>This poster provides an overview of the CryoSat data quality status and the QC activities performed by the IDEAS-QA4EO consortium, including both operational and reprocessing QC. Also presented are the main evolutions and improvements that have implemented to the processors, and anticipated evolutions for the future.</p>

scholarly journals Assimilation of radar altimeter data in numerical wave models: an impact study in two different wave climate regions

2007 ◽  
Vol 25 (3) ◽  
pp. 581-595 ◽  
Author(s):  
G. Emmanouil ◽  
G. Galanis ◽  
G. Kallos ◽  
L. A. Breivik ◽  
H. Heiberg ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Mediterranean Sea ◽  
European Space Agency ◽  
Wave Climate ◽  
Altimeter Data ◽  
Radar Altimeter ◽  
The Indian Ocean ◽  
Numerical Wave ◽  
The Mediterranean ◽  
Wave Models

Abstract. An operational assimilation system incorporating significant wave height observations in high resolution numerical wave models is studied and evaluated. In particular, altimeter satellite data provided by the European Space Agency (ESA-ENVISAT) are assimilated in the wave model WAM which operates in two different wave climate areas: the Mediterranean Sea and the Indian Ocean. The first is a wind-sea dominated area while in the second, swell is the principal part of the sea state, a fact that seriously affects the performance of the assimilation scheme. A detailed study of the different impact is presented and the resulting forecasts are evaluated against available buoy and satellite observations. The corresponding results show a considerable improvement in wave forecasting for the Indian Ocean while in the Mediterranean Sea the assimilation impact is restricted to isolated areas.

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