Conference Agenda

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Session Overview
Welcome Reception & Poster Session
Monday, 20/Mar/2017:
6:00pm - 7:30pm

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Evolutions of the Cryosat-2 Instrument Processing Facility (IPF)

Pier-Luca Mantovani1, Michele Scagliola2, Stéphanie Urien3, David Brockley4, Steven Baker4, Jerome Bouffard5, Pierre Feménias5, Marco Fornari5, Tommaso Parrinello5, Rubunder Mannan6

1Advanced Computer Systems ACS S.r.l., Italy; 2ARESYS; 3CLS; 4MSSL-UCL; 5ESA; 6Telespazio UK

Ever since the Cryosat-2 launch in April 2010, the on-ground facility devoted to process SIRAL data from Level 0 up to Level 2, i.e. the Instrument Processing Facility (IPF) has continuously evolved with the purpose to improve the quality of the production.

This goal has been pursued in two main ways: refinement of the products contents and increase of the products number.

The products contents have been enriched in terms of new fields and more accurate and precise figures computed by means of the algorithms continuously in evolution.

As to the most important changes the IPF processing of Level 1b has undergone it is worth mentioning: computation of refined attitude information from the same star tracker that is selected on-board by AOCS; Hamming windowing in beamforming; oversampling in range of the waveforms by factor 2 without reducing the range window; surface sample stack weighting to increase the clutter suppression on the L1b waveform. The level 2 processing has been updated to add sea-ice freeboard processing and phase-wrap detection for SARin ice-sheet margins.

The original Cryosat production, mainly devoted to ice scientists, was extended in March 2015 with the generation of products specific for the ocean community, which got interested in the exploitation of the Cryosat measurement for innovative research mainly in polar ocean, coastal seas and sea-floor mapping.

In this production, LRM and SAR L0 products are processed to generate Intermediate and Geophysical Ocean Products (IOP and GOP respectively). In Q2 2017, this production will be further improved by processing SARin L0 products and by using SAR retrackers (SAMOSA)

Last but not least, ESA decided to add value to the Cryosat-2 production by changing the format of the products distributed to the users: the original Earth Explorer format, a binary format inherited by the ENVISAT mission, has been replaced by a new format based on netCDF (called CONFORM), which is easier to use and more flexible. These products are planned to be distributed in Q2 2017.

Improving CryoSat-2 Elevation Change Estimates using TanDEM-X

Veit Helm1, Angelika Humbert1,2

1Alfred Wegener Institut, Germany; 2University of Bremen, Germany

Estimating the contribution of ice sheets to sea level change is a major goal of glaciologists and of high interest for the society. Therefore, there is a strong need for robust volume change and in consequence mass change estimates of the ice sheets including reliable uncertainty estimates. There are numerous sources for uncertainties, ranging from instrumental errors, different processing approaches towards the interpolation between sparsely distributed data and especially for CryoSat-2 the combination of two different measurement modes is challenging. To our understanding the slope correction of the altimetry signal is one of the critical parameters for reliable elevation estimates of satellite-borne altimeters. For this purpose we analyse 6 years of CryoSat-2 altimeter data acquired from 2011 to 2017 in three to four different test sites characterized by different surface topography and covering CryoSat’s LRM and SIN zones, respectively. We present the influence of different slope corrections applied to the CryoSat-2 data on derived volume change estimates. The slope corrections will be based on coarse resolution ice-sheet wide elevation models and high-resolution very precise elevation models derived from TanDEM-X.

A Digital Elevation Model Of Antarctica Derived From 6 Years Of Continuous Cryosat-2 Observations

Thomas Slater1, Andrew Shepherd1, Malcolm McMillan1, Alan Muir2

1University of Leeds, United Kingdom; 2University College London, United Kingdom

Surface topography measurements of Antarctica are important datasets in the validation and initialising of numerical ice-sheet models, fieldwork planning, and the calculation of mass balance. In addition, accurate and current knowledge of ice-sheet topography is also required for InSAR measurements of ice velocity to distinguish between interferometric phase difference caused by topography and ice motion. Here we present a new digital elevation model (DEM) for the Antarctic ice-sheet, derived from 6 years of continuous Cryosat-2 radar altimetry. At a resolution of 2 km we find that CryoSat-2 provides an elevation measurement for 92% of the total ice-sheet area. We assess the accuracy of the generated DEM by comparison with airborne laser altimeter measurements from NASA IceBridge campaigns over the time period 2008-2015, in various locations across the Antarctic ice-sheet.

Evolution of Fast Ice Thickness from Four Years of Cryosat-2 Data, a Case Study in Scar Inlet, Antarctica

Mahsa Sadat Moussavi1,2,3, Ted Scambos1,3, Erin Pettit4, Waleed Abdalati2,3

1National Snow and Ice Data Center (NSIDC), United States of America; 2Cooperative Institute for Research in Environmental Sciences (CIRES), United States of America; 3University of Colorado, Boulder, United States of America; 4University of Alaska, Fairbanks, United States of America

While the last substantial fragment of the former Larsen B Ice shelf, namely the Scar Inlet Ice Shelf, has undergone dramatic changes ever since the breakup of Larsen B in 2002, it has remained largely intact. A thin layer of frozen ocean ice fastened to the coastline, or ‘fast ice’, may be responsible for supporting the weakened ice shelf over the past few years. Some evidence from ice flow speed and direction changes measured on the shelf suggest this is the case. However, the degree to which the fast ice impedes the full collapse of the Scar Inlet Shelf is not well understood. One source of uncertainty is the lack of current fast ice thickness data, and moreover, data that would describe how the fast ice has evolved over the past several years. The European Space Agency’s (ESA) Cryosat-2 radar altimeter is a new satellite sensor that has the potential to provide data on the evolution of the Scar Inlet Ice Shelf itself and the adjacent fast ice since 2013. We analyze four years (2013-2016) of Cryosat-2 data to determine the thickness of the fast ice and study its seasonal and annual variation patterns in relation to in-situ temperature measurements collected by the nearby weather stations. We apply automatic freeboard retrieval procedures to the ESA level-2 SAR Interferometric (SIN) mode data (Baseline-C) to estimate the ice thickness. To evaluate errors, we undertake a supervised lead detection procedure, through which we manually establish sea surface height from Cryosat-2 measurements over leads visible in imagery from the Moderate Resolution Imaging Spectrometer (MODIS). This study provides the first long-term satellite-based evaluation of fast ice thickness and offers insight into processes affecting ice shelf stability.

Finite-element GIA Estimations For Antarctica Based On A New Lithospheric Model

Bas Blank1, Haiyang Hu1, Wouter van der Wal1, Folker Pappa2, Jorg Ebbing2

1TU Delft, Netherlands, The; 2CAU Kiel, Germany

The GRACE mission provided the scientific community an opportunity to observe mass transport processes during a longer period than imagined. One of the most important mass transport processes in the last decades, is the melting of glaciers and ice caps. However, the melting of past ice caps induced Glacial Isostatic Adjustment (GIA) in these regions, which is also an important cause for mass transport in the Earth’s mantle. GRACE cannot distinguish between ice cap melting and GIA. Therefore it is important that we are able to model the GIA process in order to extract the present-day ice mass loss from the GRACE data.

We are developing a GIA model based on finite-elements which is tailored towards GIA in Antarctica. This new GIA model is developed in cooperation with the ESA’s GOCE+ “Dynamic Antarctic Lithosphere” project. Within the GOCE+ project a more accurate model of e.g. the lithosphere and upper mantle is developed, based on seismic tomography, satellite and airborne gravity data and realistic mantle composition. The lithosphere and mantle models will be implemented in the finite element based model of Antarctica, to investigate the influence of local variations in mantle and lithosphere parameters, in particular low viscosities in West Antarctica, on GIA in Antarctica.

A benchmark of the FE model has been done versus semi-analytic normal mode models. Test cases without ocean loading showed an error of less than 2% for deflection 10 kyear after unloading. However, the elastic response showed an error at the deflection bulge. A varying mesh was implemented to achieve a resolution of up to 50 km by 50 km at specifically targeted locations.

Validation of CryoSat-2 Performance Over Arctic Sea Ice

Alessandro Di Bella1, Henriette Skourup1, Jerome Bouffard2, Tommaso Parrinello2

1Technical University of Denmark / National Space Institute, Denmark; 2ESA/ESRIN

The main objective of this work is to validate CryoSat-2 (CS2) SARIn performance over sea ice by use of airborne laser altimetry data obtained during the CryoVEx 2012 campaign. A study by [1] has shown that the extra information from the CS2 SARIn mode increases the number of valid sea surface height estimates which are usually discarded in the SAR mode due to snagging of the radar signal. As the number of valid detected leads increases, the uncertainty of the freeboard heights decreases.

In this study, the snow freeboard heights estimated using data from the airborne laser scanner are used to validate the sea ice freeboard obtained by processing CS2 SARIn level 1b waveforms. The possible reduction in the random freeboard uncertainty is investigated comparing two scenarios, i.e. a SAR-like and a SARIn acquisition.

It is observed that using the extra phase information, CS2 is able to detect leads up to 2370 m off-nadir. A reduction in the the total random freeboard uncertainty of ∼40% is observed by taking advantage of the CS2 interferometric capabilities, which enable to include ∼35% of the waveforms discarded in the SAR-like scenario.

Cryosat2 Assessment of Inland Water Height Retrieval over River Networks

Philippa A. M. Berry1, Robert Balmbra2, Richard G. Smith3

1Roch Remote Sensing, United Kingdom; 2Cyber Security Centre Warwick University; 3STRL/CSC De Montfort University

The Cryosat2 mission presents challenges for measurement of inland water heights as the long repeat period complicates generation of useful time series. Modelling techniques can be used to propagate the measurements to common virtual ground stations; in-situ gauge data may be interpolated to the Cryosat2 track locations [e.g. 1] for validation purposes.
However, the Cryosat2 mission offers a unique perspective on observing river networks. The dense spatial sampling allows detailed analysis of river waveforms in both SAR and LRM modes, allowing characterisation of river systems in terms of the successful retrieval of ‘clean’ waveforms. Combining these results with assessment of river height time series from prior missions, including time series successfully retrieved from Envisat, ERS2, Topex and Jason1/2 [e.g. 2], and, crucially, analysis of locations where useable time series were not retrieved, enables an assessment of the extent to which river network heights may be accessible from Sentinel3 and future missions.
This paper presents series of analyses across multiple river networks in varying terrain and climate conditions, including the Amazon basin, Ganges, Brahmaputra, Orinoco, Syr Darya and Nile, using Cryosat2 SAR and LRM mode waveforms. Multiple cycles of data are utilised.
The results show that there is successful retrieval of small numbers of ‘clean’ waveforms from all river systems examined in both SAR and LRM modes at 20Hz. Time series analysis from prior missions over these river networks confirms the successful retrieval of heights even when only one or two ‘clean’ waveforms are present. Combining these results enables classification of these river networks in terms of their accessibility for altimeter monitoring. The availability of Cryosat2 FBR data in SAR mode increases the time series generation capability to 80Hz (due to the discontinuous sampling); together with an assessment of the 1800Hz Envisat burst echoes over river networks [3] this is shown to allow retrieval over smaller tributaries and also demonstrates enhanced measurement capability where islands and sandbars interrupt the river course towards the minimum of the hydrological cycle. Over all river systems presented, monitoring of river networks using satellite altimetry is concluded to be an effective strategy. The availability of waveforms at a higher sampling frequency is demonstrated to increase this monitoring capability, allowing monitoring of smaller tributaries and also enabling recovery of river heights towards the minimum of the hydrological cycle.

1 R. Schneider, P.N.Godiksen, M.-E. Ridler et al., 2016. Combining Envisat and CryoSat-2 Altimetry to Inform Hydrodynamic Models. Proc. ‘Living Planet Symposium 2016’, Prague, Czech Republic, 9–13 May 2016 (ESA SP-740, August 2016)

2 Berry, P.A.M., Smith,R.G. & Benveniste, J., 2012. Envisat Altimetry For River And Lakes Monitoring. Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International pp 1844-1848.

3 Berry, P. A. M., Smith, R. G., Salloway, M. K., Benveniste, J., 2011. "Global Analysis of EnviSat Burst Echoes Over Inland Water," IEEE Trans. Geoscience and Remote Sensing, Issue 99, pp.1-6. doi: 10.1109/TGRS.2011.2170695

Sensitivity of NEMO-LIM3 Coupled Ice-Ocean Model to Initial Sea Ice Thickness States from CryoSat-2

Heidi Sallila, Eero Rinne, Petteri Uotila

Finnish Meteorological Institute, Finland

We present the sensitivity of a coupled sea-ice-atmosphere model NEMO-LIM3 to the initial sea ice thickness. To study the sensitivity we built a scheme where the sea ice thickness of the model is nudged with CryoSat-2 measured ice thickness with different relaxation parameters in the spring 2012. We then run the model with atmospheric forcing till fall 2012 and compare the sea ice extent and volume to different independent estimates of the sea ice in the Arctic. In other words we want to see how well our model is able to reproduce the record sea ice minimum of 2012 and will the nudging improve the modelled sea ice estimates.

All simulations presented here are based on the version 3.6_STABLE of the NEMO-LIM ocean-ice modelling system, in the ORCA025 horizontal grid configuration with 75 vertical ocean levels. In NEMO, the OPA ocean component is coupled with the LIM3.6 sea-ice model. LIM3.6 is a sea-ice model in the line of the AIDJEX model, with multiple sea-ice categories. Multiple categories allow to resolve the intense growth and melt of thin ice, as well as the redistribution of thinner ice onto thicker ice due to ridging and rafting. Thermodynamics are multi-layer and include an explicit description of the effect of brine on the storage and conduction of heat, and a parameterization of brine drainage that affects ocean-ice salt exchanges. The default NEMO3.6 configuration uses five ice thickness categories and two vertical layers for thermodynamics. Simulations were forced by the DFS5.2 atmospheric data set, developed through the DRAKKAR consortium. Prescribed ocean-atmosphere surface boundary conditions were calculated by using the CORE bulk formulae.

We show that nudging the NEMO-LIM3 towards CryoSat-2 thickness estimates at the start of melt season has a significant impact on the sea ice volume estimates for end of melt season. Varying the relaxation parameter influences both sea ice volume and extent estimates. Furthermore, we speculate that the winter-to-summer sea-ice extent and volume predictions are improved if more realistic sea-ice volume initial conditions are used.

Optimizing Spectral Windows For Processing CryoSat SAR Mode Data Over Sea Ice

Walter H F Smith1, Alejandro E Egido1,2

1NOAA Lab for Satellite Altimetry, United States of America; 2University of Maryland, College Park, Maryland, USA

In satellite radar altimetry, the elevation, roughness, and radar cross section of Earth surfaces are estimated by fitting models to power spectral density (PSD) estimates known as “waveforms”. In conventional altimetry the PSD is one-dimensional and maps backscattered power to range (distance). In the “Delay/Doppler” or “multi-looked SAR” process (hereafter, “D/D-SAR”) the PSD is two-dimensional, mapping power to range and along-track position on the ground. In each dimension the PSD estimate suffers from “leakage” because the Earth returns power at a continuum of ranges and along-track positions, and not merely those corresponding to the frequencies correctly sampled by the discrete Fourier transform (DFT).

Leakage may be mitigated, and the PSD resolution function shaped, by use of a spectral window. To date, altimetry has used either no window, or a Hamming window. No window achieves the highest possible resolution (desirable) but allows the most leakage (undesirable). The Hamming window suppresses the leakage but at the expense of about a 30% degradation of resolution; for example, the along-track resolution of Cryosat and Sentinel-3 D/D-SAR is increased from about 300 m to about 400 m.

The signal-to-noise ratio (SNR, noise being due to quantization, random thermal and also image clutter sources) in altimetry is usually not more than 25 dB, and so there is no point in choosing a window with (mainlobe integral)/(sidelobe integral) ratio, MSR, much larger than about 30 dB. The Hamming window has too much MSR (38 dB), and too much widening of the mainlobe (degrading resolution). Better resolution can be achieved by designing a window to have only as much MSR as the application needs or the data SNR permits.

This paper suggests better windows. Here, “better” means that the PSD resolution function (known in the radar literature as the “point target response”, PTR) is as Gaussian as possible, and as narrow in its main lobe as possible, while achieving only as much leakage suppression as the data signal-to-noise ratio allows.

The estimated PSD is (to a good approximation) the true PSD convolved with the PTR. Since convolution is an integral, one should characterize the PTR’s performance using integral measures of bandwidth, side lobe energy, etc., as opposed to point values (bandwidth at half power or at zero crossings, peak side lobe levels). These integrals can be evaluated in terms of matrix-vector quadratic forms, the eigenvectors of which can build good windows.

The (mainlobe integral)/(sidelobe integral) ratio, MSR, has a maximizing eigenvector, the (first) DPSS (or multi-taper or Slepian) window. The root-mean-square window bandwidth (PTR σ), called here RMS, has a minimizing eigenvector known as the Sine Window and used in MPEG compression. Windows having the most Gaussian performance under convolution can be built from linear combinations of eigenvectors associated with the RMS bandwidth measure.

We will present CryoSat SAR mode data obtained over areas of sea ice with leads, and will process the FBR data using no window, the Hamming window, and “better” windows, in order to show the value obtained by optimizing the window’s performance.

A Synthesis of Snow Depth Observations in the Arctic: Towards a Seasonal Snow Depth Product for CryoSat-2

Melinda Webster1, Alek Petty1,2, Linette Boisvert1,2, Thorsten Markus1

1NASA Goddard Space Flight Center, USA; 2Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, USA

Knowledge of snow depth on sea ice is critical for accurate retrievals of sea ice thickness from current (CryoSat-2) and next-generation altimetry data (e.g. ICESat-2, CryoSat-3). In 1937 and 1954-1991, efforts led by the former Soviet Union established the first time-series of snow depth measurements in the central Arctic, a record which has become the most widely-used snow climatology for snow depth on Arctic sea ice to date. Since then, limited efforts have been made towards continued monitoring of Pan-Arctic snow conditions, forming an acute gap in our understanding of the Arctic system as it evolves in a changing climate.

In recognition of this knowledge gap, we present initial results from the Precipitation, Accumulation and Snow Thickness in the Arctic (PASTA) project; a new initiative aimed at improving seasonal estimates of Pan-Arctic snow depth for use by the modeling and remote sensing communities. Here we present an overview of the different sources of data (and additional data we hope to obtain) in this Arctic snow depth synthesis, including in-situ, buoy, airborne and satellite datasets. We describe our initial efforts to optimally interpolate datasets that span different spatial scales, and discuss planned efforts to assimilate these data with dynamic snowfall estimates from reanalysis products. We also present preliminary efforts to initiate a community snow data repository for the continued production of an up-to-date, synthesized, Arctic snow depth dataset.

We anticipate that this new snow depth dataset will provide information that is more representative of the current state of the Arctic, improving altimeter-derived retrievals of sea ice thickness and assessments of polar climate variability in global climate models.

Improving the Short Wavelengths of Mean Sea Surface using CryoSat Data

Philippe Schaeffer1, Yannice Faugère1, Isabelle Pujol1, Nicolas Picot2

1CLS, France; 2CNES

The CNES_CLS 2015 Mean Sea Surface, as well as its former versions, was determined from altimetric data which are sampled at a frequency of 1 Hz (7 km along tracks). Theoretically, this introduces limits concerning the mapping of wavelengths less than 20-30 km.

Until now, this sampling represented a good compromise between signal and instrumental noises. Thanks to the implementation of more efficient altimeters and also considering the improvement of the processing methods (e.g. retracking), the CryoSat LRM-mode and more especially the SAR-mode allow us today to access to less noisy observations at higher frequencies.

It is therefore particularly interesting to use this new kind of observations in order to analyze their contribution for mapping topographic structures at wavelengths less than 30 km. We propose to present results obtained from analyzes carried out with Cryosat data sampled at 20 Hz. Goal is here to prepare these data for the determination of the next reference fields, and in particular to improve the finest topographic structures of the MSS which is used as support for ongoing and future missions such as SWOT.

The CryoSat SciEnce-oriented Data ANalysis Over Sea-ICE Areas Project

Pierre Laurent Fabry1, Nicolas Bercher1, Stefan Hendricks2, Robert Ricker2, Sara Fleury3, Frédérique Rémy3, Jean-Christophe Poisson4, Pierre Thibaut4, Jérôme Bouffard5, Pierre Féménias5

1ALONG-TRACK SAS, France; 2AWI, Germany; 3CNRS/LEGOS, France; 4CLS, France; 5ESA/ESRIN, Italy

This communication presents the many aspects and some preliminary results of the ESA funded Cryo-seaNice project that just started (November 2016). The acronym stands for CryoSat SciEnce-oriented data ANalysis over sea-ICE areas. The high level objectives of the project are

- to provide an independent evaluation of Baseline-C operational IPF2 freeboard products,

- to support ESA in the definition of future CryoSat IPF evolutions based on the outcomes of targeted R&D activities focusing on CryoSat data analysis over sea-ice areas,

- to study, prototype, test new or optimized algorithms that may impact IPF-1 and/or IPF-2,

- to study, prototype, test new freeboard products.

A team with very complementary expertises has been set to address the complex subject of sea-ice remote sensing from both the high spatial diversity and the strong temporal variability aspects due to the sea-ice physics, meteorological events as well as local surface currents.

Dedicated science oriented tools therefore need to be put in place to make best profit of both in situ data and imagery to thoroughly understand the signatures within the altimeter signals.

It is expected tha some of the CryoSat Ice Processor limitations be detected/analysed through a refined analysis of the physics behind the Ku band SAR/SARin altimeter products and Ka band products over the Sea-Ice domain.

The team will also implement and assess the outputs of new/recent geophysical retrackers.

The various aspects and steps of the projects will be presented : Refine the surface type detection; Improve retracking using physical based retrackers instead of threshold based retrackers ; Tackle continuity issues (proper retracking of specular and brownian WF in sequence, off-nadir hookings, side lobe contamination effects, freeboard continuity especially

at the pack ice - fast ice transitions and between SAR and SARIN modes), assess snow cover impact onto freeboard and ice-thickness measurements, Analyse and Improve the existing freeboard SNR, Study, Prototype and Assess new freeboard measurement techniques, Exploit SARIN mode for freeboard measurement, test SARIN swath-altimetry over sea-ice.

Greenland Surface Elevation Validation and DEM/Retracker Accuracy Assessment from in-situ GPS measurments

Thomas B. Overly1, Robert L. Hawley1, Eric Lutz1, Erich C. Osterberg1, Veit Helm2, Sebastion B. Simonsen3, Zoe Courville4, Gifford J Wong1

1Dartmouth College, Hanover, NH, United States of America; 2Glaciology Section, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany; 32DTU Space, National Space Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark; 4Cold Regions Research and Engineering Laboratory, US Army Corps of Engineers, Hanover, NH, USA

Observation of variations in surface elevation of the continental ice sheets improves understanding of the short-term response of the cryosphere to climate change. CryoSat-2's synthetic aperture interferometric radar altimeter (SIRAL) seeks to observe ice sheet surface elevation within a few centimeters accuracy. CryoSat-2 elevation products must be validated against independent ground based observations. Kinematic GPS collected during the 2011 Greenland Inland Traverse (GrIT) from Thule to Summit Station provides surface elevation measurements across 1120km of the Greenland Ice Sheet. We compare GrIT GPS elevations to published and custom Digital Elevation Models (DEMs) generated from CryoSat-2 Level 1B and Level 2 products (Baseline C). The ground-based GPS measurements validate regional surface-height changes observed by CryoSat-2. We examine L1B elevation accuracy using three re-tracker algorithms: a threshold first maximum re-tracker (TFMRA), a midpoint threshold re-tracker (a variation of NASA's Goddard Space Flight Center re-tracker), and an offset center of gravity re-tracker (OCOG). Results of the re-tracker assessment indicate optimal methods for surface re-tracking and DEM generation, reducing uncertainty of Surface Elevation Change estimates.

An Assessment of Arctic Radiative Feedbacks in Coupled Ocean-Atmosphere Models

Brian Soden, Eui-Seok Chung

University of Miami, United States of America

Climate models project that in response to increases in anthropogenic greenhouse gases Arctic surface air temperatures increase 2-3 times faster than the global average. Although the amplified warming of the Arctic region has been attributed in large part to the lapse rate and surface albedo feedbacks, the radiative feedback processes have been less comprehensively analyzed from the surface perspective. To enhance understanding of the contribution of radiative feedback processes to Arctic warming amplification, we apply a radiative kernel method to coupled model simulations forced by an abrupt increase in atmospheric CO2 to determine the strength of radiative feedbacks at the surface as well as at the top of the atmosphere (TOA). Consistent with previous studies, our analysis indicates that from the TOA perspective the lapse rate and surface albedo feedbacks play a more important role in Arctic warming amplification than the water vapor and cloud feedbacks. When quantified at the surface, however, the lapse rate feedback is shown to oppose the surface warming because the temperatures in the troposphere increase less than the surface air temperature over the Arctic region. In addition, the surface-based cloud feedback is found to exhibit a positive contribution to the surface warming relative to the TOA perspective, whereas the opposite is noted for the water vapor feedback.

CryoTop Evolution - CryoSat-2 Swath Elevation, Digital Elevation Models, Rates of Elevation Change Products

Noel Gourmelen1, Maria Jose Escorihuela2, Anna Hogg3, Jan Wuite4, Flora Weissgerber1, Monica Roca2, Thomas Nagler4

1University of Edinburgh, United Kingdom; 2isardSAT, Spain; 3Center for Polar Observation and Modeling, University of Leeds, UK; 4ENVEO, Austria

Reference and repeat-observations of ice sheet margin topography is critical to identify changes in ice thickness, provide estimates of mass gain or loss and thus quantify the contribution of the cryosphere to sea level change. The ESA Altimetry mission CryoSat-2 aims at gaining better insight into the evolution of the cryosphere, in particular over the steep slopes typically found along ice sheet margins where the majority of the mass loss is taking place. CryoSat’s revolutionary design features a Synthetic Interferometric Radar Altimeter (SIRAL), with two antennas for interferometry, the corresponding SAR Interferometer (SARIn) mode of operation increases spatial resolution while resolving the angular origin of off-nadir echoes occurring over sloping terrain. The SARIn mode is activated over ice sheet margins and the elevation for the Point Of Closest Approach (POCA), or level-2, is a standard product of the CryoSat-2 mission.

CryoSat-2 SARIn mode allows a new approach for more comprehensively exploiting the CryoSat-2 record and produce ice elevation and elevation change with enhanced spatial resolution compared to standard CryoSat-2 level-2 products. In this so-called CryoSat-2 Swath SARIn (CSSARIn) approach, the entire waveform is analysed providing elevation beyond the POCA, leading to between 1 and 2 orders of magnitude more elevation measurements than conventional level-2 product. As part of the European Space Agency project CryoTop Evolution we are generating CSSARIn elevation, Digital Elevation Models and maps of rates of surface elevation change over the Greenland and Antarctic Ice Sheets. These products will be generated and distributed to the community. Here we will present the methods and quality assessment of the products as well as showcase examples of the added value of the products.

Multi-Sensor Radar Measurements of Snow on Sea Ice near Eureka, Nunavut, Canada

Joshua King1, Paul Donchenko2, Justin Beckers3, Stephen Howell1, Christian Haas4, Richard Kelly2

1Environment and Climate Change Canada, Canada; 2University of Waterloo, Canada; 3University of Alberta, Canada; 4York University, Canada

The influence of heterogeneous snow properties on wideband radar is evaluated for data collected over first year sea ice (FYI) near Eureka, Nunavut, Canada (79°59’20”N, 85°56’27”W) on March 25th, 2014. As part a collaborative CryoVex and Operation IceBridge (OIB) mission, the Airborne Synthetic Aperture and Interferometric Radar Altimeter System (ASIRAS; 12.5-14.5 GHz), the Center for Remote Sensing of Ice Sheets (CReSIS) Ku-Band Radar Altimeter (13-17 GHz), and CReSIS Snow Radar (2-8 GHz) were flown over a 60 km FYI transect within Eureka Sound, coincident with an Environment and Climate Change Canada (ECCC) field campaign. In situ snow and ice measurements within the footprints of the CryoVex and OIB radars were completed over a 6-day period immediately following the overflights. Distributed measurements of snow depth, snow density, and snow salinity were collected along the flight lines with 95% falling within the OIB and CryoVex radar footprints. In addition to the along-track sampling, three intensive measurement grids (250 m x 500 m) were completed to evaluate spatial variability in the radar across-track dimension and at finer spatial scales relative to potential radar products. An extended sampling protocol at these sites included multiple snow pits to characterize local-scale variations in snow stratigraphy and grain size. Strong spatial and temporal coincidence amongst the CryoVex, OIB, and ECCC datasets provides a unique opportunity to evaluate the multi-sensor radar response of snow on land fast FYI with direct applicability to altimetry-based snow and sea ice property retrievals. Synergistic retrieval potential is discussed along with a set of recommendations for future campaign design.

Retrieving Surface Soil Moisture from Cryosat2 Data in Arid and Semi-Arid Terrain

Philippa A. M. Berry1, Robert Balmbra2

1Roch Remote Sensing; 2Cyber Security Centre Warwick University

Measuring soil surface moisture using satellite radar altimeter backscatter is a comparatively new application. The basis of the technique is to construct very detailed DRy EArth ModelS (DREAMS) [1], using multi-mission recalculated and cross-calibrated altimeter backscatter fused with ground truth, with repeat arc analysis used to identify and mask out remaining areas of model instability [2]. For the current generation of DREAMS, there is a requirement that the surface be dry for at least one month of the year, so this technique was tested over desert and semi-arid terrain.

For the Cryosat2 mission, both the technique and the DREAMS had to be re-engineered to compensate for the mission long repeat period. This severely curtailed repeat arc analysis and required the DREAMS to be consistent and accurate over the entire model, due to the dense track sampling. To meet this standard, the models were completely re-engineered, incorporating detailed ground truth and enhanced modelling techniques. DREAMS were initially crafted for three desert regions to test the derivation of soil moisture. The Simpson desert was chosen despite the complex dune structure because detailed campaign data were available from collaborative research with the BNR (now QLCCC). The Tenere desert was selected as a small annual signal had been observed in soil moisture data derived from ERS2. The Kalahari desert was included because this is a region where significant moisture is present for several months each year so this offered the greatest likelihood for signal detection.

After initial work as part of the EU LOTUS project[ [3], several years of Cryosat2 data were processed and analysed. Over the Kalahari, Cryosat2 soil moisture estimates have now been successfully validated with other remote sensed soil moisture estimates [4] and sample results are presented here.

New DREAMS have now been created for the Gibson and Victoria deserts in Australia, and the whole of the Arabian desert. Each new area is tested with Cryosat2 data, which provides a stringent test of the remodelled DREAMS. Results are extremely promising, and it is concluded that all arid and semi-arid regions modelled with this enhanced technique will allow soil moisture estimates to be derived from Sentinel3.

1 Berry, P.A.M., Carter, J.O., 2011. Altimeter derived Soil Moisture Determination – Global Scope and Validation. IAHS ‘red book’ for IUGG 2011.

2 Berry, P.A.M., Dowson, M., Smith, R.G., Benveniste, J., 2012. Soil Moisture From Satellite Radar Altimetry (SMALT). Proceedings of the ESA Living Planet Symposium 2012.

3 Berry, P.A.M. & Balmbra, R., 2016. Soil Surface Moisture from Cryosat2 and Sentinel-3 Satellite Radar Altimetry. Proc. ‘Living Planet Symposium 2016’, Prague, Czech Republic, 9–13 May 2016 (ESA SP-740, August 2016).

4 Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals. Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321

Analysis of CryoSat-2 SAR data over ice sheets and algorithm development in preparation for Sentinel-3

Malcolm McMillan1, Roger Escola2, Monica Roca2, Maria Jose Escorihuela2, Pierre Thibaut3, Andrew Shepherd1, Frederique Remy4, Jerome Benveniste5, Americo Ambrozio5, Marco Restano5

1University of Leeds, United Kingdom; 2isardSAT Ltd, United Kingdom; 3CLS, France; 4LEGOS, France; 5ESA, Italy

In late 2014, CryoSat-2 was switched from LRM to SAR mode over 3 Antarctic study sites to provide an exploratory SAR dataset in advance of the Sentinel-3 launch in 2016. Here we present analysis of these SAR acquisitions and describe ongoing work to use these CryoSat-2 data to improve SAR altimetry processing methods for ice sheets. This work has been undertaken as part of the SPICE (Sentinel-3 Performance Improvement for Ice Sheets) study, funded by ESA’s SEOM (Scientific Exploitation of Operational Missions) programme.

More specifically, we will (1) compare the CryoSat-2 SAR elevation measurements to LRM observations acquired during the subsequent orbit cycle, (2) evaluate SAR elevation retrievals using different retrackers, and (3) develop pseudo-LRM measurements from the SAR FBR data, to investigate the ability to generate a low resolution product from a closed burst SAR system. For all processing scenarios, we will evaluate the ice sheet elevation measurement using reference airborne and satellite datasets. Finally, we will describe future SPICE activities, which will focus on algorithm developments to existing Delay-Doppler processing schemes, implementation of new SAR retrackers designed for ice sheets, and comparison to AltiKa Ka-band altimetry to study radar wave penetration into the snowpack.

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