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CoReH2O Radar Mission for Snow and Ice Observations

This study presents the preparations for a radar mission, called CoReH2O, for snow and ice observations. The mission aims to study various aspects such as lake and river ice, glaciers, sea ice, and snow. The study includes the development of retrieval algorithms, SAR image simulation, performance analysis, and field campaigns. The findings will be used to develop a high-resolution observatory for cold regions hydrology.

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CoReH2O Radar Mission for Snow and Ice Observations

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  1. CoReH2O – Preparations for a Radar Mission for Snow and Ice Observations H. Rott1, D. Cline2, C. Duguay3, R. Essery4, P. Etchevers5, I. Hajnsek6, M. Kern7, G. Macelloni8, E. Malnes9, J. Pulliainen10, S. Yueh11 1 University of Innsbruck & ENVEO IT, Austria 2 NOAA, NWS, Hydrology Laboratory, USA 3 University of Waterloo, Canada 4 University of Edinburgh, UK 5 Meteo-France, Saint Martin d’Héres, France 6 DLR-HR, Germany & ETH Zürich, Switzerland 7 ESA-ESTEC, Noordwijk, NL 8 IFAC-CNR, Firenze, Italy 9 NORUT IT, Tromsǿ, Norway 10 Finish Meteorological Institute, Helsinki, Finland 11 JPL-Caltech, Pasadena, USA

  2. Background Information • CoReH2O  Cold Regions Hydrology –High Resolution Observatory • Submitted to ESA in response to the 2005 Call for Earth Explorer Core Missions (EE-7) • Selected as one of 6 missions for Pre-Phase A studies • In 2009 selected as one of 3 missions for detailed scientific and technical studies, Phase A • Scientific studies included retrieval algorithm development, SAR image simulator, performance analysis, field campaigns, synergy with other satellites, etc. • 2 parallel contracts on sensor & satellite development • March 2013: Down-selection to one EE7 mission > Biomass

  3. Scientific Observation Requirements Lake and river ice Glaciers Sea ice Snow Diagenetic facies types, glacial lakes Ice area; freeze up and melt onset Snow on ice (SWE, melt onset and area); type and thickness of thin ice Melting snow area, snow depth Secondary parameters

  4. Signal as Basis for SWE Retrieval SnowScat° (dB) at Ku-band (16.7 GHz) and X-band (10.2 GHz),  = 40° winter 2010/11, vs. SWE in snow pits, Sodankylä, Finland (NoSREx-2).

  5. CoReH2O SAR Sensor Requirements Thales-Alenia 2 Mission concepts ScanSAR EADS-Astrium

  6. Iterative SWE Retrieval – Constrained Minimization Forward model - Measurement Cost Function Regularization F(.) backscatter forward model (radiative transfer, RT) X 2 free model parameters (SWE, eff. grain radius RE) iith CoReH2O Band (for i=1,..4: Xvv, vh; Ku vv, vh) j index for free model parameters: SWE vari variance of measured s° backscatter value in CoReH2O band i c1,..,cr RT model configuration parameters (Ts, s, as) Regularization parameters are needed to constrain the inversion: a-priori RE, SWE Forward model used for iteration:

  7. Performance Analysis SWE Retrieval – Simulated Data Retrievals with improved algorithm 50 m grid size; speckle filter 7 x 7 Snow on open land RMSD between retrieved and true SWE Red grid: observ requirement SWE in open forest 20% fractional cover Based on backscatter simulations with Synthetic Scene Generator (SSG) Unbiased regularization

  8. Performance Analysis SWE Retrieval – Simulated Data Impact of bias in regularization parameters  Snow on open land. 15% bias for regularization parameter RE (effective grain radius) 50% bias for regularization parameter SWE

  9. Field Experiments withAirborne Sensor SnowSAR Field campaigns Sodankylä March 2011, winter 2011/12 AlpSAR 2013 – Austrian Alps AlpSAR Leutasch 23-02-2013 SnowSAR Characteristics Frequencies 9.6 GHz, 17.25 GHz Polarization Polarimetric Modulation FMCW Bandwidth 150 MHz Look angle  35° to 45°

  10. SWE Map from Airborne Backscatter Data Performance: SWEobs– SWEret = -5 mm Stand. error : 11 mm A-priori estimates for retrieval input by CoSDAS snow model driven by HIRLAM forecast data SWE map, derived from SnowSAR data, Sodankylä, 15/03/2011

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