TY - JOUR
T1 - Observing system simulation of snow microwave emissions over data sparse regions part I
T2 - Single layer physics
AU - Kang, Do Hyuk
AU - Barros, Ana P.
N1 - Funding Information:
Manuscript received November 30, 2010; revised May 28, 2011 and August 19, 2011; accepted September 11, 2011. Date of publication November 3, 2011; date of current version April 18, 2012. This work was supported in part by the National Aeronautics and Space Administration (NASA) under an Earth System Science Fellowship with the first author, and NASA under Grant NNX07AK40G and the National Oceanic and Atmospheric Administration under Grant NA080AR4310701 with the second author.
Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012/5
Y1 - 2012/5
N2 - The objective of this work is to develop a framework for monitoring snow water equivalent (SWE) and snowpack radiometric properties (e.g., surface emissivity and reflectivity) and microwave emissions in remote regions where ancillary data and ground-based observations for model calibration and/or data assimilation are lacking. For this purpose, an existing land surface hydrology model (LSHM) with single-layer (SL) snow physics was coupled to a microwave emission model (MEMLS). The coupled model (MLSHM-SL) predicts microwave emissions at various frequencies and polarizations as well as snowpack radiometric properties (e.g., emissivity) based on snowpack density, temperature, snow depth, and volumetric liquid water content simulated by the hydrology model with atmospheric forcing obtained from either observations, or the analysis of weather forecasts. The MLSHM-SL was evaluated in prognostic observing system simulation (OSS) mode for two case-studies: 1) a multi-year simulation of snowpack radio-brightness behavior at Valdai, Russia compared against Scanning Multichannel Microwave Radiometer (SMMR) observations at three frequencies (18, 21, and 37 GHz, V, and H polarizations) over six years, 1978-1983; and 2) an intercomparison of simulated and observed brightness temperatures for the Special Sensor Microwave/Imager (SSM/I) and the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) during the 2002-2003 snow season as part of the Cold Land Processes Field Experiment (CLPX) in Colorado. In the case of Valdai, the model captures well the mass balance as well as radiometric behavior of the snowpack during both accumulation and melt, with significantly best skill for vertical polarization (10-16 K differences in error statistics as compared to horizontal polarization), particularly in the winter season January-March (dry snow conditions). Larger biases were detected for intermittent snowpack conditions at the beginning of the fall season due to uncertainty in fractional snow cover and snow wetness at the spatial scale of the SMMR. Similar results were obtained for the OSS of SSM/I and AMSR-E for CLPX, though differences between vertical and horizontal polarization error statistics are more modest (∼ 2-4 K). Error statistics are lower for AMSR-E V-pol at 19 and 37 GHz. MLSHM-SL predicted snowpack physical properties (bulk snow density and SWE) compare well against CLPX snowpit observations during the accumulation season with residuals smaller than 10% of observed values. Moreover, the MLSHM-SL simulations in full prognostic mode, and without calibration from the beginning through the end of the snow season, are as skillful as MEMLS with specified physical attributes from snow pit observations. This indicates that the MSLSHM-SL can be used independently as a physically based estimator of SWE in remote regions, and in a data-assimilation framework to provide a physical basis to the interpretation of satellite-based observations of snow.
AB - The objective of this work is to develop a framework for monitoring snow water equivalent (SWE) and snowpack radiometric properties (e.g., surface emissivity and reflectivity) and microwave emissions in remote regions where ancillary data and ground-based observations for model calibration and/or data assimilation are lacking. For this purpose, an existing land surface hydrology model (LSHM) with single-layer (SL) snow physics was coupled to a microwave emission model (MEMLS). The coupled model (MLSHM-SL) predicts microwave emissions at various frequencies and polarizations as well as snowpack radiometric properties (e.g., emissivity) based on snowpack density, temperature, snow depth, and volumetric liquid water content simulated by the hydrology model with atmospheric forcing obtained from either observations, or the analysis of weather forecasts. The MLSHM-SL was evaluated in prognostic observing system simulation (OSS) mode for two case-studies: 1) a multi-year simulation of snowpack radio-brightness behavior at Valdai, Russia compared against Scanning Multichannel Microwave Radiometer (SMMR) observations at three frequencies (18, 21, and 37 GHz, V, and H polarizations) over six years, 1978-1983; and 2) an intercomparison of simulated and observed brightness temperatures for the Special Sensor Microwave/Imager (SSM/I) and the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) during the 2002-2003 snow season as part of the Cold Land Processes Field Experiment (CLPX) in Colorado. In the case of Valdai, the model captures well the mass balance as well as radiometric behavior of the snowpack during both accumulation and melt, with significantly best skill for vertical polarization (10-16 K differences in error statistics as compared to horizontal polarization), particularly in the winter season January-March (dry snow conditions). Larger biases were detected for intermittent snowpack conditions at the beginning of the fall season due to uncertainty in fractional snow cover and snow wetness at the spatial scale of the SMMR. Similar results were obtained for the OSS of SSM/I and AMSR-E for CLPX, though differences between vertical and horizontal polarization error statistics are more modest (∼ 2-4 K). Error statistics are lower for AMSR-E V-pol at 19 and 37 GHz. MLSHM-SL predicted snowpack physical properties (bulk snow density and SWE) compare well against CLPX snowpit observations during the accumulation season with residuals smaller than 10% of observed values. Moreover, the MLSHM-SL simulations in full prognostic mode, and without calibration from the beginning through the end of the snow season, are as skillful as MEMLS with specified physical attributes from snow pit observations. This indicates that the MSLSHM-SL can be used independently as a physically based estimator of SWE in remote regions, and in a data-assimilation framework to provide a physical basis to the interpretation of satellite-based observations of snow.
KW - Electromagnetic propagation in absorbing media
KW - nonhomogeneous media
KW - single-layer
KW - snow hydrology
UR - http://www.scopus.com/inward/record.url?scp=84860335569&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84860335569&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2011.2169073
DO - 10.1109/TGRS.2011.2169073
M3 - Article
AN - SCOPUS:84860335569
SN - 0196-2892
VL - 50
SP - 1785
EP - 1805
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 5 PART 2
M1 - 6069584
ER -