Testing snow water equivalent retrieval algorithms for passive microwave remote sensing in an alpine watershed of western Canada

2010 ◽  
Vol 36 (sup1) ◽  
pp. S74-S86 ◽  
Author(s):  
Jinjun Tong ◽  
Stephen J Déry ◽  
Peter L Jackson ◽  
Chris Derksen
Keyword(s):  
Remote Sensing ◽  
Snow Water Equivalent ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Western Canada ◽  
Passive Microwave Remote Sensing ◽  
Retrieval Algorithms ◽  
Snow Water ◽  
Alpine Watershed

scholarly journals Evaluation of long term Northern Hemisphere snow water equivalent products

2019 ◽  
Author(s):  
Colleen Mortimer ◽  
Lawrence Mudryk ◽  
Chris Derksen ◽  
Kari Luojus ◽  
Ross Brown ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
European Space Agency ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Temporal Correlations ◽  
Surface Snow ◽  
Snow Water ◽  
Surface Observations

Abstract. Seven gridded northern hemisphere snow water equivalent (SWE) products were evaluated as part of the European Space Agency (ESA) Satellite Snow Product Inter-comparison and Evaluation Exercise (SnowPEx). Three categories of datasets were assessed: (1) those utilizing some form of reanalysis (the NASA Global Land Data Assimilation System version 2 – GLDAS; the European Centre for Medium-Range Forecasts interim land surface reanalysis – ERA-land; the NASA Modern-Era Retrospective Analysis for Research and Applications – MERRA; the Crocus snow model driven by ERA-Interim meteorology – Crocus); (2) passive microwave remote sensing combined with daily surface snow depth observations (ESA GlobSnow v2.0); and (3) standalone passive microwave retrievals (NASA AMSR-E historical and operational algorithms) which do not utilize surface snow observations. Evaluation included comparisons against independent surface observations from Russia, Finland, and Canada, and calculation of spatial and temporal correlations in SWE anomalies. The standalone passive microwave SWE products (AMSR-E historical and operational SWE algorithms) exhibit low spatial and temporal correlations to other products, and RMSE nearly double the best performing product. Constraining passive microwave retrievals with surface observations (GlobSnow) provides comparable performance to the reanalysis-based products; RMSEs over Finland and Russia for all but the AMSR-E products is ~50 mm or less. Using a four-dataset ensemble that excluded the standalone passive microwave products reduced the RMSE by 10 mm (20%) and increased the correlation by 0.1; ensembles that contain Crocus and/or MERRA perform better than those that do not. The observed RMSE of the best performing datasets is still at the margins of acceptable uncertainty for scientific and operational requirements; only through combined and integrated improvements in remote sensing, modeling, and observations will real progress in SWE product development be achieved.

scholarly journals Discrimination of a wet snow cover using passive microwave satellite data

1993 ◽  
Vol 17 ◽  
pp. 307-311 ◽  
Author(s):  
A.E. Walker ◽  
B.E. Goodison
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Western Canada ◽  
Polarization Data ◽  
Wet Snow ◽  
Snow Water ◽  
Remote Sensing Methods

Snow-cover monitoring using passive microwave remote sensing methods has been shown to be seriously limited under melt conditions when the snowpack becomes wet. A wet snow indicator has been developed using DMSP SSM/I 37 GHz dual-polarization data for the open prairie region of western Canada. The indicator is used to identify areas of wet snow and discriminate them from areas of snow-free land. Validation and testing efforts have illustrated that the addition of the indicator to the current SSM/I snow water equivalent algorithm provides a more accurate representation of spatial snow coverage throughout the winter season for the open prairie region. The improved spatial and temporal information resulting from the use of the indicator enhances both climatological and hydrological analyses of snow-cover conditions using passive microwave data. Although the wet snow indicator has only been validated for the open prairie region of western Canada, it may also be applicable to other regions of similar terrain and vegetative characteristics. However, in areas of dense vegetation, such as the boreal forest, the performance of the indicator is poor due to the generally low 37 GHz polarization differences of the vegetation cover.

scholarly journals Discrimination of a wet snow cover using passive microwave satellite data

1993 ◽  
Vol 17 ◽  
pp. 307-311 ◽  
Author(s):  
A.E. Walker ◽  
B.E. Goodison
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Western Canada ◽  
Polarization Data ◽  
Wet Snow ◽  
Snow Water ◽  
Remote Sensing Methods

Snow-cover monitoring using passive microwave remote sensing methods has been shown to be seriously limited under melt conditions when the snowpack becomes wet. A wet snow indicator has been developed using DMSP SSM/I 37 GHz dual-polarization data for the open prairie region of western Canada. The indicator is used to identify areas of wet snow and discriminate them from areas of snow-free land. Validation and testing efforts have illustrated that the addition of the indicator to the current SSM/I snow water equivalent algorithm provides a more accurate representation of spatial snow coverage throughout the winter season for the open prairie region. The improved spatial and temporal information resulting from the use of the indicator enhances both climatological and hydrological analyses of snow-cover conditions using passive microwave data. Although the wet snow indicator has only been validated for the open prairie region of western Canada, it may also be applicable to other regions of similar terrain and vegetative characteristics. However, in areas of dense vegetation, such as the boreal forest, the performance of the indicator is poor due to the generally low 37 GHz polarization differences of the vegetation cover.

scholarly journals Evaluation of long-term Northern Hemisphere snow water equivalent products

2020 ◽  
Vol 14 (5) ◽  
pp. 1579-1594 ◽  
Author(s):  
Colleen Mortimer ◽  
Lawrence Mudryk ◽  
Chris Derksen ◽  
Kari Luojus ◽  
Ross Brown ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Northern Hemisphere ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
European Space Agency ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Temporal Correlations ◽  
Surface Snow ◽  
Snow Water

Abstract. Nine gridded Northern Hemisphere snow water equivalent (SWE) products were evaluated as part of the European Space Agency (ESA) Satellite Snow Product Intercomparison and Evaluation Exercise (SnowPEx). Three categories of datasets were assessed: (1) those utilizing some form of reanalysis (the NASA Global Land Data Assimilation System version 2 – GLDAS-2; the European Centre for Medium-Range Weather Forecasts (ECMWF) interim land surface reanalysis – ERA-Interim/Land and ERA5; the NASA Modern-Era Retrospective Analysis for Research and Applications version 1 (MERRA) and version 2 (MERRA-2); the Crocus snow model driven by ERA-Interim meteorology – Crocus); (2) passive microwave remote sensing combined with daily surface snow depth observations (ESA GlobSnow v2.0); and (3) stand-alone passive microwave retrievals (NASA AMSR-E SWE versions 1.0 and 2.0) which do not utilize surface snow observations. Evaluation included validation against independent snow course measurements from Russia, Finland, and Canada and product intercomparison through the calculation of spatial and temporal correlations in SWE anomalies. The stand-alone passive microwave SWE products (AMSR-E v1.0 and v2.0 SWE) exhibit low spatial and temporal correlations to other products and RMSE nearly double the best performing product. Constraining passive microwave retrievals with surface observations (GlobSnow) provides performance comparable to the reanalysis-based products; RMSE over Finland and Russia for all but the AMSR-E products is ∼50 mm or less, with the exception of ERA-Interim/Land over Russia. Using a seven-dataset ensemble that excluded the stand-alone passive microwave products reduced the RMSE by 10 mm (20 %) and increased the correlation from 0.67 to 0.78 compared to any individual product. The overall performance of the best multiproduct combinations is still at the margins of acceptable uncertainty for scientific and operational requirements; only through combined and integrated improvements in remote sensing, modeling, and observations will real progress in SWE product development be achieved.

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