Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

Satellite‐passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resol...

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Bibliographic Details
Published inWater resources research Vol. 48; no. 12
Main Authors Langlois, A., Royer, A., Derksen, C., Montpetit, B., Dupont, F., Goïta, K.
Format Journal Article
LanguageEnglish
Published Washington Blackwell Publishing Ltd 01.12.2012
John Wiley & Sons, Inc
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Summary:Satellite‐passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two‐step iteration method compared to standalone simulations with the snow model. Key Points Improved SWE retrieval Method independent from field measurements Quantification of snow grain uncertainties in microwave models
Bibliography:ArticleID:2012WR012133
ark:/67375/WNG-CH6JW5MV-T
istex:308D9C7993EA80969D8E4FCDCDA765DF47931521
Tab-delimited Table 1.Tab-delimited Table 2.Tab-delimited Table 3.Tab-delimited Table 4.Tab-delimited Table 5.
ISSN:0043-1397
1944-7973
DOI:10.1029/2012WR012133