Comparative Analysis of Snowfall Accumulation and Gauge Undercatch Correction Factors from Diverse Data Sets: In Situ, Satellite, and Reanalysis
AffiliationUniv Arizona, Dept Hydrol & Atmospher Sci
Univ Arizona, Dept Geosci
MetadataShow full item record
PublisherKOREAN METEOROLOGICAL SOC
CitationPanahi, M., Behrangi, A. Comparative Analysis of Snowfall Accumulation and Gauge Undercatch Correction Factors from Diverse Data Sets: In Situ, Satellite, and Reanalysis. Asia-Pacific J Atmos Sci (2019). https://doi.org/10.1007/s13143-019-00161-6
Rights© Korean Meteorological Society and Springer Nature B.V. 2019
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AbstractDespite its importance for hydrology and water resources, accurate estimation of snowfall rate over snow-covered regions has remained a major observational challenge from both in-situ and remote sensing instruments. Snowfall accumulation can be measured by either accumulating snowfall estimates or measuring snowpack properties such as Snow Water Equivalent (SWE) and mass. By focusing on snowfall over snow accumulation period and using case studies and long-term average (2003 to 2015) over CONUS, this study compares snowfall accumulation from gauge stations (using GPCC and PRISM products), satellite products (GPCP and the suite of IMERG products), and reanalysis (ERA-interim, ERA5, and MERRA-2). Changes in SWE based on the recent UA-SWE product together with mass change observation from GRACE were used for assessment of precipitation products. We also investigated two popular gauge undercatch correction factors (CFs) used to mitigate precipitation undercatch in GPCC and GPCP. The results show that snow accumulation from most of the products is bounded by GPCC with and without correction, highlighting the critical importance of selecting proper CFs for gauge-undercatch correction. The CF based on Legates and Willmott method was found to be more consistent with the SWE-based analysis than CF based on the Fuchs method. Reanalysis show very similar spatial pattern among themselves, but represent large variation in simulating snow accumulation, with ERA-interim showing the least accumulation and MERRA-2 showing the highest accumulation and closest to the snow accumulation suggested by SWE.
Note12 month embargo; published online: 13 December 2019
VersionFinal accepted manuscript