Research

Despite the crucial role of snowpack in the water cycle for many places around the world, it has been usually neglected in the drought assessment. In this work, daily gridded snow water equivalent (SWE) from the UA-SWE in conjunction with precipitation (P) and temperature (T) from PRISM over CONUS, were explored to identify relationships and develop a snowpack scheme that has been implemented in the Leaky Bucket (LB) water balance model of the Climate Prediction Center (CPC/NCEP/NOAA). Through LB (LBS including snowpack treatment) the CPC post-processes P and T for drought monitoring (using observation-based data) and forecast (using NWP outputs). LBS shows a good agreement with SWE observations (UA-SWE and SNOTEL), even better than a complex Land Surface Model (Noah/NLDAS-2; Figs. 1a,b). Snowpack representation on LBS impacts the annual cycle of soil moisture. This led to an improved representation of the drought condition with respect to the original LB (objective, based on standardized anomalies of LBS/LB simulated soil moisture) when compared to the U.S. Drought Monitor (U.S.-DM; subjective, multi-variable analysis by experts), as in the example on Figs. 1c-e. The scheme is currently implemented operationally at CPC for global analysis, and it represents CPC’s contribution to the multi-agency U.S.-DM. Model results are available from the CPC’s website https://www.cpc.ncep.noaa.gov/products/Soilmst_Monitoring/index.shtml