A Multialgorithm Reanalysis-Based Freezing-Precipitation Dataset for Climate Studies in the South-Central United States

Abstract

reezing precipitation, including freezing rain, freezing drizzle, and ice pellets, presents substantial hazards to transportation, energy, and infrastructure. Most quantitative climate-length (>30 years) datasets for freezing precipitation are obtained from in situ instrumentation, such as National Weather Service (NWS) automated observing systems or the NWS Cooperative Observer Program, that can be spatially and temporally inhomogeneous. This work investigates whether the 32-km North American Regional Reanalysis (NARR) is a viable dataset for developing a comprehensive and high-resolution spatially gridded dataset for freezing precipitation and its associated meteorological environment, with a focus on the south-central United States. NARR includes categorical precipitation type as a variable; to permit a translatable method across other gridded multidimensional reanalyses, however, a multialgorithm approach is also used to extract environmental conditions, event counts, and liquid water equivalent (LWE) for freezing precipitation, defined as total accumulated freezing rain and ice pellets. The resulting datasets are evaluated spatially and temporally against hourly and daily event counts and LWE compiled from 13 first-order NWS stations, the National Centers for Environmental Information Storm Data product, and ?meteorological phenomena identification near the ground? (mPING) observations. Very good statistical agreement is evident for many of the station sites, and NARR is able, in most cases, to reproduce years with heavy-ice events and the spatial extent of such events. Climatological freezing precipitation tends to be underestimated in the western subdomain and overestimated in the south. It is concluded that the derived datasets could be a useful tool for climatological research and hazard analysis, with some caveats.