Evaluation of MRMS snowfall products over the Western United States

Yixin Wen, Pierre Kirstetter, J. J. Gourley, Yang Hong, Ali Behrangi, Zachary Flamig

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Snow is important to water resources and is of critical importance to society. Ground-weather-radar-based snowfall observations have been highly desirable for large-scale weather monitoring and water resources applications. This study conducts an evaluation of the Multi-Radar Multi-Sensor (MRMS) quantitative estimates of snow rate using the Snowpack Telemetry (SNOTEL) daily snow water equivalent (SWE) datasets. A detectability evaluation shows that MRMS is limited in detecting very light snow (daily snow accumulation < 5 mm) because of the quality control module in MRMS filtering out weak signals (< 5 dBZ). For daily snow accumulation greater than 10 mm, MRMS has good detectability. The quantitative comparisons reveal a bias of -77.37% between MRMS and SNOTEL. A majority of the underestimation bias occurs in relatively warm conditions with surface temperatures ranging from -10° to 0°C. A constant reflectivity-SWE intensity relationship does not capture the snow mass flux increase associated with denser snow particles at these relatively warm temperatures. There is no clear dependence of the bias on radar beam height. The findings in this study indicate that further improvement in radar snowfall products might occur by deriving appropriate reflectivity-SWE relationships considering the degree of riming and snowflake size.

Original languageEnglish (US)
Pages (from-to)1707-1713
Number of pages7
JournalJournal of Hydrometeorology
Volume18
Issue number6
DOIs
StatePublished - Jun 1 2017
Externally publishedYes

Keywords

  • Freezing precipitation
  • Precipitation
  • Radars/Radar observations
  • Remote sensing

ASJC Scopus subject areas

  • Atmospheric Science

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