Probabilistic precipitation forecast skill as a function of ensemble size and spatial scale in a convection-allowing ensemble

Adam J. Clark, John S. Kain, David J. Stensrud, Ming Xue, Fanyou Kong, Michael C. Coniglio, Kevin W. Thomas, Yunheng Wang, Keith Brewster, Jidong Gao, Xuguang Wang, Steven J. Weiss, Jun Du

Research output: Contribution to journalArticlepeer-review

88 Scopus citations

Abstract

Probabilistic quantitative precipitation forecasts (PQPFs) from the storm-scale ensemble forecast system run by the Center for Analysis and Prediction of Storms during the spring of 2009 are evaluated using area under the relative operating characteristic curve (ROC area). ROC area, which measures discriminating ability, is examined for ensemble size n from 1 to 17 members and for spatial scales ranging from 4 to 200 km. Expectedly, incremental gains in skill decrease with increasing n. Significance tests comparing ROC areas for each n to those of the full 17-member ensemble revealed that more members are required to reach statistically indistinguishable PQPF skill relative to the full ensemble as forecast lead time increases and spatial scale decreases. These results appear to reflect the broadening of the forecast probability distribution function (PDF) of future atmospheric states associated with decreasing spatial scale and increasing forecast lead time. They also illustrate that efficient allocation of computing resources for convection-allowing ensembles requires careful consideration of spatial scale and forecast length desired.

Original languageEnglish (US)
Pages (from-to)1410-1418
Number of pages9
JournalMonthly Weather Review
Volume139
Issue number5
DOIs
StatePublished - May 2011

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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