Stochastic convective parameterization improving the simulation of tropical precipitation variability

TitleStochastic convective parameterization improving the simulation of tropical precipitation variability
Publication TypeJournal Article
Year of Publication2016
AuthorsWang Y., Zhang GJ, Craig G.C
JournalGeophysical Research Letters
Volume43
Pagination6612-6619
Date Published2016/06
Type of ArticleArticle
ISBN Number0094-8276
Accession NumberWOS:000380910100084
Keywordsclimate; community atmosphere model; energy; ensemble; equilibrium statistics; fluctuations; impact; part i; scheme; shallow convection; simulations
Abstract

The Plant-Craig (PC) stochastic convective parameterization scheme is implemented into the National Center for Atmospheric Research Community Atmosphere Model version 5 (CAM5) to couple with the Zhang-McFarlane deterministic convection scheme. To evaluate its impact on tropical precipitation simulation, two experiments are conducted: one with the standard CAM5 and the other with the stochastic scheme incorporated. Results show that the PC stochastic parameterization decreases the frequency of weak precipitation and increases the frequency of strong precipitation, resulting in better agreement with observations. The most striking improvement is in the probability distribution function (PDF) of precipitation intensity, with the well-known too-much-drizzle problem in CAM5 largely eliminated. In the global tropical belt, the precipitation intensity PDF from the simulation agrees remarkably well with that of Tropical Rainfall Measuring Mission observations. The stochastic scheme also yields a similar magnitude of intraseasonal variability of precipitation to observations and improves the simulation of the eastward propagating intraseasonal signals of precipitation and zonal wind.

DOI10.1002/2016gl069818
Student Publication: 
No