Open AccessThe Berry and Reinhardt Autoconversion Parameterization: A Digest
Author(s) -
Matthew S. Gilmore,
Jerry M. Straka
Publication year - 2008
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/2007jamc1573.1
Subject(s) - berry , parametrization (atmospheric modeling) , cloud computing , environmental science , bin , implementation , meteorology , computer science , mathematics , atmospheric sciences , statistical physics , geology , physics , algorithm , botany , quantum mechanics , biology , programming language , radiative transfer , operating system
The simplified version of the Berry and Reinhardt parameterization used for initiating rain from cloud droplets is presented and is compared with 12 other versions of itself from the literature. Many of the versions that appear to be different from each other can be brought into agreement with the original parameterization by making the same assumptions: a mean diameter based upon mass or volume and distribution shape parameters chosen to give the same cloud mass relative variance as the original Berry and Reinhardt parameterization. However, there are differences in how authors have chosen to parameterize the cloud number concentration sink and rain number concentration source, and those choices, along with model limitations, have important impacts on rain development within the scheme. These differences among versions are shown to have important time-integrated feedbacks upon the developing initial rain distribution. Three of 12 implementations of the bulk scheme are shown to be able to reproduce the original Berry and Reinhardt bin-model solutions very well, and about 6 of 12 do poorly.