Premium
Influence of a stochastic moist convective parameterization on tropical climate variability
Author(s) -
Lin Johnny WeiBing,
Neelin J. David
Publication year - 2000
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2000gl011964
Subject(s) - convection , convective available potential energy , autocorrelation , noise (video) , climatology , moment (physics) , stochastic modelling , atmospheric sciences , atmospheric convection , general circulation model , environmental science , statistical physics , meteorology , physics , climate change , geology , mathematics , statistics , computer science , classical mechanics , oceanography , artificial intelligence , image (mathematics)
Convective parameterizations used in general circulation models (GCMs) generally only simulate the mean or first‐order moment of convective ensembles and do not explicitly include higher‐order moments. The influence of including unresolved higher‐order moments is investigated using a simple stochastic convective parameterization that includes a random contribution to the convective available potential energy (CAPE) in the deep convective scheme. Impacts are tested in an tropical atmospheric model of intermediate complexity. Adding convective noise noticeably affects tropical intraseasonal variability, suggesting inclusion of such noise in GCMs might be beneficial. Model response to the noise is sensitive not only to the noise amplitude, but also to such particulars of the stochastic parameterization as autocorrelation time.