Toward stochastic moist convective parameterization in general circulation models.

Johnny W.-B. Lin and J. David Neelin
Geophys. Res. Lett., 30(4), 2003.

Paper (PDF 510 KB). © Copyright 2003 by the American Geophysical Union.

Abstract. For the first time, a stochastic deep convective parameterization to represent variability arising from small-scale processes that are unresolved by traditional deterministic moist convective parameterizations is tested in a general circulation model. Two physical pathways of representing small-scale variability as a stochastic process are explored. First, the relationship between cloud-base mass flux M_b and large-scale convective available potential energy (CAPE) is posited to have a stochastic component (the CAPE-M_b scheme). Second, the vertical structure of heating is modified by a simple random process about the structure given by the traditional convective scheme (the VSH scheme). The CAPE-M_b scheme increases the overall variance of precipitation toward observations with a realistic spatial pattern. The VSH scheme has smaller impacts on precipitation variance but yields preferential enhancement at large spatial scales and low frequencies.

Citation. Lin, J. W.-B., and J. D. Neelin, 2003: Toward stochastic moist convective parameterization in general circulation models. Geophys. Res. Lett., 30(4), 1162, doi: 10.1029/2002GL016203, 2003.

Acknowledgments. This research was partially supported by a visiting fellowship from the Cooperative Institute for Research in Environmental Sciences at the University of Colorado, Boulder (JWL), National Science Foundation grants OPP-0129800 (JWL) and ATM-0082529 and National Oceanic Atmospheric Administration grant NA16GP2003. This is UCLA IGPP contribution number 5769. The NCAR Scientific Computing and Climate and Global Dynamics divisions provided the computing resources. The MSU precipitation data is from the NOAA-CIRES Climate Diagnostics Center, Boulder, Colorado (http://www.cdc.noaa.gov/) and the NCAR data archives.