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Modeling springtime shallow frontal clouds with cloud-resolving and single-column models

  • Kuan Man Xu
  • , Minghua H. Zhang
  • , Zachary A. Eitzen
  • , Steven J. Ghan
  • , Stephen A. Klein
  • , Xiaoqing Wu
  • , Shaocheng Xie
  • , Mark Branson
  • , Anthony D. Del Genio
  • , Sam F. Iacobellis
  • , Marat Khairoutdinov
  • , Wuyin Lin
  • , Ulrike Lohmann
  • , David A. Randall
  • , Richard C.J. Somerville
  • , Yogesh C. Sud
  • , Gregory K. Walker
  • , Audrey Wolf
  • , J. John Yio
  • , Junhua Zhang
  • NASA Langley Research Center
  • SAIC
  • Pacific Northwest National Laboratory
  • Princeton University
  • Lawrence Livermore National Laboratory
  • Iowa State University
  • Colorado State University
  • NASA Goddard Institute for Space Studies
  • University of California at San Diego
  • Stony Brook University
  • Dalhousie University
  • Swiss Federal Institute of Technology Zurich
  • NASA Goddard Space Flight Center

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

This modeling study compares the performance of eight single-column models (SCMs) and four cloud-resolving models (CRMs) in simulating shallow frontal cloud systems observed during a short period of the March 2000 Atmospheric Radiation Measurement (ARM) intensive operational period. Except for the passage of a cold front at the beginning of this period, frontal cloud systems are under the influence of an upper tropospheric ridge and are driven by a persistent frontogenesis over the Southern Great Plains and moisture transport from the northwestern part of the Gulf of Mexico. This study emphasizes quantitative comparisons among the model simulations and with the ARM data, focusing on a 27-hour period when only shallow frontal clouds were observed. All CRMs and SCMs simulate clouds in the observed shallow cloud layer. Most SCMs also produce clouds in the middle and upper troposphere, while none of the CRMs produce any clouds there. One possible cause for this is the decoupling between cloud condensate and cloud fraction in nearly all SCM parameterizations. Another possible cause is the weak upper tropospheric subsidence that has been averaged over both descending and ascending regions. Significantly different cloud amounts and cloud microphysical properties are found in the model simulations. All CRMs and most SCMs underestimate shallow clouds in the lowest 125 hPa near the surface, but most SCMs overestimate the cloud amount above this layer. These results are related to the detailed formulations of cloud microphysical processes and fractional cloud parameterizations in the SCMs, and possibly to the dynamical framework and two-dimensional configuration of the CRMs. Although two of the CRMs with anelastic dynamical frameworks simulate the shallow frontal clouds much better than the SCMs, the CRMs do not necessarily perform much better than the SCMs for the entire period when deep and shallow frontal clouds are present.

Original languageEnglish
Pages (from-to)1-26
Number of pages26
JournalJournal of Geophysical Research Atmospheres
Volume110
Issue number15
DOIs
StatePublished - Aug 16 2005

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