Multi-Scale Observational Analysis and Modeling to Improve GCM Simulation of Global Shallow Cloud Processes and Feedbacks

Principal Investigator(s):
Ann Fridlind, NASA - Goddard Space Flight Center

Co-Investigator(s):
Andrew Ackerman, NASA GSFC
George Tselioudis, NASA GSFC
Daniel Knopf, Stony Brook University
Pavlos Kollias, Stony Brook University / Brookhaven National Laboratory

We propose a multi-scale analysis of Atmospheric Radiation Measurement (ARM) Program long-term data sets that will be targeted to improve the simulation of warm and mixed-phase shallow clouds in general circulation models (GCMs). Integrated multi-scale analysis of observations and simulations (described below) will guide improvements to parameterization of stratiform and convective dynamical schemes and microphysics (drizzle, rain, and ice properties and processes). Shallow cloud processes determine to a large extent the cloud water content, and thus the radiative properties of boundary layer and mixed-phase clouds, and have been implicated as primary processes in determining both the sign and magnitude of global cloud radiative feedbacks. The climate model to be used as a testbed is ModelE from NASA GISS, but the techniques and procedures used to improve representation of cloud processes are applicable to any GCM. In addition, the two-moment microphysics scheme with prognostic precipitation to be used in ModelE is an adaptation of that used in other GCMs, and improvements in its representation of microphysical processes would therefore be readily adaptable to related DOE models, for instance.

Each continuous data set to be mined for shallow cloud statistics (including Arctic, Oklahoma and Azores sites) will be first subject to multi-scale analysis that yields a time series of globally defined cloud regimes and their associated radiative fluxes. Site-wise regime statistics will be then compared with collocated extractions from current climate ModelE simulations, and with statistics at the global scale from observations and ModelE simulations. The foregoing analysis will allow identification of shallow cloud regime deficiencies and their associated radiative impacts at the global scale, paired with means of establishing their occurrence in the continuous data sets examined and identifying any number of cases for more detailed study using large-eddy simulation and ModelE's single-column model. For case studies selected, ARM measurements and retrievals of cloud, aerosol, and atmospheric properties will be used to constrain large-eddy and single-column simulations, which will in turn guide improvements in ModelE parameterizations.

Overall, this coordinated application of analysis across microphysical-to-global scales allows selection of case studies for detailed analysis that represent shallow cloud regimes with errors that matter most to GCM radiative fluxes. Thus, effort is aimed where it may have a significant impact at the global scale rather than at any particular fixed site. We expect similar effects across disparate global regions with similar shallow cloud processes. For instance, improvement of GCM phase partitioning based on Arctic site data is expected to improve representation of mixed-phase clouds over the Southern Ocean, as will be tested by this project using the global-scale observation and ModelE statistics.