Extended Abstract (1.2M)7.10
(Formerly 7.7) Evaluating new cloud-radiation and hydrologic cycle parameterizations
Sam F. Iacobellis, SIO/Univ. of California, La Jolla, CA; and R. C. J. Somerville
We report on recent intercomparisons and evaluations of new cloud-radiation and hydrologic cycle parameterizations for large-scale atmospheric models. This work addresses several distinct applications, including data assimilation, numerical weather prediction, and climate simulation. In all of these applications, physical process realism is critical. In the past, general circulation models (GCMs) have been seriously handicapped by deficiencies in the representations of key aspects of atmospheric physics, with cloud-radiation interactions being a paramount example. Recently, advances in theory, diagnostic process modeling, and surface- and space-based observations have pointed the way to substantial improvements in current GCM treatments of these processes. These advances have made it possible to take the next step and build on this progress to develop significantly improved parameterizations, incorporate them in state-of-the-art global atmospheric models, and diagnose and evaluate the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable.
The availability of new observational data from field programs has also yielded new insights into the relationships between cloud microphysics and cloud radiative effects. Tests in single-column mode, carried out in the maritime tropics, in polar regions, and in mid-latitudes, have shown that parameterizations based on these new results can significantly reduce typical model biases in cloud-modulated fields such as surface insolation. One fruitful strategy for evaluating advances in GCM parameterizations is to use short-range numerical weather prediction (NWP) as a testbed within which to implement and improve parameterizations for modeling and predicting climate variability. The work reported here consists of three distinct elements. One element involves the development of new parameterizations for improved treatment of cloud-radiation interactions. A second element concentrates on using a single-column model, which is a process-oriented or phenomenological model, for direct evaluation of the parameterizations against measurements. The third element involves testing the parameterizations in operational NWP models and in a range of GCMs.
Session 7, Development of In Situ, Satellite, and Model Data Focused on Hydrometeorological Processes in the Atmosphere and Land Surface (parallel with Session 6)
Tuesday, 11 January 2005, 1:30 PM-5:30 PM
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