Abstract

The Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was organized to promote the development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. GCSS uses models to anal... Show moreThe Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was organized to promote the development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. GCSS uses models to analyze and understand observations of the behavior of cloud systems. Cloud-system-resolving models (CSRMs) have sufficient spatial and temporal resolution to represent individual cloud elements, but cover a wide enough range of time and space scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the column physics components of atmospheric general circulation models (GCMs). SCMs are used to test cloud parameterizations in an uncoupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data are collected in various field programs and provided to the CSRM community, which first uses the data to ?certify? the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM community. Results of a rethinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data, are reported on herein. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, an explicit recognition of the importance of data integration, and an increasing use of observed cloud-scale statistics for model evaluations. Show less