Stochastic Variation of Parameterized Physical Processes in Idealized Forecast Ensembles: Stochastic Physics

Cornell Univ - State: Awds Made Prior May 2010, Ithaca NY

Investigators

Abstract

Recently, it has been shown that one major source of errors in numerical weather predictions is generated by using comparatively deterministic functions of resolvable variables to represent the unresolved sub-grid processes. One effort in improving ensemble predictions involves perturbing the physical parameterizations of the model. To tackle the problem, the PI will study the sub-grid scale signatures in various verification measures and use a combination of them to improve the ensemble forecasts. An idealized model with low-dimension configurations will be used for the study. The research focus will be on the interactions of the resolvable variables and unresolved processes with particular attention on the effects of different perturbation amplitudes, correlation scales for the random element of physical parameterizations, and possible signatures of these errors in appropriate diagnostics. The overall goal of the research is to provide knowledge on the structure of perturbations in physical parameterizations and to represent them properly in ensemble forecasts. The research study has the potential of generating useful information for operational weather prediction.