A Design of Experiments Approach to Evaluating Parameterization Schemes for Numerical Weather Prediction: Problem Definition and Proposed Solution Approach
Jeffrey A. Smith
U.S. Army Research Laboratory
Richard S. Penc
U.S. Army Research Laboratory
Numerical Weather Prediction (NWP) is the science of forecasting weather or climatic conditions based on past and present observations using computational methods applied to mathematical representations of the atmosphere. Temporally, weather forecasts range from a few hours to a several days in the future, while climate forecasts range from several months to years (or decades) into the future. Spatially, forecasts can cover small scale, highly resolved "local" weather conditions to large scale global weather features and climates. The foundation of NWP is the conservation of mass, heat, momentum, and water vapor, along with other gaseous and aerosol materials over a region of interest called the domain. Statistical design of experiments, a technique applied successfully in other areas to large scale simulation models, shows promise in assisting in a structured exploration of these parameterized processes in NWP codes. In this article, we develop an extended problem definition; we present a method for developing a design matrix suitable for that problem; and, we illustrate how to apply that design to study the role parameterizations play in a relevant forecast metric of interest.