A new procedure to parameterize climate processes within climate models has been developed. It is described in a paper that is in press with the National Weather Digest entitled “A New Paradigm for Parameterizations in Numerical Weather Prediction and other Atmospheric Models” with authors Roger A. Pielke Sr., Toshihisa Matsui, Giovanni Leoncini, Timothy Nobis, Udaysankar S. Nair,Er Lu, Joe Eastman, Sujay Kumar, Christa Peters-Lidard, Yudong Tian and Robert L. Walko. The abstract states,
“The use of look-up-tables (LUTs) to represent parameterizations within numerical weather prediction and other atmospheric models is presented. We discuss several approaches as to how the use of LUTs can be optimized in order to retain the physical representation of the parameterization, yet be much more computationally efficient than the parent parameterization from which they are derived.”
As we elaborate on in our paper,
“….the LUT-approach, utilizes data access and retrieval procedures, and methods to reduce the dimensionality of the original parameterization to create this method of model improvement. A major advantage of the LUT-approach, for example, includes the ability to create more realizations in the creation of ensemble forecasts. ”
This approach is an alternate procedure to the so-called “superparameterizations”. With that approach, as we discuss in our paper,
“…… a cloud-resolving model (is embedded) within a larger-scale model in order to improve the accuracy of simulating cloud interactions with the larger-scale model. This has been called a âsuperparameterizationâ?. Superparameterization refers to using a 2-D or 3-D cloud-resolving model to simulate a process in place of a very simplified parameterization that has been commonly used in weather and climate models in order to keep the computational cost low. Superparameterization-embedded Multi-Modeling Frameworks (MMF) are recently under development at several institutions, and there are plans to create global cloud libraries, which includes detailed mass and energy output from cloud resolving models. With the LUT-based approach the superparameterization approach could be used much more efficiently since the simulations (e.g., the 3-D cloud model) are integrated offline and the results are archived in a database for future retrieval. ”
The LUT-approach will allow more computationally efficient climate model simulations than are possible using the currently applied parameterization procedure.