A New Paper From Model Based Parameterizations To Lookup Tables: An EOF Approach By Leoncini et al paper 2008

We have a new research paper that has been published. This paper applies a new methodology that we reported on in

Pielke Sr., R.A., T. Matsui, G. Leoncini, T. Nobis, U. Nair, E. Lu, J. Eastman, S. Kumar, C. Peters-Lidard, Y. Tian, and R. Walko, 2006: A new paradigm for parameterizations in numerical weather prediction and other atmospheric models. National Wea. Digest, 30, 93-99.

In that paper, we wrote

“Superparameterization embedded, Multi-Modeling Frameworks (MMF) are ….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 oflline, and the results are archived in a database for future retrieval.”

In our new paper, we demonstrate, using a radiation parameterization, that the LUT-based aproach is a computationally efficient method to replace existing parameterization approaches and as an effective alternative to the MMF approach.

Our new 2008 paper also further demonstrates that the answers provided on Real Climate by Gavin Schmidt with respect to parameterizations (see) do not adequately recognize that parameterizations in weather and climate models are engineering code. They are not basic physics.

Our paper is

 Leoncini, G., R.A. Pielke Sr., and P. Gabriel, 2008: From model based parameterizations to Lookup Tables: An EOF approach. Wea. Forecasting, 23, 1127.1145.

The abstract reads

“The goal of this study is to transform the Harrington radiation parameterization into a transfer scheme
or lookup table, which provides essentially the same output (heating rate profile and short- and longwave
fluxes at the surface) at a fraction of the computational cost. The methodology put forth here does not
introduce a new parameterization simply derived from the Harrington scheme but, rather, shows that given
a generic parameterization it is possible to build an algorithm, largely not based on the physics, that mimics
the outcome of the parent parameterization. The core concept is to compute the empiricalorthogonal
functions (EOFs) of all of the input variables of the parent scheme, run the scheme on the EOFs, and
express the output of a generic input sounding exploiting the input–output pairs associated with the EOFs.
The weights are based on the difference between the input and EOFs water vapor mixing ratios. A detailed
overview of the algorithm and the development of a few transfer schemes are also presented. Results show
very good agreement (r > 0.91) between the different transfer schemes and the Harrington radiation
parameterization with a very significant reduction in computational cost (at least 95%).”

The conclusion ends with

“While this study is limited to the Harrington radiation parameterization, it is reasonable to believe that the same methodology can be extended to a cloudy sky and applied to other parameterizations with similar results, as first envisioned in Pielke et al. (2006).”

 

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