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1. Introduction

The dramatic increase in computer power over the last decades has not fulfilled the ever-increasing needs of the climate and weather sciences. Improving the efficiency of numerical models is still topical. In their paper "New approach to calculation of atmospheric model physics: Accurate and fast neural network emulation of longwave radiation in a climate model," Krasnopolsky et al. (2005, hereafter KFC05) develop the idea that artificial neural networks could accelerate model physics components in an atmospheric general circulation model (AGCM). As a first step, they apply it to the computation of longwave (LW) cooling rates and fluxes, which usually represent the main ...

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