Wiley, Quarterly Journal of the Royal Meteorological Society, 563(126), p. 761-776, 2000
Wiley, Quarterly Journal of the Royal Meteorological Society, 563(126), p. 761-776
DOI: 10.1256/smsqj.56317
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The definition of an approach for radiative-transfer modelling that would enable computation limes suitable for climate studies and a satisfactory accuracy, has proved to be a challenge for modellers. A fast radiative-transfer model is tested at ECMWF: NeuroFlux. It is based on an artificial neural-network technique used in conjunction with a classical cloud approximation (the multilayer grey-body model). The accuracy of (he method is assessed through code-by-code comparisons, climate simulations and ten-day forecasts with the ECMWF model. The accuracy of NeuroFlux appears to be comparable to the accuracy of the ECMWF operational scheme, with a negligible impact on the simulations, while its computing time is seven times faster.