A methodology to generate cloud attenution fields from NWP products

Abstract

A methodology to generate cloud attenuation fields from Numerical Weather Prediction (NWP) products is presented. Spatially correlated cloud fields are synthesized using a stochastic approach and the main model's parameters are extracted from a set of high-resolution cloud fields observed by the MODIS sensor onboard the Aqua satellite. The model is devised to receive as input the average fractional cloud cover and cloud liquid water content provided by a NWP dataset (e.g. ERA40 reanalysis database) with large integration area and coarse temporal resolution. Synthetic cloud fields are afterwards converted into attenuation fields according to recommendation ITU-R P.840–4. Preliminary tests on the validity of the proposed methodology indicate that both first-order (Complementary Cumulative Distribution Function — CCDF) and second-order (spatial distribution) statistics of cloud liquid water content are reproduced with good accuracy. The proposed methodology represents a key step towards the development of a comprehensive tool for the synthesis of correlated fields of the relevant atmospheric constituents at centimetric and millimetric wavelengths (rain, clouds, water vapor and oxygen) from NWP data.