ESTIMATING LONGWAVE NET-RADIATION AT SEA-SURFACE FROM THE SPECIAL SENSOR MICROWAVE IMAGER (SSM I)/

A neural network is used to calculate the longwave net radiation (L-ne t) at the sea surface from measurements of the Special Sensor Microwav e/Imager (SSM/I). The neural network applied in this study is able to account largely for the nonlinearity between L-net and the satellite-m easured brightness temperatures (TB). The algorithm can be applied for instantaneous measurements over oceanic regions with the area extent of satellite passive microwave observations (30-60 km in diameter). Co mparing with a linear regression method the neural network reduces the standard error for L-net from 17 to 5 W m(-2) when applied to model r esults. For clear-sky cases, a good agreement with an error of less th an 5 W m-(2) for L-net between calculations from SSM/I observations an d pyrgeometer measurements on the German research vessel Poseidon duri ng the International Cirrus Experiment (ICE) 1989 is obtained. For clo udy cases, the comparison is problematic due to the inhomogenities of clouds and the low and different spatial resolutions of the SSM/I data .-Global monthly mean values of L-net for October 1989 are computed an d compared to other sources. Differences are observed among the climat ological values from previous studies by H.-J. Isemer and L. Hasse, th e climatological values from R. Lindau and L. Hasse, the values of W. L. Darnell et al., and results from this study. Some structures of L-n et are similar for results from W. L. Darnell et al. and the present a uthors. The differences between both results are generally less than 1 5 W m(-2). Over the North Atlantic Ocean the authors found a poleward increase for L-net, which is contrary to the results of H.-J. Isemer a nd L. Hasse.