ALBERT

Description: A neural network is used to calculate the longwave net radiation (Lnet) at the sea surface from measurements of the Special Sensor Microwave/Imager (SSM/I). The neural network applied in this study is able to account largely for the nonlinearity between Lnet and the satellite-measured 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). Comparing with a linear regression method the neural network reduces the standard error for Lnet from 17 to 5 W m−2 when applied to model results. For clear-sky cases, a good agreement with an error of less than 5 W m−2 for Lnet between calculations from SSM/I observations and pyrgeometer measurements on the German research vessel Poseidon during the International Cirrus Experiment (ICE) 1989 is obtained. For cloudy 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 Lnet for October 1989 are computed and compared to other sources. Differences are observed among the climatological values from previous studies by H.-J. Isemer and L. Hasse, the climatological values from R. Lindau and L. Hasse, the values of W. L. Darnell et al., and results from this study. Some structures of Lnet are similar for results from W. L. Darnell et al. and the present authors. The differences between both results are generally less than 15 W m−2. Over the North Atlantic Ocean the authors found a poleward increase for Lnet, which is contrary to the results of H.-J. Isemer and L. Hasse.

Description: The incidence angles of the SSM/I radiometers on the DMSP satellites vary from satellite to satellite and exhibit variations of up to 1.5° during one orbit. The effects of these variations on the measured brightness temperatures are investigated on the basis of simulated and measured data for oceanic arm. A deviation of 1° from the nominal incidence angle of 53.0° causes brightness temperature changes of up to 2 K depending on surface and atmospheric conditions. Errors of retrieved geophysical parameters on the order of 5%–10% result when the incidence angle variation is not taken into account. This is a common property of most published statistical algorithms. For total precipitable water and cloud liquid water content the error increases with increasing parameter value. For wind speed the error is largest for low wind speed and decreases with increasing wind speed. Due to the slowly varying latitudinal dependence of the incidence angle, these errors do not cancel out when monthly means are computed. A correction method is developed on the basis of simulated data and tested successfully with measured data. Observed brightness temperature differences between DMSP F10 and F11 are reduced when using corrected data. If diurnal variations of geophysical parameters are investigated, the incidence angle correction is mandatory to obtain useful results, especially for DMSP F10.