A new methodology of rainfall retrievals from indirect measurements

A new methodology for rainfall retrievals from indirect measurements ii pro posed and illustrated using IR brightness temperature and radar rainfall ob servations collected during TOGA-COARE. Since (1) rain rate has a mixed dis tribution with a delta-function for a zero rain and lognormal distribution for nonzero and (2) the least squares method which is used to calculate reg ression coefficients gives a priori consistent estimates only for normally distributed data. it is proposed to convert the rain rate to a normally dis tributed set and only after that to develop a retrieval method and estimate the skill of this method. Consideration of the physics of clouds and cloud ensembles, the goal to minimize errors in the radar data, and the desire t o remove the influence of cirrus clouds lead us to use: a) minimum of IR br ightness temperatures over a 1 degrees x 1 degrees area and a 3 hour interv al as a predictor, and b) radar rainfall, averaged over 3 hours over a 1 de grees x 1 degrees area, with the radar in its center, as the truth. Results using the TOGA-COARE data show that the correlation of the rain rate trans formed to normal distribution is significantly higher with minimum temperat ure than with the fraction of area covered by high clouds. The sizes of hea vy rainfall areas obtained using the new methodology are reasonable. The re gression coefficients should change with latitude, season and location. Tak en together, the results indicate that it is possible, in principle, to ret rieve rainfall from IR satellite observations and obtain reliable rainfall data. To realize this goal it is necessary to process radar and IR data usi ng the new methodology for different latitudes, seasons, over land and ocea n.