Statistical adjustment of satellite microwave monthly rainfall estimates over Amazonia

A technique is described for quantifying nonlinear adjustment to the half-d egree monthly rainfall estimates over land, derived from the Special Sensor Microwave Imager (SSM/I) observations. The technique uses a function that represents the distortion between the probability distributions of SSM/I an d rain gauge half-degree monthly rainfall. The proposed adjustment procedur e is assessed and evaluated with a 10-yr period (1988-97) of SSM/I observat ions over the northern South America region (15 degrees N-15 degrees S, 80 degrees-35 degrees W), which includes the Amazon basin. The rain estimates are derived from the National Aeronautics and Space Administration's Goddar d Profiling (GPROF) algorithm instantaneous rain-rate retrievals, averaged in half-degree areas and aggregated into monthly accumulations. Monthly rai n accumulations from a network of 650 rain gauges distributed across the Am azon basin and the state of Ceara in northeastern Brazil are used for calib ration and validation, respectively. Assessment of the adjustment relations hip with the validation dataset shows an overall 45% GPROF-gauge root-mean- square (rms) difference reduction with respect to no adjustment, which is d ue mainly to elimination of the mean bias, and a respective 10% increase in the GPROF-gauge correlation. The rms difference between 5 degrees gridbox monthly rain averages of adjusted GPROF and rain gauges is 23% of the mean rain, and the corresponding correlation coefficient is 0.94.