An analysis of the performance of hybrid infrared and microwave satellite precipitation algorithms over India and adjacent regions

The measurement of precipitation is fundamental to our understanding of the hydrological cycle. Increasingly, there exists the capacity to independently determine components of the hydrological cycle from remote sensing data. Developing techniques to combine effectively the multiple streams of information required for a water budget assessment provides a difficult challenge, particularly given the disparities in spatial and temporal scales between measurements and predictions. Two research groups, the Naval Research Laboratory Monterey (NRL) and the University of Arizona (UA), are using a combination of geostationary infrared and polar-orbiting microwave satellite data to derive 6-hourly precipitation estimates over a global 0.25° grid. We examine the performance of these two algorithms for estimating the 24-h rainfall accumulation over India and Sri Lanka for the years 2002 and 2003. The derived values are compared with observations from a network of 39 national weather stations. In addition, two locations, Minicoy in the Laccadive Islands and Port Blair in the Andaman Islands were selected as being representative of the ocean environment to compare these satellite rainfall products against measurements from local rain gauges and Tropical Rainfall Measuring Mission (TRMM) satellite data. The NRL technique was accurate to within 25% of observed precipitation for only 33% of station locations, while the UA technique was accurate to within 25% of observed precipitation for about 47% of station locations.