A real-time global half-hourly pixel-resolution infrared dataset and its applications

A system has been developed and implemented that merges pixel resolution (s imilar to4 km) infrared (IR) satellite data from all available geostationar y meteorological satellites into a global (60 degreesN-60 degreesS) product . The resulting research-quality, nearly seamless global array of informati on is made possible by recent work by Joyce et al., who developed a techniq ue to correct IR temperatures at targets far from satellite nadir. At such locations, IR temperatures are colder than if identical features were measu red at a target near satellite nadir. This correction procedure yields a da taset that is considerably more amenable to quantitative manipulation than if the data from the individual satellites were merely spliced together. Several unique features of this product exist. First, the data from individ ual geostationary satellites have been merged to form nearly seamless maps after correcting the IR brightness temperatures for viewing angle effects. Second, with the availability of IR data from the Meteosat-5 satellite (cur rently positioned at a subsatellite longitude of 63 degreesE), globally com plete (60 degreesN-60 degreesS) fields can be produced. Third, the data hav e been transformed from the native satellite projection of each individual geostationary satellite and have been remapped to a uniform latitude/longit ude grid. Fourth, globally merged datasets of full resolution IR brightness temperature have been produced routinely every half hour since November 19 98. Fifth, seven days of globally merged, half-hourly data are available on a rotating archive that is maintained by the Climate Prediction Center Web page (http://www.cpc.ncep.noaagov/products/global_precip/html/web.html). U nfortunately, international agreement prevents us from distributing Meteosa t data within three days of real time, so the data availability is delayed appropriately. Finally, these data are permanently saved at the National Cl imatic Data Center in Asheville, North Carolina, beginning with data in mid -September of 1999. In this paper, the authors briefly describe the merging methodology and des cribe key aspects of the merged product. Present and potential applications of this dataset are also discussed. Applications include near-real time gl obal disaster monitoring and mitigation and assimilation of these data into numerical weather prediction models and research, among others.