CPC MORPHING Technique (CMORPH)

Abstract

IR data are available globally nearly everywhere nearly all the time. However, IR channels measure cloud top temperatures and those temperatures do not always correlate well with rainfall. In many instances the cold cloud shield in a precipitating complex may be several times larger than the areal coverage of the actual precipitating region, sometimes with no rainfall directly under the coldest section. In contrast to the IR, relatively low frequency passive microwave (PMW) signals sense the thermal emission of raindrops while higher frequencies sense the scattering of upwelling radiation from the earth to space due to ice particles in the rain layer and tops of convective systems. Although rainfall estimates from PMW instruments are more accurate than those that are derived from IR data, PMW sensors are restricted to low orbit platforms and thus the temporal sampling from them is substantially less compared to geostationary IR data. Given this situation, the natural next step is to combine the data from these disparate sensors to take advantage of the strengths that each has to offer. A number of techniques have been developed in which the IR data are manipulated in a statistical fashion to mimic the behavior of PMW derived precipitation estimates. In these techniques, precipitation estimates are calculated directly from IR data through an empirical relationship between the rain rate and cloud top temperature and are used when PMW data are unavailable. An alternative method of combining these disparate data is proposed, one that uses precipitation estimates derived from low orbiter satellite PMW retrievals exclusively, and whose features are transported via spatial propagation information obtained from geostationary satellite IR data during periods when instantaneous PMW data are not available at a location.