The Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, dataset available on our FTP here) is a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05◦ 25 monthly precipitation climatology is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities. A paper discussing the CHPclim is available here
Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring.
Extended records of geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05◦) global precipitation climatologies that perform reasonably well in data sparse regions.
Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. The CHPclim is a demonstration of how these relationships provide a good basis for building global climatologies.