PUBLICATION HIGHLIGHT: Comparison of Global Precipitation Estimates across a Range of Temporal and Spatial Scales

Rainy street (Photo courtesy: PublicDomainPictures.net)
Rainy street (Photo courtesy: PublicDomainPictures.net)

DECEMBER 7, 2016—The need for daily global precipitation estimates has become increasingly important for a variety of applications such as model validation, input for land surface models, and characterizing extreme events. Detailed knowledge about current precipitation distribution is also necessary to quantify changes in precipitation due to global warming as estimated by models. In a new study led by CIRES and NOAA scientists at ESRL's Physical Sciences Division, researchers were interested in identifying the strengths and shortcomings of several global precipitation datasets and providing guidance as to which estimates are likely to perform better in certain situations. Their paper, published in the November 2016 issue of the Journal of Climate, compares several widely used near global satellite precipitation data sets on various time scales to assess their uncertainty. The researchers also compare the evolution of continental precipitation averages over time, as well as rain rate and rain amount distributions. Their findings show that precipitation estimates differ significantly in terms of rain rate and rain amount distribution and temporal evolution even when considering continental averages.

With differences between the precipitation estimates as large as 0.8mm/day on continental scales, it is very hard to reconcile the global moisture budget. These large differences also mean that choosing the best precipitation product for a certain application is of utmost importance. It may be prudent to use multiple precipitation products for model validation, since any two different precipitation products could give opposite results.

Authors of Comparison of Global Precipitation Estimates across a Range of Temporal and Spatial Scales are: Maria Gehne, Thomas Hamill, and George Kiladis of the ESRL Physical Sciences Division, and Kevin Trenberth of NCAR.