Using TRMM vround validation data to assess global rainfall products

The long-term goal of monitoring surface rainfall from space has been advanced over the past ten years with the addition of a new generation of satellites equipped with multi-channel passive microwave rain sensors. These satellites provide instantaneous rain estimates along the orbital track of the satellite. This rain information is global in character and provides important observations over the vast oceans that cover over 70% of the earth's surface, but each satellite by itself only collects about two snapshots per day over any particular region of the earth. Long-term estimates of rainfall consequently contain large sampling errors due to the long time gaps between observations.

In recent years, a new rain-monitoring paradigm has emerged which seeks to combine the rain information from a “family” of satellites to improve the temporal resolution, spatial coverage and accuracy of the rain estimates and correct for the shortcoming of relying on the measurements from a single satellite. These so-called multi-satellite rain products provide 3-hr rain rates gridded at 0.25° resolution between 50° N and 50° S latitude and are being applied to numerous hydrological applications across a diversity of fields.

We present an assessment of several of these global-rainfall products using TRMM Ground Validation (GV) data as a reference. The global products include NASA's TRMM Multi-Satellite Precipitation Analysis (3B42 and 3B42-RT), the Climate Data Center's Morphed rainfall product (CMORPH), and the University of Arizona's Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN).