Introducing and evaluating two new satellite-gauge gridded precipitation products: CHIRPS3.0 and AgMERG

Monitoring and understanding hydro-climatic extremes requires high-quality, high-resolution, homogeneous and timely data, yet the number of available rain gauge observations is declining. Fortunately, satellite-based thermal infrared radiation (TIR) and passive microwave (PM) observations can be combined with station observations to provide reasonably accurate estimates. Two widely used products, the Integrated Multi-satellite Retrievals for the Global Precipitation Measurement version 6 ( IMERG ) and the Climate Hazards center Infrared Precipitation with Stations version 2 ( CHIRPS ) provide quasi-global high resolution precipitation fields. IMERG uses inter-calibrated TIR and PM retrievals from an international constellation to produce 2000-to-present 0.1° gridded datasets. The Climate Hazard Center (CHC) CHIRPS product uses TIR values and a high resolution climatology to produce a 1981-present 0.05 ° data that extends from 50 North to 50 South latitude.

Here we describe two new datasets: version 3 of CHIRPS and a timely gauge-enhanced version of the IMERG late product (AgMERG). These products have been designed to support early warning and hazard modeling and monitoring. Both products utilize a new monthly climatology based on IMERG06, elevation and ~80K gauge under-catch corrected station normals. Both products are updated monthly as unbiased CHIRP3 and IMERG late are combined with a curated set of monthly gauge observations. These `final' products have ~2 week latencies, which is much lower than the ~2.5 month latency for the IMERG final data. Sub-monthly `preliminary' products are also produced every five days.

A major improvement to the CHIRP3 TIR-to-rain rate estimation process is described and evaluated. We show that the CHIRP2's tendency to underestimate rainfall variance can be dramatically reduced.

Evaluations for the products are carried out on sub-monthly and seasonal time scales using gridded REGEN data and in-situ observations. In general, the AgMERG performance is very good at both seasonal and sub-seasonal time scales. The TIR-only CHIRPS3 performs less well, but provides a deeper period of record. Together, these two new datasets will substantially improve our ability to track droughts and floods.