Developing a bias- and gauge-adjusted precipitation climatology for the Colorado River Basin from the GPM constellation sensors.

Water is a limited resource in the Colorado River Basin, and improving precipitation estimates is important for water management. The Goddard Profiling Algorithm (GPROF) estimates precipitation globally, but it can be improved upon at regional scales when additional prior information is used. An adapted version of the GPROF retrieval restricts the global databases of paired GMI brightness temperature and footprint-averaged Multi-Radar Multi-Sensor precipitation to the Southwestern U.S. Mountain region. Some further adjustments were made to the retrieval to accommodate the limited size of the regional database. The CRB-GPROF retrieval was run for all GPM constellation orbits that crossed the region from October 2001 until September 2017. Precipitation estimates for each satellite and sensor were gridded into 0.1°, 6-hourly resolution dataset. Gauge data from the Colorado Basin River Forecast Center (CBRFC) was also gridded and used to calculate a rain season (May - October) and snow season (November - April) bias adjustment for each sensor. A bias-adjusted precipitation climatology was produced by accounting for the bias and combining the GPM constellation sensor estimates. The gridded gauge data was then used to gauge-adjust the bias-adjusted precipitation estimates in the CRB, using a distance-weighted adjustment technique. An evaluation of the gauge-adjusted CRB precipitation dataset against Parameter elevation Regression on Independent Slopes Model (PRISM) precipitation data shows that this methodology produces lower bias and RMS error, compared to the Integrated Multi-Satellite Retrievals for GPM (IMERG) gauge-adjusted passive microwave precipitation product.