The near-real-time precipitation dataset developed by the Center for Hydrometeorology and Remote Sensing (CHRS) of the University of California, Irvine, has been updated and improved, as documented in a recent article in the Journal of Meteorology.
Developed and maintained with support from UNESCO, ICIWaRM and others, the original Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks– Cloud Classification System (PERSIANN-CCS) dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min).
The new product, PERSIANN Dynamic Infrared Rain Rate (PDIR-Now), is intended to supersede PERSIANN–CCS as the primary near-real-time, quasi-global satellite precipitation dataset of the PERSIANN family.
An evaluation done during 2017–18 showed that PDIR-Now gave improved results over PERSIANN-CCS at all temporal scales, including the estimation of rain/no-rain days, seasonal and diurnal cycles of precipitation, and regional precipitation patterns.
PDIR-Now has already been incorporated into the iRain interface (https://irain.eng.uci.edu/), a website that provides a user-friendly interface to visualize global precipitation dataset for the last 72 hours, and can be downloaded from the CHRS Data Portal (https://chrsdata.eng.uci.edu/), which is an interface for the download of PDIR-Now dataset as well as other PERSIANN family datasets.