Evaluation of Integrated Multi-satellitE Retrievals for GPM with All Weather Gauge Observations over CONUS

Abstract:

The Global Precipitation Measurement (GPM) mission is composed of an international network of satellites that provide the next-generation global observations of rain and snow. Integrated Multi-satellitE Retrievals for GPM (IMERG) is the state-of-art precipitation products with high spatio-temporal resolution of 0.1°/30min. IMERG unifies precipitation measurements from a constellation of research and operational satellites with the core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI) on board a “Core” satellite. Additionally, IMERG blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. In this study, the final run post real-time IMERG is evaluated with all-weather manual gauge observations over CONUS from June 2014 through May 2015. Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of IMERG. The performance of IMERG in estimating snowfall precipitation is highlighted in the study. This timely evaluation with all-weather gauge observations is expected to offer insights into performance of IMERG and thus provide useful feedback to the algorithm developers as well as the GPM data users.