The NOAA Microwave Integrated Retrieval System (MiRS): Validation of Precipitation From Multiple Polar-Orbiting Satellites

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 13; pp. 3019 - 3031
• Main Authors: Liu, Shuyan, Grassotti, Christopher, Liu, Quanhua, Lee, Yong-Keun, Honeyager, Ryan, Zhou, Yan, Fang, Ming
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Advanced microwave sounding unit-A (AMUSA)-microwave humidity sounder (MHS); advanced technology microwave sounder (ATMS); Algorithms; Annual precipitation; Atmospheric precipitations; Cold season; Instruments; Microwave imaging; microwave integrated retrieval system (MiRS); Microwave measurement; Microwave theory and techniques; Ocean temperature; Performance measurement; Polar orbiting satellites; Precipitation; Precipitation rate; Radar; Rain gauges; Rainfall; Rainfall intensity; Retrieval; satellite; Satellite observation; Satellites; Seasons; Statistical methods; US Government agencies
• ISSN: 1939-1404; 2151-1535
• DOI: 10.1109/JSTARS.2020.3000348

This article describes a multisatellite validation study of precipitation from the microwave integrated retrieval system (MiRS). MiRS is a variational algorithm designed to process passive microwave measurements using a common core of retrieval software, and currently runs operationally on data from ten different earth-observing satellites. The primary validation was conducted for the polar-orbiting satellites SNPP, NOAA20 (both bearing the ATMS instrument), MetopB, and MetopC (both bearing the AMSUA and MHS instruments) during the period from December 1, 2018 through December 31, 2019. Validation was conducted using operational ground-based radar-rain gauge analyses from Stage-IV and multiradar multisensor (MRMS) over the continental United States. Results indicate that the precipitation estimates are largely consistent with one another and that agreement with ground-based analyses has a strong seasonal component. Warm season performance is generally higher and more stable than during the cold season. SNPP and NOAA20 estimates appeared to show slightly higher biases, outside of July and August. Frequency distributions of precipitation intensity also showed better agreement between MiRS and Stage-IV for higher precipitation rates in the warm season, highlighting the difficulty of estimating over land precipitation rates associated with stratiform precipitation systems that typically occur during the cold season. All satellites depicted the annual mean precipitation rate global distribution with good interconsistency, but with some differences possibly related to individual temporal sampling characteristics of each satellite. Summary validation statistics and scores stratified by season show that MiRS performance metrics using MRMS as a reference are largely similar to those based on using Stage-IV.