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

Shuyan Liu; Christopher Grassotti; Quanhua Liu; Yong-Keun Lee; Ryan Honeyager; Yan Zhou; Ming Fang

doi:10.1109/JSTARS.2020.3000348

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2020)

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

Shuyan Liu,
Christopher Grassotti,
Quanhua Liu,
Yong-Keun Lee,
Ryan Honeyager,
Yan Zhou,
Ming Fang

Affiliations

Shuyan Liu: ORCiD; Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
Christopher Grassotti: ORCiD; Earth System Science Interdisciplinary Center, Cooperative Institute for Satellite and Earth System Studies, University of Maryland, College Park, MD, USA
Quanhua Liu: ORCiD; National Oceanic and Atmospheric Administration Center for Satellite Applications and Research, National Environmental Satellite, Data, and Information Service, College Park, MD, USA
Yong-Keun Lee: Earth System Science Interdisciplinary Center, Cooperative Institute for Satellite and Earth System Studies, University of Maryland, College Park, MD, USA
Ryan Honeyager: ORCiD; National Oceanic and Atmospheric Administration National Centers for Environmental Prediction, Environmental Modeling Center, University Corporation for Atmospheric Research, College Park, MD, USA
Yan Zhou: Earth System Science Interdisciplinary Center, Cooperative Institute for Satellite and Earth System Studies, University of Maryland, College Park, MD, USA
Ming Fang: I.M. Systems Group, College Park, MD, USA

DOI: https://doi.org/10.1109/JSTARS.2020.3000348
Journal volume & issue: Vol. 13
pp. 3019 – 3031

Abstract

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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.

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

ISSN: 1939-1404 (Print); 2151-1535 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Ocean engineering; Science: Physics: Geophysics. Cosmic physics
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4609443

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