2019•Journal of the Meteorological Society of Japan Ser IIOpen access

The Detection of Mesoscale Convective Systems by the GPM Ku-Band Spaceborne Radar

Jingyu Wang, Robert A. Houze, Jiwen Fan, Stella R. Brodzik, Zhe Feng, Joseph Clinton Hardin

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Abstract

The Global Precipitation Measurement (GPM) core observatory satellite launched in 2014 features more extended latitudinal coverage (65°S-65°N) than its predecessor Tropical Rainfall Measuring Mission (TRMM, 35°S-35°N). The Ku-band radar onboard the GPM is known to be capable of characterizing the 3D structure of deep convection globally. In this study, the GPM's capability for detecting mesoscale convective systems (MCSs) is evaluated. Extreme convective echoes seen by GPM are compared against an MCS database that tracks convective entities over the contiguous US. The tracking is based on a geostationary satellite and ground-based Next Generation Radar (NEXRAD) network data obtained during the 2014-2016 warm seasons. Results indicate that more than 70 % of the GPM-detected deep–wide convective core (DWC) and wide convective core (WCC) objects are part of NEXRAD identified MCSs, indicating that GPM-classified DWCs and WCCs correlate well with typical MCSs containing large convective features. By applying this method to the rest of the world, a global view of MCS distribution is obtained. This work reveals GPM's potential in MCS detection at the global scale, particularly over remote regions without a dense observation network.

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The Global Precipitation Measurement (GPM) core observatory satellite launched in 2014 features more extended latitudinal coverage (65°S-65°N) than its predecessor Tropical Rainfall Measuring Mission (TRMM, 35°S-35°N). The Ku-band radar onboard the GPM is known to be capable of characterizing the 3D structure of deep convection globally. In this study, the GPM's capability for detecting mesoscale convective systems (MCSs) is evaluated. Extreme convective echoes seen by GPM are compared against an MCS database that tracks convective entities over the contiguous US. The tracking is based on a geostationary satellite and ground-based Next Generation Radar (NEXRAD) network data obtained during the 2014-2016 warm seasons. Results indicate that more than 70 % of the GPM-detected deep–wide convective core (DWC) and wide convective core (WCC) objects are part of NEXRAD identified MCSs, indicating that GPM-classified DWCs and WCCs correlate well with typical MCSs containing large convective features. By applying this method to the rest of the world, a global view of MCS distribution is obtained. This work reveals GPM's potential in MCS detection at the global scale, particularly over remote regions without a dense observation network.

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Available abstract

The Global Precipitation Measurement (GPM) core observatory satellite launched in 2014 features more extended latitudinal coverage (65°S-65°N) than its predecessor Tropical Rainfall Measuring Mission (TRMM, 35°S-35°N). The Ku-band radar onboard the GPM is known to be capable of characterizing the 3D structure of deep convection globally. In this study, the GPM's capability for detecting mesoscale convective systems (MCSs) is evaluated. Extreme convective echoes seen by GPM are compared against an MCS database that tracks convective entities over the contiguous US. The tracking is based on a geostationary satellite and ground-based Next Generation Radar (NEXRAD) network data obtained during the 2014-2016 warm seasons. Results indicate that more than 70 % of the GPM-detected deep–wide convective core (DWC) and wide convective core (WCC) objects are part of NEXRAD identified MCSs, indicating that GPM-classified DWCs and WCCs correlate well with typical MCSs containing large convective features. By applying this method to the rest of the world, a global view of MCS distribution is obtained. This work reveals GPM's potential in MCS detection at the global scale, particularly over remote regions without a dense observation network.

Key concepts: Mesoscale convective system, Satellite, Mesoscale meteorology, Meteorology, Radar, Geostationary orbit, Remote sensing, Convection

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