Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals
Precipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rat...
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description | Precipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rate. This study investigates the vertical precipitation profiles estimated by two passive MW-based retrieval algorithms, i.e., the emissivity principal components (EPC) algorithm and the Goddard profiling algorithm (GPROF). The passive MW-based condensed water content profiles estimated from the Global Precipitation Measurement Microwave Imager (GMI) are validated using the GMI + Dual-Frequency Precipitation Radar combined algorithm as the reference product. It is shown that the EPC generally underestimates the magnitude of the condensed water content profiles, described by the mean condensed water content, by about 20%–50% in the middle-to-high latitudes, while GPROF overestimates it by about 20%–50% in the middle-to-high latitudes and more than 50% in the tropics. Part of the EPC magnitude biases is associated with the representation of the precipitation type (i.e., convective and stratiform) in the retrieval algorithm. This suggests that a separate technique for precipitation type identification would aid in mitigating these biases. In contrast to the magnitude of the profile, the profile shapes are relatively well represented by these two passive MW-based retrievals. The joint analysis between the estimation performances of the vertical profiles and surface precipitation rate shows that the physically reasonable connections between the surface precipitation rate and the associated vertical profiles are achieved to some extent by the passive MW-based algorithms. |
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Joseph ; Haddad, Ziad S. ; Kirstetter, Pierre-Emmanuel ; Kim, Hyungjun</creator><creatorcontrib>Utsumi, Nobuyuki ; Turk, F. Joseph ; Haddad, Ziad S. ; Kirstetter, Pierre-Emmanuel ; Kim, Hyungjun</creatorcontrib><description>Precipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rate. This study investigates the vertical precipitation profiles estimated by two passive MW-based retrieval algorithms, i.e., the emissivity principal components (EPC) algorithm and the Goddard profiling algorithm (GPROF). The passive MW-based condensed water content profiles estimated from the Global Precipitation Measurement Microwave Imager (GMI) are validated using the GMI + Dual-Frequency Precipitation Radar combined algorithm as the reference product. It is shown that the EPC generally underestimates the magnitude of the condensed water content profiles, described by the mean condensed water content, by about 20%–50% in the middle-to-high latitudes, while GPROF overestimates it by about 20%–50% in the middle-to-high latitudes and more than 50% in the tropics. Part of the EPC magnitude biases is associated with the representation of the precipitation type (i.e., convective and stratiform) in the retrieval algorithm. This suggests that a separate technique for precipitation type identification would aid in mitigating these biases. In contrast to the magnitude of the profile, the profile shapes are relatively well represented by these two passive MW-based retrievals. The joint analysis between the estimation performances of the vertical profiles and surface precipitation rate shows that the physically reasonable connections between the surface precipitation rate and the associated vertical profiles are achieved to some extent by the passive MW-based algorithms.</description><identifier>ISSN: 1525-755X</identifier><identifier>EISSN: 1525-7541</identifier><identifier>DOI: 10.1175/jhm-d-20-0160.1</identifier><identifier>PMID: 34045927</identifier><language>eng</language><publisher>BOSTON: American Meteorological Society</publisher><subject>Algorithms ; Emissivity ; Estimates ; Global climate ; Global precipitation ; Latitude ; Low earth orbits ; Meteorology & Atmospheric Sciences ; Moisture content ; Physical Sciences ; Precipitation ; Precipitation estimation ; Precipitation rate ; Principal components analysis ; Profiles ; Radar ; Radiometers ; Retrieval ; Satellite observation ; Science & Technology ; SPECIAL COLLECTION: IPC12 ; Tropical environments ; Variables ; Vertical profiles ; Water content</subject><ispartof>Journal of hydrometeorology, 2021-01, Vol.22 (1), p.95-112</ispartof><rights>2020 American Meteorological Society</rights><rights>Copyright American Meteorological Society Jan 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>9</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000656693400006</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c486t-35c1309bf9ecedb08101d4ca2caf7358eeab3b82f7f8f57d84790e82bbb882e63</citedby><cites>FETCH-LOGICAL-c486t-35c1309bf9ecedb08101d4ca2caf7358eeab3b82f7f8f57d84790e82bbb882e63</cites><orcidid>0000-0002-0480-2559 ; 0000-0002-7381-0229</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/27074410$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/27074410$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,315,781,785,804,886,3682,27928,27929,58021,58254</link.rule.ids></links><search><creatorcontrib>Utsumi, Nobuyuki</creatorcontrib><creatorcontrib>Turk, F. Joseph</creatorcontrib><creatorcontrib>Haddad, Ziad S.</creatorcontrib><creatorcontrib>Kirstetter, Pierre-Emmanuel</creatorcontrib><creatorcontrib>Kim, Hyungjun</creatorcontrib><title>Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals</title><title>Journal of hydrometeorology</title><addtitle>J HYDROMETEOROL</addtitle><description>Precipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rate. This study investigates the vertical precipitation profiles estimated by two passive MW-based retrieval algorithms, i.e., the emissivity principal components (EPC) algorithm and the Goddard profiling algorithm (GPROF). The passive MW-based condensed water content profiles estimated from the Global Precipitation Measurement Microwave Imager (GMI) are validated using the GMI + Dual-Frequency Precipitation Radar combined algorithm as the reference product. It is shown that the EPC generally underestimates the magnitude of the condensed water content profiles, described by the mean condensed water content, by about 20%–50% in the middle-to-high latitudes, while GPROF overestimates it by about 20%–50% in the middle-to-high latitudes and more than 50% in the tropics. Part of the EPC magnitude biases is associated with the representation of the precipitation type (i.e., convective and stratiform) in the retrieval algorithm. This suggests that a separate technique for precipitation type identification would aid in mitigating these biases. In contrast to the magnitude of the profile, the profile shapes are relatively well represented by these two passive MW-based retrievals. The joint analysis between the estimation performances of the vertical profiles and surface precipitation rate shows that the physically reasonable connections between the surface precipitation rate and the associated vertical profiles are achieved to some extent by the passive MW-based algorithms.</description><subject>Algorithms</subject><subject>Emissivity</subject><subject>Estimates</subject><subject>Global climate</subject><subject>Global precipitation</subject><subject>Latitude</subject><subject>Low earth orbits</subject><subject>Meteorology & Atmospheric Sciences</subject><subject>Moisture content</subject><subject>Physical Sciences</subject><subject>Precipitation</subject><subject>Precipitation estimation</subject><subject>Precipitation rate</subject><subject>Principal components analysis</subject><subject>Profiles</subject><subject>Radar</subject><subject>Radiometers</subject><subject>Retrieval</subject><subject>Satellite observation</subject><subject>Science & Technology</subject><subject>SPECIAL COLLECTION: IPC12</subject><subject>Tropical environments</subject><subject>Variables</subject><subject>Vertical profiles</subject><subject>Water content</subject><issn>1525-755X</issn><issn>1525-7541</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>HGBXW</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNkU2LFDEQhhtR3A89exIavAhLu0kn6U5fhHUcd5UdHPzCW0jSFTdDT2dM0rPsv7eGGQb05ClF1fNWquotiheUvKG0FZeru3XVVzWpCG0w9ag4paIWVSs4fXyMxc-T4iylFSGEd1Q-LU4YJ1x0dXtahPlWD5POPoxlcOUygvUbn_eJHxCzt3rAdHB-gFTOU_ZrnaEvzUN5vVxU86jLr5gYBp-heqcTlpY6Jb-FcuFtDPcaoy-Qowf8KT0rnjh84PnhPS--f5h_m91Ut5-vP86ubivLZZMrJixlpDOuAwu9IZIS2nOra6tdy4QE0IYZWbvWSSfaXvK2IyBrY4yUNTTsvHi777uZzBp6C2OOelCbiOPHBxW0V39XRn-nfoWtkng0Sjg2eH1oEMPvCVJWa58s7qlHCFNStWC8oVRIhuirf9BVmOKI6yFFCWNUSorU5Z7Co6QUwR2HoUTtzFSfbhbqvaqJ2pmpdgq5V9yDCS5ZD6OFowrdbETTdOjlLpwdTJuFacwovfh_KdIv9_Qq5RCPWN2SlnNc4A-oAr2k</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Utsumi, Nobuyuki</creator><creator>Turk, F. 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Joseph ; Haddad, Ziad S. ; Kirstetter, Pierre-Emmanuel ; Kim, Hyungjun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c486t-35c1309bf9ecedb08101d4ca2caf7358eeab3b82f7f8f57d84790e82bbb882e63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Emissivity</topic><topic>Estimates</topic><topic>Global climate</topic><topic>Global precipitation</topic><topic>Latitude</topic><topic>Low earth orbits</topic><topic>Meteorology & Atmospheric Sciences</topic><topic>Moisture content</topic><topic>Physical Sciences</topic><topic>Precipitation</topic><topic>Precipitation estimation</topic><topic>Precipitation rate</topic><topic>Principal components analysis</topic><topic>Profiles</topic><topic>Radar</topic><topic>Radiometers</topic><topic>Retrieval</topic><topic>Satellite observation</topic><topic>Science & Technology</topic><topic>SPECIAL COLLECTION: IPC12</topic><topic>Tropical environments</topic><topic>Variables</topic><topic>Vertical profiles</topic><topic>Water content</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Utsumi, Nobuyuki</creatorcontrib><creatorcontrib>Turk, F. 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Joseph</au><au>Haddad, Ziad S.</au><au>Kirstetter, Pierre-Emmanuel</au><au>Kim, Hyungjun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals</atitle><jtitle>Journal of hydrometeorology</jtitle><stitle>J HYDROMETEOROL</stitle><date>2021-01-01</date><risdate>2021</risdate><volume>22</volume><issue>1</issue><spage>95</spage><epage>112</epage><pages>95-112</pages><issn>1525-755X</issn><eissn>1525-7541</eissn><abstract>Precipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rate. This study investigates the vertical precipitation profiles estimated by two passive MW-based retrieval algorithms, i.e., the emissivity principal components (EPC) algorithm and the Goddard profiling algorithm (GPROF). The passive MW-based condensed water content profiles estimated from the Global Precipitation Measurement Microwave Imager (GMI) are validated using the GMI + Dual-Frequency Precipitation Radar combined algorithm as the reference product. It is shown that the EPC generally underestimates the magnitude of the condensed water content profiles, described by the mean condensed water content, by about 20%–50% in the middle-to-high latitudes, while GPROF overestimates it by about 20%–50% in the middle-to-high latitudes and more than 50% in the tropics. Part of the EPC magnitude biases is associated with the representation of the precipitation type (i.e., convective and stratiform) in the retrieval algorithm. This suggests that a separate technique for precipitation type identification would aid in mitigating these biases. In contrast to the magnitude of the profile, the profile shapes are relatively well represented by these two passive MW-based retrievals. The joint analysis between the estimation performances of the vertical profiles and surface precipitation rate shows that the physically reasonable connections between the surface precipitation rate and the associated vertical profiles are achieved to some extent by the passive MW-based algorithms.</abstract><cop>BOSTON</cop><pub>American Meteorological Society</pub><pmid>34045927</pmid><doi>10.1175/jhm-d-20-0160.1</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-0480-2559</orcidid><orcidid>https://orcid.org/0000-0002-7381-0229</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Emissivity Estimates Global climate Global precipitation Latitude Low earth orbits Meteorology & Atmospheric Sciences Moisture content Physical Sciences Precipitation Precipitation estimation Precipitation rate Principal components analysis Profiles Radar Radiometers Retrieval Satellite observation Science & Technology SPECIAL COLLECTION: IPC12 Tropical environments Variables Vertical profiles Water content |
title | Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals |
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