Satellite precipitation bias estimation and correction using in situ observations and climatology isohyets for the MENA region
The availability of reliable gridded precipitation datasets is limited around the world, especially in arid regions. In this study, we utilized observations from satellite-based precipitation data and in situ rain gauge observations to determine a suitable precipitation dataset in the Middle East &a...
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Veröffentlicht in: | Journal of arid environments 2023-08, Vol.215, p.105010, Article 105010 |
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creator | Kagone, S. Velpuri, N.M. Khand, K. Senay, G.B. van der Valk, M.R. Goode, D.J. Abu Hantash, S. Al-Momani, T.M. Momejian, N. Eggleston, J.R. |
description | The availability of reliable gridded precipitation datasets is limited around the world, especially in arid regions. In this study, we utilized observations from satellite-based precipitation data and in situ rain gauge observations to determine a suitable precipitation dataset in the Middle East & North Africa (MENA) region. First, we evaluated seven different precipitation products using rain gauge observations. The validation was conducted at the daily, monthly, and annual time scales. Results indicated a weaker correlation between in situ rain gauge observation and satellite precipitation data at the daily time step (r: 0.02 to 0.44), mainly due to the lack of range in precipitation distribution. However, the agreement between precipitation estimates and in situ gauge observations improved at monthly (r: 0.02 to 0.66) and annual time scales (r: −0.22 to 0.57), indicating greater reliability of satellite-based precipitation at monthly and annual time scales. Based on the results and dataset availability, the Multi-Source Weighted-Ensemble Precipitation (MSWEP) was deemed suitable to create a bias-corrected new precipitation dataset for the MENA region. This study highlights the benefits of an adjusted regional precipitation product for hydrologic applications in the MENA region, such as streamflow or runoff estimation, to improve the reliability of the model outputs.
[Display omitted]
•Spatio-temporal distribution of precipitation is critical for addressing water issues.•Used satellite, gauge observation and climatology precipitation datasets.•Bias-corrected gridded precipitation dataset for the MENA region. |
doi_str_mv | 10.1016/j.jaridenv.2023.105010 |
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[Display omitted]
•Spatio-temporal distribution of precipitation is critical for addressing water issues.•Used satellite, gauge observation and climatology precipitation datasets.•Bias-corrected gridded precipitation dataset for the MENA region.</description><identifier>ISSN: 0140-1963</identifier><identifier>EISSN: 1095-922X</identifier><identifier>DOI: 10.1016/j.jaridenv.2023.105010</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>climatology ; data collection ; In situ precipitation measurements ; MENA ; Middle East ; Northern Africa ; Precipitation ; rain gauges ; Remote sensing ; runoff ; satellites ; stream flow</subject><ispartof>Journal of arid environments, 2023-08, Vol.215, p.105010, Article 105010</ispartof><rights>2023 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c393t-fb98f1f24391a317ac59ec94c472307e8c5048dae567b840f50508bd8ab378843</citedby><cites>FETCH-LOGICAL-c393t-fb98f1f24391a317ac59ec94c472307e8c5048dae567b840f50508bd8ab378843</cites><orcidid>0000-0002-2979-4655</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0140196323000812$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Kagone, S.</creatorcontrib><creatorcontrib>Velpuri, N.M.</creatorcontrib><creatorcontrib>Khand, K.</creatorcontrib><creatorcontrib>Senay, G.B.</creatorcontrib><creatorcontrib>van der Valk, M.R.</creatorcontrib><creatorcontrib>Goode, D.J.</creatorcontrib><creatorcontrib>Abu Hantash, S.</creatorcontrib><creatorcontrib>Al-Momani, T.M.</creatorcontrib><creatorcontrib>Momejian, N.</creatorcontrib><creatorcontrib>Eggleston, J.R.</creatorcontrib><title>Satellite precipitation bias estimation and correction using in situ observations and climatology isohyets for the MENA region</title><title>Journal of arid environments</title><description>The availability of reliable gridded precipitation datasets is limited around the world, especially in arid regions. In this study, we utilized observations from satellite-based precipitation data and in situ rain gauge observations to determine a suitable precipitation dataset in the Middle East & North Africa (MENA) region. First, we evaluated seven different precipitation products using rain gauge observations. The validation was conducted at the daily, monthly, and annual time scales. Results indicated a weaker correlation between in situ rain gauge observation and satellite precipitation data at the daily time step (r: 0.02 to 0.44), mainly due to the lack of range in precipitation distribution. However, the agreement between precipitation estimates and in situ gauge observations improved at monthly (r: 0.02 to 0.66) and annual time scales (r: −0.22 to 0.57), indicating greater reliability of satellite-based precipitation at monthly and annual time scales. Based on the results and dataset availability, the Multi-Source Weighted-Ensemble Precipitation (MSWEP) was deemed suitable to create a bias-corrected new precipitation dataset for the MENA region. This study highlights the benefits of an adjusted regional precipitation product for hydrologic applications in the MENA region, such as streamflow or runoff estimation, to improve the reliability of the model outputs.
[Display omitted]
•Spatio-temporal distribution of precipitation is critical for addressing water issues.•Used satellite, gauge observation and climatology precipitation datasets.•Bias-corrected gridded precipitation dataset for the MENA region.</description><subject>climatology</subject><subject>data collection</subject><subject>In situ precipitation measurements</subject><subject>MENA</subject><subject>Middle East</subject><subject>Northern Africa</subject><subject>Precipitation</subject><subject>rain gauges</subject><subject>Remote sensing</subject><subject>runoff</subject><subject>satellites</subject><subject>stream flow</subject><issn>0140-1963</issn><issn>1095-922X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkMtOwzAQRS0EEuXxC8hLNil27CT2jqoqD4nHApDYWY4zaV2lcbHdSt3w7bgNrFmNZnTuSPcgdEXJmBJa3izHS-1tA_12nJOcpWNBKDlCI0pkkck8_zxGI0I5yags2Sk6C2FJCKVFwUbo-01H6DobAa89GLu2UUfrelxbHTCEaFfDrvsGG-cTc1g3wfZzbHscbNxgVwfw2wMYBrLb51zn5jtsg1vsIAbcOo_jAvDz7GWCPcwTfYFOWt0FuPyd5-jjbvY-fcieXu8fp5OnzDDJYtbWUrS0zTmTVDNaaVNIMJIbXuWMVCBMQbhoNBRlVQtO2iI5EHUjdM0qITg7R9fD37V3X5tUS61sMKm47sFtgsoF43lVSk4SWg6o8S4ED61a-1TG7xQlai9cLdWfcLUXrgbhKXg7BCEV2VrwKhgLvYHG7q2pxtn_XvwA6laPXw</recordid><startdate>202308</startdate><enddate>202308</enddate><creator>Kagone, S.</creator><creator>Velpuri, N.M.</creator><creator>Khand, K.</creator><creator>Senay, G.B.</creator><creator>van der Valk, M.R.</creator><creator>Goode, D.J.</creator><creator>Abu Hantash, S.</creator><creator>Al-Momani, T.M.</creator><creator>Momejian, N.</creator><creator>Eggleston, J.R.</creator><general>Elsevier Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0002-2979-4655</orcidid></search><sort><creationdate>202308</creationdate><title>Satellite precipitation bias estimation and correction using in situ observations and climatology isohyets for the MENA region</title><author>Kagone, S. ; Velpuri, N.M. ; Khand, K. ; Senay, G.B. ; van der Valk, M.R. ; Goode, D.J. ; Abu Hantash, S. ; Al-Momani, T.M. ; Momejian, N. ; Eggleston, J.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c393t-fb98f1f24391a317ac59ec94c472307e8c5048dae567b840f50508bd8ab378843</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>climatology</topic><topic>data collection</topic><topic>In situ precipitation measurements</topic><topic>MENA</topic><topic>Middle East</topic><topic>Northern Africa</topic><topic>Precipitation</topic><topic>rain gauges</topic><topic>Remote sensing</topic><topic>runoff</topic><topic>satellites</topic><topic>stream flow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kagone, S.</creatorcontrib><creatorcontrib>Velpuri, N.M.</creatorcontrib><creatorcontrib>Khand, K.</creatorcontrib><creatorcontrib>Senay, G.B.</creatorcontrib><creatorcontrib>van der Valk, M.R.</creatorcontrib><creatorcontrib>Goode, D.J.</creatorcontrib><creatorcontrib>Abu Hantash, S.</creatorcontrib><creatorcontrib>Al-Momani, T.M.</creatorcontrib><creatorcontrib>Momejian, N.</creatorcontrib><creatorcontrib>Eggleston, J.R.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Journal of arid environments</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kagone, S.</au><au>Velpuri, N.M.</au><au>Khand, K.</au><au>Senay, G.B.</au><au>van der Valk, M.R.</au><au>Goode, D.J.</au><au>Abu Hantash, S.</au><au>Al-Momani, T.M.</au><au>Momejian, N.</au><au>Eggleston, J.R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Satellite precipitation bias estimation and correction using in situ observations and climatology isohyets for the MENA region</atitle><jtitle>Journal of arid environments</jtitle><date>2023-08</date><risdate>2023</risdate><volume>215</volume><spage>105010</spage><pages>105010-</pages><artnum>105010</artnum><issn>0140-1963</issn><eissn>1095-922X</eissn><abstract>The availability of reliable gridded precipitation datasets is limited around the world, especially in arid regions. In this study, we utilized observations from satellite-based precipitation data and in situ rain gauge observations to determine a suitable precipitation dataset in the Middle East & North Africa (MENA) region. First, we evaluated seven different precipitation products using rain gauge observations. The validation was conducted at the daily, monthly, and annual time scales. Results indicated a weaker correlation between in situ rain gauge observation and satellite precipitation data at the daily time step (r: 0.02 to 0.44), mainly due to the lack of range in precipitation distribution. However, the agreement between precipitation estimates and in situ gauge observations improved at monthly (r: 0.02 to 0.66) and annual time scales (r: −0.22 to 0.57), indicating greater reliability of satellite-based precipitation at monthly and annual time scales. Based on the results and dataset availability, the Multi-Source Weighted-Ensemble Precipitation (MSWEP) was deemed suitable to create a bias-corrected new precipitation dataset for the MENA region. This study highlights the benefits of an adjusted regional precipitation product for hydrologic applications in the MENA region, such as streamflow or runoff estimation, to improve the reliability of the model outputs.
[Display omitted]
•Spatio-temporal distribution of precipitation is critical for addressing water issues.•Used satellite, gauge observation and climatology precipitation datasets.•Bias-corrected gridded precipitation dataset for the MENA region.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.jaridenv.2023.105010</doi><orcidid>https://orcid.org/0000-0002-2979-4655</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | climatology data collection In situ precipitation measurements MENA Middle East Northern Africa Precipitation rain gauges Remote sensing runoff satellites stream flow |
title | Satellite precipitation bias estimation and correction using in situ observations and climatology isohyets for the MENA region |
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