Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates
With the projected expansion of arid/semi‐arid regions in a warming world, precipitation enhancement activities such as cloud seeding will become increasingly popular and relied upon. Due to the inherent costs, a successful planning is crucial, which involves accurate model predictions. In this stud...
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description | With the projected expansion of arid/semi‐arid regions in a warming world, precipitation enhancement activities such as cloud seeding will become increasingly popular and relied upon. Due to the inherent costs, a successful planning is crucial, which involves accurate model predictions. In this study, the usefulness of the Weather Research and Forecasting (WRF) model forecasts for guidance into seeding operations in the United Arab Emirates, where seeding activities have been conducted for more than two decades, is assessed. The WRF predictions are compared with ground‐based, satellite‐derived and radar reflectivity data, and in‐situ observations onboard the airplanes used to perform the seeding operations. WRF is found to have higher skill in simulating the observed cloud top pressure/temperature than the cloud fraction, with the model vertical velocity predictions also more skillful than those of the radar reflectivity. A stronger Arabian Heat Low (AHL) in the model leads to drier conditions which, together with a surface cold bias, limits the spatial extent and vertical depth of the simulated convective clouds. Development of convective rolls in the boundary layer is reported in both observations and simulations and their interaction with cold pools from convective clouds promote the development of secondary convection. Sensitivity to the choice of the Planetary Boundary Layer (PBL) scheme is also noticed, with the Yonsei University PBL scheme giving the best performance. When considering the two factors needed for a successful seeding operation that is, the presence of an updraft and clouds, the model‐predicted seeding regions largely match the areas where precipitation was observed. As the proposed WRF set up can be used operationally, the model forecasts will bring added value to the seeding activities in the country.
Key Points
The usefulness of Weather Research and Forecasting model forecasts for cloud seeding activities in the United Arab Emirates is assessed
Updrafts generally weaker in the model due to colder surface, but if the position of cells is accounted for the magnitudes are comparable
Seeding regions predicted by the model are in agreement with observed convective regions, and proposed set up can be used operationally |
doi_str_mv | 10.1029/2022EA002269 |
format | Article |
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Key Points
The usefulness of Weather Research and Forecasting model forecasts for cloud seeding activities in the United Arab Emirates is assessed
Updrafts generally weaker in the model due to colder surface, but if the position of cells is accounted for the magnitudes are comparable
Seeding regions predicted by the model are in agreement with observed convective regions, and proposed set up can be used operationally</description><identifier>ISSN: 2333-5084</identifier><identifier>EISSN: 2333-5084</identifier><identifier>DOI: 10.1029/2022EA002269</identifier><language>eng</language><publisher>Hoboken: John Wiley & Sons, Inc</publisher><subject>Arid regions ; Arid zones ; Boundary layers ; Cloud seeding ; Clouds ; cold pools ; convective rolls ; convective updrafts ; Meteorological research ; Numerical weather forecasting ; Planetary boundary layer ; Precipitation ; Precipitation (Meteorology) ; Radar ; Rain-making ; sea breeze ; summertime convection ; Weather forecasting ; Wind</subject><ispartof>Earth and Space Science, 2022-05, Vol.9 (5), p.n/a</ispartof><rights>2022 The Authors. Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3834-13d8d5360b4eca10803eb0fc1ff865fd765527ae5a471f7846407fe71a2f94963</citedby><cites>FETCH-LOGICAL-c3834-13d8d5360b4eca10803eb0fc1ff865fd765527ae5a471f7846407fe71a2f94963</cites><orcidid>0000-0002-8562-7368 ; 0000-0002-7587-0006</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2022EA002269$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2022EA002269$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,865,1418,11567,27929,27930,45579,45580,46057,46481</link.rule.ids></links><search><creatorcontrib>Fonseca, Ricardo</creatorcontrib><creatorcontrib>Francis, Diana</creatorcontrib><creatorcontrib>Nelli, Narendra</creatorcontrib><creatorcontrib>Farrah, Sufian</creatorcontrib><creatorcontrib>Wehbe, Youssef</creatorcontrib><creatorcontrib>Al Hosari, Taha</creatorcontrib><creatorcontrib>Al Mazroui, Alya</creatorcontrib><title>Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates</title><title>Earth and Space Science</title><description>With the projected expansion of arid/semi‐arid regions in a warming world, precipitation enhancement activities such as cloud seeding will become increasingly popular and relied upon. Due to the inherent costs, a successful planning is crucial, which involves accurate model predictions. In this study, the usefulness of the Weather Research and Forecasting (WRF) model forecasts for guidance into seeding operations in the United Arab Emirates, where seeding activities have been conducted for more than two decades, is assessed. The WRF predictions are compared with ground‐based, satellite‐derived and radar reflectivity data, and in‐situ observations onboard the airplanes used to perform the seeding operations. WRF is found to have higher skill in simulating the observed cloud top pressure/temperature than the cloud fraction, with the model vertical velocity predictions also more skillful than those of the radar reflectivity. A stronger Arabian Heat Low (AHL) in the model leads to drier conditions which, together with a surface cold bias, limits the spatial extent and vertical depth of the simulated convective clouds. Development of convective rolls in the boundary layer is reported in both observations and simulations and their interaction with cold pools from convective clouds promote the development of secondary convection. Sensitivity to the choice of the Planetary Boundary Layer (PBL) scheme is also noticed, with the Yonsei University PBL scheme giving the best performance. When considering the two factors needed for a successful seeding operation that is, the presence of an updraft and clouds, the model‐predicted seeding regions largely match the areas where precipitation was observed. As the proposed WRF set up can be used operationally, the model forecasts will bring added value to the seeding activities in the country.
Key Points
The usefulness of Weather Research and Forecasting model forecasts for cloud seeding activities in the United Arab Emirates is assessed
Updrafts generally weaker in the model due to colder surface, but if the position of cells is accounted for the magnitudes are comparable
Seeding regions predicted by the model are in agreement with observed convective regions, and proposed set up can be used operationally</description><subject>Arid regions</subject><subject>Arid zones</subject><subject>Boundary layers</subject><subject>Cloud seeding</subject><subject>Clouds</subject><subject>cold pools</subject><subject>convective rolls</subject><subject>convective updrafts</subject><subject>Meteorological research</subject><subject>Numerical weather forecasting</subject><subject>Planetary boundary layer</subject><subject>Precipitation</subject><subject>Precipitation (Meteorology)</subject><subject>Radar</subject><subject>Rain-making</subject><subject>sea breeze</subject><subject>summertime convection</subject><subject>Weather forecasting</subject><subject>Wind</subject><issn>2333-5084</issn><issn>2333-5084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kE1LAzEQhoMoKNWbPyDg1dZ8bbJ7XEpbhUrBtnhc0s2kRrZJTbZI_73RevAkgckw88w7w4vQLSUjSlj1wAhjk5rkKKszdMU458OClOL8T36JblJ6J4RQVkjCxBV6q1OClHbgexws7t8Av75M8XMw0GGdsMazgzPat4BXIXT4yfcBj7twMHgJYJzf4sUeou5d8Ak7_6Ow9q4Hg-uoN3iyc7kL6RpdWN0luPn9B2g9nazGj8P5YvY0rufDlpdcDCk3pSm4JBsBraakJBw2xLbU2lIW1ihZFExpKLRQ1KpSSEGUBUU1s5WoJB-gu5PuPoaPA6S-eQ-H6PPKhklZFRUVQmVqdKK2uoPGeRv6qNv8DOxcGzxYl-u1EoJRqbJ9A3R_GmhjSCmCbfbR7XQ8NpQ03_43f_3PODvhn1nn-C_bTJZLRvNV_As4tYNG</recordid><startdate>202205</startdate><enddate>202205</enddate><creator>Fonseca, Ricardo</creator><creator>Francis, Diana</creator><creator>Nelli, Narendra</creator><creator>Farrah, Sufian</creator><creator>Wehbe, Youssef</creator><creator>Al Hosari, Taha</creator><creator>Al Mazroui, Alya</creator><general>John Wiley & Sons, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IAO</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-8562-7368</orcidid><orcidid>https://orcid.org/0000-0002-7587-0006</orcidid></search><sort><creationdate>202205</creationdate><title>Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates</title><author>Fonseca, Ricardo ; Francis, Diana ; Nelli, Narendra ; Farrah, Sufian ; Wehbe, Youssef ; Al Hosari, Taha ; Al Mazroui, Alya</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3834-13d8d5360b4eca10803eb0fc1ff865fd765527ae5a471f7846407fe71a2f94963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Arid regions</topic><topic>Arid zones</topic><topic>Boundary layers</topic><topic>Cloud seeding</topic><topic>Clouds</topic><topic>cold pools</topic><topic>convective rolls</topic><topic>convective updrafts</topic><topic>Meteorological research</topic><topic>Numerical weather forecasting</topic><topic>Planetary boundary layer</topic><topic>Precipitation</topic><topic>Precipitation (Meteorology)</topic><topic>Radar</topic><topic>Rain-making</topic><topic>sea breeze</topic><topic>summertime convection</topic><topic>Weather forecasting</topic><topic>Wind</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fonseca, Ricardo</creatorcontrib><creatorcontrib>Francis, Diana</creatorcontrib><creatorcontrib>Nelli, Narendra</creatorcontrib><creatorcontrib>Farrah, Sufian</creatorcontrib><creatorcontrib>Wehbe, Youssef</creatorcontrib><creatorcontrib>Al Hosari, Taha</creatorcontrib><creatorcontrib>Al Mazroui, Alya</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Gale Academic OneFile</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Earth and Space Science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fonseca, Ricardo</au><au>Francis, Diana</au><au>Nelli, Narendra</au><au>Farrah, Sufian</au><au>Wehbe, Youssef</au><au>Al Hosari, Taha</au><au>Al Mazroui, Alya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates</atitle><jtitle>Earth and Space Science</jtitle><date>2022-05</date><risdate>2022</risdate><volume>9</volume><issue>5</issue><epage>n/a</epage><issn>2333-5084</issn><eissn>2333-5084</eissn><abstract>With the projected expansion of arid/semi‐arid regions in a warming world, precipitation enhancement activities such as cloud seeding will become increasingly popular and relied upon. Due to the inherent costs, a successful planning is crucial, which involves accurate model predictions. In this study, the usefulness of the Weather Research and Forecasting (WRF) model forecasts for guidance into seeding operations in the United Arab Emirates, where seeding activities have been conducted for more than two decades, is assessed. The WRF predictions are compared with ground‐based, satellite‐derived and radar reflectivity data, and in‐situ observations onboard the airplanes used to perform the seeding operations. WRF is found to have higher skill in simulating the observed cloud top pressure/temperature than the cloud fraction, with the model vertical velocity predictions also more skillful than those of the radar reflectivity. A stronger Arabian Heat Low (AHL) in the model leads to drier conditions which, together with a surface cold bias, limits the spatial extent and vertical depth of the simulated convective clouds. Development of convective rolls in the boundary layer is reported in both observations and simulations and their interaction with cold pools from convective clouds promote the development of secondary convection. Sensitivity to the choice of the Planetary Boundary Layer (PBL) scheme is also noticed, with the Yonsei University PBL scheme giving the best performance. When considering the two factors needed for a successful seeding operation that is, the presence of an updraft and clouds, the model‐predicted seeding regions largely match the areas where precipitation was observed. As the proposed WRF set up can be used operationally, the model forecasts will bring added value to the seeding activities in the country.
Key Points
The usefulness of Weather Research and Forecasting model forecasts for cloud seeding activities in the United Arab Emirates is assessed
Updrafts generally weaker in the model due to colder surface, but if the position of cells is accounted for the magnitudes are comparable
Seeding regions predicted by the model are in agreement with observed convective regions, and proposed set up can be used operationally</abstract><cop>Hoboken</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1029/2022EA002269</doi><tpages>29</tpages><orcidid>https://orcid.org/0000-0002-8562-7368</orcidid><orcidid>https://orcid.org/0000-0002-7587-0006</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Arid regions Arid zones Boundary layers Cloud seeding Clouds cold pools convective rolls convective updrafts Meteorological research Numerical weather forecasting Planetary boundary layer Precipitation Precipitation (Meteorology) Radar Rain-making sea breeze summertime convection Weather forecasting Wind |
title | Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates |
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