Bulk Parameterization of the Snow Field in a Cloud Model
A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the "bulk water" mi...
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Veröffentlicht in: | Journal of climate and applied meteorology 1983-06, Vol.22 (6), p.1065-1092 |
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creator | Lin, Yuh-Lang Farley, Richard D. Orville, Harold D. |
description | A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the "bulk water" microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron processes and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outside the cloud. The melting of hail and snow are included in the model. Wet and dry growth of hail and shedding of rain from hail are simulated. The simulations show that the inclusion of snow has improved the realism of the results compared to a model without snow. The formation of virga from cloud anvils is now modeled. Addition of the snow field has resulted in the inclusion of more diverse and physically sound mechanisms for initiating the hail field, yielding greater potential for distinguishing dominant embryo types characteristically different from warm- and cold-based clouds. |
doi_str_mv | 10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2 |
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Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the "bulk water" microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron processes and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outside the cloud. The melting of hail and snow are included in the model. Wet and dry growth of hail and shedding of rain from hail are simulated. The simulations show that the inclusion of snow has improved the realism of the results compared to a model without snow. The formation of virga from cloud anvils is now modeled. Addition of the snow field has resulted in the inclusion of more diverse and physically sound mechanisms for initiating the hail field, yielding greater potential for distinguishing dominant embryo types characteristically different from warm- and cold-based clouds.</description><identifier>ISSN: 0733-3021</identifier><identifier>EISSN: 2163-5366</identifier><identifier>DOI: 10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2</identifier><language>eng</language><publisher>Boston, MA: American Meteorological Society</publisher><subject>Cloud physics ; Clouds ; Crystals ; Earth, ocean, space ; Exact sciences and technology ; External geophysics ; Graupel ; Hail ; Ice ; Melting ; Meteorology ; Precipitation ; Rain ; Snow</subject><ispartof>Journal of climate and applied meteorology, 1983-06, Vol.22 (6), p.1065-1092</ispartof><rights>Copyright 1983, American Meteorological Society (AMS)</rights><rights>1984 INIST-CNRS</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26180993$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26180993$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,777,781,800,27905,27906,57998,58231</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=9436799$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, Yuh-Lang</creatorcontrib><creatorcontrib>Farley, Richard D.</creatorcontrib><creatorcontrib>Orville, Harold D.</creatorcontrib><title>Bulk Parameterization of the Snow Field in a Cloud Model</title><title>Journal of climate and applied meteorology</title><description>A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the "bulk water" microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron processes and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outside the cloud. The melting of hail and snow are included in the model. Wet and dry growth of hail and shedding of rain from hail are simulated. The simulations show that the inclusion of snow has improved the realism of the results compared to a model without snow. The formation of virga from cloud anvils is now modeled. Addition of the snow field has resulted in the inclusion of more diverse and physically sound mechanisms for initiating the hail field, yielding greater potential for distinguishing dominant embryo types characteristically different from warm- and cold-based clouds.</description><subject>Cloud physics</subject><subject>Clouds</subject><subject>Crystals</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>External geophysics</subject><subject>Graupel</subject><subject>Hail</subject><subject>Ice</subject><subject>Melting</subject><subject>Meteorology</subject><subject>Precipitation</subject><subject>Rain</subject><subject>Snow</subject><issn>0733-3021</issn><issn>2163-5366</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1983</creationdate><recordtype>article</recordtype><recordid>eNo9kFFr2zAUhcXoYGm2nzDQwyjdg5MrXUuK2zFYTZMNMhJI9yxkWaJuHauVHEr362uT0Kf7cL5zLnyEzBnMGFNizgSHDHIBl6xY4Hfg_AcDKa5utpu73fInn8Gs3FzzD2TCmcRMoJRnZAIKMUPg7BM5T-kBAGGBYkIWN4f2kW5NNHvXu9j8N30TOho87e8d3XXhhS4b19a06aihZRsONf0batd-Jh-9aZP7crpT8m95e1f-ztab1Z_y1zqzKPM-U4X0lVe8qqTxVtWecQRpVeVryG0NFnPvPAqphFC28hVYKQsUufcChjJOycVx9ymG54NLvd43ybq2NZ0Lh6Q5MpYXSg3g6gjaGFKKzuun2OxNfNUM9GhOj-b0aE6P5vRgTo_m9NGc5hp0uRkGp-Tb6aVJ1rQ-ms426X2uyFGqohiwr0fsIfUhvsdcsgUMMb4BG356AQ</recordid><startdate>19830601</startdate><enddate>19830601</enddate><creator>Lin, Yuh-Lang</creator><creator>Farley, Richard D.</creator><creator>Orville, Harold D.</creator><general>American Meteorological Society</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>19830601</creationdate><title>Bulk Parameterization of the Snow Field in a Cloud Model</title><author>Lin, Yuh-Lang ; Farley, Richard D. ; Orville, Harold D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-796fbf72bb6afc7df12306c7bfd04cd0c34fef3567557cbfb0c669354ff507963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1983</creationdate><topic>Cloud physics</topic><topic>Clouds</topic><topic>Crystals</topic><topic>Earth, ocean, space</topic><topic>Exact sciences and technology</topic><topic>External geophysics</topic><topic>Graupel</topic><topic>Hail</topic><topic>Ice</topic><topic>Melting</topic><topic>Meteorology</topic><topic>Precipitation</topic><topic>Rain</topic><topic>Snow</topic><toplevel>online_resources</toplevel><creatorcontrib>Lin, Yuh-Lang</creatorcontrib><creatorcontrib>Farley, Richard D.</creatorcontrib><creatorcontrib>Orville, Harold D.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of climate and applied meteorology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, Yuh-Lang</au><au>Farley, Richard D.</au><au>Orville, Harold D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bulk Parameterization of the Snow Field in a Cloud Model</atitle><jtitle>Journal of climate and applied meteorology</jtitle><date>1983-06-01</date><risdate>1983</risdate><volume>22</volume><issue>6</issue><spage>1065</spage><epage>1092</epage><pages>1065-1092</pages><issn>0733-3021</issn><eissn>2163-5366</eissn><abstract>A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the "bulk water" microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron processes and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outside the cloud. The melting of hail and snow are included in the model. Wet and dry growth of hail and shedding of rain from hail are simulated. The simulations show that the inclusion of snow has improved the realism of the results compared to a model without snow. The formation of virga from cloud anvils is now modeled. Addition of the snow field has resulted in the inclusion of more diverse and physically sound mechanisms for initiating the hail field, yielding greater potential for distinguishing dominant embryo types characteristically different from warm- and cold-based clouds.</abstract><cop>Boston, MA</cop><pub>American Meteorological Society</pub><doi>10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2</doi><tpages>28</tpages><oa>free_for_read</oa></addata></record> |
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issn | 0733-3021 2163-5366 |
language | eng |
recordid | cdi_proquest_miscellaneous_23114977 |
source | Jstor Complete Legacy |
subjects | Cloud physics Clouds Crystals Earth, ocean, space Exact sciences and technology External geophysics Graupel Hail Ice Melting Meteorology Precipitation Rain Snow |
title | Bulk Parameterization of the Snow Field in a Cloud Model |
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