Simulating the Refractive Index Structure Constant in the Surface Layer at Antarctica with a Mesoscale Model
In this paper, we introduce an approach wherein the Weather Research and Forecasting (WRF) model is coupled with the bulk aerodynamic method to estimate the surface layer refractive index structure constant (Cn2) above Taishan Station in Antarctica. First, we use the measured meteorological paramete...
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Veröffentlicht in: | The Astronomical journal 2018-01, Vol.155 (1), p.37 |
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description | In this paper, we introduce an approach wherein the Weather Research and Forecasting (WRF) model is coupled with the bulk aerodynamic method to estimate the surface layer refractive index structure constant (Cn2) above Taishan Station in Antarctica. First, we use the measured meteorological parameters to estimate Cn2 using the bulk aerodynamic method, and second, we use the WRF model output parameters to estimate Cn2 using the bulk aerodynamic method. Finally, the corresponding Cn2 values from the micro-thermometer are compared with the Cn2 values estimated using the WRF model coupled with the bulk aerodynamic method. We analyzed the statistical operators-the bias, root mean square error (RMSE), bias-corrected RMSE ( ), and correlation coefficient (Rxy)-in a 20 day data set to assess how this approach performs. In addition, we employ contingency tables to investigate the estimation quality of this approach, which provides complementary key information with respect to the bias, RMSE, , and Rxy. The quantitative results are encouraging and permit us to confirm the fine performance of this approach. The main conclusions of this study tell us that this approach provides a positive impact on optimizing the observing time in astronomical applications and provides complementary key information for potential astronomical sites. |
doi_str_mv | 10.3847/1538-3881/aa9e8f |
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First, we use the measured meteorological parameters to estimate Cn2 using the bulk aerodynamic method, and second, we use the WRF model output parameters to estimate Cn2 using the bulk aerodynamic method. Finally, the corresponding Cn2 values from the micro-thermometer are compared with the Cn2 values estimated using the WRF model coupled with the bulk aerodynamic method. We analyzed the statistical operators-the bias, root mean square error (RMSE), bias-corrected RMSE ( ), and correlation coefficient (Rxy)-in a 20 day data set to assess how this approach performs. In addition, we employ contingency tables to investigate the estimation quality of this approach, which provides complementary key information with respect to the bias, RMSE, , and Rxy. The quantitative results are encouraging and permit us to confirm the fine performance of this approach. The main conclusions of this study tell us that this approach provides a positive impact on optimizing the observing time in astronomical applications and provides complementary key information for potential astronomical sites.</description><identifier>ISSN: 0004-6256</identifier><identifier>EISSN: 1538-3881</identifier><identifier>DOI: 10.3847/1538-3881/aa9e8f</identifier><language>eng</language><publisher>Madison: The American Astronomical Society</publisher><subject>Aerodynamics ; Astronomy ; atmospheric effects ; Bias ; Computer simulation ; Contingency ; Correlation coefficient ; Correlation coefficients ; Error correction ; Mathematical models ; Meteorological parameters ; methods: data analysis ; methods: numerical ; Parameter estimation ; Refractive index ; Refractivity ; Root-mean-square errors ; site testing ; Surface boundary layer ; Surface layers ; turbulence ; Weather forecasting</subject><ispartof>The Astronomical journal, 2018-01, Vol.155 (1), p.37</ispartof><rights>2017. The American Astronomical Society.</rights><rights>Copyright IOP Publishing Jan 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c378t-d813d18bae5d071032cb76d632ddfcacc454d9423cf3760102fd226fc6fd6e23</citedby><cites>FETCH-LOGICAL-c378t-d813d18bae5d071032cb76d632ddfcacc454d9423cf3760102fd226fc6fd6e23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.3847/1538-3881/aa9e8f/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,780,784,27924,27925,38868,38890,53840,53867</link.rule.ids></links><search><creatorcontrib>Qing, Chun</creatorcontrib><creatorcontrib>Wu, Xiaoqing</creatorcontrib><creatorcontrib>Li, Xuebin</creatorcontrib><creatorcontrib>Tian, Qiguo</creatorcontrib><creatorcontrib>Liu, Dong</creatorcontrib><creatorcontrib>Rao, Ruizhong</creatorcontrib><creatorcontrib>Zhu, Wenyue</creatorcontrib><title>Simulating the Refractive Index Structure Constant in the Surface Layer at Antarctica with a Mesoscale Model</title><title>The Astronomical journal</title><addtitle>AJ</addtitle><addtitle>Astron. J</addtitle><description>In this paper, we introduce an approach wherein the Weather Research and Forecasting (WRF) model is coupled with the bulk aerodynamic method to estimate the surface layer refractive index structure constant (Cn2) above Taishan Station in Antarctica. First, we use the measured meteorological parameters to estimate Cn2 using the bulk aerodynamic method, and second, we use the WRF model output parameters to estimate Cn2 using the bulk aerodynamic method. Finally, the corresponding Cn2 values from the micro-thermometer are compared with the Cn2 values estimated using the WRF model coupled with the bulk aerodynamic method. We analyzed the statistical operators-the bias, root mean square error (RMSE), bias-corrected RMSE ( ), and correlation coefficient (Rxy)-in a 20 day data set to assess how this approach performs. In addition, we employ contingency tables to investigate the estimation quality of this approach, which provides complementary key information with respect to the bias, RMSE, , and Rxy. The quantitative results are encouraging and permit us to confirm the fine performance of this approach. The main conclusions of this study tell us that this approach provides a positive impact on optimizing the observing time in astronomical applications and provides complementary key information for potential astronomical sites.</description><subject>Aerodynamics</subject><subject>Astronomy</subject><subject>atmospheric effects</subject><subject>Bias</subject><subject>Computer simulation</subject><subject>Contingency</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Error correction</subject><subject>Mathematical models</subject><subject>Meteorological parameters</subject><subject>methods: data analysis</subject><subject>methods: numerical</subject><subject>Parameter estimation</subject><subject>Refractive index</subject><subject>Refractivity</subject><subject>Root-mean-square errors</subject><subject>site testing</subject><subject>Surface boundary layer</subject><subject>Surface layers</subject><subject>turbulence</subject><subject>Weather forecasting</subject><issn>0004-6256</issn><issn>1538-3881</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><recordid>eNp9kEtLw0AUhQdRsFb3Lge6NXYeyWS6LMVHoUWw3Q-387ApaRJnJmr_vakR3YirC4fvnAsfQteU3HKZ5mOacZlwKekYYGKlO0GDn-gUDQghaSJYJs7RRQg7QiiVJB2gclXs2xJiUb3guLX42ToPOhZvFs8rYz_wKvpWx9ZbPKurEKGKuKi-0FXrHWiLF3CwHkPE0yqC77oa8HsRtxjw0oY6aCgtXtbGlpfozEEZ7NX3HaL1_d169pgsnh7ms-ki0TyXMTGSckPlBmxmSE4JZ3qTCyM4M8Zp0DrNUjNJGdeO54JQwpxhTDgtnBGW8SEa9bONr19bG6La1a2vuo-KcZEJmRKWdxTpKe3rELx1qvHFHvxBUaKOStXRnzr6U73SrnLTV4q6-d38Bx_9gcOuIzNFFc9VYxz_BImihTM</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Qing, Chun</creator><creator>Wu, Xiaoqing</creator><creator>Li, Xuebin</creator><creator>Tian, Qiguo</creator><creator>Liu, Dong</creator><creator>Rao, Ruizhong</creator><creator>Zhu, Wenyue</creator><general>The American Astronomical Society</general><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>8FD</scope><scope>H8D</scope><scope>KL.</scope><scope>L7M</scope></search><sort><creationdate>20180101</creationdate><title>Simulating the Refractive Index Structure Constant in the Surface Layer at Antarctica with a Mesoscale Model</title><author>Qing, Chun ; Wu, Xiaoqing ; Li, Xuebin ; Tian, Qiguo ; Liu, Dong ; Rao, Ruizhong ; Zhu, Wenyue</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c378t-d813d18bae5d071032cb76d632ddfcacc454d9423cf3760102fd226fc6fd6e23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aerodynamics</topic><topic>Astronomy</topic><topic>atmospheric effects</topic><topic>Bias</topic><topic>Computer simulation</topic><topic>Contingency</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Error correction</topic><topic>Mathematical models</topic><topic>Meteorological parameters</topic><topic>methods: data analysis</topic><topic>methods: numerical</topic><topic>Parameter estimation</topic><topic>Refractive index</topic><topic>Refractivity</topic><topic>Root-mean-square errors</topic><topic>site testing</topic><topic>Surface boundary layer</topic><topic>Surface layers</topic><topic>turbulence</topic><topic>Weather forecasting</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Qing, Chun</creatorcontrib><creatorcontrib>Wu, Xiaoqing</creatorcontrib><creatorcontrib>Li, Xuebin</creatorcontrib><creatorcontrib>Tian, Qiguo</creatorcontrib><creatorcontrib>Liu, Dong</creatorcontrib><creatorcontrib>Rao, Ruizhong</creatorcontrib><creatorcontrib>Zhu, Wenyue</creatorcontrib><collection>Institute of Physics Open Access Journal Titles</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>The Astronomical journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Qing, Chun</au><au>Wu, Xiaoqing</au><au>Li, Xuebin</au><au>Tian, Qiguo</au><au>Liu, Dong</au><au>Rao, Ruizhong</au><au>Zhu, Wenyue</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulating the Refractive Index Structure Constant in the Surface Layer at Antarctica with a Mesoscale Model</atitle><jtitle>The Astronomical journal</jtitle><stitle>AJ</stitle><addtitle>Astron. J</addtitle><date>2018-01-01</date><risdate>2018</risdate><volume>155</volume><issue>1</issue><spage>37</spage><pages>37-</pages><issn>0004-6256</issn><eissn>1538-3881</eissn><abstract>In this paper, we introduce an approach wherein the Weather Research and Forecasting (WRF) model is coupled with the bulk aerodynamic method to estimate the surface layer refractive index structure constant (Cn2) above Taishan Station in Antarctica. First, we use the measured meteorological parameters to estimate Cn2 using the bulk aerodynamic method, and second, we use the WRF model output parameters to estimate Cn2 using the bulk aerodynamic method. Finally, the corresponding Cn2 values from the micro-thermometer are compared with the Cn2 values estimated using the WRF model coupled with the bulk aerodynamic method. We analyzed the statistical operators-the bias, root mean square error (RMSE), bias-corrected RMSE ( ), and correlation coefficient (Rxy)-in a 20 day data set to assess how this approach performs. In addition, we employ contingency tables to investigate the estimation quality of this approach, which provides complementary key information with respect to the bias, RMSE, , and Rxy. The quantitative results are encouraging and permit us to confirm the fine performance of this approach. The main conclusions of this study tell us that this approach provides a positive impact on optimizing the observing time in astronomical applications and provides complementary key information for potential astronomical sites.</abstract><cop>Madison</cop><pub>The American Astronomical Society</pub><doi>10.3847/1538-3881/aa9e8f</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aerodynamics Astronomy atmospheric effects Bias Computer simulation Contingency Correlation coefficient Correlation coefficients Error correction Mathematical models Meteorological parameters methods: data analysis methods: numerical Parameter estimation Refractive index Refractivity Root-mean-square errors site testing Surface boundary layer Surface layers turbulence Weather forecasting |
title | Simulating the Refractive Index Structure Constant in the Surface Layer at Antarctica with a Mesoscale Model |
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