Macrophysical properties of specific cloud types from radiosonde and surface active remote sensing measurements over the ARM Southern Great Plains site
Accurate observation of clouds is challenging because of the high variability and complexity of cloud types and occurrences. By using the long-term cloud data collected during the ARM program at the Southern Great Plains central facility during 2001-2010, the consistencies and differences in the mac...
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description | Accurate observation of clouds is challenging because of the high variability and complexity of cloud types and occurrences. By using the long-term cloud data collected during the ARM program at the Southern Great Plains central facility during 2001-2010, the consistencies and differences in the macrophysical properties of clouds between radiosonde and ground-based active remote sensing are quantitatively evaluated according to six cloud types: low; mid-low (ML); high-mid-low; mid; high-mid (HM); and high. A similar variability trend is exhibited by the radiosonde and surface observations for the cloud fractions of the six cloud types. However, the magnitudes of the differences between the two methods are different among the six cloud types, with the largest difference seen in the high clouds. The distribution of the cloud-base height of the ML, mid, and HM clouds agrees in both methods, whereas large differences are seen in the cloud-top height for the ML and high clouds. The cloud thickness variations generally agree between the two datasets for the six cloud types. |
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The cloud thickness variations generally agree between the two datasets for the six cloud types.</description><subject>Cloud macrophysical properties</subject><subject>cloud types</subject><subject>Height</subject><subject>Methods</subject><subject>Plains</subject><subject>Properties</subject><subject>radiosonde</subject><subject>Radiosondes</subject><subject>Remote sensing</subject><subject>Variability</subject><subject>云宏观特征</subject><subject>云类型</subject><subject>探空</subject><subject>遥感</subject><issn>1674-2834</issn><issn>2376-6123</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>0YH</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><sourceid>DOA</sourceid><recordid>eNqFkdtuEzEQhlcIJKLSR0Cy4A4pwYe1vbmjqmip1ArE4dqa9Y4Tp7t2Ym9a8iS8Ll4SyiXyhcejb_4Zz19VrxldMNrQ90zpmjeiXnDK9IJxsZRUPqtmXGg1V-X9vJpNzHyCXlbnOW8opUxwpamYVb_uwKa4XR-yt9CTbYkxjR4ziY7kLVrvvCW2j_uOjIdtybsUB5Kg8zHH0CGB0JG8Tw5sie3oH5AkHOKIJGPIPqzIgFAAHDCMRfYBExnXSC6-3pFvcV_CFMh1QhjJlx58yCT7EV9VLxz0Gc9P91n14-rj98tP89vP1zeXF7dzK5kY57UQlDOpdNtwxSWIpmtpV05dW7rUgiJvaolSIbilXmpXo2ytqwFtu2StEGfVzVG3i7Ax2-QHSAcTwZs_iZhWBso-bI-m1Qpk0yoKja0dila1nW2sUK7tuKqxaL07aj1CcBBWZhP3KZTpTbdbrw_3P-_bySTKKJUFfnuEy8p3e8zjP5qXH3FZa8oLJY9UMSnnhO5pREbN5L_567-ZpM3J_1L34Vjng4tpgMeY-s6McOhjcgmC9dmI_0m8ObVex7DaFSOfeivNCk-1EL8BdD3EeQ</recordid><startdate>20170102</startdate><enddate>20170102</enddate><creator>ZHANG, Jin-Qiang</creator><creator>CHEN, Hong-Bin</creator><general>Taylor & Francis</general><general>KeAi Publishing Communications Ltd</general><general>KeAi Communications Co., Ltd</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W94</scope><scope>~WA</scope><scope>0YH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TN</scope><scope>7XB</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H96</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope><scope>DOA</scope></search><sort><creationdate>20170102</creationdate><title>Macrophysical properties of specific cloud types from radiosonde and surface active remote sensing measurements over the ARM Southern Great Plains site</title><author>ZHANG, Jin-Qiang ; 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By using the long-term cloud data collected during the ARM program at the Southern Great Plains central facility during 2001-2010, the consistencies and differences in the macrophysical properties of clouds between radiosonde and ground-based active remote sensing are quantitatively evaluated according to six cloud types: low; mid-low (ML); high-mid-low; mid; high-mid (HM); and high. A similar variability trend is exhibited by the radiosonde and surface observations for the cloud fractions of the six cloud types. However, the magnitudes of the differences between the two methods are different among the six cloud types, with the largest difference seen in the high clouds. The distribution of the cloud-base height of the ML, mid, and HM clouds agrees in both methods, whereas large differences are seen in the cloud-top height for the ML and high clouds. The cloud thickness variations generally agree between the two datasets for the six cloud types.</abstract><cop>Beijing</cop><pub>Taylor & Francis</pub><doi>10.1080/16742834.2017.1239505</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Cloud macrophysical properties cloud types Height Methods Plains Properties radiosonde Radiosondes Remote sensing Variability 云宏观特征 云类型 探空 遥感 |
title | Macrophysical properties of specific cloud types from radiosonde and surface active remote sensing measurements over the ARM Southern Great Plains site |
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