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AVHRR warm‐season cloud climatologies under various synoptic regimes across the Iberian Peninsula and the Balearic Islands
ABSTRACT In this study we retrieved the spatial distribution of mid‐afternoon clouds under various synoptic regimes across the Iberian Peninsula and the Balearic Islands for the warm/convective‐season, from May to October. Accurate daily cloud masks were derived by applying a daytime over land multi...
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Published in: | International journal of climatology 2015-06, Vol.35 (8), p.1984-2002 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | ABSTRACT
In this study we retrieved the spatial distribution of mid‐afternoon clouds under various synoptic regimes across the Iberian Peninsula and the Balearic Islands for the warm/convective‐season, from May to October. Accurate daily cloud masks were derived by applying a daytime over land multispectral convective cloud detection algorithm spanning 15 years (1997–2011) of Advanced Very High Resolution Radiometer (AVHRR) HRPT data. We processed a total of 2094 afternoon overpasses (between 1230 and 1720 UTC) corresponding to the NOAA‐14, NOAA‐16 and NOAA‐18 spacecrafts, and stratified daily cloud masks as a function of: (1) the automated circulation‐typing scheme of Jenkinson and Collinson and (2) the prevailing wind field at 850 hPa. The AVHRR warm‐season cloud climatology with high spatial resolution (1.1‐km) identified six representative areas (regions of interest; ROIs) with intensified cloud activity (hot spots). The results also revealed the typical spatial distribution of clouds for each synoptic regime across the whole region, identified the synoptic patterns and wind regimes under which high amounts of clouds occur for each ROIs, and showed that strong boundary layer winds in general increase the frequency of clouds. The regional cloud climatology presented here could be useful, e.g. to improve convective short‐term forecasting by identifying active cloud areas for each atmospheric type. |
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ISSN: | 0899-8418 1097-0088 1097-0088 |
DOI: | 10.1002/joc.4102 |