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DOI | 10.1002/2017JD027432 |
Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery | |
Klein, Cornelia1; Belusic, Danijel2; Taylor, Christopher M.1,3 | |
2018-03-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2018 |
卷号 | 123期号:6页码:3035-3050 |
文章类型 | Article |
语种 | 英语 |
国家 | England; Sweden |
英文摘要 | Mesoscale convective systems (MCSs) are frequently associated with rainfall extremes and are expected to further intensify under global warming. However, despite the significant impact of such extreme events, the dominant processes favoring their occurrence are still under debate. Meteosat geostationary satellites provide unique long-term subhourly records of cloud top temperatures, allowing to track changes in MCS structures that could be linked to rainfall intensification. Focusing on West Africa, we show that Meteosat cloud top temperatures are a useful proxy for rainfall intensities, as derived from snapshots from the Tropical Rainfall Measuring Mission 2A25 product: MCSs larger than 15,000km(2) at a temperature threshold of -40 degrees C are found to produce 91% of all extreme rainfall occurrences in the study region, with 80% of the storms producing extreme rain when their minimum temperature drops below -80 degrees C. Furthermore, we present a new method based on 2-D continuous wavelet transform to explore the relationship between cloud top temperature and rainfall intensity for subcloud features at different length scales. The method shows great potential for separating convective and stratiform cloud parts when combining information on temperature and scale, improving the common approach of using a temperature threshold only. We find that below -80 degrees C, every fifth pixel is associated with deep convection. This frequency is doubled when looking at subcloud features smaller than 35km. Scale analysis of subcloud features can thus help to better exploit cloud top temperature data sets, which provide much more spatiotemporal detail of MCS characteristics than available rainfall data sets alone. |
英文关键词 | cloud top temperature extreme rain deep convection mesoscale convective system scale decomposition wavelets |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000430108900006 |
WOS关键词 | TRMM PRECIPITATION RADAR ; SUB-SAHARAN AFRICA ; WEST-AFRICA ; LIFE-CYCLE ; SATELLITE-OBSERVATIONS ; DIURNAL CYCLE ; RAINFALL ; VARIABILITY ; ALGORITHM ; PATTERNS |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/32848 |
专题 | 气候变化 |
作者单位 | 1.Ctr Ecol & Hydrol, Wallingford, Oxon, England; 2.Swedish Meteorol & Hydrol Inst, Norrkoping, Sweden; 3.Natl Ctr Earth Observat, Wallingford, Oxon, England |
推荐引用方式 GB/T 7714 | Klein, Cornelia,Belusic, Danijel,Taylor, Christopher M.. Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(6):3035-3050. |
APA | Klein, Cornelia,Belusic, Danijel,&Taylor, Christopher M..(2018).Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(6),3035-3050. |
MLA | Klein, Cornelia,et al."Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.6(2018):3035-3050. |
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