Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.5194/acp-17-9535-2017 |
Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks | |
Andersen, Hendrik1,2; Cermak, Jan1,2; Fuchs, Julia1,2; Knutti, Reto3; Lohmann, Ulrike3 | |
2017-08-08 | |
发表期刊 | ATMOSPHERIC CHEMISTRY AND PHYSICS |
ISSN | 1680-7316 |
EISSN | 1680-7324 |
出版年 | 2017 |
卷号 | 17期号:15 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany; Switzerland |
英文摘要 | The role of aerosols, clouds and their interactions with radiation remain among the largest unknowns in the climate system. Even though the processes involved are complex, aerosol-cloud interactions are often analyzed by means of bivariate relationships. In this study, 15 years (2001-2015) of monthly satellite-retrieved near-global aerosol products are combined with reanalysis data of various meteorological parameters to predict satellite-derived marine liquid-water cloud occurrence and properties by means of region-specific artificial neural networks. The statistical models used are shown to be capable of predicting clouds, especially in regions of high cloud variability. On this monthly scale, lower-tropospheric stability is shown to be the main determinant of cloud fraction and droplet size, especially in stratocumulus regions, while boundary layer height controls the liquid-water amount and thus the optical thickness of clouds. While aerosols show the expected impact on clouds, at this scale they are less relevant than some meteorological factors. Global patterns of the derived sensitivities point to regional characteristics of aerosol and cloud processes. |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000407330200004 |
WOS关键词 | AEROSOL OPTICAL DEPTH ; SATELLITE ; PRECIPITATION ; IMPACT ; ALBEDO ; WARM ; ATLANTIC ; MODIS ; SUSCEPTIBILITY ; INVIGORATION |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; 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/28341 |
专题 | 地球科学 |
作者单位 | 1.KIT, Inst Meteorol & Climate Res, Karlsruhe, Germany; 2.KIT, Inst Photogrammetry & Remote Sensing, Karlsruhe, Germany; 3.ETH, Inst Atmospher & Climate Sci, Zurich, Switzerland |
推荐引用方式 GB/T 7714 | Andersen, Hendrik,Cermak, Jan,Fuchs, Julia,et al. Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2017,17(15). |
APA | Andersen, Hendrik,Cermak, Jan,Fuchs, Julia,Knutti, Reto,&Lohmann, Ulrike.(2017).Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks.ATMOSPHERIC CHEMISTRY AND PHYSICS,17(15). |
MLA | Andersen, Hendrik,et al."Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks".ATMOSPHERIC CHEMISTRY AND PHYSICS 17.15(2017). |
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