DOI: 10.1175/JCLI-D-14-00734.1
Scopus记录号: 2-s2.0-84942906591
论文题名: External influences on modeled and observed cloud trends
作者: Marvel K. ; Zelinka M. ; Klein S.A. ; Bonfils C. ; Caldwell P. ; Doutriaux C. ; Santer B.D. ; Taylor K.E.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2015
卷: 28, 期: 12 起始页码: 4820
结束页码: 4840
语种: 英语
Scopus关键词: Atmospheric radiation
; Clouds
; Satellites
; Signal detection
; Cloud observations
; Detection and attributions
; External influences
; Multivariate signals
; Pattern detection
; Radiative forcings
; Response to external forcing
; Satellite observations
; Pattern recognition
; atmospheric modeling
; climate forcing
; cloud cover
; radiative forcing
; satellite data
; trend analysis
英文摘要: Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein areCMIP5 model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP andPATMOS-x. The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forcedCMIP5 models.Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions. © 2015 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50651
Appears in Collections: 气候变化事实与影响
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作者单位: Lawrence Livermore National Laboratory, Livermore, CA, United States; NASA Goddard Institute for Space Studies, Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, United States
Recommended Citation:
Marvel K.,Zelinka M.,Klein S.A.,et al. External influences on modeled and observed cloud trends[J]. Journal of Climate,2015-01-01,28(12)