气候变化领域集成服务门户(CCPortal): Spectral attenuation coefficients from measurements of light transmission in bare ice on the Greenland Ice Sheet

CCPortal

DOI	10.5194/tc-15-1931-2021
	Spectral attenuation coefficients from measurements of light transmission in bare ice on the Greenland Ice Sheet
	Cooper M.G.; Smith L.C.; Rennermalm A.K.; Tedesco M.; Muthyala R.; Leidman S.Z.; Moustafa S.E.; Fayne J.V.
发表日期	2021
ISSN	19940416
起始页码	1931
结束页码	1953
卷号	15 期号:4
英文摘要	Extreme weather and climate events such as floods, droughts, and heat waves can cause extensive societal damages. While various statistical and climate models have been developed for the purpose of simulating extremes, a consistent definition of extreme events is still lacking. Furthermore, to better assess the performance of the climate models, a variety of spatial forecast verification measures have been developed. However, in most cases, the spatial verification measures that are widely used to compare mean states do not have sufficient theoretical justification to benchmark extreme events. In order to alleviate inconsistencies when defining extreme events within different scientific communities, we propose a new generalized Spatio-Temporal Threshold Clustering method for the identification of extreme event episodes, which uses machine learning techniques to couple existing pattern recognition indices with high or low threshold choices. The method consists of five main steps: (1) construction of essential field quantities; (2) dimension reduction; (3) spatial domain mapping; (4) time series clustering; and (5) threshold selection. We develop and apply this method using a gridded daily precipitation dataset derived from rain gauge stations over the contiguous United States. We observe changes in the distribution of conditional frequency of extreme precipitation from large-scale well-connected spatial patterns to smaller-scale more isolated rainfall clusters, possibly leading to more localized droughts and heat waves, especially during the summer months. The proposed method automates the threshold selection process through a clustering algorithm and can be directly applicable in conjunction with modeling and spatial forecast verification of extremes. Additionally, it allows for the identification of synoptic-scale spatial patterns that can be directly traced to the individual extreme episodes, and it offers users the flexibility to select an extreme threshold that is linked to the desired geometrical properties. The approach can be applied to broad scientific disciplines. © 2021 EDP Sciences. All rights reserved.
英文关键词	climate modeling; detection method; drought; extreme event; flash flood; flood; measurement method; rainfall; Arctic; Greenland; Greenland Ice Sheet; United States
语种	英语
来源期刊	Cryosphere
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/202293
作者单位	Department of Geography, University of California, Los Angeles, CA 90027, United States; Pacific Northwest National Laboratory, Richland, WA 99354, United States; Institute at Brown for Environment and Society, Brown University, Providence, RI 02912, United States; Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI 02912, United States; Department of Geography, Rutgers, The State University of New Jersey, New Brunswick, NJ 08854, United States; NASA Goddard Institute for Space Studies, New York, NY 10025, United States; Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10964, United States
推荐引用方式 GB/T 7714	Cooper M.G.,Smith L.C.,Rennermalm A.K.,et al. Spectral attenuation coefficients from measurements of light transmission in bare ice on the Greenland Ice Sheet[J],2021,15(4).
APA	Cooper M.G..,Smith L.C..,Rennermalm A.K..,Tedesco M..,Muthyala R..,...&Fayne J.V..(2021).Spectral attenuation coefficients from measurements of light transmission in bare ice on the Greenland Ice Sheet.Cryosphere,15(4).
MLA	Cooper M.G.,et al."Spectral attenuation coefficients from measurements of light transmission in bare ice on the Greenland Ice Sheet".Cryosphere 15.4(2021).