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  Detection and attribution of large spatiotemporal extreme events in Earth observation data

Zscheischler, J., Mahecha, M., Harmeling, S., & Reichstein, M. (2013). Detection and attribution of large spatiotemporal extreme events in Earth observation data. Ecological Informatics, 15, 66-73. doi:10.1016/j.ecoinf.2013.03.004.

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資料種別: 学術論文

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BGC1779.pdf (出版社版), 2MB
 
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 作成者:
Zscheischler, Jakob1, 2, 著者           
Mahecha, M.D., 著者
Harmeling, S., 著者
Reichstein, Markus1, 著者           
所属:
1Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139              
2IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Max Planck Society, Hans-Knöll-Str. 10, 07745 Jena, DE, ou_1497757              

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 要旨: Latest climate projections suggest that both frequency and intensity of climate extremes will be substantially modified over the course of the coming decades. As a consequence, we need to understand to what extent and via which pathways climate extremes affect the state and functionality of terrestrial ecosystems and the associated biogeochemical cycles on a global scale. So far the impacts of climate extremes on the terrestrial biosphere were mainly investigated on the basis of case studies, while global assessments are widely lacking. In order to facilitate global analysis of this kind, we present a methodological framework that firstly detects spatiotemporally contiguous extremes in Earth observations, and secondly infers the likely pathway of the preceding climate anomaly. The approach does not require long time series, is computationally fast, and easily applicable to a variety of data sets with different spatial and temporal resolutions. The key element of our analysis strategy is to directly search in the relevant observations for spatiotemporally connected components exceeding a certain percentile threshold. We also put an emphasis on characterization of extreme event distribution, and scrutinize the attribution issue. We exemplify the analysis strategy by exploring the fraction of absorbed photosynthetically active radiation (fAPAR) from 1982 to 2011. Our results suggest that the hot spots of extremes in fAPAR lie in Northeastern Brazil, Southeastern Australia, Kenya and Tanzania. Moreover, we demonstrate that the size distribution of extremes follow a distinct power law. The attribution framework reveals that extremes in fAPAR are primarily driven by phases of water scarcity.

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 日付: 2013-03-252013-05
 出版の状態: オンラインで出版済み
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 識別子(DOI, ISBNなど): その他: BGC1779
DOI: 10.1016/j.ecoinf.2013.03.004
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出版物 1

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出版物名: Ecological Informatics
種別: 学術雑誌
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出版社, 出版地: Amsterdam [u.a.] : Elsevier
ページ: - 巻号: 15 通巻号: - 開始・終了ページ: 66 - 73 識別子(ISBN, ISSN, DOIなど): その他: 1878-0512
CoNE: https://pure.mpg.de/cone/journals/resource/1878-0512