globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2016JD026332
论文题名:
Regional reanalysis without local data: Exploiting the downscaling paradigm
作者: von Storch H.; Feser F.; Geyer B.; Klehmet K.; Li D.; Rockel B.; Schubert-Frisius M.; Tim N.; Zorita E.
刊名: Journal of Geophysical Research: Atmospheres
出版年: 2017
卷: 122, 期:16
起始页码: 8631
结束页码: 8649
语种: 英语
英文关键词: Addd Value ; Dynamical Downcsaling ; Gobal Downscaling
英文摘要: This paper demonstrates two important aspects of regional dynamical downscaling of multidecadal atmospheric reanalysis. First, that in this way skillful regional descriptions of multidecadal climate variability may be constructed in regions with little or no local data. Second, that the concept of large-scale constraining allows global downscaling, so that global reanalyses may be completed by additions of consistent detail in all regions of the world. Global reanalyses suffer from inhomogeneities. However, their large-scale componenst are mostly homogeneous; Therefore, the concept of downscaling may be applied to homogeneously complement the large-scale state of the reanalyses with regional detail—wherever the condition of homogeneity of the description of large scales is fulfilled. Technically, this can be done by dynamical downscaling using a regional or global climate model, which's large scales are constrained by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional weather risks—in particular marine risks—was identified. We have run this system in regions with reduced or absent local data coverage, such as Central Siberia, the Bohai and Yellow Sea, Southwestern Africa, and the South Atlantic. Also, a global simulation was computed, which adds regional features to prescribed global dynamics. Our cases demonstrate that spatially detailed reconstructions of the climate state and its change in the recent three to six decades add useful supplementary information to existing observational data for midlatitude and subtropical regions of the world. ©2017. American Geophysical Union. All Rights Reserved.
资助项目: "The work was partly supported through the Cluster of Excellence “CliSAP” (EXC177), Universität Hamburg, funded through the German Research Foundation (DFG). It is a contribution to the Helmholtz Climate Initiative REKLIM (Regional Climate Change), a joint research project of the Helmholtz Association of German research centers (HGF). The CCLM is the community model of the German climate research (www.clm-community.eu). The German Climate Computing Center (DKRZ) provided the computer hardware for the regional and global climate model simulations. The simulation data are accessible at the German Climate Computing center (DKRZ): the BYS data via https://cera-www.dkrz.de/WDCC/ui/cerasearch/q?query=*:*&project_name_ss=coastDat-2%20%28coastDat-2%29 ; the Siberian data at doi:10.1594/WDCC/COSMO-CLM_siberia ; the South Atlantic data at https://www.dkrz.de/Nutzerportal-en/doku/hpss ; and the global simulations at http://icdc.cen.uni-hamburg.de/1/daten/atmosphere/echam6-climate-reconstruction.html. Sources for observational data are listed in the text and in Appendix A.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62603
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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作者单位: Institute of Coastal Research, Helmholtz Zentrum Geesthacht, Geesthacht, Germany; CliSAP, University of Hamburg, Hamburg, Germany; Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China; Institute for Geology, University of Hamburg, Hamburg, Germany

Recommended Citation:
von Storch H.,Feser F.,Geyer B.,et al. Regional reanalysis without local data: Exploiting the downscaling paradigm[J]. Journal of Geophysical Research: Atmospheres,2017-01-01,122(16)
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