气候变化领域集成服务门户(CCPortal): GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

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DOI	10.5194/gmd-12-4661-2019
	GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses
	Cao, Bin; Quan, Xiaojing; Brown, Nicholas; Stewart-Jones, Emilie; Gruber, Stephan
通讯作者	Gruber, S (通讯作者)
发表日期	2019
ISSN	1991-959X
EISSN	1991-9603
起始页码	4661
结束页码	4679
卷号	12 期号:11
英文摘要	Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses - currently ERA5, ERA-Interim, JRA-55 and MERRA-2 - to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for 10 terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulations and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.
关键词	PERMAFROST RESEARCH SITE LAND-SURFACE GROUND TEMPERATURES MODEL SIMULATIONS MACKENZIE DELTA ACTIVE-LAYER CLIMATE SNOW UNCERTAINTIES PRECIPITATION
语种	英语
WOS研究方向	Geology
WOS类目	Geosciences, Multidisciplinary
WOS记录号	WOS:000496540200002
来源期刊	GEOSCIENTIFIC MODEL DEVELOPMENT
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/259402
推荐引用方式 GB/T 7714	Cao, Bin,Quan, Xiaojing,Brown, Nicholas,et al. GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses[J]. 中国科学院青藏高原研究所,2019,12(11).
APA	Cao, Bin,Quan, Xiaojing,Brown, Nicholas,Stewart-Jones, Emilie,&Gruber, Stephan.(2019).GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses.GEOSCIENTIFIC MODEL DEVELOPMENT,12(11).
MLA	Cao, Bin,et al."GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses".GEOSCIENTIFIC MODEL DEVELOPMENT 12.11(2019).