globalchange  > 气候减缓与适应
DOI: 10.1002/joc.5213
论文题名:
Update to the Global Climate Data package: analysis of empirical bias correction methods in the context of producing very high resolution climate projections
作者: Mosier T.M.; Hill D.F.; Sharp K.V.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期:2
起始页码: 825
结束页码: 840
语种: 英语
英文关键词: bias correction ; change factors ; climate models ; delta change method ; gridded climate ; monthly time-series ; precipitation ; temperature
Scopus关键词: Climate models ; Distribution functions ; Earth (planet) ; Image resolution ; Precipitation (chemical) ; Probability distributions ; Temperature ; Time series ; Bias correction ; Change factors ; Cumulative distribution function ; Delta change method ; Global historical climatology network ; Gridded climate ; Joint probability distributions ; Very high spatial resolutions ; Climate change ; air temperature ; climate modeling ; climate prediction ; correction ; empirical analysis ; global climate ; precipitation (climatology) ; time series analysis ; Alps ; Bangladesh ; Europe ; Ganges Delta ; India ; Oregon ; United States
英文摘要: While global climate models (GCMs) are useful for simulating climatic responses to perturbations in the Earth's climate system, there are many instances where higher spatial resolution information is necessary. In all instances, interpretation of interpolated or downscaled GCMs must be done cautiously because each method has its own set of assumptions and potential disadvantages. Here, we present an update to the Global Climate Data (GCD) package, which enables the package to efficiently bias correct and interpolate precipitation and air temperature output from GCM simulations to very high spatial resolutions using the delta change method. While the delta change method is relatively simple, it has previously been shown to enhance the physical representation of interpolated climate time-series compared to directly interpolating the gridded climate time-series to a higher spatial resolution. The bias correction methods programmed into the GCD package are univariate empirical quantile mapping (QM) and bivariate empirical joint bias correction (JBC). The skill of QM and JBC for improving GCM simulations processed with the delta change method is evaluated through comparing the cumulative distribution functions (CDFs) of the interpolated GCM simulations to the CDFs of Global Historical Climatology Network (GHCN) station observations for three test regions: Oregon (in the USA), the Alps (spanning several countries in Europe), and the Ganges Delta (in India and Bangladesh). We also assess the representation of precipitation and mean temperature joint probability distributions relative to those present in GHCN station observations. Overall, GCM simulations that are bias corrected with QM prior to being input to the delta change method perform best under our analysis. © 2017 Royal Meteorological Society
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117104
Appears in Collections:气候减缓与适应

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作者单位: Water Resources Graduate Program, School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, United States; School of Civil and Construction Engineering, Oregon State University, Corvallis, OR, United States; School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, United States

Recommended Citation:
Mosier T.M.,Hill D.F.,Sharp K.V.. Update to the Global Climate Data package: analysis of empirical bias correction methods in the context of producing very high resolution climate projections[J]. International Journal of Climatology,2018-01-01,38(2)
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