DOI: 10.1002/jgrd.50765
论文题名: Performance of climate field reconstruction methods over multiple seasons and climate variables
作者: Dannenberg M.P. ; Wise E.K.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 17 起始页码: 9595
结束页码: 9610
语种: 英语
英文关键词: Canonical Correlation Analysis
; Climate Field Reconstruction
; Dendrochronology
; Paleoclimatology
; Point-by-Point Regression
; Regularized Expectation Maximization
Scopus关键词: Atmospheric temperature
; Climatology
; Forestry
; Maximum principle
; Canonical correlation analysis
; Climate field reconstruction
; Dendrochronology
; Paleoclimatology
; Point-by-Point Regression
; Regularized expectation maximizations
; Wave effects
; calibration
; canonical analysis
; climate variation
; data set
; dendrochronology
; instrumentation
; paleoclimate
; performance assessment
; proxy climate record
; reconstruction
; regression analysis
; seasonality
; temporal analysis
; tree ring
英文摘要: Studies of climate variability require long time series of data but are limited by the absence of preindustrial instrumental records. For such studies, proxy-based climate reconstructions, such as those produced from tree-ring widths, provide the opportunity to extend climatic records into preindustrial periods. Climate field reconstruction (CFR) methods are capable of producing spatially-resolved reconstructions of climate fields. We assessed the performance of three commonly used CFR methods (canonical correlation analysis, point-by-point regression, and regularized expectation maximization) over spatially-resolved fields using multiple seasons and climate variables. Warm- and cool-season geopotential height, precipitable water, and surface temperature were tested for each method using tree-ring chronologies. Spatial patterns of reconstructive skill were found to be generally consistent across each of the methods, but the robustness of the validation metrics varied by CFR method, season, and climate variable. The most robust validation metrics were achieved with geopotential height, the October through March temporal composite, and the Regularized Expectation Maximization method. While our study is limited to assessment of skill over multidecadal (rather than multi-centennial) time scales, our findings suggest that the climate variable of interest, seasonality, and spatial domain of the target field should be considered when assessing potential CFR methods for real-world applications. Key Points CCA, PPR, and RegEM climate field reconstruction (CFR) methods were comparedTree-ring widths calibrated against seasonal GPH, temp, and precipitable waterMost robust method depends on season, climate variable, and location of interest ©2013. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63323
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: Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3220, United States
Recommended Citation:
Dannenberg M.P.,Wise E.K.. Performance of climate field reconstruction methods over multiple seasons and climate variables[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(17)