DOI: 10.1175/JCLI-D-17-0243.1
Scopus记录号: 2-s2.0-85041650779
论文题名: The sensitivity of daily temperature variability and extremes to dataset choice
作者: Gross M.H. ; Donat M.G. ; Alexander L.V. ; Sisson S.A.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2018
卷: 31, 期: 4 起始页码: 1337
结束页码: 1359
语种: 英语
英文关键词: Climate change
; Climate variability
; Extreme events
; Statistics
; Surface observations
; Trends
Scopus关键词: Climate change
; Climatology
; Distribution functions
; Statistics
; Temperature distribution
; Climate variability
; Empirical probabilities
; Extreme events
; Global historical climatology network
; Mediterranean region
; Surface observation
; Temperature variability
; Trends
; Probability distributions
; climate change
; climate variation
; data set
; extreme event
; global warming
; Northern Hemisphere
; observational method
; statistical analysis
; temperature anomaly
; trend analysis
; Africa
; Mediterranean Region
英文摘要: Robust conclusions regarding changes in the temperature distribution rely on the accuracy and reliability of the input datasets used. Differences between methodologies and datasets in previous studies add uncertainty when comparing and quantifying findings. Here, the authors investigate the sensitivity of assessing global and regional temperature variability and extremes over 1980-2014 in gridded datasets of daily temperature anomalies. A gridded in situ-based dataset, Hadley Centre Global Historical Climatology Network-Daily (HadGHCND), is compared against several commonly used reanalysis products by assessing both the entire distribution and the tails of the distribution. Empirical probability distribution functions show sensitivity to the input dataset when estimating aspects such as standard deviation and skewness, with the mean showing robust results for most regions, irrespective of dataset choice. Standard deviation is especially sensitive, with larger disagreements between datasets for some regions more than others, such as Africa and the Mediterranean region, and with larger differences in minimum temperatures compared with maximum temperatures. Estimates of extreme parameters also show sensitivity to dataset choice, particularly in the lower tails and for daily minimum temperature anomalies. Comparing changes in the means and the extremes of the temperature distributions, the cold extremes in the lower tails have been warming at a faster rate than the mean of the entire distribution for much of the Northern Hemisphere extratropics, with warm extremes warming at a faster rate than the mean in some subtropical regions. These documented sensitivities call for caution when assessing changes in temperature variability and extremes, as dataset choice can have substantial effects on results. © 2018 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/111686
Appears in Collections: 气候减缓与适应
There are no files associated with this item.
作者单位: Climate Change Research Centre, ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, NSW, Australia; School of Mathematics and Statistics, University of New South Wales, Sydney, NSW, Australia
Recommended Citation:
Gross M.H.,Donat M.G.,Alexander L.V.,et al. The sensitivity of daily temperature variability and extremes to dataset choice[J]. Journal of Climate,2018-01-01,31(4)