globalchange  > 气候减缓与适应
DOI: 10.1002/joc.5524
论文题名:
Changing temperature extremes based on CMIP5 output via semi-parametric quantile regression approach
作者: Yang C.; Li L.; Xu J.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期:9
起始页码: 3736
结束页码: 3748
语种: 英语
英文关键词: CLIMDEX ; CMIP5 ; empirical quantile estimator ; ETCCDI indices ; percentile-based indices ; representative concentration pathways ; semi-parametric quantile regression ; temperature extremes
Scopus关键词: Climate change ; Regression analysis ; CLIMDEX ; CMIP5 ; ETCCDI indices ; Percentile-based indices ; Quantile estimators ; Quantile regression ; Representative concentration pathways ; Temperature extremes ; Climate models ; air temperature ; climate change ; CMIP ; extreme event ; parameter estimation ; precipitation (climatology) ; regression analysis ; spatiotemporal analysis ; Amazon Basin ; Southeast Asia
英文摘要: The Expert Team on Climate Change Detection and Indices (ETCCDI) proposed a set of 27 core indices, describing extreme weather and climate events based on daily temperature and precipitation data. There are six percentile-based temperature extreme indices: four exceedance rates (ERs) (TN10p, TN90p, TX10p and TX90p) and two durations (cold spell duration [CSDI] and warm spell duration [WSDI]), derived by using percentiles for calendar days during the base period 1961–1990 as thresholds. The widely used empirical quantile (percentile) estimator or its bootstrap resampling adjustment may result in inhomogeneity in the derived annual ER series or in their linear trends, as well as seasonally varying biases in the monthly ER series. We present a new data set of the six indices for the historical and three representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5) scenarios simulated by 19 global climate models participating the Coupled Model Intercomparison Project Phase 5, generated via the semi-parametric quantile regression approach. Percentiles estimated upon the independence condition, inhomogeneity and seasonal biases are removed from the new data set, so that the changes in temperature extremes can be authentically revealed from the climatological distribution point of view. Compared with its counterpart produced by the CLIMDEX project, the new data set shows similar spatial and temporal change patterns under the RCP scenarios, but with much smaller magnitudes. By the end of 21st century, TN90p increases to 17.3, 24.5 and 40.0%, and TX90p increases to 16.9, 22.1 and 35.3%, under RCP2.6, RCP4.5 and RCP8.5, respectively. WSDI increases to 35 days under RCP8.5. For the three increasing indices, the most significant changes occur in tropical and extratropical regions. The greatest increases in TN90p and TX90p occur in southeast Asia and Amazon Basin, up to 85 and 68% in the summer under RCP8.5; that in WSDI occurs in Amazon Basin up to 120 days under RCP8.5. © 2018 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the 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/116844
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作者单位: College of Global Change and Earth System Science, Beijing Normal University, Beijing, China; State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China

Recommended Citation:
Yang C.,Li L.,Xu J.. Changing temperature extremes based on CMIP5 output via semi-parametric quantile regression approach[J]. International Journal of Climatology,2018-01-01,38(9)
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