Dataset of Percentile-Based ETCCDI Temperature Extremes Indices for CMIP5 Model Output
1College of Global Change and Earth System Science，Beijing Normal University，Beijing 100875，China
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climate extremes,ETCCDI indices,CMIP5,semi-parametric quantile regression,Atmospheric Science Letters
Using daily maximum temperature (tasmax) and minimum temperature (tasmin) data for the 4 greenhouse gas emission scenarios (Historical, RCP2.6, RCP4.5 and RCP8.5) simulated by 19 CMIP5 (Coupled Model Intercomparison Project Phase 5) global climate models (GCMs) (https://pcmdi.llnl.gov/projects/cmip5/), the 6 percentile-based ETCCDI (http://wcrp-climate.org/etccdi) temperature extremes indices (TN10p, TN90p, TX10p, TX90p, CSDI and WSDI) were recalculated through the semi-parametric quantile regression approach proposed by Yang and Xu (Atmospheric Science Letters, 2017, DOI: 10.1002/asl.724.), to provide improved alternatives to those from the CLIMDEX (http://www.climdex.org) datasets. For the first 4 indices, the monthly values are also provided. The source RCP2.6 data are missing for CMCC-CM, CMCC-CMS and HadGEM2-CC GCMs. The period of the Historical scenario is from the individual start year of each model to 2005, and that of the RCPs is from 2006 to 2100. Their spatial resolutions are the same as those of their GCM sources. The data is archived in NetCDF format (*.nc) with the compressed data size of 4.78GB (39 GB original). In addition, the comparison was plotted between globally averaged time series of indices for each GCM and their counterparts from the CLIMDEX datasets.
Ministry of Education of P. R. China (2012LZD12)
YANG Chi.2017.Dataset of Percentile-Based ETCCDI Temperature Extremes Indices for CMIP5 Model Output ( CMIP5TEI ) ,Global Change Research Data Publishing & Repository,DOI:10.3974/geodb.2017.02.09.V1