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Dataset of Percentile-Based ETCCDI Temperature Extremes Indices for CMIP5 Model Output


YANG Chi1
1College of Global Change and Earth System Science,Beijing Normal University,Beijing 100875,China

DOI:10.3974/geodb.2017.02.09.V1

Published:Mar. 2017

Visitors:429       Data Files Downloaded:982      
Data Downloaded:214731.43 MB      Citations:

Key Words:

climate extremes,ETCCDI indices,CMIP5,semi-parametric quantile regression,Atmospheric Science Letters

Abstract:

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.

Foundation Item:

Ministry of Education of P. R. China (2012LZD12)

Data Citation:

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

Data Product:

ID Data Name Data Size Operation
1 BNU-ESM.zip 74891.03kb DownLoad
2 CMCC-CMS.zip 163799.14kb DownLoad
3 CMCC-CM_1.zip 475723.51kb DownLoad
4 CMCC-CM_2.zip 295771.00kb DownLoad
5 CMCC-CM_3.zip 285161.14kb DownLoad
6 CNRM-CM5.zip 343443.35kb DownLoad
7 GFDL-CM3.zip 148046.98kb DownLoad
8 GFDL-ESM2G.zip 147434.65kb DownLoad
9 GFDL-ESM2M.zip 147315.14kb DownLoad
10 HadGEM2-AO.zip 301754.75kb DownLoad
11 HadGEM2-CC.zip 235786.14kb DownLoad
12 HadGEM2-ES.zip 303426.31kb DownLoad
13 IPSL-CM5A-LR.zip 114707.08kb DownLoad
14 IPSL-CM5A-MR.zip 240036.91kb DownLoad
15 MIROC-ESM-CHEM.zip 97867.38kb DownLoad
16 MIROC-ESM.zip 97880.40kb DownLoad
17 MIROC5.zip 349985.61kb DownLoad
18 MPI-ESM-LR.zip 210296.45kb DownLoad
19 MPI-ESM-MR.zip 210918.23kb DownLoad
20 MRI-CGCM3_1.zip 350181.38kb DownLoad
21 MRI-CGCM3_2.zip 266830.88kb DownLoad
22 NorESM1-M.zip 157938.88kb DownLoad
23 _FileList.xlsx 28.76kb DownLoad
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum