Dataset List

Vol.|Area

Oceanic region
Data Details

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:6186       Data Files Downloaded:1825      
Data Downloaded:403233.07 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.Dataset of Percentile-Based ETCCDI Temperature Extremes Indices for CMIP5 Model Output[DB/OL].Global Change Data Repository,2017.DOI:10.3974/geodb.2017.02.09.V1.

Data Product:

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