CMIP6 ScenarioMIP CCCR-IITM IITM-ESM ssp245 r1i1p1f1 Amon pr gn v20200915

hdl:21.14100/d385b2ca-3edb-3e74-bae7-41ff9141dce6

Singh, Manmeet et al.

Dataset
CCCR-IITMclimate changeCMIP6IITM-ESMIPCCIPCC-AR6IPCC-DDCprScenarioMIPssp245
Summary
[ Derived from parent entry - See data hierarchy tab ]

These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CCCR-IITM.IITM-ESM.ssp245' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The IITM-ESM climate model, released in 2015, includes the following components: aerosol: prescribed MAC-v2, atmos: IITM-GFSv1 (T62L64, Linearly Reduced Gaussian Grid; 192 x 94 longitude/latitude; 64 levels; top level 0.2 mb), land: NOAH LSMv2.7.1, ocean: MOM4p1 (tripolar, primarily 1deg; 360 x 200 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: TOPAZv2.0, seaIce: SISv1.0. The model was run by the Centre for Climate Change Research, Indian Institute of Tropical Meteorology Pune, Maharashtra 411 008, India (CCCR-IITM) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
Project
IPCC-AR6_CMIP6 (Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets)
Location(s)
global
Spatial Coverage
Longitude 0 to 360 Latitude -90 to 90
Temporal Coverage
2015-01-16 to 2099-12-16 (gregorian)
Use constraints
Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Access constraints
registered users
Size
63.95 MiB (67057503 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Review Date
2020-09-15
Download Permission
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Preview data headers
Cite as
[ Derived from parent entry - See data hierarchy tab ]
Singh, Manmeet; Panickal, Swapna; Narayanasetti, Sandeep; Gopinathan, Prajeesh A.; Choudhury, Ayantika Dey; Raghavan, Krishnan (2023). IPCC DDC: CCCR-IITM IITM-ESM model output prepared for CMIP6 ScenarioMIP ssp245. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/AR6.C6SPCIIITs245

BibTeX RIS
VariableCodeAggregationUnit
precipitation_flux
CF
pr (IPCC_DDC_AR6: 780)
monkg m-2 s-1

Is referenced by

[1] DOI IPCC Data Distribution Centre. (2025). CMIP6 input data usage information for IPCC WGI AR6 figure 3.14. doi:10.5281/zenodo.14986340
[2] DOI IPCC Data Distribution Centre. (2025). CMIP6 input data usage information for IPCC WGI AR6 figure 8.14. doi:10.5281/zenodo.14986455

Is source of

[1] IPCC. (2023). Figure 8.14 | Projected long-term relative changes in seasonal mean precipitation. In IPCC, 2023: Chapter 8. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-8/figure-8-14
[2] IPCC. (2023). Figure 8.22 | Projected regional monsoons precipitation changes. In IPCC, 2023: Chapter 8. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-8/figure-8-22
[3] IPCC. (2023). Box 8.2 Figure 1 | Projected long-term changes in precipitation seasonality. . https://www.ipcc.ch/report/ar6/wg1/figures/chapter-8/box-8-2-figure-1
[4] IPCC. (2023). Figure 4.2 | Selected indicators of global climate change from CMIP6 historical and scenario simulations. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-2
[5] IPCC. (2023). Figure 4.4 | CMIP6 annual mean precipitation changes (%) from historical and scenario simulations. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-4
[6] IPCC. (2023). Figure 4.14 | Time series of global land monsoon precipitation and Northern Hemisphere summer monsoon (NHSM) circulation index anomalies. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-14
[7] IPCC. (2023). Figure 3.14 | Wet (a) and dry (b) region tropical mean (30°S–30°N) annual precipitation anomalies. In IPCC, 2023: Chapter 3. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-3/figure-3-14
[8] IPCC. (2023). Figure 4.10 | Changes in amplitude of ENSO Variability. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-10
[9] DOI Kazeroni, R.; Schurer, A.; Bock, L. (2023). Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.14 (v20211001). doi:10.5285/8c9c35e4c877440abcaa10b9aa173c33
[10] DOI Sénési, S. (2023). Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.14 (v20220718). doi:10.5285/bbf5ae3b78c44bf28ccb17b487d58a94
[11] IPCC. (2023). Code for Figure 3.14 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-3_Fig14
[12] IPCC. (2023). Code for Figure 8.14 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-8
[13] IPCC. (2023). Code for Box8.2 Figure 1 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-8
[14] DOI Sénési, Stéphane. (2021). IPCC WGI AR6 Chapter 8. doi:10.5281/zenodo.5217343
[15] DOI Schurer, A.; Kazeroni, R. (2022). IPCC AR6 WGI - Figure 3.14. doi:10.5281/zenodo.6778068
[16] DOI Sénési, Stéphane. (2021). IPCC WGI AR6 Chapter 8. doi:10.5281/zenodo.5217343

Parent

CMIP6 ScenarioMIP CCCR-IITM IITM-ESM ssp245
Details

Parent project(s)

Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets

[Entry acronym: C6SPCIIITs245r111Amprgn00915] [Entry id: 3915543]