CMIP6 CMIP MPI-M MPI-ESM1-2-LR historical r10i1p1f1 Amon pr gn v20190710

Wieners, Karl-Hermann et al.

Dataset
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.CMIP.MPI-M.MPI-ESM1-2-LR.historical' 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 MPI-ESM1.2-LR climate model, released in 2017, includes the following components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the Max Planck Institute for Meteorology, Hamburg 20146, Germany (MPI-M) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: none, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 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
1850-01-16 to 2014-12-16 (gregorian)
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Access constraints
registered users
Size
104.31 MiB (109373095 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2032-07-10
Download Permission
Please login to check permission and download options
Cite as
[ Derived from parent entry - See data hierarchy tab ]
Wieners, Karl-Hermann; Giorgetta, Marco; Jungclaus, Johann; Reick, Christian; Esch, Monika; Bittner, Matthias; Legutke, Stephanie; Schupfner, Martin; Wachsmann, Fabian; Gayler, Veronika; Haak, Helmuth; de Vrese, Philipp; Raddatz, Thomas; Mauritsen, Thorsten; von Storch, Jin-Song; Behrens, Jörg; Brovkin, Victor; Claussen, Martin; Crueger, Traute; Fast, Irina; Fiedler, Stephanie; Hagemann, Stefan; Hohenegger, Cathy; Jahns, Thomas; Kloster, Silvia; Kinne, Stefan; Lasslop, Gitta; Kornblueh, Luis; Marotzke, Jochem; Matei, Daniela; Meraner, Katharina; Mikolajewicz, Uwe; Modali, Kameswarrao; Müller, Wolfgang; Nabel, Julia; Notz, Dirk; Peters-von Gehlen, Karsten; Pincus, Robert; Pohlmann, Holger; Pongratz, Julia; Rast, Sebastian; Schmidt, Hauke; Schnur, Reiner; Schulzweida, Uwe; Six, Katharina; Stevens, Bjorn; Voigt, Aiko; Roeckner, Erich (2023). IPCC DDC: MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP historical. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/AR6.C6CMMXML2hi

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

Is source of

[1] IPCC. (2023). FAQ 3.3, Figure 1 | Pattern correlations between models and observations of three different variables: surface air temperature, precipitation and sea level pressure. In IPCC, 2023: Chapter 3. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-3/faq-3-3-figure-1
[2] IPCC. (2023). Figure 3.15 | Observed and simulated time series of anomalies in zonal average annual mean precipitation. In IPCC, 2023: Chapter 3. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-3/figure-3-15
[3] 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
[4] IPCC. (2023). Figure 3.41 | Summary figure showing simulated and observed changes in key large-scale indicators of climate change across the climate system, for continental, ocean basin and larger scales. In IPCC, 2023: Chapter 3. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-3/figure-3-41
[5] DOI Bock, L. (2023). Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.15 (v20211001). doi:10.5285/a6b79b1abac64d72a1a3f2fcf62ee81e
[6] 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
[7] DOI Bock, L. (2023). Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.41 (v20211028). doi:10.5285/43b0c376ad184543a1bbceeceec0e85d
[8] DOI Bock, L. (2023). Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for FAQ 3.3, Figure 1 (v20220615). doi:10.5285/afe80eb32a1c4164a3b84396c6d7a5d6
[9] IPCC. (2023). Code for Figure 3.15 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-3_Fig15
[10] 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
[11] IPCC. (2023). Code for Figure 3.41 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-3_Fig41
[12] IPCC. (2023). Code for Figure FAQ3.3.1 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-3_FAQ3_Fig01
[13] DOI Schurer, A.; Kazeroni, R. (2022). IPCC AR6 WGI - Figure 3.14. doi:10.5281/zenodo.6778068
[14] DOI Bock, L.; Barreiro, M.; Eyring, V. (2022). IPCC AR6 WGI - Figure 3.15. doi:10.5281/zenodo.6656240
[15] DOI Bock, L.; Gillett, N. (2022). IPCC AR6 WGI - Figure 3.41. doi:10.5281/zenodo.6656913
[16] DOI IPCC-WG1. (2022). IPCC AR6 WGI - FAQ3_Fig01. doi:10.5281/zenodo.6786682

Parent

CMIP6 CMIP MPI-M MPI-ESM1-2-LR historical
Details
[Entry acronym: C6CMMXML2hir10111Amprgn90710] [Entry id: 3914062]