- Latest period
- 2100-12-01
- Value · °C
- 19.86
- Valid periods
- 1032 / 1032
- Latest area coverage
- 100.0%
- Spatial scale
- country
- Release status
- Provisional / unconfirmed
Absolute values; no anomaly baseline applied. Reviewed 2026-09-15.
Method, coverage and provenance
Area-weighted regional monthly means from 26 CMIP6 models under SSP5-8.5. Value is the across-model median; the p10 and p90 fields carry the LOWEST and HIGHEST member values, not interpolated percentiles, because five named models are not a sample a percentile can be read from. Temperature converted from K; precipitation converted from kg m-2 s-1 to mm per month using each model's OWN calendar month length. Native calendars: 360_day: 2 (KACE-1-0-G, UKESM1-0-LL); 365_day: 9 (BCC-CSM2-MR, CAMS-CSM1-0, CESM2, CMCC-CM2-SR5, CanESM5-CanOE, FGOALS-f3-L, FGOALS-g3, INM-CM4-8, INM-CM5-0); gregorian: 6 (CNRM-CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, IPSL-CM6A-LR, MIROC-ES2L, MIROC6); julian: 1 (IITM-ESM); noleap: 4 (GFDL-ESM4, MCM-UA-1-0, NorESM2-MM, TaiESM1); proleptic_gregorian: 4 (ACCESS-CM2, AWI-CM-1-1-MR, MPI-ESM1-2-LR, MRI-ESM2-0). Output periods are real calendar months. Each model is weighted on its own grid; the provenance grid figures describe the COARSEST member, which bounds the ensemble, rather than any one model's grid.
26 CMIP6 models, one run each. One run per model is deliberate: a model contributing fifty members would otherwise outvote the rest of the archive. The value is the across-model mean and the p10/p90 fields are the 10th and 90th percentiles of the member distribution, the range the IPCC AR6 Atlas reports for regional projections. Members are weighted by climwip-independence/1: the ClimWIP independence term (Knutti et al. 2017; Brunner et al. 2020), which shares one vote between models whose historical runs resemble each other, with the shape parameter set to this region's median inter-model distance rather than calibrated by a perfect-model test; there is no performance term, so no model is up- or down-weighted for matching observations. The weighting leaves an effective 17.5 of 26 models (Kish), which is the number the spread is actually estimated from. This is not a calibrated confidence interval, not a probability distribution over outcomes, and carries no downscaling or bias correction — regional absolute values retain each model's own bias. Ensemble membership is part of the campaign digest, because adding or removing a model changes both the mean and the spread. A month is emitted only where every member supplies it. Realisation note: for CESM2 (r1i1p1f1 historical, r4i1p1f1 SSP5-8.5); MCM-UA-1-0 (r1i1p1f1 historical, r1i1p1f2 SSP5-8.5), the historical run is a different realisation from the projection published here. CDS serves whichever realisation it holds for a named model, and the request carries no variant key. The independence weighting takes its distances from the historical fields, so for these members the run that sets the weight is not the run being weighted. The last 12 month(s) are NOT model output: no member of the ensemble runs past 2099-12-01, so that month's value is repeated to the end of the series, and each such point carries carried_from. A repeated value understates a rising trend, which under a high scenario is steepest at the end, so the closing figure is a floor rather than a projection.
Geometry: admin0:sha256:afff7d5dc22279a90216f1ad1c8d50dff130f6b176e5720ce968f306a03c7749 · weighting: area · method: coterran-cmip6-ensemble/1.
46 intersecting cells; 27.9 effective cells · 2.24° × 3.75° grid.
Minimum valid area: 95.0% · coverage is represented area, not accuracy.
Campaign SHA-256: 04849d821b9da32b5ebb052a46751df63480a7168561b832e72009a1a28ae3f9
28 input checksums and software versions
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campaign · campaign.json · 436,412 bytesecd5f66e89c5e750159802107a974d404d2f42444a165ffbd74406f424b65314
climate_grid · tas-ssp5_8_5-access_cm2.zip · 77,344,890 bytes30628d1f262b17fb5383284283a291e7ffc5526d7ffe6c340695ff3370fc8293
climate_grid · tas-ssp5_8_5-awi_cm_1_1_mr.zip · 235,145,476 bytese59851bc784c8b080c4c4f4147c1e9fc1f94b433ad535f443ddc6866562b9dbf
climate_grid · tas-ssp5_8_5-bcc_csm2_mr.zip · 211,654,476 bytes3e98f27e567ecd5fb98bf32b669e17f54ac3d4eb3e2badec44756a8bd28d5c8d
climate_grid · tas-ssp5_8_5-cams_csm1_0.zip · 209,198,722 bytes66b31dc90c0236fd8a94669a449054cce8f384ac8a5df2e6243524dafd78f46d
climate_grid · tas-ssp5_8_5-canesm5_canoe.zip · 27,494,541 bytes8dfa6607db0707449e2a0db2b7ea7494207228016181387f7719260b2414c985
climate_grid · tas-ssp5_8_5-cesm2.zip · 126,228,463 bytes2a9137e9b00fd633f052b14262155895a38cfb503ba121f2c45e0837ceb03e63
climate_grid · tas-ssp5_8_5-cmcc_cm2_sr5.zip · 127,133,104 bytesa9db8bf2fde5ce4b88b37edc1e873eadf1d1d65fa858dbbf656e02da7a0de063
climate_grid · tas-ssp5_8_5-cnrm_cm6_1.zip · 74,809,174 bytes73c983c4d8be30e0663750c8350d13f328e0421ec443a63dcf1d2d95508cbda2
climate_grid · tas-ssp5_8_5-cnrm_cm6_1_hr.zip · 532,777,928 bytesea66f650aae86e26e06e60882f1b97769713678c0d7b0bbb478672639583ac89
climate_grid · tas-ssp5_8_5-cnrm_esm2_1.zip · 74,826,302 bytes0d0e537b14b2ae3a2360493e514b1b661182068d4ba5200001abe2c9bbfaa5ca
climate_grid · tas-ssp5_8_5-fgoals_f3_l.zip · 214,296,074 bytesb0315d6bdeb2ac80c50c2265481d9bb7657d0752a69520bbd0df0e963506ee40
climate_grid · tas-ssp5_8_5-fgoals_g3.zip · 59,873,068 bytesb8183eb7e5d8d270e5cd0c7afc8ff3331fc7f29e532e75f00f9545ab28ad0549
climate_grid · tas-ssp5_8_5-gfdl_esm4.zip · 119,836,077 bytesb4045d355df06066086b1ff57cba8c4387fd4f50f45abfb9229ca13ea975c84b
climate_grid · tas-ssp5_8_5-iitm_esm.zip · 57,762,044 bytese3580b8ad48ae07fc9f4607d2f1b6214b9019e3bb98aeecf5a8883601574fc40
climate_grid · tas-ssp5_8_5-inm_cm4_8.zip · 52,630,727 bytesfd73dd378fef873bbac8bb72b3ca265c8c469f80d336de6d6d38c7a591343d64
climate_grid · tas-ssp5_8_5-inm_cm5_0.zip · 69,310,977 bytes30f926bae5c2b476febaaab88a00e17ddd909c47c4c775bb1dc385528feb6101
climate_grid · tas-ssp5_8_5-ipsl_cm6a_lr.zip · 49,659,467 bytesd5fe6a06447db745335526479df0a9f90e72e7e58030d8af9a321a7e601e434e
climate_grid · tas-ssp5_8_5-kace_1_0_g.zip · 114,416,145 bytes90cf8a36384c94e692ee3e56360d52eefa279f8608154bc1a9e378d4ef7e23ae
climate_grid · tas-ssp5_8_5-mcm_ua_1_0.zip · 31,998,291 bytesffdc8be5b1c0da78cc74bcbad95919702908e7c8986a1ee795cab80c34923c7d
climate_grid · tas-ssp5_8_5-miroc6.zip · 74,761,899 bytesf260d50347ea01d56748c80e5ad13f6457c62ebb180527b0b5400135845eafbf
climate_grid · tas-ssp5_8_5-miroc_es2l.zip · 19,605,786 bytes5c06102679ce19f71faa5fb26e3e8d672bafc47d889a46a676e16bcbbf870967
climate_grid · tas-ssp5_8_5-mpi_esm1_2_lr.zip · 34,734,371 bytes50675311e2afe5f4a43723acc7571eea02399d9b0b8ec14c94e8d6088811f009
climate_grid · tas-ssp5_8_5-mri_esm2_0.zip · 117,204,012 bytes5e368d524876ea5293426eb1cc5a683aa7ba4bfaf32b1fa494dcc6455359162e
climate_grid · tas-ssp5_8_5-noresm2_mm.zip · 126,102,070 bytesaa1c74a7ec535c118f24a699e77972380bf6f48a285177994fe5da3a0ebdf197
climate_grid · tas-ssp5_8_5-taiesm1.zip · 126,190,335 bytes85b9d9381d83b1902e9034a8a8bdc76d69d6e0160fc380d0aea32ffa9fa0056e
climate_grid · tas-ssp5_8_5-ukesm1_0_ll.zip · 66,418,539 bytes3d6b0b756fcbf2132b8e68b026a684308a96879bf45bd76f617c15ebe3bc7d7c
numpy==2.5.3 · pandas==3.0.5 · xarray==2026.7.0 · shapely==2.1.2 · netCDF4==1.7.4 · Python==3.14.6
Regional input SHA-256: e4e9f5ae293009c9292b4b790aebc14df064cc4bf46aebe36ea3aef25e33c9ea
Source version: projections-cmip6 · revision: campaign-04849d821b9da32b5ebb052a46.
Provider issue time unavailable. Retrieved 2026-09-14T23:30:31Z.