- Latest period
- 2100-12-01
- Value · °C
- 29.47
- 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 SSP2-4.5. 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 21.0 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 SSP2-4.5); MCM-UA-1-0 (r1i1p1f1 historical, r1i1p1f2 SSP2-4.5), 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.
1 intersecting cells; 1.0 effective cells · 2.24° × 3.75° grid. Grid-limited: the regional result draws on fewer than four effective cells.
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-ssp2_4_5-access_cm2.zip · 77,337,057 bytes1418335303c4ba12d803a1f12702d2b830e3f5154baebc6caa9cc20a1ed52f32
climate_grid · tas-ssp2_4_5-awi_cm_1_1_mr.zip · 235,336,576 bytesf444ed0ea96169edfd585640798831f4d2500988dbf5129ac7031c231d1af8b4
climate_grid · tas-ssp2_4_5-bcc_csm2_mr.zip · 211,654,509 bytes1881bd2f577f31270bc217958138a57ef5f0e1636c35f59a599722dc22723fb6
climate_grid · tas-ssp2_4_5-cams_csm1_0.zip · 209,197,805 bytesd7b5aa0da9c01b895b6390a82f9e797f5bc3ac308ac58acc8c2bb0cf8f0e5c93
climate_grid · tas-ssp2_4_5-canesm5_canoe.zip · 27,529,325 bytes9ee90b54a3bd05c0e4c583b3b7a51db97968e6ebfd8bcdefb057a2216dbc203e
climate_grid · tas-ssp2_4_5-cesm2.zip · 126,414,350 bytes65545e59ab10bca028822a44723e00227d9e6cc5ea1b44411b8d40ce8dd2c1f3
climate_grid · tas-ssp2_4_5-cmcc_cm2_sr5.zip · 127,325,577 bytes41b9e622b986aee7e628eeca562a7ff27d798af686d5722d594cbf0260a93b8b
climate_grid · tas-ssp2_4_5-cnrm_cm6_1.zip · 74,899,634 bytes932756c423fae796fd82bd88349b265083e9d96389313dfbdf0ee0073efdcf0c
climate_grid · tas-ssp2_4_5-cnrm_cm6_1_hr.zip · 533,110,019 bytes7897d44f42cba719ea5b06fab4051c3521a1e147ca34de65d2a7b5afa8f55806
climate_grid · tas-ssp2_4_5-cnrm_esm2_1.zip · 74,894,846 bytes476cdee1eee8bd49d2f52c929d8d70a85f0baa013a153aba33e87c83683852d5
climate_grid · tas-ssp2_4_5-fgoals_f3_l.zip · 214,295,652 bytes5115183b53a13a5e5955d2a3bdfc07c4786343648299f75a4bfe5df1d64a3a91
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climate_grid · tas-ssp2_4_5-gfdl_esm4.zip · 119,933,938 bytes35bf80f2af02cde4837c4d37a4d1417503ff13299d4bb22325ac0394c17f5b07
climate_grid · tas-ssp2_4_5-iitm_esm.zip · 57,773,407 bytes51140e573462e1435b2b708d610712f10cc9342ce26022337c1dd45ef3a67b03
climate_grid · tas-ssp2_4_5-inm_cm4_8.zip · 52,678,770 bytesf02b167ca368e703ff2958cf467b3e30258eed9ad0a3bb4a1340f05787f6721c
climate_grid · tas-ssp2_4_5-inm_cm5_0.zip · 52,709,155 bytesf5e3e1197e51f09a095334c4c3f85a23071f1b807a911171a997236ca273aa02
climate_grid · tas-ssp2_4_5-ipsl_cm6a_lr.zip · 49,731,623 bytes051315bad8b7d1ba23e8b1bdda9084e260842218e914d91a2c6ac18dfc5a388c
climate_grid · tas-ssp2_4_5-kace_1_0_g.zip · 58,276,640 bytes2cb1d389987b728b2bcb6b0058b58dac1f32b64fd63a93957c743713c9fff8d0
climate_grid · tas-ssp2_4_5-mcm_ua_1_0.zip · 31,997,333 bytesdcfd32b8e20e936d1c810031ec36907b826c35f6a37e59137716b463557c808a
climate_grid · tas-ssp2_4_5-miroc6.zip · 74,834,375 bytes3ac2ca9c269df7c6e55fa07e7354de8aa73667aa14cec2e1855b046bdafcd641
climate_grid · tas-ssp2_4_5-miroc_es2l.zip · 19,621,567 bytes42a5c5040e65c474d636ba9e47b4a62bc8d998ed7827cf214083dca8175e5949
climate_grid · tas-ssp2_4_5-mpi_esm1_2_lr.zip · 34,759,246 bytesff25137a3fcadae98cf9bc8f6b3e6bb6856cfae359add8ae9a6e1dfad2de8eff
climate_grid · tas-ssp2_4_5-mri_esm2_0.zip · 117,317,104 bytesf5fd26c745014f6c8e9150dd5c425f1c21752b116e071f56fb6f800a54bf70db
climate_grid · tas-ssp2_4_5-noresm2_mm.zip · 126,211,222 bytes890adc977fd44ade30382ba9926b5f4603c98cf7a81593b23edbf8a6bdf266f5
climate_grid · tas-ssp2_4_5-taiesm1.zip · 126,413,532 bytes8f1861210c02a488667b5545428cf0930f131c09626b4cc68cd921ca46017eec
climate_grid · tas-ssp2_4_5-ukesm1_0_ll.zip · 66,495,495 bytes19a4fa36af3347c64e27146b13543502e4a5e611e4e2cfab30979ff630ce7909
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.