INM INM-CM4-8 model output prepared for CMIP6 ScenarioMIP

Volodin, Evgeny; Mortikov, Evgeny; Gritsun, Andrey; Lykossov, Vasily; Galin, Vener; Diansky, Nikolay; Gusev, Anatoly; Kostrykin, Sergey; Iakovlev, Nikolay; Shestakova, Anna; Emelina, Svetlana

WCRP CMIP6 ScenarioMIP INM INM-CM4-8

hdl:21.14106/fe429381faff5002ab6a7894d66f14a704d04794

Volodin, Evgeny et al.

Experiment

CMIP6 INM INM-CM4-8 model-output ScenarioMIP

Summary: These data include all datasets published for 'CMIP6.ScenarioMIP.INM.INM-CM4-8' 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 INM-CM4-8 climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM4-8 (2x1.5; 180 x 120 longitude/latitude; 21 levels; top level sigma = 0.01), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E; 360 x 318 longitude/latitude; 40 levels; sigma vertical coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
Project: CMIP6 (WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets)
Contact: Evgeny Volodin (
volodinev@nullgmail.com
)
Location(s): global
Spatial Coverage: Longitude 0 to 360 Latitude -90 to 90
Temporal Coverage: 2015-01-01 to 2100-12-31 (gregorian)
Use constraints: Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/)
Data Catalog: World Data Center for Climate
Size: 1.61 TiB (1774064515500 Byte)
Format: NetCDF
Status: completely archived
Creation Date: 2019-06-03
Review Date: 2026-10-23

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Cite as: Volodin, Evgeny; Mortikov, Evgeny; Gritsun, Andrey; Lykossov, Vasily; Galin, Vener; Diansky, Nikolay; Gusev, Anatoly; Kostrykin, Sergey; Iakovlev, Nikolay; Shestakova, Anna; Emelina, Svetlana (2023). INM INM-CM4-8 model output prepared for CMIP6 ScenarioMIP. World Data Center for Climate (WDCC) at DKRZ. https://www.wdc-climate.de/ui/entry?acronym=C6_4411131

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Funding: Institute of Numerical Mathematics

Consistency report

as consistent as the model(s) INM-CM4-8

Description: as consistent as the model(s) INM-CM4-8

Technical Quality Assurance (TQA)

TQA - Technical Quality Assurance "approved by WDCC"

Description: All TQA checks where passed for WCRP CMIP6 ScenarioMIP INM INM-CM4-8.
Method: CMIP6-TQA Checks
Method Description: Checks performed by WDCC. CMIP6-TQA metrics are documented: https://redmine.dkrz.de/projects/cmip6-lta-and-data-citation/wiki/Quality_Checks
Method Url: https://redmine.dkrz.de/projects/cmip6-lta-and-data-citation/wiki/Quality_Checks
Result Date: 2026-10-23

Contact type	Person	ORCID	Organization
Contact	Evgeny Volodin	-	Institute of Numerical Mathematics
Author	Evgeny Volodin	-	Institute of Numerical Mathematics
Author	Evgeny Mortikov	-	Moscow State University
Author	Andrey Gritsun	-	Institute of Numerical Mathematics
Author	Vasily Lykossov	-	Moscow State University
Author	Vener Galin	-	Institute of Numerical Mathematics
Author	Nikolay Diansky	-	Moscow State University
Author	Anatoly Gusev	-	Institute of Numerical Mathematics
Author	Sergey Kostrykin	-	Institute of Numerical Mathematics
Author	Nikolay Iakovlev	-	Institute of Numerical Mathematics
Author	Anna Shestakova	-	Moscow State University
Author	Svetlana Emelina	-	Hydrometcenter of Russia
Funder	-	-	Institute of Numerical Mathematics

Is part of

[1] DOI Volodin, Evgeny; Mortikov, Evgeny; Gritsun, Andrey; Lykossov, Vasily; Galin, Vener; Diansky, Nikolay; Gusev, Anatoly; Kostrykin, Sergey; Iakovlev, Nikolay; Shestakova, Anna; Emelina, Svetlana. (2019). INM INM-CM4-8 model output prepared for CMIP6 ScenarioMIP. doi:10.22033/ESGF/CMIP6.12321

Is referenced by

[1] DOI McKenna, Christine M.; Maycock, Amanda C.; Forster, Piers M.; Smith, Christopher J.; Tokarska, Katarzyna B. (2020). Stringent mitigation substantially reduces risk of unprecedented near-term warming rates. doi:10.1038/s41558-020-00957-9

[2] DOI Dike, Victor Nnamdi; Lin, Zhaohui; Fei, Kece; Langendijk, Gaby S.; Nath, Debashis. (2022). Evaluation and multimodel projection of seasonal precipitation extremes over central Asia based on CMIP6 simulations. doi:10.1002/joc.7641

[3] DOI Jung, Christopher; Schindler, Dirk. (2022). Development of onshore wind turbine fleet counteracts climate change-induced reduction in global capacity factor. doi:10.1038/s41560-022-01056-z

[4] DOI Anderegg, William R. L.; Wu, Chao; Acil, Nezha; Carvalhais, Nuno; Pugh, Thomas A. M.; Sadler, Jon P.; Seidl, Rupert. (2022). A climate risk analysis of Earth’s forests in the 21st century. doi:10.1126/science.abp9723

[5] DOI Sung, Jang Hyun; Seo, Seung Beom; Ryu, Young. (2022). Deep Learning-Based Projection of Occurrence Frequency of Forest Fires under SSP Scenario: Exploring the Link between Drought Characteristics and Forest Fires. doi:10.3390/su14095494

[6] DOI Rivera, Paris. (2023). Climate change projections in Guatemala: temperature and precipitation changes according to CMIP6 models. doi:10.1007/s40808-023-01881-5

[7] DOI Seltzer, Alan M.; Blard, Pierre-Henri; Sherwood, Steven C.; Kageyama, Masa. (2023). Terrestrial amplification of past, present, and future climate change. doi:10.1126/sciadv.adf8119

[8] DOI Kim, Chaeyoung; Kim, Wheemoon; Song, Wonkyong; Cho, Jaepil; Choi, Jaeyong. (2023). Prediction of Native Seed Habitat Distribution According to SSP Scenario and Seed Transfer Zones: A Focus on Acer pictum subsp. mono and Quercus acuta. doi:10.3390/f14010087

[9] DOI Lee, Taesam; Choi, Younghwan; Singh, Vijay P. (2023). Stochastic Spatial Binary Simulation with Multivariate Normal Distribution for Illustrating Future Evolution of Umbrella-Shape Summer Shelter under Climate Change. doi:10.3390/su15043147

[10] DOI Jung, Jin-Yong; Kim, Jin-Hee; Baek, Minju; Cho, Chuloh; Cho, Jaepil; Kim, Junhwan; Pavan, Willingthon; Kim, Kwang-Hyung. (2022). Adapting to the projected epidemics of Fusarium head blight of wheat in Korea under climate change scenarios. doi:10.3389/fpls.2022.1040752

[11] DOI Rettie, Fasil M.; Gayler, Sebastian; Weber, Tobias K. D.; Tesfaye, Kindie; Streck, Thilo. (2023). High-resolution CMIP6 climate projections for Ethiopia using the gridded statistical downscaling method. doi:10.1038/s41597-023-02337-2

[12] DOI Lee, Taesam; Jo, Jaephil; Singh, Vijay P. (2022). Temporal downscaling of daily precipitation to 10 min data for assessment of climate change impact on floods in small-size watersheds applied to Jinju, South Korea. doi:10.1007/s00382-022-06216-1

[13] DOI Li, Juan; Zhao, Yuexuan; Wang, Menglu; Tan, Wei; Yin, Jiyuan. (2024). Projected Changes of Wind Energy Input to Surface Waves in the North Indian Ocean Based on CMIP6. doi:10.3390/atmos15010139

[14] DOI Sung, Jang Hyun; Kang, Dong Ho; Seo, Young-Ho; Kim, Byung Sik. (2023). Analysis of Extreme Rainfall Characteristics in 2022 and Projection of Extreme Rainfall Based on Climate Change Scenarios. doi:10.3390/w15223986

Is cited by

[1] DOI Fox-Kemper, B.; Hewitt, H.T.; Xiao, C.; Aðalgeirsdóttir, G.; Drijfhout, S.S.; Edwards, T.L.; Golledge, N.R.; Hemer, M.; Kopp, R.E.; Krinner, G.; Mix, A.; Notz, D.; Nowicki, S.; Nurhati, I.S.; Ruiz, L.; Sallée, J.-B.; Slangen, A.B.A.; Yu, Y. (2023). Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.011

[2] DOI Lee, J.-Y.; Marotzke, J.; Bala, G.; Cao, L.; Corti, S.; Dunne, J.P.; Engelbrecht, F.; Fischer, E.; Fyfe, J.C; Jones, C.; Maycock, A.; Mutemi, J.; Ndiaye, O.; Panickal, S.; Zhou,T. (2023). Future Global Climate: Scenario-Based Projections and Near-Term Information. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.006

[3] DOI Eyring, V.; Gillett, N.P.; Achuta Rao, K.M.; Barimalala, R.; Barreiro Parrillo, M.; Bellouin, N.; Cassou, C.; Durack, P.J.; Kosaka, Y.; McGregor, S.; Min, S.; Morgenstern, O.; Sun, Y. (2023). Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.005

[4] DOI Doblas-Reyes, F.J.; Sörensson, A.A.; Almazroui, M.; Dosio, A.; Gutowski, W.J.; Haarsma, R.; Hamdi, R.; Hewitson, B.; Kwon, W.-T.; Lamptey, B.L.; Maraun, D.; Stephenson, T.S.; Takayabu, I.; Terray, L.; Turner, A.; Zuo, Z. (2023). Linking Global to Regional Climate Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.012

[5] DOI Seneviratne, S.I.; Zhang, X.; Adnan, M.; Badi, W.; Dereczynski, C.; Di Luca, A.; Ghosh, S.; Iskandar, I.; Kossin, J.; Lewis, S.; Otto, F.; Pinto, I.; Satoh, M.; Vicente-Serrano, S.M.; Wehner, M.; Zhou, B. (2023). Weather and Climate Extreme Events in a Changing Climate. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.013

[6] DOI Gutiérrez, J.M.; Jones, R.G.; Narisma, G.T.; Alves, L.M.; Amjad, M.; Gorodetskaya, I.V.; Grose, M.; Klutse, N.A.B.; Krakovska, S.; Li, J.; Martínez-Castro, D.; Mearns, L.O.; Mernild, S.H.; Ngo-Duc, T.; van den Hurk, B.; Yoon, J.-H. (2023). Atlas. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.021

[7] DOI Intergovernmental Panel on Climate Change (IPCC). (2023). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896

[8] DOI Douville, H.; Raghavan, K.; Renwick, J.; Allan, R.P.; Arias, P.A.; Barlow, M.; Cerezo-Mota, R.; Cherchi, A.; Gan, T.Y.; Gergis, J.; Jiang, D.; Khan, A.; Pokam Mba, W.; Rosenfeld, D.; Tierney, J.; Zolina, O. (2023). Water Cycle Changes. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.010

[9] DOI François, Bastien; Vrac, Mathieu. (2023). Time of emergence of compound events: contribution of univariate and dependence properties. doi:10.5194/nhess-23-21-2023

[10] DOI Malles, Jan-Hendrik; Maussion, Fabien; Ultee, Lizz; Kochtitzky, William; Copland, Luke; Marzeion, Ben. (2023). Exploring the impact of a frontal ablation parameterization on projected 21st-century mass change for Northern Hemisphere glaciers. doi:10.1017/jog.2023.19

[11] DOI Rajulapati, Chandra Rupa; Papalexiou, Simon Michael. (2023). Precipitation Bias Correction: A Novel Semi‐parametric Quantile Mapping Method. doi:10.1029/2023ea002823

[12] DOI Yalcin, Emrah. (2023). Quantifying climate change impacts on hydropower production under CMIP6 multi-model ensemble projections using SWAT model. doi:10.1080/02626667.2023.2245815

[13] DOI Sellevold, Raymond; Vizcaino, Miren. (2021). First Application of Artificial Neural Networks to Estimate 21st Century Greenland Ice Sheet Surface Melt. doi:10.1029/2021gl092449

Attached Dataset Groups ( 4 )

Parent project(s)

WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets

[Entry acronym: C6_4411131] [Entry id: 4411131]