INM INM-CM5-0 model output prepared for CMIP6 CMIP

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

WCRP CMIP6 CMIP INM INM-CM5-0

hdl:21.14106/15a4ea652bba0818da3943deb8b0ac28b9679d87

Volodin, Evgeny et al.

Experiment

CMIP CMIP6 INM INM-CM5-0 model-output

Summary: These data include all datasets published for 'CMIP6.CMIP.INM.INM-CM5-0' 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-CM5-0 climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM5-0 (2x1.5; 180 x 120 longitude/latitude; 73 levels; top level sigma = 0.0002), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E. 0.5x0.25; 720 x 720 longitude/latitude; 40 levels; vertical sigma 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: 50 km, seaIce: 50 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: 1850-01-01 to 3196-12-31 (gregorian)
Use constraints: Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/)
Data Catalog: World Data Center for Climate
Size: 17.24 TiB (18951322845200 Byte)
Format: NetCDF
Status: completely archived
Creation Date: 2019-06-10
Review Date: 2026-10-21

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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-CM5-0 model output prepared for CMIP6 CMIP. World Data Center for Climate (WDCC) at DKRZ. https://www.wdc-climate.de/ui/entry?acronym=C6_4406832

BibTeX RIS

Funding: Institute of Numerical Mathematics

Consistency report

as consistent as the model(s) INM-CM5-0

Description: as consistent as the model(s) INM-CM5-0

Technical Quality Assurance (TQA)

TQA - Technical Quality Assurance 'approved by WDCC'

Description: All TQA checks were passed for WCRP CMIP6 CMIP INM INM-CM5-0.
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: 2024-09-24

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-CM5-0 model output prepared for CMIP6 CMIP. doi:10.22033/ESGF/CMIP6.1423

Is referenced by

[1] DOI Jain, Shipra; Mishra, Saroj K.; Anand, Abhishek; Salunke, Popat; Fasullo, John T. (2020). Historical and projected low-frequency variability in the Somali Jet and Indian Summer Monsoon. doi:10.1007/s00382-020-05492-z

[2] DOI Hannachi, Abdel; Finke, Kathrin; Trendafilov, Nickolay. (2022). Common EOFs: a tool for multi-model comparison and evaluation. doi:10.1007/s00382-022-06409-8

[3] DOI Koteswara Rao, K.; Lakshmi Kumar, T. V.; Kulkarni, Ashwini; Chowdary, Jasti S.; Desamsetti, Srinivas. (2022). Characteristic changes in climate projections over Indus Basin using the bias corrected CMIP6 simulations. doi:10.1007/s00382-021-06108-w

[4] DOI Studholme, Joshua; Fedorov, Alexey V.; Gulev, Sergey K.; Emanuel, Kerry; Hodges, Kevin. (2021). Poleward expansion of tropical cyclone latitudes in warming climates. doi:10.1038/s41561-021-00859-1

[5] DOI Bustos Usta, David Francisco; Torres Parra, Rafael Ricardo. (2022). Projected wind changes in the Caribbean Sea based on CMIP6 models. doi:10.1007/s00382-022-06535-3

[6] DOI Hassani, Amirhossein; Azapagic, Adisa; Shokri, Nima. (2021). Global predictions of primary soil salinization under changing climate in the 21st century. doi:10.1038/s41467-021-26907-3

[7] DOI Balting, Daniel F.; AghaKouchak, Amir; Lohmann, Gerrit; Ionita, Monica. (2021). Northern Hemisphere drought risk in a warming climate. doi:10.1038/s41612-021-00218-2

[8] DOI Datta, Rajarshi; Reddy, Manne Janga. (2023). Trivariate frequency analysis of droughts using copulas under future climate change over Vidarbha region in India. doi:10.1007/s00477-023-02484-3

[9] DOI Karmouche, Soufiane; Galytska, Evgenia; Runge, Jakob; Meehl, Gerald A.; Phillips, Adam S.; Weigel, Katja; Eyring, Veronika. (2022). Regime-oriented causal model evaluation of Atlantic-Pacific teleconnections in CMIP6. doi:10.5194/egusphere-2022-1013

[10] DOI Zhao, Siyi; Zhang, Jiankai; Zhang, Chongyang; Xu, Mian; Keeble, James; Wang, Zhe; Xia, Xufan. (2022). Evaluating Long-Term Variability of the Arctic Stratospheric Polar Vortex Simulated by CMIP6 Models. doi:10.3390/rs14194701

[11] DOI Usta, David Francisco Bustos; Teymouri, Maryam; Chatterjee, Uday. (2022). Assessment of temperature changes over Iran during the twenty-first century using CMIP6 models under SSP1-26, SSP2-4.5, and SSP5-8.5 scenarios. doi:10.1007/s12517-022-09709-9

[12] DOI Lou, ‪Jiale; Newman, Matthew; Hoell, Andrew. (2023). Multi-decadal variation of ENSO forecast skill since the late 1800s. doi:10.21203/rs.3.rs-2544766/v1

[13] DOI Papalexiou, Simon Michael; Rajulapati, Chandra Rupa; Andreadis, Konstantinos M.; Foufoula‐Georgiou, Efi; Clark, Martyn P.; Trenberth, Kevin E. (2021). Probabilistic Evaluation of Drought in CMIP6 Simulations. doi:10.1029/2021ef002150

[14] DOI Ferrero, Bruno; Tonelli, Marcos; Marcello, Fernanda; Wainer, Ilana. (2021). Long-term Regional Dynamic Sea Level Changes from CMIP6 Projections. doi:10.1007/s00376-020-0178-4

[15] DOI Karmouche, Soufiane. (2023). Reply on RC2. doi:10.5194/egusphere-2022-1013-ac2

[16] DOI Bjarke, Nels; Barsugli, Joseph; Livneh, Ben. (2023). Ensemble of CMIP6 derived reference and potential evapotranspiration with radiative and advective components. doi:10.1038/s41597-023-02290-0

[17] DOI Duffy, Margaret L; O'Gorman, Paul A. (2022). Intermodel spread in Walker circulation responses linked to spread in moist stability and radiation responses. doi:10.22541/essoar.167078790.00035564/v1

[18] DOI Lin, Hai; Tang, Jianping; Wang, Shuyu; Wang, Shuguang; Dong, Guangtao. (2023). Deep learning downscaled high-resolution daily near surface meteorological datasets over East Asia. doi:10.1038/s41597-023-02805-9

[19] DOI Vogel, Annika; Alessa, Ghazi; Scheele, Robert; Weber, Lisa; Dubovik, Oleg; North, Peter; Fiedler, Stephanie. (2022). Uncertainty in Aerosol Optical Depth From Modern Aerosol‐Climate Models, Reanalyses, and Satellite Products. doi:10.1029/2021jd035483

[20] DOI Jönsson, Aiden. (2022). Reply on RC1. doi:10.5194/egusphere-2022-811-ac1

[21] DOI Silva, Paulo; Verona, Laura; Wainer, Ilana; Khodri, Myriam. (2024). Tropical atlantic climate biases and DAMIP experiments: insights from CMIP6 models. doi:10.1007/s00382-024-07253-8

[22] DOI Paçal, Aytaç; Hassler, Birgit; Weigel, Katja; Kurnaz, M. Levent; Wehner, Michael F.; Eyring, Veronika. (2023). Detecting Extreme Temperature Events Using Gaussian Mixture Models. doi:10.1029/2023jd038906

[23] DOI Karmouche, Soufiane. (2023). Reply on RC1. doi:10.5194/egusphere-2022-1013-ac1

[24] DOI Liu, Zhu; Zhang, Guoping; Ding, Jin; Xiao, Xiong. (2022). Biases of the Mean and Shape Properties in CMIP6 Extreme Precipitation Over Central Asia. doi:10.3389/feart.2022.918337

[25] DOI KUNDETI, KOTESWARARAO; T.V, Lakshmi Kumar; Kulkarni, Ashwini; J.S, Chowdary; Desamsetti, Srinivas. (2021). Climate change projections over Indus basin using CMIP6 model simulations. doi:10.21203/rs.3.rs-365154/v1

[26] DOI Lou, Jiale; Newman, Matthew; Hoell, Andrew. (2023). Multi-decadal variation of ENSO forecast skill since the late 1800s. doi:10.1038/s41612-023-00417-z

[27] 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

[28] DOI Vrac, Mathieu; Allard, Denis; Mariéthoz, Grégoire; Thao, Soulivanh; Schmutz, Lucas. (2024). Distribution-based pooling for combination and multi-model bias correction of climate simulations. doi:10.5194/esd-15-735-2024

[29] DOI Karmouche, Soufiane; Galytska, Evgenia; Runge, Jakob; Meehl, Gerald A.; Phillips, Adam S.; Weigel, Katja; Eyring, Veronika. (2023). Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6. doi:10.5194/esd-14-309-2023

[30] DOI PAÇAL, Aytaç; Hassler, Birgit; Weigel, Katja; Kurnaz, Mehmet Levent; Wehner, Michael F; Eyring, Veronika. (2023). Detecting Extreme Temperature Events Using Gaussian Mixture Models. doi:10.22541/essoar.168275876.64237989/v1

[31] DOI Boussalim, Youssef; Dallahi, Youssef. (2024). Future shifts in climatic conditions promoting northward expansion of the Mediterranean climate in the circum-Mediterranean region. doi:10.1007/s10661-024-13286-7

[32] DOI Aryal, Sugam; Grießinger, Jussi; Dyola, Nita; Gaire, Narayan Prasad; Bhattarai, Tribikram; Bräuning, Achim. (2023). INTRAGRO: A machine learning approach to predict future growth of trees under climate change. doi:10.1002/ece3.10626

References

[1] DOI Volodin E., Mortikov E., Kostrykin S., Galin V., Lykossov V., Gritsun A., Diansky N., Gusev A., Iakovlev N. (2017). Simulation of the present-day climate with the climate model INMCM5. doi:10.1007/s00382-017-3539-7

Is related to

[1] DOI Leung, Jeremy Cheuk-Hin; Zhang, Banglin; Gan, Qiuying; Wang, Lei; Qian, Weihong; Hu, Zeng-Zhen. (2022). Differential expansion speeds of Indo-Pacific warm pool and deep convection favoring pool under greenhouse warming. doi:10.1038/s41612-022-00315-w

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 Vrac, Mathieu; Thao, Soulivanh; Yiou, Pascal. (2022). Changes in temperature–precipitation correlations over Europe: are climate models reliable?. doi:10.1007/s00382-022-06436-5

[9] DOI Yiou, Pascal; Faranda, Davide; Thao, Soulivanh; Vrac, Mathieu. (2021). Projected Changes in the Atmospheric Dynamics of Climate Extremes in France. doi:10.3390/atmos12111440

[10] DOI Leung, Jeremy Cheuk-Hin; Zhang, Banglin; Gan, Qiuying; Wang, Lei; Qian, Weihong; Hu, Zeng-Zhen. (2022). Differential expansion speeds of Indo-Pacific warm pool and deep convection favoring pool under greenhouse warming. doi:10.1038/s41612-022-00315-w

[11] 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

[12] DOI Jönsson, Aiden R.; Bender, Frida A.-M. (2022). The response of hemispheric differences in Earth’s albedo to CO<sub>2</sub> forcing in coupled models and its implications for shortwave radiative feedback strength. doi:10.5194/egusphere-2022-811

[13] DOI Duffy, Margaret L.; O’Gorman, Paul A. (2022). Intermodel Spread in Walker Circulation Responses Linked to Spread in Moist Stability and Radiation Responses. doi:10.1029/2022jd037382

[14] DOI Sobral Verona, Laura; Silva, Paulo; Wainer, Ilana; Khodri, Myriam. (2023). Weakened interannual Tropical Atlantic variability in CMIP6 historical simulations. doi:10.1007/s00382-023-06696-9

[15] DOI Jönsson, Aiden R.; Bender, Frida A.-M. (2023). The implications of maintaining Earth's hemispheric albedo symmetry for shortwave radiative feedbacks. doi:10.5194/esd-14-345-2023

[16] DOI Jönsson, Aiden. (2022). Reply on RC2. doi:10.5194/egusphere-2022-811-ac2

[17] DOI Smith, Callum; Baker, Jessica; Robertson, Eddy; Chadwick, Robin; Kelley, Douglas; Argles, Arthur; Coelho, Caio; Castilho, Dayana; Kubota, Paulo; Talamoni, Isabella; Spracklen, Dominick. (2023). Observed and simulated local climate responses to tropical deforestation. doi:10.5194/egusphere-egu23-5938

[18] DOI Cao, Ruyin; Ling, Xiaofang; Liu, Licong; Wang, Weiyi; Li, Luchun; Shen, Miaogen. (2023). Remotely Sensed Vegetation Green-Up Onset Date on the Tibetan Plateau: Simulations and Future Predictions. doi:10.1109/jstars.2023.3310617

Attached Dataset Groups ( 5 )

Parent project(s)

WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets

[Entry acronym: C6_4406832] [Entry id: 4406832]