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[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