WCRP CMIP6 CMIP MRI MRI-ESM2-0

[1] DOI Yukimoto, Seiji; Koshiro, Tsuyoshi; Kawai, Hideaki; Oshima, Naga; Yoshida, Kohei; Urakawa, Shogo; Tsujino, Hiroyuki; Deushi, Makoto; Tanaka, Taichu; Hosaka, Masahiro; Yoshimura, Hiromasa; Shindo, Eiki; Mizuta, Ryo; Ishii, Masayoshi; Obata, Atsushi; Adachi, Yukimasa. (2019). MRI MRI-ESM2.0 model output prepared for CMIP6 CMIP. doi:10.22033/ESGF/CMIP6.621

[1] DOI Wang, Meirong; Wang, Jun; Chen, Deliang; Duan, Anmin; Liu, Yimin; Zhou, Shunwu; Guo, Dong; Wang, Hengmao; Ju, Weimin. (2020). Recent recovery of the boreal spring sensible heating over the Tibetan Plateau will continue in CMIP6 future projections. doi:10.1088/1748-9326/ab57a3

[2] DOI Burke, Eleanor J.; Zhang, Yu; Krinner, Gerhard. (2020). Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change. doi:10.5194/tc-14-3155-2020

[3] DOI Ayugi, Brian; Zhihong, Jiang; Zhu, Huanhuan; Ngoma, Hamida; Babaousmail, Hassen; Rizwan, Karim; Dike, Victor. (2021). Comparison of CMIP6 and CMIP5 models in simulating mean and extreme precipitation over East Africa. doi:10.1002/joc.7207

[4] DOI Faye, Aissatou; Akinsanola, Akintomide Afolayan. (2021). Evaluation of extreme precipitation indices over West Africa in CMIP6 models. doi:10.1007/s00382-021-05942-2

[5] 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

[6] DOI Zhang, Kequan; Duan, Jiakang; Zhao, Siyi; Zhang, Jiankai; Keeble, James; Liu, Hongwen. (2021). Evaluating the Ozone Valley over the Tibetan Plateau in CMIP6 Models. doi:10.1007/s00376-021-0442-2

[7] DOI Vrac, Mathieu; Thao, Soulivanh; Yiou, Pascal. (2022). Should multivariate bias corrections of climate simulations account for changes of rank correlation over time?. doi:10.1002/essoar.10510318.1

[8] DOI Cai, Wenju; Yang, Kai; Wu, Lixin; Huang, Gang; Santoso, Agus; Ng, Benjamin; Wang, Guojian; Yamagata, Toshio. (2020). Opposite response of strong and moderate positive Indian Ocean Dipole to global warming. doi:10.1038/s41558-020-00943-1

[9] DOI Liu, Jingchen; Guan, Xiaodan; Gao, Zhaokui; Huang, Xiaoqian; Ma, Jieru; He, Yongli; Xie, Tiejun. (2021). Inter-decadal variability of the heat source over the Tibetan Plateau. doi:10.1007/s00382-021-05929-z

[10] 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

[11] 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

[12] 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

[13] 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

[14] DOI Tian, Lei; Tao, Yu; Fu, Wenxue; Li, Tao; Ren, Fang; Li, Mingyang. (2022). Dynamic Simulation of Land Use/Cover Change and Assessment of Forest Ecosystem Carbon Storage under Climate Change Scenarios in Guangdong Province, China. doi:10.3390/rs14102330

[15] DOI Carlson, Kimberly M.; Mora, Camilo; Xu, Jinwen; Setter, Renee O.; Harangody, Michelle; Franklin, Erik C.; Kantar, Michael B.; Lucas, Matthew; Menzo, Zachary M.; Spirandelli, Daniele; Schanzenbach, David; Courtlandt Warr, C.; Wong, Amanda E.; Businger, Steven. (2022). Global rainbow distribution under current and future climates. doi:10.1016/j.gloenvcha.2022.102604

[16] DOI Liu, Meng; Yang, Linqing. (2022). Northward expansion of fire-adaptative vegetation in future warming. doi:10.1088/1748-9326/ac417d

[17] DOI Yang, Shuyu; Yang, Dawen; Zhao, Baoxu; Ma, Teng; Lu, Weiwei; Santisirisomboon, Jerasorn. (2022). Future Changes in High and Low Flows under the Impacts of Climate and Land Use Changes in the Jiulong River Basin of Southeast China. doi:10.3390/atmos13020150

[18] DOI Rashid, Haroon; Yang, Kaijie; Zeng, Aicong; Ju, Song; Rashid, Abdur; Guo, Futao; Lan, Siren. (2021). Predicting the Hydrological Impacts of Future Climate Change in a Humid-Subtropical Watershed. doi:10.3390/atmos13010012

[19] DOI Cook, B. I.; Mankin, J. S.; Marvel, K.; Williams, A. P.; Smerdon, J. E.; Anchukaitis, K. J. (2020). Twenty‐First Century Drought Projections in the CMIP6 Forcing Scenarios. doi:10.1029/2019ef001461

[20] DOI Allan, Richard P.; Barlow, Mathew; Byrne, Michael P.; Cherchi, Annalisa; Douville, Hervé; Fowler, Hayley J.; Gan, Thian Y.; Pendergrass, Angeline G.; Rosenfeld, Daniel; Swann, Abigail L. S.; Wilcox, Laura J.; Zolina, Olga. (2020). Advances in understanding large‐scale responses of the water cycle to climate change. doi:10.1111/nyas.14337

[21] DOI Cotterill, Daniel F.; Pope, James O.; Stott, Peter A. (2022). Future Extension Of The UK Summer And Its Impact On Autumn Precipitation. doi:10.21203/rs.3.rs-1427756/v1

[22] DOI Jönsson, A., Bender, F. A. (2022). Persistence and Variability of Earth`s Interhemispheric Albedo Symmetry in 19 Years of CERES EBAF Observations. doi:10.1175/jcli-d-20-0970.1

[23] DOI Rivera, Paris. (2022). Evaluation of Historical Simulations of CMIP6 Models for Temperature and Precipitation in Guatemala. doi:10.1007/s41748-022-00333-x

[24] DOI AYUGI, Brian; Zhidong, Jiang; Zhu, Huanhuan; Ngoma, Hamida; Babaousmail, Hassen; Rizwan, Karim; Dike, Victor. (2021). Comparison of CMIP6 and CMIP5 Models in Simulating Mean and Extreme Precipitation over East Africa. doi:10.20944/preprints202102.0111.v1

[25] DOI Lea, James M.; Fitt, Robert N. L.; Brough, Stephen; Carr, Georgia; Dick, Jonathan; Jones, Natasha; Webster, Richard J. (2024). Making climate reanalysis and CMIP6 data processing easy: two “point-and-click” cloud based user interfaces for environmental and ecological studies. doi:10.3389/fenvs.2024.1294446

[26] DOI Han, Pengfei; Long, Di; Zhao, Fanyu; Slater, Louise J. (2023). Response of Two Glaciers in Different Climate Settings of the Tibetan Plateau to Climate Change Through Year 2100 Using a Hybrid Modeling Approach. doi:10.1029/2022wr033618

[27] DOI Shang, Lin; Luo, Jiali; Wang, Chunxiao. (2021). Ozone Variation Trends under Different CMIP6 Scenarios. doi:10.3390/atmos12010112

[28] DOI Azirani, Tayebeh Akbari; Ghorbani, Hossein. (2023). The impact of climate change on Quaternary glaciers of Gharaghom Basin in Iran. doi:10.1007/s00704-023-04701-z

[29] DOI Kunchala, Ravi Kumar; Attada, Raju; Karumuri, Rama Krishna; Seelanki, Vivek; Singh, Bhupendra Bahadur; Ashok, Karumuri; Hoteit, Ibrahim. (2022). Aerosol Optical Depth over the Middle East and North Africa region in CMIP6 Models: Climatology, Variability, and Trends. doi:10.21203/rs.3.rs-1903026/v1

[30] DOI Gerber, Edwin. (2021). Comment on acp-2021-206. doi:10.5194/acp-2021-206-rc2

[31] DOI Bhatti, Yusuf; Revell, Laura; Schuddeboom, Alex; McDonald, Adrian; Archibald, Alex; Williams, Jonny; Venugopal, Abhijith; Hardacre, Catherine; Behrens, Erik. (2023). The sensitivity of Southern Ocean atmospheric dimethyl sulfide to modelled sources and emissions. doi:10.5194/egusphere-2023-868

[32] 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

[33] DOI Correa, Wesley de Souza Campos; Soares, Wagner Rodrigues; Aylas, Georgynio Yossimar Rosales; Reis Junior, Neyval Costa; Marengo, José Antonio; Chou, Sin Chan; Nobre, Carlos. (2023). Avaliação das simulações de temperatura e precipitação de um subconjunto de modelos do CMIP6 para o Brasil. doi:10.14295/derb.v43.774

[34] DOI Shukla, Krishna Kumar; Attada, Raju. (2023). CMIP6 models informed summer human thermal discomfort conditions in Indian regional hotspot. doi:10.1038/s41598-023-38602-y

[35] DOI Ngoma, Hamida; Wen, Wang; Ayugi, Brian; Babaousmail, Hassen; Karim, Riwzan; Ongoma, Victor. (2021). Evaluation of the Global Climate Models in CMIP6 over Uganda. doi:10.20944/preprints202012.0782.v1

[36] DOI Annor, Thompson; Ackon, Apphia Tetteh; James, Rachel; Dyer, Ellen; Webb, Thomas; Pokam, Wilfried Mba; Kuete Gouandjo, Giresse; Washington, Richard; Abiodun, Babatunde J. (2023). Heat band, rain band and heat low migration: process-based evaluation of some CMIP6 GCMs over West Africa. doi:10.1007/s00382-023-06930-4

[37] DOI Cook, B. I.; Mankin, J. S.; Marvel, K.; Williams, A. P.; Smerdon, J. E.; Anchukaitis, K. J. (2020). Twenty-First Century Drought Projections in the CMIP6 Forcing Scenarios. doi:10.1029/2019EF001461

[38] DOI Kouki, Kerttu; Räisänen, Petri; Luojus, Kari; Luomaranta, Anna; Riihelä, Aku. (2022). Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982–2014. doi:10.5194/tc-16-1007-2022

[39] 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

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

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

[42] DOI Wong, Suki Cheuk-Kiu; McKinley, Galen A; Seager, Richard. (2022). Equatorial Pacific pCO2 Interannual Variability in CMIP6 Models. doi:10.1002/essoar.10512730.1

[43] DOI Wang, Rongyao; Zhao, Junsan; Lin, Yilin; Chen, Guoping; Cao, Qing; Feng, Yixiang. (2022). Land Change Simulation and Forest Carbon Storage of Central Yunnan Urban Agglomeration, China Based on SSP-RCP Scenarios. doi:10.3390/f13122030

[44] DOI Olusegun, Christiana; Ojo, Olusola; Olusola, Adeyemi; Ogunjo, Samuel. (2023). Solar radiation variability across Nigeria’s climatic zones: a validation and projection study with CORDEX, CMIP5, and CMIP6 models. doi:10.1007/s40808-023-01848-6

[45] DOI Ngoma, Hamida; Wen, Wang; Ayugi, Brian; Babaousmail, Hassen; Karim, Rizwan; Ongoma, Victor. (2021). Evaluation of precipitation simulations in CMIP6 models over Uganda. doi:10.1002/joc.7098

[46] DOI Mohan, Soumya; Ruchith, R. D. (2023). On the simulations of latent heat flux over the Indian Ocean in CMIP6 models. doi:10.1007/s00382-023-06871-y

[47] 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

[48] DOI Yang, Mingxi. (2023). Comment on egusphere-2023-868. doi:10.5194/egusphere-2023-868-rc2

[49] 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

[50] DOI Abalos, Marta. (2021). Reply to CC1. doi:10.5194/acp-2021-206-ac1

[51] DOI Vrac, M.; Thao, S.; Yiou, P. (2022). Should Multivariate Bias Corrections of Climate Simulations Account for Changes of Rank Correlation Over Time?. doi:10.1029/2022jd036562

[52] 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

[53] DOI Vaittinada Ayar, Pradeebane; Tjiputra, Jerry; Bopp, Laurent; Christian, Jim R.; Ilyina, Tatiana; Krasting, John P.; Séférian, Roland; Tsujino, Hiroyuki; Watanabe, Michio; Yool, Andrew. (2022). Contrasting projection of the ENSO-driven CO<sub>2</sub> flux variability in the Equatorial Pacific under high warming scenario. doi:10.5194/esd-2022-12

[54] DOI AYAR, Pradeebane VAITTINADA; Battisti, David S.; Li, Camille; King, Martin Peter; Vrac, Mathieu; Tjiputra, Jerry Fong. (2023). A regime view of ENSO flavours through clustering in CMIP6 models. doi:10.22541/essoar.167458065.54814300/v2

[55] DOI Aylmer, Jake R.; Ferreira, David; Feltham, Daniel L. (2024). Impact of ocean heat transport on sea ice captured by a simple energy balance model. doi:10.1038/s43247-024-01565-7

[56] DOI Andersson, Tom R.; Hosking, J. Scott; Pérez-Ortiz, María; Paige, Brooks; Elliott, Andrew; Russell, Chris; Law, Stephen; Jones, Daniel C.; Wilkinson, Jeremy; Phillips, Tony; Byrne, James; Tietsche, Steffen; Sarojini, Beena Balan; Blanchard-Wrigglesworth, Eduardo; Aksenov, Yevgeny; Downie, Rod; Shuckburgh, Emily. (2021). Seasonal Arctic sea ice forecasting with probabilistic deep learning. doi:10.1038/s41467-021-25257-4

[57] DOI Lotfirad, Morteza; Adib, Arash; Riyahi, Mohammad Mehdi; Jafarpour, Mohammad. (2022). Evaluating the effects of CMIP6 model uncertainty on extreme flows of the Caspian Hyrcanian forest watersheds by BMA method. doi:10.21203/rs.3.rs-1479406/v1

[58] DOI Lotfirad, Morteza; Adib, Arash; Riyahi, Mohammad Mehdi; Jafarpour, Mohammad. (2022). Evaluating the effect of the uncertainty of CMIP6 models on extreme flows of the Caspian Hyrcanian forest watersheds using the BMA method. doi:10.1007/s00477-022-02269-0

[59] DOI Wong, S. C. K.; McKinley, G. A.; Seager, R. (2022). Equatorial Pacific pCO2 interannual variability in CMIP6 models. doi:10.1029/2022JG007243

[60] DOI Andrade-Velázquez, Mercedes; Montero-Martínez, Martín José. (2023). Historical and Projected Trends of the Mean Surface Temperature in South-Southeast Mexico Using ERA5 and CMIP6. doi:10.3390/cli11050111

[61] DOI Wong, Suki C. K.; McKinley, Galen A.; Seager, Richard. (2022). Equatorial Pacific pCO 2 Interannual Variability in CMIP6 Models. doi:10.7916/dzbv-zs62

[62] DOI Cook, B. I.; Mankin, J. S.; Marvel, K.; Williams, A. P.; Smerdon, J. E.; Anchukaitis, K. J. (2022). Twenty-First Century Drought Projections in the CMIP6 Forcing Scenarios. doi:10.7916/k1h7-mm35

[63] DOI Rusli, Steven Reinaldo; Bense, Victor F.; Mustafa, Syed M. T.; Weerts, Albrecht H. (2024). The impact of future climate projections and anthropogenic activities on basin-scale groundwater availability. doi:10.5194/hess-2024-26

[64] DOI Smith, Christopher. (2024). Comment on egusphere-2023-2427. doi:10.5194/egusphere-2023-2427-rc1

[65] DOI Kalisoras, Alkiviadis. (2024). Reply on RC1. doi:10.5194/egusphere-2023-2571-ac2

[66] DOI Komelo, Crépin K.; Fotso-Nguemo, Thierry C.; Ngavom, Zakariahou; Dessacka, Abdon K.; Taguela, Thierry N.; Yepdo, Zéphirin D.; Nghonda, Jean P.; Diedhiou, Arona; Monkam, David; Tchawoua, Clément. (2024). Evaluation of extreme precipitation events as simulated by CMIP6 models over Central Africa: Spatial patterns. doi:10.1007/s00704-024-05198-w

[67] DOI Sun, Zhe; Archibald, Alexander. (2021). Multi-stage Ensemble-learning-based Model Fusion for Surface Ozone Simulations: A Focus on CMIP6 Models. doi:10.1002/essoar.10507571.1

[68] DOI Kouki, Kerttu; Räisänen, Petri; Luojus, Kari; Luomaranta, Anna; Riihelä, Aku. (2022). Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982-2014. doi:10.5194/ems2022-447

[69] 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

[70] DOI Semenov, Mikhail A.; Senapati, Nimai; Coleman, Kevin; Collins, Adrian L. (2024). A dataset of CMIP6-based climate scenarios for climate change impact assessment in Great Britain. doi:10.1016/j.dib.2024.110709

[71] DOI Kalisoras, Alkiviadis; Georgoulias, Aristeidis K.; Akritidis, Dimitris; Allen, Robert J.; Naik, Vaishali; Kuo, Chaincy; Szopa, Sophie; Nabat, Pierre; Olivié, Dirk; van Noije, Twan; Le Sager, Philippe; Neubauer, David; Oshima, Naga; Mulcahy, Jane; Horowitz, Larry W.; Zanis, Prodromos. (2024). Decomposing the effective radiative forcing of anthropogenic aerosols based on CMIP6 Earth system models. doi:10.5194/acp-24-7837-2024

[72] DOI Kivimäki, Mika; Batty, G. David; Pentti, Jaana; Suomi, Juuso; Nyberg, Solja T.; Merikanto, Joonas; Nordling, Kalle; Ervasti, Jenni; Suominen, Sakari B.; Partanen, Antti-Ilari; Stenholm, Sari; Käyhkö, Jukka; Vahtera, Jussi. (2023). Climate Change, Summer Temperature, and Heat-Related Mortality in Finland: Multicohort Study with Projections for a Sustainable vs. Fossil-Fueled Future to 2050. doi:10.1289/ehp12080

[73] DOI Azirani, Tayebeh Akbari; Ghorbani, Hossein. (2022). The impact of climate change on Quaternary glaciers of Gharaghom Basin in Iran. doi:10.21203/rs.3.rs-2196055/v1

[74] DOI Shafeeque, Muhammad; Bibi, Amna. (2023). Assessing the impact of future climate scenarios on crop water requirements and agricultural water supply across different climatic zones of Pakistan. doi:10.3389/feart.2023.1283171

[75] DOI Zhou, Putian; Lu, Zhengyao; Keskinen, Jukka-Pekka; Zhang, Qiong; Lento, Juha; Bian, Jianpu; van Noije, Twan; Le Sager, Philippe; Kerminen, Veli-Matti; Kulmala, Markku; Boy, Michael; Makkonen, Risto. (2023). Simulating dust emissions and secondary organic aerosol formation over northern Africa during the mid-Holocene Green Sahara period. doi:10.5194/cp-19-2445-2023

[76] DOI De Keyser, Jan; Hayes, Daniel S.; Marti, Beatrice; Siegfried, Tobias; Seliger, Carina; Schwedhelm, Hannah; Anarbekov, Oyture; Gafurov, Zafar; López Fernández, Raquel M.; Ramos Diez, Ivan; Alapfy, Bertalan; Carey, Justine; Karimov, Bakhtiyor; Karimov, Erkin; Wagner, Beatrice; Habersack, Helmut. (2023). Integrating Open-Source Datasets to Analyze the Transboundary Water–Food–Energy–Climate Nexus in Central Asia. doi:10.3390/w15193482

[77] 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

[78] DOI Vaittinada Ayar, Pradeebane; Battisti, David; Li, Camille; King, Martin; Vrac, Mathieu; Tjiputra, Jerry. (2024). A Regime View of ENSO Flavors Through Clustering in CMIP6 Models. doi:10.5194/egusphere-egu24-12936

[79] DOI DeRepentigny, Patricia; Jahn, Alexandra; Holland, Marika M.; Kay, Jennifer E.; Fasullo, John; Lamarque, Jean-François; Tilmes, Simone; Hannay, Cécile; Mills, Michael J.; Bailey, David A.; Barrett, Andrew P. (2022). Enhanced simulated early 21st century Arctic sea ice loss due to CMIP6 biomass burning emissions. doi:10.1126/sciadv.abo2405

[1] DOI YUKIMOTO, Seiji; KAWAI, Hideaki; KOSHIRO, Tsuyoshi; OSHIMA, Naga; YOSHIDA, Kohei; URAKAWA, Shogo; TSUJINO, Hiroyuki; DEUSHI, Makoto; TANAKA, Taichu; HOSAKA, Masahiro; YABU, Shokichi; YOSHIMURA, Hiromasa; SHINDO, Eiki; MIZUTA, Ryo; OBATA, Atsushi; ADACHI, Yukimasa; ISHII, Masayoshi. (2019). The Meteorological Research Institute Earth System Model Version 2.0, MRI-ESM2.0: Description and Basic Evaluation of the Physical Component. doi:10.2151/jmsj.2019-051

[2] DOI Kawai, Hideaki; Yukimoto, Seiji; Koshiro, Tsuyoshi; Oshima, Naga; Tanaka, Taichu; Yoshimura, Hiromasa; Nagasawa, Ryoji. (2019). Significant improvement of cloud representation in the global climate model MRI-ESM2. doi:10.5194/gmd-12-2875-2019

[3] DOI Urakawa, L. Shogo; Tsujino, Hiroyuki; Nakano, Hideyuki; Sakamoto, Kei; Yamanaka, Goro; Toyoda, Takahiro. (2020). The sensitivity of a depth-coordinate model to diapycnal mixing induced by practical implementations of the isopycnal tracer diffusion scheme. doi:10.1016/j.ocemod.2020.101693

[4] DOI Kawai, Hideaki; Yukimoto, Seiji; Koshiro, Tsuyoshi; Oshima, Naga; Tanaka, Taichu; Yoshimura, Hiromasa; Nagasawa, Ryoji. (2019). Significant Improvement of Cloud Representation in Global Climate Model MRI-ESM2. doi:10.5194/gmd-2019-23

[1] DOI Oshima, Naga; Yukimoto, Seiji; Deushi, Makoto; Koshiro, Tsuyoshi; Kawai, Hideaki; Tanaka, Taichu Y.; Yoshida, Kohei. (2020). Global and Arctic effective radiative forcing of anthropogenic gases and aerosols in MRI-ESM2.0. doi:10.1186/s40645-020-00348-w

[2] DOI Guglielmo, Magda; Zambonini, Dario; Porta, Giovanni; Malik, Arunima; Tang, Fiona.H.M.; Maggi, Federico. (2020). Time- and depth-resolved mechanistic assessment of water stress in Australian ecosystems under the CMIP6 scenarios. doi:10.1016/j.advwatres.2020.103837

[3] DOI Lange, Stefan; Quesada-Chacón, Dánnell; Büchner, Matthias. (2023). Secondary ISIMIP3b bias-adjusted atmospheric climate input data. doi:10.48364/isimip.581124.2

[4] 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

[5] DOI Fallah, Bijan; Russo, Emmanuele; Menz, Christoph; Hoffmann, Peter; Didovets, Iulii; Hattermann, Fred F. (2023). Anthropogenic influence on extreme temperature and precipitation in Central Asia. doi:10.1038/s41598-023-33921-6

[6] 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

[7] DOI Cotterill, Daniel F.; Pope, James O.; Stott, Peter A. (2022). Future extension of the UK summer and its impact on autumn precipitation. doi:10.1007/s00382-022-06403-0

[8] DOI Nastula, Jolanta; Śliwińska, Justyna; Kur, Tomasz; Wińska, Małgorzata; Partyka, Aleksander. (2022). Preliminary study on hydrological angular momentum determined from CMIP6 historical simulations. doi:10.1186/s40623-022-01636-z

[9] 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

[10] DOI Lange, Stefan; Quesada-Chacón, Dánnell; Büchner, Matthias. (2023). Secondary ISIMIP3b bias-adjusted atmospheric climate input data. doi:10.48364/isimip.581124.3

[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 Szopa, S.; Naik, V.; Adhikary, B.; Artaxo, P.; Berntsen, T.; Collins, W.D.; Fuzzi, S.; Gallardo, L.; Kiendler-Scharr, A.; Klimont, Z.; Liao, H.; Unger, N.; Zanis, P. (2023). Short-Lived Climate Forcers. 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:10.1017/9781009157896.008

[9] 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

[1] DOI Lange, Stefan; Büchner, Matthias. (2021). ISIMIP3b bias-adjusted atmospheric climate input data. doi:10.48364/isimip.842396.1

[2] DOI Lange, Stefan; Büchner, Matthias. (2021). ISIMIP3b bias-adjusted atmospheric climate input data. doi:10.48364/isimip.842396

[3] DOI Lange, Stefan; Büchner, Matthias. (2022). Secondary ISIMIP3b bias-adjusted atmospheric climate input data. doi:10.48364/isimip.581124.1

[4] DOI Lange, Stefan; Büchner, Matthias. (2022). Secondary ISIMIP3b bias-adjusted atmospheric climate input data. doi:10.48364/isimip.581124