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Added value of CMIP6 over CMIP5 models in simulating Indian summer monsoon rainfall

Gusain, A., Ghosh, S., Karmakar, S.·2020·Atmospheric Research

DOI 10.1016/j.atmosres.2019.104680

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Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-1937-2016 · Cited by 11,981
A dipole mode in the tropical Indian Ocean
Saji, N. H., Goswami, B. N., Vinayachandran, P. N., & Yamagata, T. (1999) · Nature · doi:10.1038/43854 · Cited by 5,510
The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., et al. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-3461-2016 · Cited by 5,241
Coupled ocean–atmosphere dynamics in the Indian Ocean during 1997–98
Webster, P. J., Moore, A. M., Loschnigg, J. P., & Leben, R. R. (1999) · Nature · doi:10.1038/43848 · Cited by 2,144
On the Weakening Relationship Between the Indian Monsoon and ENSO
Kumar, K., Rajagopalan, B., & Cane, M. A. (1999) · Science · doi:10.1126/science.284.5423.2156 · Cited by 1,618
Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes
Fischer, E. M., & Knutti, R. (2015) · Nature Climate Change · doi:10.1038/nclimate2617 · Cited by 1,427
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Haarsma, R., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guémas, V., et al. (2016) · Geoscientific model development · doi:10.5194/gmd-9-4185-2016 · Cited by 1,229
Evaluation of CMIP6 DECK Experiments With CNRM‐CM6‐1
Voldoire, A., Saint‐Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., Colin, J., Guérémy, J., Michou, M., Moine, M., et al. (2019) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2019ms001683 · Cited by 1,184
The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6
Wu, T., Lu, Y., Fang, Y., Xin, X., Li, L., Li, W., Jie, W., Zhang, J., Liu, Y., Zhang, L., et al. (2019) · Geoscientific Model Development · doi:10.5194/gmd-12-1573-2019 · Cited by 1,069

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Authors: Gusain, A., Ghosh, S., & Karmakar, S.
Affiliations: Indian Institute of Technology Bombay (IN)
Corresponding author: Karmakar, S.
ORCID: Gusain, A.
Karmakar, S.
Venue: Atmospheric Research
Publisher: Elsevier BV
Published: 2020-02
Volume: 232
Pages: 104680
ISSN: 0169-8095 (ISSN-L)
DOI: 10.1016/j.atmosres.2019.104680
OpenAlex: W2973173718
Cited by: 408
References: 56
Citations by year: 2026: 50 · 2025: 60 · 2024: 70 · 2023: 73 · 2022: 70 · 2021: 61 · 2020: 24
FWCI: 19.95
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Atmospheric Research (publishedVersion)
Funders: Department of Science & Technology (DST/CCP/CoE/140/2018, 00000000000010013072 (UC ID: 18192442))
Government of India
World Climate Research Programme
CNRM-CM6-1
IPSL-CM6A-LR
Indian Institute of Technology Bombay
IIT Bombay
Topics: Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Geology and Paleoclimatology Research
Keywords: Indian summer monsoon rainfall, CMIP6, CMIP5, model intercomparison, multi-model ensemble, Western Ghats, Himalaya, annual maximum daily rainfall, global warming, precipitation simulation

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Added value of CMIP6 over CMIP5 models in simulating Indian summer monsoon rainfall

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