Intra-seasonal oscillations of South Asian summer monsoon in coupled climate model cohort CMIP6

Singh, Charu

doi:10.1007/s00382-022-06323-z

Cited by 5 publications

(3 citation statements)

References 61 publications

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“…Dry bias over the Indian subcontinent showed by IITM‐ESM was also documented by a previous study (Swapna et al, 2015). Therefore, the role of model biases and coarser resolution plays a role in the failure of simulation by these models (Singh et al, 2017, 2018a, 2018b, 2023).…”

Section: Discussionmentioning

confidence: 99%

“…The variables are ensemble members of ‘atmospheric realm ’, the parent variant label is ‘ r1i1p1f1 ’ and the parent experiment ids are ‘ piControl ’. Another criterion for the selection of the models is the observations and recommendations of the previous research works (Banerjee and Singh, 2021; Kundu et al, 2021; Kundu & Singh, 2020; Menon et al, 2013; Sabeerali et al, 2012; Singh et al, 2017; Singh et al 2018a; Singh et al, 2018b; Singh, 2023). Table 1 illustrates the description of the 12 CMIP6 models selected for the study.…”

Section: Datasets Usedmentioning

confidence: 99%

“…The Indian Ocean Dipole (IOD) impact on these models' ENSO‐ISM teleconnections is minimal, and therefore more research is needed. Also, the studies regarding the active and break cycle of monsoon are very few (Singh, 2023).…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the characteristics of Indian summer monsoon simulated by CMIP6 models

Saha,

Singh

2024

Intl Journal of Climatology

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The present research is aimed at evaluating the climate coupled models with respect to the observational datasets for the investigation of the characteristics of the Indian summer monsoon (ISM). The monthly averaged historical simulations from 12 coupled climate models that participated in Coupled Model Intercomparison Project Phase 6 (CMIP6) are compared with the ground based observational data, satellite and reanalysis datasets for the study period of 1980–2014. This study uses these high‐resolution models to investigate monsoon features, onset and withdrawal dates, primarily focusing on individual model performances rather than highly documented multi‐model mean performance. Performance evaluation of the models suggests that sea surface temperature (SST) simulations by the models are in better agreement for the Arabian Sea than the Bay of Bengal with respect to the ERA5 reanalysis data sets. Further, inter‐model differences amongst the CMIP6 models in estimating the spatial distribution of various monsoon system variables during pre‐monsoon and monsoon seasons are noted which may be attributed to the different model components and varying physics configuration, nonetheless, models like NESM3 and INM‐CN5 are able to reproduce ISM pattern reasonably well. The annual precipitation cycle demonstrates a good agreement between most climate models and IMD data. Evolution of tropospheric temperature gradient (ΔTT) estimated from the CMIP6 models mimics the temporal pattern of the annual rainfall and therefore, is used to estimate the onset and withdrawal dates from CMIP6 models; however, high variability is noted amongst the CMIP6 models in retrieving the onset and withdrawal dates when compared with the IMD observations. Most of the models show a shorter rainy season except NorESM2‐MM. Overall our results suggest that the CMIP6 models can be used for the seasonal mean evaluation of monsoon system parameters and process‐based studies to improve our present understanding of the ISM system.

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