Adler, R. F., and Coauthors, 2018: The global precipitation climatology project (GPCP) monthly analysis (new version 2.3) and a review of 2017 global precipitation. Atmosphere, 9, 138, https://doi.org/10.3390/atmos9040138.
Bellomo, K., M. Angeloni, S. Corti, and J. von Hardenberg, 2021: Future climate change shaped by inter-model differences in Atlantic meridional overturning circulation response. Nature Communications, 12, 3659, https://doi.org/10.1038/s41467-021-24015-w.
Bindoff, N., and S.-K. Min, 2013: Detection and attribution of climate change: From global to regional. Climate Change 2013: The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 867−952.
Branstator, G., and F. Selten, 2009: “Modes of Variability” and climate change. J. Climate, 22, 2639−2658, https://doi.org/10.1175/2008JCLI2517.1.
Buckley, M. W., and J. Marshall, 2016: Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review. Rev. Geophys., 54, 5−63, https://doi.org/10.1002/2015RG000493.
Chan, D., and P. Huybers, 2021: Correcting observational biases in sea-surface temperature observations removes anomalous warmth during World War II. J. Climate, 34, 4585−4602, https://doi.org/10.1175/JCLI-D-20-0907.1.
Chen, M. Y., P. P. Xie, J. E. Janowiak, and P. A. Arkin, 2002: Global land precipitation: A 50-yr monthly analysis based on gauge observations. Journal of Hydrometeorology, 3, 249−266, https://doi.org/10.1175/1525-7541(2002)003<0249:GLPAYM>2.0.CO;2.
Chen, X. L., and T. J. Zhou, 2015: Distinct effects of global mean warming and regional sea surface warming pattern on projected uncertainty in the South Asian summer monsoon. Geophys. Res. Lett., 42, 9433−9439, https://doi.org/10.1002/2015GL066384.
Cheng, J., Z. Y. Liu, S. Q. Zhang, W. Liu, L. N. Dong, P. Liu, and H. L. Li, 2016: Reduced interdecadal variability of Atlantic Meridional Overturning Circulation under global warming. Proceedings of the National Academy of Sciences of the United States of America, 113, 3175−3178, https://doi.org/10.1073/pnas.1519827113.
Church, J. A., and Coauthors, 2013: Sea level change. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Dai, A. G., and C. E. Bloecker, 2019: Impacts of internal variability on temperature and precipitation trends in large ensemble simulations by two climate models. Climate Dyn., 52, 289−306, https://doi.org/10.1007/s00382-018-4132-4.
Dai, A. G., J. C. Fyfe, S.-P. Xie, and X. G. Dai, 2015: Decadal modulation of global surface temperature by internal climate variability. Nature Climate Change, 5, 555−559, https://doi.org/10.1038/nclimate2605.
Danabasoglu, G., and Coauthors, 2020: The community earth system model version 2 (CESM2). Journal of Advances in Modeling Earth Systems, 12, e2019MS001916, https://doi.org/10.1029/2019MS001916.
Deser, C., A. Phillips, V. Bourdette, and H. Y. Teng, 2012a: Uncertainty in climate change projections: The role of internal variability. Climate Dyn., 38, 527−546, https://doi.org/10.1007/s00382-010-0977-x.
Deser, C., R. Knutti, S. Solomon, and A. S. Phillips, 2012b: Communication of the role of natural variability in future North American climate. Nature Climate Change, 2, 775−779, https://doi.org/10.1038/nclimate1562.
Deser, C., and Coauthors, 2020: Insights from Earth system model initial-condition large ensembles and future prospects. Nature Climate Change, 10, 277−286, https://doi.org/10.1038/s41558-020-0731-2.
Dima, M., D. R. Nichita, G. Lohmann, M. Ionita, and M. Voiculescu, 2021: Early-onset of Atlantic Meridional Overturning Circulation weakening in response to atmospheric CO2 concentration. npj Climate and Atmospheric Science, 4, 27, https://doi.org/10.1038/s41612-021-00182-x.
Doblas-Reyes, F. J., and Coauthors, 2013: Initialized near-term regional climate change prediction. Nature Communications, 4, 1715, https://doi.org/10.1038/ncomms2704.
Döscher, R., and Coauthors, 2021: The EC-Earth3 earth system model for the climate model intercomparison project 6. Geoscientific Model Development Discussions,
Drijfhout, S., G. J. van Oldenborgh, and A. Cimatoribus, 2012: Is a decline of AMOC causing the warming hole above the North Atlantic in observed and modeled warming patterns? J. Climate, 25, 8373−8379, https://doi.org/10.1175/JCLI-D-12-00490.1.
Drijfhout, S., W. Hazeleger, F. Selten, and R. Haarsma, 2008: Future changes in internal variability of the Atlantic Meridional Overturning Circulation. Climate Dyn., 30, 407−419, https://doi.org/10.1007/s00382-007-0297-y.
Dunn, R. J. H., and Coauthors, 2020: Development of an updated global land in situ-based data set of temperature and precipitation extremes: HadEX3,. J. Geophys. Res.: Atmos., 125, e2019JD032263, https://doi.org/10.1029/2019JD032263.
Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9, 1937−1958, https://doi.org/10.5194/gmd-9-1937-2016.
Fang, J. Y., G. R. Yu, L. L. Liu, S. J. Hu, and F. S. Chapin, 2018: Climate change, human impacts, and carbon sequestration in China. Proceedings of the National Academy of Sciences of the United States of America, 115, 4015−4020, https://doi.org/10.1073/pnas.1700304115.
Flato, G., and Coauthors, 2013: Evaluation of climate models. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker et al., Eds., Cambridge University Press, 741−882.
Frankcombe, L. M., M. H. England, J. B. Kajtar, M. E. Mann, and B. A. Steinman, 2018: On the choice of ensemble mean for estimating the forced signal in the presence of internal variability. J. Climate, 31, 5681−5693, https://doi.org/10.1175/JCLI-D-17-0662.1.
Frankignoul, C., G. Gastineau, and Y.-O. Kwon, 2017: Estimation of the SST response to anthropogenic and external forcing and its impact on the Atlantic multidecadal oscillation and the Pacific decadal oscillation. J. Climate, 30, 9871−9895, https://doi.org/10.1175/JCLI-D-17-0009.1.
Harris, I., T. J. Osborn, P. Jones, and D. Lister, 2020: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data, 7, 109, https://doi.org/10.1038/s41597-020-0453-3.
Hatfield, J. L., and C. L. Walthall, 2014: Climate change: Cropping system changes and adaptations. Encyclopedia of Agriculture and Food Systems, N. K. Van Alfen, Ed., Academic Press, 256−265,
Hawkins, E., and R. Sutton, 2009: The potential to narrow uncertainty in regional climate predictions. Bull. Amer. Meteor. Soc., 90, 1095−1108, https://doi.org/10.1175/2009BAMS2607.1.
Hawkins, E., R. S. Smith, J. M. Gregory, and D. A. Stainforth, 2016: Irreducible uncertainty in near-term climate projections. Climate Dyn., 46, 3807−3819, https://doi.org/10.1007/s00382-015-2806-8.
Hazeleger, W., and Coauthors, 2010: EC-Earth: A seamless Earth-system prediction approach in action. Bull. Amer. Meteor. Soc., 91, 1357−1364, https://doi.org/10.1175/2010BAMS2877.1.
Huang, X., and Coauthors, 2020: South Asian summer monsoon projections constrained by the interdecadal Pacific oscillation. Science Advances, 6, eaay6546, https://doi.org/10.1126/sciadv.aay6546.
Jeffrey, S., L. Rotstayn, M. Collier, S. Dravitzki, C. Hamalainen, C. Moeseneder, K. Wong, and J. Syktus, 2013: Australia’s CMIP5 submission using the CSIRO-Mk3.6 model. Australian Meteorological and Oceanographic Journal, 63, 1−13, https://doi.org/10.22499/2.6301.001.
Kay, J. E., and Coauthors, 2015: The community earth system model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability. Bull. Amer. Meteor. Soc., 96, 1333−1349, https://doi.org/10.1175/BAMS-D-13-00255.1.
Kennedy, J. J., 2014: A review of uncertainty in in situ measurements and data sets of sea surface temperature. Rev. Geophys., 52, 1−32, https://doi.org/10.1002/2013RG000434.
Kennedy, J. J., N. A. Rayner, C. P. Atkinson, and R. E. Killick, 2019: An ensemble data set of sea surface temperature change from 1850: The met office Hadley Centre HadSST. 4.0.0.0 data set. J. Geophys. Res.: Atmos., 124, 7719−7763, https://doi.org/10.1029/2018JD029867.
Kirchmeier-Young, M. C., F. W. Zwiers, and N. P. Gillett, 2017: Attribution of extreme events in Arctic Sea Ice Extent. J. Climate, 30, 553−571, https://doi.org/10.1175/JCLI-D-16-0412.1.
Kopparla, P., E. M. Fischer, C. Hannay, and R. Knutti, 2013: Improved simulation of extreme precipitation in a high-resolution atmosphere model. Geophys. Res. Lett., 40, 5803−5808, https://doi.org/10.1002/2013GL057866.
Li, L., and Coauthors, 2020a: The GAMIL3: Model description and evaluation. J. Geophys. Res.: Atmos., 125, e2020JD032574, https://doi.org/10.1029/2020JD032574.
Li, L. J., and Coauthors, 2020b: The flexible global ocean-atmosphere-land system model grid-point version 3 (FGOALS-g3): Description and evaluation. Journal of Advances in Modeling Earth Systems, 12, e2019MS002012, https://doi.org/10.1029/2019MS002012.
Lin, P. F., and Coauthors, 2020: LICOM model datasets for the CMIP6 ocean model intercomparison project. Advances in Atmospheric Sciences, 37, 239−249, https://doi.org/10.1007/s00376-019-9208-5.
Liu, W., A. V. Fedorov, S.-P. Xie, and S. N. Hu, 2020: Climate impacts of a weakened Atlantic Meridional Overturning Circulation in a warming climate. Science Advances, 6, eaaz4876, https://doi.org/10.1126/sciadv.aaz4876.
Loo, Y. Y., L. Billa, and A. Singh, 2015: Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia. Geoscience Frontiers, 6, 817−823, https://doi.org/10.1016/j.gsf.2014.02.009.
Maher, N., S. Milinski, and R. Ludwig, 2021: Large ensemble climate model simulations: Introduction, overview, and future prospects for utilising multiple types of large ensemble. Earth System Dynamics, 12, 401−418, https://doi.org/10.5194/esd-12-401-2021.
Maher, N., and Coauthors, 2019: The max Planck institute grand ensemble: Enabling the exploration of climate system variability. Journal of Advances in Modeling Earth Systems, 11, 2050−2069, https://doi.org/10.1029/2019MS001639.
Mamalakis, A., and Coauthors, 2021: Zonally contrasting shifts of the tropical rain belt in response to climate change. Nature Climate Change, 11, 143−151, https://doi.org/10.1038/s41558-020-00963-x.
Meehl, G. A., H. Y. Teng, and J. M. Arblaster, 2014: Climate model simulations of the observed early-2000s hiatus of global warming. Nature Climate Change, 4, 898−902, https://doi.org/10.1038/nclimate2357.
Meehl, G. A., A. X. Hu, B. D. Santer, and S.-P. Xie, 2016: Contribution of the Interdecadal Pacific Oscillation to twentieth-century global surface temperature trends. Nature Climate Change, 6, 1005−1008, https://doi.org/10.1038/NCLIMATE3107.
Milinski, S., N. Maher, and D. Olonscheck, 2020: How large does a large ensemble need to be? Earth System Dynamics, 11, 885−901, https://doi.org/10.5194/esd-11-885-2020.
Moon, S., and K.-J. Ha, 2020: Future changes in monsoon duration and precipitation using CMIP6,. npj Climate and Atmospheric Science, 3, 45, https://doi.org/10.1038/s41612-020-00151-w.
Morice, C. P., and Coauthors, 2021: An updated assessment of near-surface temperature change from 1850: The HadCRUT5 data set. J. Geophys. Res.: Atmos., 126, e2019JD032361, https://doi.org/10.1029/2019JD032361.
Norris, J., A. Hall, D. Chen, C. W. Thackeray, and G. D. Madakumbura, 2021: Assessing the representation of synoptic variability associated with California extreme precipitation in CMIP6 models. J. Geophys. Res.: Atmos., 126, e2020JD033938, https://doi.org/10.1029/2020JD033938.
Pathak, R., S. Sahany, S. K. Mishra, and S. K. Dash, 2019: Precipitation biases in CMIP5 models over the South Asian region. Scientific Reports, 9, 9589, https://doi.org/10.1038/s41598-019-45907-4.
Rahmstorf, S., J. E. Box, G. Feulner, M. E. Mann, A. Robinson, S. Rutherford, and E. J. Schaffernicht, 2015: Exceptional twentieth-century slowdown in Atlantic Ocean overturning circulation. Nature Climate Change, 5, 475−480, https://doi.org/10.1038/nclimate2554.
Rodgers, K. B., J. Lin, and T. L. Frölicher, 2015: Emergence of multiple ocean ecosystem drivers in a large ensemble suite with an Earth system model. Biogeosciences, 12, 3301−3320, https://doi.org/10.5194/bg-12-3301-2015.
Rodgers, K. B., and Coauthors, 2021: Ubiquity of human-induced changes in climate variability. Earth System Dynamics, 12, 1393−1411, https://doi.org/10.5194/esd-12-1393-2021.
Rohde, R. A., and Z. Hausfather, 2020: The berkeley earth land/ocean temperature record. Earth System Science Data, 12, 3469−3479, https://doi.org/10.5194/essd-12-3469-2020.
Schiemann, R., M. E. Demory, M. S. Mizielinski, M. J. Roberts, L. C. Shaffrey, J. Strachan, and P. L. Vidale, 2014: The sensitivity of the tropical circulation and Maritime Continent precipitation to climate model resolution. Climate Dyn., 42, 2455−2468, https://doi.org/10.1007/s00382-013-1997-0.
Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, M. Ziese, and B. Rudolf, 2014: GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor. Appl. Climatol., 115, 15−40, https://doi.org/10.1007/s00704-013-0860-x.
Selten, F. M., G. W. Branstator, H. A. Dijkstra, and M. Kliphuis, 2004: Tropical origins for recent and future Northern Hemisphere climate change. Geophys. Res. Lett., 31, L21205, https://doi.org/10.1029/2004GL020739.
Seneviratne, S. I., and Coauthors, 2021: Weather and climate extreme events in a changing climate. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, V. Masson-Delmotte et al., Eds., Cambridge University Press.
Smeed, D. A., and Coauthors, 2018: The North Atlantic Ocean is in a state of reduced overturning. Geophys. Res. Lett., 45, 1527−1533, https://doi.org/10.1002/2017GL076350.
Swart, N. C., and Coauthors, 2019: The Canadian earth system model version 5 (CanESM5.0.3). Geoscientific Model Development, 12, 4823−4873, https://doi.org/10.5194/gmd-12-4823-2019.
Wang, B., and Q. H. Ding, 2008: Global monsoon: Dominant mode of annual variation in the tropics. Dyn. Atmos. Oceans, 44, 165−183, https://doi.org/10.1016/j.dynatmoce.2007.05.002.
Weijer, W., W. Cheng, O. A. Garuba, A. Hu, and B. T. Nadiga, 2020: CMIP6 models predict significant 21st century decline of the Atlantic meridional overturning circulation. Geophys. Res. Lett., 47, e2019GL086075, https://doi.org/10.1029/2019GL086075.
Wyser, K., T. Koenigk, U. Fladrich, R. Fuentes-Franco, M. P. Karami, and T. Kruschke, 2021: The SMHI Large Ensemble (SMHI-LENS) with EC-Earth3.3.1,. Geoscientific Model Development, 14, 4781−4796, https://doi.org/10.5194/gmd-14-4781-2021.
Xie, Z., and Coauthors, 2020: Land surface model CAS-LSM: Model description and evaluation. Journal of Advances in Modeling Earth Systems, 12, e2020MS002339, https://doi.org/10.1029/2020MS002339.
Yang, B., and Coauthors, 2019: Better monsoon precipitation in coupled climate models due to bias compensation. npj Climate and Atmospheric Science, 2, 43, https://doi.org/10.1038/s41612-019-0100-x.
Zelle, H., G. J. van Oldenborgh, G. Burgers, and H. Dijkstra, 2005: El Niño and greenhouse warming: Results from ensemble simulations with the NCAR CCSM. J. Climate, 18, 4669−4683, https://doi.org/10.1175/JCLI3574.1.
Zhang, R., R. Sutton, G. Danabasoglu, Y. O. Kwon, R. Marsh, S. G. Yeager, D. E. Amrhein, and C. M. Little, 2019: A review of the role of the Atlantic meridional overturning circulation in Atlantic multidecadal variability and associated climate impacts. Rev. Geophys., 57, 316−375, https://doi.org/10.1029/2019RG000644.
Zhang, X. B., L. Alexander, G. C. Hegerl, P. Jones, A. K. Tank, T. C. Peterson, B. Trewin, and F. W. Zwiers, 2011: Indices for monitoring changes in extremes based on daily temperature and precipitation data. WIREs Climate Change, 2, 851−870, https://doi.org/10.1002/wcc.147.
Zhou, T. J., 2021: New physical science behind climate change: What does IPCC AR6 tell us? The Innovation, 2, 100173, https://doi.org/10.1016/j.xinn.2021.100173.
Zhou, X., H. Matthes, A. Rinke, B. Huang, K. Yang, and K. Dethloff, 2019: Simulating Arctic 2-m air temperature and its linear trends using the HIRHAM5 regional climate model. Atmospheric Research, 217, 137−149, https://doi.org/10.1016/j.atmosres.2018.10.022.