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(Researchers supported by PCMDI funding are in bold face font)
- Ahn, M.-S., P. A. Ullrich, P. J. Gleckler, J. Lee, A. C. Ordonez, and A. G. Pendergrass, 2023: Evaluating Precipitation Distributions at Regional Scales: A benchmarking framework and application to CMIP5 and CMIP6, Geosci. Model Dev., doi: 10.5194/egusphere-2022-1106, under review.
- Santer, B. D., S. Po-Chedley, L. Zhao, C.-Z. Zou, Q. Fu, S. Solomon, D. W. J. Thompson, C. Mears, and K. E. Taylor, 2023: Exceptional stratospheric contribution to human fingerprints on atmospheric temperature. Proc. Natl. Acad. Sci., in press.
- Diffenbaugh, N. S. and E. A. Barnes, 2023: Data-driven predictions of the time remaining until critical global warming thresholds are reached. Proc. Natl. Acad. Sci., 120 (6) e2207183120, doi: 10.1073/pnas.2207183120.
- Tesdal, J.-E., G. A. MacGilchrist, R. L. Beadling, S. M. Griffies, J. P. Krasting and P. J. Durack, 2023: Revisiting interior water mass responses to surface forcing changes and the subsequent effects on overturning in the Southern Ocean. J. Geophys. Res.: Oceans, 128 (3), e2022JC019105, doi: 10.1029/2022JC019105.
- Zhou, C., M. Wang, M. D. Zelinka, Y. Liu, Y. Dong, K. C. Armour, 2023: Explaining Forcing Efficacy with Pattern Effect and State Dependence, Geophys. Res. Lett., doi: 10.1029/2022GL101700.
- Beobide-Arsuaga, G., A. Düsterhus, W. A. Müller, E. A. Barnes and J. Baehr, 2023: Spring regional sea surface temperatures as a precursor of European summer heatwaves. Geophys. Res. Lett. 50 (2), doi: 10.1029/2022gl100727.
- Zelinka, M. D., I. Tan, L. Oreopoulos, G. Tselioudis, 2023: Detailing cloud property feedbacks with a regime-based decomposition, Clim Dyn., 60, 2983–3003, doi: 10.1007/s00382-022-06488-7.
- Po-Chedley, S., J. T. Fasullo, N. Siler, E. A. Barnes, Z. M. Labe, C. J. W. Bonfils, B. D. Santer, 2022: Internal variability and forcing influence model-satellite differences in the rate of tropical tropospheric warming. Proc. Natl. Acad. Sci., 119 (47) e2209431119, doi: 10.1073/pnas.2209431119.
- Ahn, M.-S., P. J. Gleckler, J. Lee, A. G. Pendergrass, and C. Jakob, 2022: Benchmarking simulated precipitation variability across timescales. J. Clim., 35, 3173--3196, doi: 10.1175/JCLI-D-21-0542.1.
- Chen, D., J. Norris, C. W. Thackeray and A. Hall, 2022: Increasing precipitation whiplash in climate change hotspots. Environ. Res. Lett., 17, 124011, doi: 10.1088/1748-9326/aca3b9.
- Hausfather, Z., K. Marvel, G. A. Schmidt, J. W. Nielsen-Gammon, and M. D. Zelinka, 2022: Climate simulations: recognize the 'hot model' problem. Nature, doi: 10.1038/d41586-022-01192-2.
- Kim, D., D. Kang, M.-S. Ahn, C. DeMott, C.-W. Hsu, C. Yoo, L. R. Leung, S. Hagos, and P. J. Rasch, 2022: The Madden--Julian Oscillation in the Energy Exascale Earth System Model Version 1. J. Adv. Model. Earth Syst., 14, 1--25, doi: .
- Kim, K.-B., K.-S. Lim, and J. Lee, 2022: Numerical errors in ice microphysics parameterizations and their effects on simulated regional climate. Asia Pac. J. Atm. Sci., doi: 10.1007/s13143-022-00288-z.
- Ma, H.-Y., S. A. Klein, J. Lee, M.-S. Ahn, C. Tao and P. J. Gleckler, 2022: Superior daily and sub-daily precipitation statistics for intense and long-lived storms in global storm-resolving models. Geophys. Res. Lett., 49 (8) e2021GL096759, doi: 10.1029/2021GL096759.
- Ma, P. L., et al. including S. A. Klein and M. D. Zelinka, 2022: Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1. Geosci. Model Dev., 15(7), 2881-2916, doi: 10.5194/gmd-15-2881-2022.
- Norris, J., A. Hall, C. W. Thackeray, D. Chen and G. D. Madakumbura, 2022: Evaluating hydrologic sensitivity in CMIP6 models: anthropogenic forcing versus ENSO, J. Climate, 35, 3355-3368, doi: 10.1175/JCLI-D-21-0842.1.
- Norris, J., D. Chen, A. Hall, and C. W. Thackeray, 2022: Moisture-budget drivers of global projections of meteorological drought from multiple GCM large ensembles, J. Geophys. Res. Atmos., 127, e2022JD037745, doi: 10.1029/2022JD037745.
- Arcodia, M., E. A. Barnes, C. Connolly, F. Davenport, Z. C. Frontera, E. Gordon, D. Hueholt, A. Mamalakis and E. Valkonen, 2022: Applied machine learning tutorial for Earth scientists. doi: 10.5281/zenodo.6686879 (not peer reviewed).
- Mayer, K. J. and E. A. Barnes, 2022: Quantifying the effect of climate change on midlatitude subseasonal prediction skill provided by the tropics. Geophys. Res. Lett., 49 (14) e2022GL098663, doi: 10.1029/2022GL098663.
- Peace, A, B. Booth, L. Regayre, K. Carslaw, D. Sexton, C. Bonfils, J. Rostron, 2022: Evaluating uncertainty in aerosol forcing of tropical precipitation shifts. Earth Syst. Dynam., 13, 1215--1232, doi: 10.5194/esd-13-1215-2022.
- Persad, G.G., B.H. Samset and L.J. Wilcox, 2022: Aerosols must be included in climate risk assessments. Nature, 611:662-664. Co-signatories: R.J. Allen, M.A. Bollasina, B.B.B. Booth, C. Bonfils, M. Joshi, M.T. Lund, K. Marvel, J. Merikanto, K. Nordling, S. Undorf, D. van Vuuren, D.M. Westervelt, A. Zhao, doi: 10.1038/d41586-022-03763-9.
- Po-Chedley, S, J. R. Christy, L. Haimberger, and C. A. Mears, 2022: Tropospheric Temperature [in "State of the Climate in 2021"], Bull. Amer. Meteor. Soc., 103 (8) S36 - S39, doi: 10.1175/BAMS-D-22-0092.1.
- Qin, Y., M. D. Zelinka, and S. A. Klein, 2022: On the Correspondence between Atmosphere-Only and Coupled Simulations for Radiative Feedbacks and Forcing from CO2, J. Geophys. Res., 127, e2021JD035460. doi:10.1029/2021JD035460.
- Samset, B., C. Zhou, J. Fuglestvedt, M. Lund, J. Marotzke, M. D. Zelinka, 2022: Earlier emergence of a temperature response to mitigation by filtering annual variability, Nat. Commun., 13, 1578, doi: 10.1038/s41467-022-29247-y.
- Thackeray, C. W., A. Hall, J. Norris and D. Chen, 2022: Constraining the increased frequency of global precipitation extremes under warming, Nat. Clim. Change, 12, 441--448, doi: 10.1038/s41558-022-01329-1.
- Labe, Z. M. and E. A. Barnes, 2022: Predicting slowdowns in decadal climate warming trends with explainable neural networks. Geophys. Res. Lett. 49 (9), doi: 10.1029/2022gl098173.
- Santer, B. D., S. Po-Chedley, N. Feldl, J. C. Fyfe, Q. Fu, S. Solomon, M. England, K. B. Rodgers, M. F. Stuecker, C. Mears, C.-Z. Zou, C. J. W. Bonfils, G. Pallotta, M. D. Zelinka, N. Rosenbloom, and J. Edwards, 2022: Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature, J. Clim., 35 (18), 6075-6100, doi: 10.1175/JCLI-D-21-0766.1.
- Tao, C., S. Xie, S. Tang, J. Lee, H.-Y. Ma, C. Zhang, and W. Lin, 2022: Diurnal cycle of precipitation over global monsoon systems in CMIP6 simulations. Clim. Dyn., doi: 10.1007/s00382-022-06546-0
- Thackeray, C.W., A. Hall, J. Norris, and D. Chen, 2022: Constraining the increased frequency of global precipitation extremes under warming. Nat. Clim. Change, 12, 441--448, doi: 10.1038/s41558-022-01329-1.
- Wang, Y., J. Mao J, F. Hoffman, C. Bonfils, H. Douville, M. Jin, P.E. Thornton, D. Ricciuto, X. Shi, H. Chen, S.D. Wullschleger, 2022, Quantification of human contribution to soil moisture-based terrestrial aridity, Nat. Commun., 13, 1-11, doi: 10.1038/s41467-022-34071-5.
- Zelinka, M. D., S. A. Klein, Y. Qin, and T. A. Myers, 2022: Evaluating climate models' cloud feedbacks against expert judgment, J. Geophys. Res., 127, e2021JD035198, doi: 10.1029/2021JD035198.
- Caldwell, P. M., and coauthors including H.-Y. Ma, 2021: Convection-permitting simulations with the E3SM global atmosphere model. J. Adv. Model. Earth Sys., doi: 10.1029/2021MS002544.
- Chen, D., A. Dai, and A. Hall, 2021: The convective-to-total precipitation ratio and the "drizzling" bias in climate models. J. Geophys. Res.-Atm., 126, e2020JD034198, doi: 10.1029/2020JD034198.
- Chen, D., J. Norris, N. Goldenson, C. W. Thackeray, and A. Hall, 2021: A distinct atmospheric mode for California precipitation. J. Geophys. Res.-Atm., 126, e2020JD034403, doi: 10.1029/2020JD034403.
- Dileepkumar, R., K. AchutoRao, C. Bonfils, T. Arulalan, 2021: On the emergence of human influence on surface air temperature changes over India. J. Geophys. Res.-Atm., 126, e2020JD032911, https://doi.org/10.1029/2020JD032911.
- Hahn, L. C., K. C. Armour, M. D. Zelinka, C. M. Bitz, and A. Donohoe, 2021: Contributions to polar amplification in CMIP5 and CMIP6 models. Front. Earth Sci., 9:710036, doi: 10.3389/feart.2021.710036.
- Kang, D., D. Kim, M.‐S. Ahn, and S.-Il An, 2021: The role of background meridional moisture gradient on the propagation of the MJO over the Maritime Continent. J. Climate, 34, 6565--6581, doi: 10.1175/JCLI-D-20-0085.1.
- Lee, J., K. Sperber, P. Gleckler, K. Taylor, and C. Bonfils, 2021: Benchmarking performance changes in the simulation of extratropical modes of variability across CMIP generations. J. Climate, https://doi.org/10.1175/JCLI-D-20-0832.1.
- Lee, J., and co-authors including P. Gleckler, K. Sperber, and G. Pallotta, 2021: On the robustness of the evaluation of ENSO in climate models: How many ensemble members are needed? Geophys. Res. Lett., 48, e2021GL095041, https://doi.org/10.1029/2021GL095041.
- Lim, K.-S. S., J.-M. Lim, J. Lee, and H. H. Shin, 2021: Impact of boundary layer simulation on predicting radioactive pollutant dispersion: a case study for HANARO Research Reactor using the WRF-MMIF-CALPUFF modeling system. Nuclear Engineering and Technology, 53, 244--252, doi: 10.1016/j.net.2020.06.011.
- Ma, H.-Y., C. Zhou, Y. Zhang, S. A. Klein, M. D. Zelinka, X. Zheng, S. Xie, W.-T. Chen, and C.-M. Wu, 2021: A multi-year short-range hindcast experiment for evaluating climate model moist processes from diurnal to interannual time scales. Geosci. Model Dev., 14, 73-90, doi: 10.5194/gmd-14-73-2021.
- Ma, H.-Y., K. Zhang, S. Tang, S. Xie, and R. Fu, 2021: Evaluation of the causes of wet-season dry biases over Amazonia in CAM5. J. Geophys. Res.Atm., 126, e2020JD033859, doi: 10.1029/2020JD0033859.
- Madakumbura, G. D., C. W. Thackeray, J. Norris, N. Goldenson, and A. Hall, 2021: Anthropogenic influence on extreme precipitation over global land areas seen in multiple observational datasets. Nature Commun., 12, 3944, doi: 10.1038/s41467-021-24262-x.
- Marvel, K., B. Cook, C. Bonfils, J. E. Smerdon, A. P. Williams, H. Liu, 2021: Projected changes to hydroclimate seasonality in the continental United States. Earth's Future, 9, e2021EF002019. https://doi.org/10.1029/2021EF002019.
- McDougall, T. J., P. M. Barker, R. M. Holmes, R. Pawlowicz, S. M. Griffies, and P. J. Durack, 2021: The interpretation of temperature and salinity variables in numerical ocean model output, and the calculation of heat fluxes and heat content. Geosci. Model Dev., 14, 6445--6466, doi: 10.5194/gmd-14-6445-2021.
- Myers, T. A., R. C. Scott, M. D. Zelinka, S. A. Klein, J. R. Norris, and P. M. Caldwell, 2021: Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity. Nature Clim. Change, 11, 501-507, doi: 10.1038/s41558-021-01039-0.
- Norris, J., A. Hall, J. D. Neelin,C. W. Thackeray, and D. Chen, 2021: Evaluation of the tail of the probability distribution of daily and sub-daily precipitation in CMIP6 models. J. Climate,34, 2701-2721, https://doi.org/10.1175/JCLI-D-20-0182.1.
- Norris, J., A. Hall, D. Chen, C. Thackeray, and G. Madakumbura, 2021: Assessing the representation of synoptic variability associated with California extreme precipitation in CMIP6 models. J. Geophys. Res.Atm., 126, e2020JD033938, doi: 10.1029/2020JD033938.
- Pan, B., and coauthors including C. Bonfils, J. Lee and H.-Y. Ma, 2021: Learning to correct climate projection biases. J. Adv. Model. Earth Sys., 13, e2021MS002509. https://doi.org/10.1029/2021MS002509.
- Petrie, R., and co-authors including S. Ames, 2021: Coordinating an operational data distribution network for CMIP6 data. Geosci. Model Dev., 14, 629--644, doi: 10.5194/gmd-14-629-2021.
- Pihl, E. and co-authors including M. D. Zelinka, 2021: 10 new insights in climate science 2020 - a horizon scan. Global Sustainability, 4, e5, 1--18, doi: 10.1017/sus.2021.2.
- Planton, Y. Y., and co-authors including J. Lee and P. J. Gleckler, 2021: Evaluating El Niño in climate models with the CLIVAR 2020 ENSO metrics package. Bull. Amer. Met. Soc., 33, E193--E217, doi: 10.1175/BAMS-D-19-0337.1.
- Po-Chedley, S., B. D. Santer, S. Fueglistaler, M. D. Zelinka, P. J. Cameron-Smith, J. Painter, and Q. Fu, 2021: Natural variability contributes to model-satellite differences in tropical tropospheric warming, Proc. Nat. Acad. Sci., 118, e2020962118, doi: 10.1073/pnas.2020962118.
- Po-Chedley, S., J. R. Christy, L. Haimberger, and C. A. Mears, 2021: Tropospheric Temperature [in " State of the Climate in 2020"], Bull. Amer. Meteor. Soc., 102, S57 - S60, https://doi.org/10.1175/BAMS-D-21-0098.1.
- Ren, P., D. Kim, M.-S. Ahn, D. Kang, and H.-L. Ren, 2021: Intercomparison of MJO column moist static energy and water vapor budget among six modern reanalysis products. J. Climate, 34, 2977--3001, doi: 10.1175/JCLI-D-20-0653.1.
- Santer, B. D., and co-authors including S. Po-Chedley, J. F. Painter, and M. D. Zelinka, 2021: Using climate model simulations to constrain observations. J. Climate, 34, 6281--6301, doi: 10.1175/JCLI-D-20-0768.1.
- Sung, H. M., and co-authors including J. Lee, 2021: Climate change projection in the twenty-first century simulated by NIMS-KMA CMIP6 model based on new GHGs concentration pathways. Asia-Pacific J. Atmos. Sci., https://doi.org/10.1007/s13143-021-00225-6.
- Szuwalski, C. and co-authors including J. Lee, 2021: Climate change and the future productivity and distribution of crab in the Bering Sea. ICES Journal of Marine Science, 78, 502--515, doi: 10.1093/icesjms/faa140.
- Tang, S., P. J. Gleckler, S. Xie, J. Lee, M.-S. Ahn, C. Covey, and C. Zhang, 2021: Evaluating diurnal and semi-diurnal cycle of precipitation in CMIP6 models using satellite- and ground-based observations, J. Climate, 34, 3189--3210, doi: https://doi.org/10.1175/JCLI-D-20-0639.1.
- Tang, S., and coauthors including H.-Y. Ma, 2021: Long-term single-column model intercomparison on the diurnal cycle of precipitation over midlatitude and tropical land. Quart. J. Roy. Met. Soc., 1--29, doi: 10.1002/qj.4222.
- Tao, C., and coauthors including H.-Y. Ma, 2021: Land-atmosphere coupling at the U.S. Southern Great Plains: A comparison on local convective regimes between ARM observations, reanalysis, and climate model simulations. J. Hydrometeorology, 22, 463--481, doi: 10.1175/JHM-D-20-0078.1.
- Thackeray, C. W.,A. Hall, M. D. Zelinka, and C. G. Fletcher, 2021: Assessing prior emergent constraints on surface albedo feedback in CMIP6. J. Climate, 34, 3889-3905, doi: 10.1175/JCLI-D-20-0703.1.
- Wang, Y., and co-authors including H.-Y. Ma, 2021: Disproportionate control on aerosol burden by light rain. Nature Geoscience, 14, 72--76, https://doi.org/10.1038/s41561-020-00675-z.
- Wang, Y., and co-authors including H.-Y. Ma, 2021: Effects of coupling a stochastic convective parameterization with the Zhang--McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model. Geosci. Model Dev., 14, 1575--1593, https://doi.org/10.5194/gmd-14-1575-2021.
- Wehner, M., J. Lee, M. Risser, P.A. Ullrich, P. Gleckler, and W. Collins, 2021: Evaluation of extreme sub-daily precipitation in high-resolution global climate model simulations. Phil. Trans. R. Soc. A, 379, 20190545, https://doi.org/10.1098/rsta.2019.0545.
- Williamson, M. S., C. W. Thackeray, P. M. Cox, A. Hall, C. Huntingford, and F. J. M. Nijsse, 2021: Emergent constraints on climate sensitivities. Rev. Mod. Phys., 93, 025004, doi: 10.1103/RevModPhys.93.025004.
- Zhou, C., M. D. Zelinka, A. E. Dessler, and M. Wang, 2021: Greater committed warming after accounting for the SST pattern effect. Nature Clim. Change, 11, 132--136, doi: 10.1038/s41558-020-00955-x.
- Ahn, M.-S., D. Kim, J. Lee, K. R. Sperber, P. J. Gleckler, X. Jiang, Y.-G. Ham, and H. Kim, 2020: MJO propagation across the Maritime Continent: Are CMIP6 models better than CMIP5 models? Geophys. Res. Lett., 47, e2020GL087250, doi: 10.1029/2020GL087250.
- Bonfils, C., B. D. Santer, J. Fyfe, K. Marvel, T. Phillips, S. Zimmerman, 2020: Human influence on joint changes in temperature, rainfall, and continental aridity. Nature Clim. Change, 10, 726–731, doi: 10.1038/s41558-020-0821-1.
- Ma, H.-Y., and Coauthors including J. Lee, A. C. Siongco and S. A. Klein, 2020: On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature. J. Climate, 34, 427–446, doi: 10.1175/JCLI-D-20-0338.1.
- Pallotta, G. and B. D. Santer, 2020: Multi-frequency analysis of simulated versus observed variability in tropospheric temperature. J. Climate, 33, 10383–10402, https://doi.org/10.1175/jcli-d-20-0023.1.
- Siongco, A. C., H.-Y. Ma, S. A. Klein, S. Xie, A. Karspeck, J. L. Anderson, K. Raeder, 2020: A hindcast approach to diagnosing the equatorial Pacific cold tongue SST bias in CESM1. J. Climate, 33, 1437–1453, doi: 10.1175/JCLI-D-19-0513.1.
- Sperber, K. R., H. Annamalai, and G. Pallotta, 2020: CMIP5: A Monte Carlo assessment of changes in summertime precipitation characteristics under RCP8.5-sensitivity to annual cycle fidelity, overconfidence, and Gaussianity. Clim. Dyn., 54, 1699–1727, doi: 10.1007/s00382-019-05082-8.
- Zelinka, M. D., T. A. Myers, D. T. McCoy, S. Po-Chedley, P. M. Caldwell, P. Ceppi, S. A. Klein, and K. E. Taylor, 2020: Causes of higher climate sensitivity in CMIP6 models. Geophys. Res. Lett., 47, e2019GL085782, doi: 10.1029/2019GL085782.
- Bretherton, C. S. and P. M. Caldwell, 2020: Combining emergent constraints for climate sensitivity. J. Climate, 33, 7413–7430, doi: 10.1175/JCLI-D-19-0911.1.
- Dong, Y. K. C. Armour, M. D. Zelinka, C. Proistosescu, D. S. Battisti, C. Zhou, and T. Andrews, 2020: Inter-model spread in the pattern effect and its contribution to climate sensitivity in CMIP5 and CMIP6 models. J. Climate, 33, 7755–7775, doi: 10.1175/JCLI-D-19-1011.1.
- Juckes, M., K. E. Taylor, P. J. Durack, B. Lawrence, M. S. Mizielinski, A. Pamment, J.-Y. Peterschmitt, M. Rixen, and S. Senesi, 2020: The CMIP6 Data Request (DREQ, version 01.00.31). Geosci. Model Dev., 13, 201–224, doi: 10.5194/gmd-13-201-2020.
- Kang, D., D. Kim, M.-S. Ahn, R. Neale, J. Lee, and P. J. Gleckler, 2020: The role of the mean state on MJO simulation in CESM2 ensemble simulation. Geophys. Res. Lett., 47, e2020GL089824, https://doi.org/10.1029/2020GL089824.
- Marvel, K., M. Biasutti, and C. Bonfils, 2020: Fingerprints of external forcings on Sahel rainfall: aerosols, greenhouse gases, and model-observation discrepancies. Environ. Res. Lett., 15, 084023, doi: 10.1088/1748-9326/ab858e.
- Meehl, G. E., C. A. Senior, V. Eyring, G. Flato, J.-F. Lamarque, R. J. Stouffer, K. E. Taylor, and M. Schlund, 2020: Context for interpreting equilibrium climate sensitivity and transient climate response from the CMIP6 earth system models. Science Advances, 6, eaba1981, doi: 10.1126/sciadv.aba1981.
- Orbe, C., and co-authors including P. J. Gleckler, J. Lee, and K. Sperber, 2020: Representation of Modes of Variability in 6 U.S. Climate Models. J. Climate, 33, 7591–7617, doi: 10.1175/JCLI-D-19-0956.1.
- Pascoe, C., B. N. Lawrence, E. Guilyardi, M. Juckes, and K. E. Taylor, 2020: Designing and documenting experiments in CMIP6. Geosci. Model Dev., 13, 2149–2167, doi: 10.5194/gmd-13-2149-2020.
- Pendergrass, A., P. J. Gleckler, L. Ruby Leung, and C. Jakob, 2020: Benchmarking simulated precipitation in Earth System Models. Bull. Amer. Met. Soc., 101, E814–E816, doi: 10.1175/BAMS-D-19-0318.1.
- Pendergrass, A. and co-authors including C. Bonfils, 2020: Flash droughts present a new challenge for subseasonal-to-seasonal prediction. Nature Clim. Change, 10, 191–199, doi: 10.1038/s41558-020-0709-0.
- Qian, Y. and co-authors including H.-Y. Ma, 2020: Neglecting irrigation contributes to the simulated summertime warm-and-dry bias in the central United States. npj Clim. Atmos. Sci., 3, 31, doi: 10.1038/s41612-020-00135-w.
- Rieger, L. A., and co-authors including P. J. Durack and S. Po-Chedley, 2020: Quantifying CanESM5 and EAMv1 sensitivities to volcanic forcing for the CMIP6 historical experiment. Geosci. Model Dev., 13, 4831–4843, doi: 10.5194/gmd-2019-381.
- Scott, R. C., T. A. Myers, J. R. Norris, M. D. Zelinka, S. A. Klein, M. Sun, and D. R. Doelling, 2020: Observed sensitivity of low cloud radiative effects to meteorological perturbations over the global oceans, J. Climate, 33, 7717–7734, doi: 10.1175/JCLI-D-19-1028.1.
- Silvy, Y., E. Guilyardi, J.-B. Sallee, and P. J. Durack, 2020: Human-induced changes to the global ocean water-masses and their time of emergence. Nature Clim. Change, 10, 1030–1036, doi: 10.1038/s41558-020-0878-x.
- Sherwood, S., and co-authors including S. A. Klein and M. D. Zelinka, 2020: An assessment of Earth’s climate sensitivity using multiple lines of evidence. Rev. Geophys., 58, e2019RG000678, doi: 10.1029/2019RG000678.
- Steiner, A., and co-authors including B. D. Santer, 2020: Observed temperature changes in the troposphere and stratosphere from 1979 to 2018. J. Climate, 33, 8165–8194, doi: 10.1175/JCLI-D-19-0998.1.
- Stephens, G. L., J. M. Slingo, E. Rignot, J. T. Reager, M. Z. Hakuba, P. J. Durack, and J. Worden, 2020: Earth's water reservoirs in a changing climate. Proc. Roy. Soc. A, 476: 20190458, doi: 10.1098/rspa.2019.0458.
- Waliser, D., and co-authors including P. J. Gleckler, K. E. Taylor, S. Ames, and P. J. Durack, 2020: Observations for Model Intercomparison Project (Obs4MIPs): Status for CMIP6. Geosci. Model Dev., 13, 2945–2958, doi: 10.5194/gmd-2019-268.
- Wehner, M., P. J. Gleckler, and J. Lee, 2020: Characterization of long period return values of extreme daily precipitation and temperature in the CMIP6 models. Weather and Climate Extremes, 30, 100283, doi: 10.1016/j.wace.2020.100283.
- Zhang, M. S. Xie, X. Liu, W. Lin, K. Zhang, H.-Y. Ma, X. Zheng, and Y. Zhang, 2020: Toward understanding the simulated phase partitioning of Arctic single-layer mixed-phase clouds in E3SM. Earth and Space Science, 7, e2020EA001125, doi: 10.1029/2020EA001125.
- Zhou, C., Y. Hu, J. Lu, and M. D. Zelinka, 2020: Responses of the Hadley Circulation to regional sea surface temperature changes, J. Climate, 33, 429–441, doi: 10.1175/JCLI-D-19-0315.1.
- Hall, A. D., P. Cox, C. Huntingford, and S. A. Klein, 2019: Progressing emergent constraints on future climate change. Nature Clim. Change, 9, 269–278, doi: 10.1038/s41558-019-0436-6.
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