Identifying Robust Cloud Feedbacks in Observations and Models




  • Chao, L.-W., M. D. Zelinka, and A. E. Dessler, 2024: Evaluating cloud feedback components in observations and their representation in climate models. J. Geophys. Res., 129, e2023JD039427. doi:10.1029/2023JD039427.

  • Qin, Y., X. Zheng, S. A. Klein, M. D. Zelinka, P.-L. Ma, J.-C. Golaz, S. Xie, 2024: Causes of Reduced Climate Sensitivity in E3SM from Version 1 to Version 2, J. Adv. Model. Earth Syst., doi:10.1029/2023MS003875.


  • Bonan, D. B., N. Feldl, M. D. Zelinka, and L. C. Hahn, 2023: Contributions to regional precipitation change and its polar-amplified pattern under warming, Environ. Res.: Climate, 2, 035010, doi:10.1088/2752-5295/ace27a.

  • Cropper, S., C. Thackeray, and J. Emile-Geay, 2023. Revisiting A Constraint On Equilibrium Climate Sensitivity From A Last Millennium Perspective, Geophys. Res. Lett. 50. doi:10.1029/2023GL104126.

  • Myers, T. A., M. D. Zelinka, and S. A. Klein, 2023: Observational Constraints on the Cloud Feedback Pattern Effect, J. Climate, 36, 6533–6545, doi:10.1175/JCLI-D-22-0862.1.

  • Rugenstein, M., M. D. Zelinka, K. Karnauskas, P. Ceppi, and T. Andrews, 2023: Patterns of Surface Warming Matter for Climate Sensitivity, Eos, 104, doi:10.1029/2023EO230411.

  • Samset, B., C. Zhou, J. S. Fuglestvedt, M. T. Lund, J. Marotzke, and M. D. Zelinka, 2023: Steady global surface warming from 1973 to 2022 but increased warming rate after 1990, Commun. Earth Environ., 4, 400, doi:10.1038/s43247-023-01061-4.

  • Tang, Q., et al. including Y. Qin, 2023: The Fully Coupled Regionally Refined Model of E3SM Version 2: Overview of the Atmosphere, Land, and River, Geosci. Model Dev., doi:10.5194/gmd-2022-262.

  • 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.

  • Zelinka, M. D., C. J. Smith, Y. Qin, and K. E. Taylor, 2023: Comparison of methods to estimate aerosol effective radiative forcings in climate models, Atmos. Chem. Phys., 23, 8879–8898, doi:10.5194/acp-23-8879-2023.

  • 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.


  • 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.

  • Golaz, J.-C., et al. including Y. Qin and P.-L. Ma, 2022: The DOE E3SM Model version 2: Overview of the physical model and initial model evaluation, J. Adv. Model. Earth Syst., 14, doi:10.1029/2022MS003156.

  • 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.

  • 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 E3SM Atmosphere Model version 1, Geosci. Model Dev., doi:10.5194/gmd-2021-298.

  • Norris, J., A. Hall, C. W. Thackeray, D. Chen, and G. Madakumbura, 2022, Evaluating hydrologic sensitivity in CMIP6 models: anthropogenic forcing versus ENSO, J. Climate, 35, 6955–6968, 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., 127, e2022JD037745, doi: 10.1029/2022JD037745.

  • 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. Chang., doi:10.1038/s41558-022-01329-1.

  • 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.


  • Chen, D., J. Norris, N. Goldenson, C. Thackeray, and A. Hall, 2021: A distinct atmospheric mode for California precipitation. J. Geophys. Res., 126, e2020JD034403, doi:10.1029/2020JD034403.

  • 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.

  • Ma, H.-Y., et al. including S. A. Klein and M. D. Zelinka, 2021: A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales, Geosci. Model Dev., 14, 73–90, doi:10.5194/gmd-14-73-2021.

  • 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, doi:10.1038/s41558-021-01039-0.

  • Norris, J., Hall, A., Neelin, J. D., Thackeray, C. W., and Chen, D., 2021: Evaluation of the Tail of the Probability Distribution of Daily and Subdaily Precipitation in CMIP6 Models, J. Climate, 34(7), 2701-2721, doi: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., 126, doi:10.1029/2020jd033938.

  • Pihl, E. et al. including M. D. Zelinka, 2021: 10 new insights in climate science 2020 - a horizon scan. Global Sustainability, 1-65, doi:10.1017/sus.2021.2.

  • Po-Chedley, S., B. D. Santer, S. Fueglistaler, M. D. Zelinka, P. J. Cameron-Smith, J. F. Painter, and Q. Fu, 2021: Natural variability can explain model-satellite differences in tropical tropospheric warming, Proc. Natl. Acad. Sci., doi:10.1073/pnas.2020962118.

  • Santer, B. D., et al. including M. D. Zelinka, 2021: Using climate model simulations to constrain observations, J. Climate, doi:10.1175/JCLI-D-20-0768.1.

  • 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(10), 3889-3905, doi:10.1175/JCLI-D-20-0703.1.

  • Williamson, M. S., C. W. Thackeray, P. M. Cox, A. Hall, C. Huntingford, and F. J. M. 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.


  • 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.

  • 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.

  • Sherwood, S., et al. 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.

  • 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, doi:10.1029/2019GL085782.

  • Zelinka, M. D., M. A. A. Rugenstein, S. A. Klein, 2020: A more confident view of Earth’s climate sensitivity, American Physical Society Topical Group on the Physics of Climate Newsletter.

  • 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.


  • Chen, Y.-J., Y.-T. Hwang, M. D. Zelinka, and C. Zhou, 2019: Distinct patterns of cloud changes associated with decadal variability and their contribution to observed cloud cover trends, J. Climate, 32, 7281-7301, doi:10.1175/JCLI-D-18-0443.1.

  • Colman, R., J. R. Brown, C. Franklin, L. Hanson, H. Ye, and M. D. Zelinka, 2019: Evaluating cloud feedbacks and rapid responses in the ACCESS model, J. Geophys. Res., 124, doi:10.1029/2018JD029189.

  • Eyring, V., et al. including A. D. Hall and S. A. Klein, 2019: Taking climate model evaluation to the next level, Nature Clim. Change, doi:10.1038/s41558-018-0355-y.

  • Golaz, J.-C., et al. including P. M. Caldwell, S. A. Klein, and M. D. Zelinka, 2019: The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution, J. Adv. Model. Earth Syst., 11, 2089-2129, doi:10.1029/2018MS001603.

  • Hall, A. D., P. Cox, C. Huntingford, and S. A. Klein, 2019: Progressing emergent constraints on future climate change, Nature Clim. Change, doi:10.1038/s41558-019-0436-6.

  • Po-Chedley, S., M. D. Zelinka, N. Jeevanjee, T. J. Thorsen, and B. D. Santer, 2019: Climatology explains intermodel spread in upper tropospheric cloud and relative humidity response to greenhouse warming, Geophys. Res. Lett., 46, doi:10.1029/2019GL084786.

  • Santer, B. D., et al. including M. D. Zelinka, 2019: Celebrating the anniversary of three key events in climate change science, Nature Clim. Change, 9, 180-182, doi:10.1038/s41558-019-0424-x.

  • Santer, B. D., et al. including M. D. Zelinka, 2019: Quantifying stochastic uncertainty in detection time of human-caused climate signals, Proc. Natl. Acad. Sci., 116 (40) 19821-19827, doi:10.1073/pnas.1904586116.

  • Terai, C. R., Y. Zhang, S. A. Klein, M. D. Zelinka, J. C. Chiu, and Q. Min, 2019: Mechanisms behind the extratropical stratiform low‐cloud optical depth response to temperature in ARM site observations, J. Geophys. Res., 124, doi:10.1029/2018JD029359.

  • Zhang, Y., et al. including M. D. Zelinka, 2019: Evaluation of Clouds in Version 1 of the E3SM Atmosphere Model with Satellite Simulators, J. Adv. Model. Earth Syst., 11, 1253-1268, doi:10.1029/2018MS001562.


  • Caldwell, P. M., M. D. Zelinka, and S. A. Klein, 2018: Evaluating Emergent Constraints on Equilibrium Climate Sensitivity, J. Climate, 31, 3921-3942, doi:10.1175/JCLI-D-17-0631.1.

  • Po-Chedley, S., K. C. Armour, C. M. Bitz, M. D. Zelinka, B. D Santer, and Q. Fu, 2018: Sources of intermodel spread in the lapse rate and water vapor feedbacks, J. Climate, 31, 3187–3206, doi:10.1175/JCLI-D-17-0674.1.

  • Qu, X., A. Hall, A. M. DeAngelis, M. D. Zelinka, S. A. Klein, H. Su, B. Tian, and C. Zhai, 2018: On the emergent constraints of climate sensitivity, J. Climate, 31, 863–875, doi:10.1175/JCLI-D-17-0482.1.

  • Santer, B. D., et al including M. D. Zelinka, 2018: Human influence on the seasonal cycle of tropospheric temperature, Science, 361, eaas8806, doi:10.1126/science.aas8806.

  • Zelinka, M. D., K. M. Grise, S. A. Klein, C. Zhou, A. M. DeAngelis, and M. W. Christensen, 2018: Drivers of the Low Cloud Response to Poleward Jet Shifts in the North Pacific in Observations and Models, J. Climate, 31, 7925–7947, doi:10.1175/JCLI-D-18-0114.1.


  • Bonfils, C., G. Anderson, B. D. Santer, T. J. Phillips, K. Taylor, M. Cuntz, M. D. Zelinka, K. Marvel, B. I. Cook, I. Cvijanovic, and P. Durack, 2017: Competing influences of anthropogenic warming, ENSO, and plant physiology on future terrestrial aridity, J. Climate, 30, 6883-6904, doi:10.1175/JCLI-D-17-0005.1.

  • Ceppi, P., F. Brient, M. D. Zelinka, and D. L. Hartmann, 2017: Cloud feedback mechanisms and their representation in global climate models. WIREs Climate Change, e465, doi:10.1002/wcc.465.

  • Klein, S. A., A. Hall, J. R. Norris, and R. Pincus, 2017: Low-Cloud Feedbacks from Cloud Controlling Factors: A Review. Surv. Geophys., 38, 1307–1329, doi:10.1007/s10712-017-9433-3.

  • Tsushima, Y., F. Brient, S. A. Klein, D. Konsta, C. Nam, X. Qu, K. D. Williams, S. C. Sherwood, K. Suzuki, and M. D. Zelinka, 2017: The Cloud Feedback Model Intercomparison Project (CFMIP) Diagnostic Codes Catalogue – metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models, Geosci. Model Dev., 10, 4285-4305,

  • Webb, M. J., Andrews, T., Bodas-Salcedo, A., Bony, S., Bretherton, C. S., Chadwick, R., Chepfer, H., Douville, H., Good, P., Kay, J. E., Klein, S. A., Marchand, R., Medeiros, B., Siebesma, A. P., Skinner, C. B., Stevens, B., Tselioudis, G., Tsushima, Y., and Watanabe, M., 2017: The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6. Geo. Mod. Dev., 10, 359-384,

  • Zelinka M. D., D. A. Randall, M. J. Webb, & S. A. Klein, 2017: Clearing clouds of uncertainty, Nature Clim. Change 7, 674–678, doi:10.1038/nclimate3402.

  • Zhou, C., M. D. Zelinka, and S. A. Klein, 2017: Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green’s Function approach. J. Adv. Model. Earth Syst., 9, 2174–2189, doi:10.1002/2017MS001096.


  • Caldwell, P. M., M. D. Zelinka, K. E. Taylor, and K. Marvel, 2016: Quantifying the sources of inter-model spread in equilibrium climate sensitivity. J. Clim., 29, 513-524, doi:10.1175/JCLI-D-15-0352.1.

  • Danco, J. F., A. M. DeAngelis, B. K. Raney, and A. J. Broccoli, 2016: Effects of a Warming Climate on Daily Snowfall Events in the Northern Hemisphere. J. Climate, 29, 6295-6318, doi:10.1175/JCLI-D-15-0687.1.

  • DeAngelis, A., X. Qu, M. D. Zelinka, and A. Hall, 2016: Corrigendum: An observational radiative constraint on hydrologic cycle intensification. Nature, doi:10.1038/nature17621.

  • DeAngelis A., X. Qu, and A. Hall, 2016: Importance of vegetation processes for model spread in the fast precipitation response to CO2 forcing. Geophysical Research Letters, 43, 12550-12559. doi:10.1002/2016GL071392.

  • Norris, J. R., R. J. Allen, A. T. Evan, M. D. Zelinka, C. W. O’Dell, and S. A. Klein, 2016: Evidence for climate change in the satellite cloud record. Nature, 536, 72-75, doi:10.1038/nature18273.

  • Terai, C. R., S. A. Klein, and M. D. Zelinka, 2016; Constraining the low-cloud optical depth feedback at middle and high latitudes using satellite observations. Journal of Geophysical Research-Atmospheres, 121, 9696-9716, doi:10.1002/2016JD025233.

  • Yuan, T., L. Oreopoulos, M. Zelinka, H. Yu, J. R. Norris, M. Chin, S. Platnick, and K. Meyer, 2016: Positive low cloud and dust feedbacks amplify tropical North Atlantic Multidecadal Oscillation, Geophys. Res. Lett., 43, 1349-1356, doi:10.1002/2016GL067679.

  • Zelinka, M. D., C. Zhou, and S. A. Klein, 2016: Insights from a Refined Decomposition of Cloud Feedbacks, Geophys. Res. Lett., 43, 9259-9269, doi:10.1002/2016GL069917.

  • Zhou, C., M. D. Zelinka, and S. A. Klein, 2016: Impact of decadal cloud variations on the Earth’s energy budget. Nature Geoscience, 9, 871-874, doi:10.1038/ngeo2828.


  • Brient, F., T. Schneider, Z. Tan, S. Bony, X. Qu, and A. Hall, 2015: Shallowness of tropical low clouds as a predictor of climate models’ response to warming. Clim. Dyn., doi: 10.1007/s00382-015-2846-0.

  • DeAngelis, A. M., X. Qu, M. D. Zelinka, and A. Hall, 2015: An observational radiative constraint on hydrologic cycle intensification. Nature, doi: 10.1038/nature15770.

  • Dessler, A.E. and M. D. Zelinka, 2015. Climate Feedbacks. In: Gerald R. North (editor-in-chief), John Pyle and Fuqing Zhang (editors). Encyclopedia of Atmospheric Sciences, 2nd edition, Vol 2, pp. 18-25.

  • Klein, S. A., and A. Hall, 2015: Emergent constraints for cloud feedbacks. Current Climate Change Reports, 1, 276-287, doi: 10.1007/s40641-015-0027-1.

  • Marvel, K., M. D. Zelinka, S. A. Klein, C. Bonfils, P. M. Caldwell, C. Doutriaux, B. D. Santer, and K. E. Taylor, 2015: External influences on modeled and observed cloud trends, J. Climate, 28, 4820-4840, doi:10.1175/JCLI-D-14-00734.1.

  • Qu, X., A. Hall, S. A. Klein and P. M. Caldwell, 2015: The strength of the tropical inversion and its response to climate change in 18 CMIP5 models. Clim. Dyn., 45, 375-396, doi: 10.1007/s00382-014-2441-9.

  • Qu, X., A. Hall, S. A. Klein, and A. M. DeAngelis, 2015: Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors. Geophys. Res. Lett., 42, 7767-7775, doi:10.1002/2015GL065627.

  • Sanderson, B. M., R. Knutti, and P. M. Caldwell, 2015: Addressing interdepedency in a mutli-model ensemble by interpolation of climate models. J. Clim., 28, 5150-5170, doi:

  • Sanderson, B. M., R. Knutti, and P. M. Caldwell, 2015: A representative democracy to reduce interdependency in a multi-model ensemble. J. Clim., 28, 5171-5194, doi:

  • Zhou, C., A. E. Dessler, M. D. Zelinka, P. Yang, and T. Wang, 2015: Cirrus feedback on interannual climate fluctuations, Geophys. Res. Lett., 41, 9166-9173, doi:10.1002/2014GL062095.

  • Zhou, C., M. D. Zelinka, A. Dessler, and S. A. Klein, 2015: Relationship between inter-annual and long-term cloud feedbacks. Geophys. Res. Lett., 42, 10,463-10,469, doi:10.1002/2015GL066698.


  • Caldwell, P. M., C. S. Bretherton, M. D. Zelinka, S. A. Klein, B. D. Santer, and B. M. Sanderson, 2014: Statistical significance of climate sensitivity predictors obtained by data mining. Geophys. Res. Lett., 41, 1803-1808, doi:10.1002/2014GL059205.

  • Ceppi, P., M. D. Zelinka, and D. L. Hartmann, 2014: The Response of the Southern Hemispheric Eddy-Driven Jet to Future Changes in Shortwave Radiation in CMIP5, Geophys. Res. Lett., 41, 3244-3250, doi:10.1002/2014GL060043.

  • Gordon, N. D. and S. A. Klein, 2014: Low-cloud optical depth feedback in climate models. J. Geophys. Res., 119, 6052-6065, doi:10.1002/2013JD021052.

  • Johnston, M. S., Eliasson, S., Eriksson, P., Forbes, R. M., Gettelman, A., Raisanen, P., and Zelinka, M. D., 2014: Diagnosing the average spatio-temporal impact of convective systems - Part 2: A model intercomparison using satellite data, Atmos. Chem. Phys., 14, 8701-8721, doi:10.5194/acp-14-8701-2014.

  • Qu, X. and A. Hall, 2014: On the persistent spread in snow-albedo feedback. Clim. Dyn., 42, 69-81, doi: 10.1007/s00382-013-1774-0.

  • Qu, X., A. Hall, S. A. Klein, and P. M. Caldwell, 2014: On the spread of changes in marine low cloud cover in climate model simulations of the 21st century. Clim. Dyn., 42, 2603-2626, 10.1007/s00382-013-1945-z

  • Zelinka, M. D., T. Andrews, P. M. Forster, and K. E. Taylor, 2014: Quantifying Components of Aerosol-Cloud-Radiation Interactions in Climate Models. Journal of Geophysical Research - Atmospheres 119:7599-7615. doi:10.1002/2014JD021710.


  • Caldwell, P. M., Y. Zhang and S. A. Klein, 2013: CMIP3 subtropical stratocumulus feedback interpreted through a mixed-layer model. J. Clim., 26, 1607-1625, doi: 10.1175/JCLI-D-12-00188.1.

  • Grise, K. M., L. M. Polvani, G. Tselioudis, Y. Wu, and M. D. Zelinka, 2013: The ozone hole indirect effect: Cloud-radiative anomalies accompanying the poleward shift of the eddy-driven jet in the Southern Hemisphere. Geophys. Res. Lett., 40, doi:10.1002/grl.50675.

  • Johnston, M. S., S. Eliasson, P. Eriksson, R. M. Forbes, K. Wyser, and M. D. Zelinka, 2013: Diagnosing the average spatio-temporal impact of convective systems - Part 1: A methodology for evaluating climate models, Atmos. Chem. Phys., 13, 12043 - 12058, doi:10.5194/acp-13-12043-2013.

  • Klein, S. A., Y. Zhang, M. D. Zelinka, R. N. Pincus, J. Boyle, and P. J. Gleckler, 2013: Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator. J. Geophys. Res., 118, 1 - 14, doi:10.1002/jgrd.50141 .

  • Zelinka, M. D., S. A. Klein, K. E. Taylor, T. Andrews, M. J. Webb, J. M. Gregory, and P. M. Forster, 2013: Contributions of different cloud types to feedbacks and rapid adjustments in CMIP5. J. Clim., 26, 5007 - 5027, 10.1175/JCLI-D-12-00555.1.

  • Zhou, C., M. D. Zelinka, A. E. Dessler, P. Yang, 2013: An analysis of the short-term cloud feedback using MODIS data. J. Clim., 26, 4803 - 4815, 10.1175/JCLI-D-12-00547.1.


  • Zelinka, M. D., S. A. Klein, and D. L. Hartmann, 2012a: Computing and partitioning cloud feedbacks using cloud property histograms. Part I: Cloud radiative kernels. J. Clim., 25, 3715-3735, doi:10.1175/JCLI-D-11-00248.1.

  • Zelinka, M. D., S. A. Klein, and D. L. Hartmann, 2012b: Computing and partitioning cloud feedbacks using cloud property histograms. Part II: Attribution to changes in cloud amount, altitude, and optical depth. J. Clim., 25, 3736 - 3754, doi: 10.1175/JCLI-D-11-00249.1.