Abstract
Earth’s energy imbalance has increased markedly over the past two decades, reaching a record in 2023. Both the long-term trend and year-to-year variations are linked to reduced reflection of sunlight by low-level clouds, which is pronounced over Northern Hemisphere oceans. However, the causes of these cloud changes and their implications for future Earth system evolution are unknown, raising concerns about a stronger-than-expected cloud feedback. Here we quantify the meteorological factors behind interannual cloud-radiative anomalies, several of which aligned to produce the extreme 2023 value. These meteorological variations are superposed on a background of declining sulfate aerosol concentrations, contributing to a sustained decrease in cloud reflection over the past 22 years. The resulting constraints on cloud feedback and aerosol forcing are consistent with previous studies, supporting an equilibrium climate sensitivity near 3∘C (likely range 2.7–4.1∘C). Thus, recent observations do not indicate an emerging stronger cloud feedback or underestimated future warming.
Similar content being viewed by others
Data availability
MODIS-COSP is available at https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD06COSP_M3_MODIS. Cloud radiative kernels are available at https://zenodo.org/records/1770442055. CERES-FBCT data is available at https://ceres.larc.nasa.gov/data/. ERA5 reanalysis is available at https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5. EAC4/CAMS reanalysis data is available at https://ads.atmosphere.copernicus.eu/datasets/cams-global-reanalysis-eac4-monthly. MODIS-derived Nd data are available at the Centre for Environmental Data Analysis at https://doi.org/10.5285/864a46cc65054008857ee5bb772a2a2b56. CMIP5 and CMIP6 models used in this study are from the Earth System Grid Federation at https://aims2.llnl.gov/search. The WCRP ECS code is available at https://doi.org/10.5281/zenodo.394527657.
Code availability
Code to reproduce the results of this study are available at https://doi.org/10.5281/zenodo.1889619558.
References
Loeb, N. G. et al. Observational Assessment of Changes in Earth’s Energy Imbalance Since 2000. Surveys in Geophysics https://doi.org/10.1007/s10712-024-09838-8 (2024).
Mauritsen, T. et al. Earth’s Energy Imbalance More Than Doubled in Recent Decades. AGU Adv. 6, e2024AV001636 (2025).
Goessling, H. F., Rackow, T. & Jung, T. Recent global temperature surge intensified by record-low planetary albedo. Science 387, 68–73 (2025).
Schmidt, G. Climate models can’t explain 2023’s huge heat anomaly — we could be in uncharted territory. Nature 627, 467–467 (2024).
Raghuraman, S. P., Paynter, D. & Ramaswamy, V. Anthropogenic forcing and response yield observed positive trend in Earth’s energy imbalance. Nat. Commun. 12, 4577 (2021).
Schmidt, G. A. et al. CERESMIP: a climate modeling protocol to investigate recent trends in the Earth’s Energy Imbalance. Front. Clim. 5, 1202161 (2023).
Hodnebrog, i et al. Recent reductions in aerosol emissions have increased Earth’s energy imbalance. Commun. Earth Environ. 5, 1–9 (2024).
Loeb, N. G. et al. New Generation of Climate Models Track Recent Unprecedented Changes in Earth’s Radiation Budget Observed by CERES. Geophys. Res. Lett. 47, e2019GL086705 (2020).
Ceppi, P. & Nowack, P. Observational evidence that cloud feedback amplifies global warming. Proc. Natl. Acad. Sci. 118 https://www.pnas.org/content/118/30/e2026290118 (2021).
Sherwood, S. C. et al. An Assessment of Earth’s Climate Sensitivity Using Multiple Lines of Evidence. Rev. Geophysics 58, e2019RG000678 (2020).
Quaas, J. et al. Robust evidence for reversal of the trend in aerosol effective climate forcing. Atmos. Chem. Phys. 22, 12221–12239 (2022).
Loeb, N. G., Su, W., Bellouin, N. & Ming, Y. Changes in Clear-Sky Shortwave Aerosol Direct Radiative Effects Since 2002. J. Geophys. Res.: Atmospheres 126, e2020JD034090 (2021).
Kramer, R. J. et al. Observational Evidence of Increasing Global Radiative Forcing. Geophys. Res. Lett. 48, e2020GL091585 (2021).
Cherian, R. & Quaas, J. Trends in AOD, Clouds, and Cloud Radiative Effects in Satellite Data and CMIP5 and CMIP6 Model Simulations Over Aerosol Source Regions. Geophys. Res. Lett. 47, e2020GL087132 (2020).
Gettelman, A. et al. Has Reducing Ship Emissions Brought Forward Global Warming? Geophys. Res. Lett. 51, e2024GL109077 (2024).
Yuan, T. et al. Abrupt reduction in shipping emission as an inadvertent geoengineering termination shock produces substantial radiative warming. Commun. Earth Environ. 5, 1–8 (2024).
Watson-Parris, D. et al. Surface temperature effects of recent reductions in shipping SO2 emissions are within internal variability. Atmos. Chem. Phys. 25, 4443–4454 (2025).
Hansen, J. E. et al. Global Warming Has Accelerated: Are the United Nations and the Public Well-Informed?. Environ.: Sci. Policy Sustain. Dev. 67, 6–44 (2025).
Scott, R. C. et al. Observed Sensitivity of Low-Cloud Radiative Effects to Meteorological Perturbations over the Global Oceans. J. Clim. 33, 7717–7734 (2020).
Myers, T. A. et al. Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity. Nat. Clim. Change 11, 501–507 (2021).
Wall, C. J. et al. Assessing effective radiative forcing from aerosol–cloud interactions over the global ocean. Proc. Natl. Acad. Sci. 119, e2210481119 (2022).
Ceppi, P., Myers, T. A., Nowack, P., Wall, C. J. & Zelinka, M. D. Implications of a Pervasive Climate Model Bias for Low-Cloud Feedback. Geophys. Res. Lett. 51, e2024GL110525 (2024).
Pincus, R. et al. Updated observations of clouds by MODIS for global model assessment. Earth Syst. Sci. Data 15, 2483–2497 (2023).
Zhou, C., Zelinka, M. D., Dessler, A. E. & Yang, P. An analysis of the short-term cloud feedback using MODIS data. J. Climate. 26, 4803–4815 (2013).
Zelinka, M. D., Klein, S. A. & Hartmann, D. L. Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels https://journals.ametsoc.org/view/journals/clim/25/11/jcli-d-11-00248.1.xml (2012).
England, M. H. et al. Drivers of the extreme North Atlantic marine heatwave during 2023. Nature 642, 636–643 (2025).
Forster, P. et al. The Earth’s energy budget, climate feedbacks, and climate sensitivity. In Masson-Delmotte, V. et al. (eds.) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2021). https://doi.org/10.1017/9781009157896.009
Bellouin, N. et al. Bounding Global Aerosol Radiative Forcing of Climate Change. Rev. Geophysics 58, e2019RG000660 (2020).
Park, C., Soden, B. J., Kramer, R. J., L’Ecuyer, T. S. & He, H. Observational constraints suggest a smaller effective radiative forcing from aerosol–cloud interactions. Atmos. Chem. Phys. 25, 7299–7313 (2025).
Qu, X., Hall, A., Klein, S. A. & DeAngelis, A. M. Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors. Geophys. Res. Lett. 42, 7767–7775 (2015).
Myers, T. A. & Norris, J. R. Reducing the uncertainty in subtropical cloud feedback. Geophys. Res. Lett. 43, 2144–2148 (2016).
Cesana, G. V. & Del Genio, A. D. Observational constraint on cloud feedbacks suggests moderate climate sensitivity. Nat. Clim. Change 11, 213–218 (2021).
Zelinka, M. D., Chao, L.-W., Myers, T. A., Qin, Y. & Klein, S. A. Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels. Atmos. Chem. Phys. 25, 1477–1495 (2025).
Sun, M. et al. Clouds and the Earth’s Radiant Energy System (CERES) FluxByCldTyp Edition 4 Data Product. J. Atmos. Ocean. Technol. 39, 303–318 (2022).
Loeb, N. G. et al. Continuity in Top-of-Atmosphere Earth Radiation Budget Observations https://journals.ametsoc.org/view/journals/clim/37/23/JCLI-D-24-0180.1.xml (2024).
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorological Soc. 146, 1999–2049 (2020).
Wood, R. & Bretherton, C. S. On the Relationship between Stratiform Low Cloud Cover and Lower-Tropospheric Stability https://journals.ametsoc.org/view/journals/clim/19/24/jcli3988.1.xml (2006).
Inness, A. et al. The CAMS reanalysis of atmospheric composition. Atmos. Chem. Phys. 19, 3515–3556 (2019).
Peuch, V.-H. et al. The Copernicus Atmosphere Monitoring Service: From Research to Operations https://journals.ametsoc.org/view/journals/bams/103/12/BAMS-D-21-0314.1.xml (2022).
Remer, L. A. et al. The MODIS Aerosol Algorithm, Products, and Validation https://journals.ametsoc.org/view/journals/atsc/62/4/jas3385.1.xml (2005).
Levy, R. C. et al. The Collection 6 MODIS aerosol products over land and ocean. Atmos. Meas. Tech. 6, 2989–3034 (2013).
Popp, T. et al. Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci). Remote Sens. 8, 421 (2016).
Seethala, C., Norris, J. R. & Myers, T. A. How Has Subtropical Stratocumulus and Associated Meteorology Changed since the 1980s? https://journals.ametsoc.org/view/journals/clim/28/21/jcli-d-15-0120.1.xml (2015).
Klein, S. A., Hall, A., Norris, J. R. & Pincus, R. Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review. Surv. Geophysics 38, 1307–1329 (2017).
Kutner, M. H., Nachtsheim, C. J., Neter, J. & Li, W.Applied Linear Statistical Models (McGraw-Hill Irwin, New York, NY, 2004), 5 edn.
Gryspeerdt, E. et al. The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data. Atmos. Meas. Tech. 15, 3875–3892 (2022).
Grosvenor, D. P. et al. Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives. Rev. Geophysics 56, 409–453 (2018).
Bennartz, R. & Rausch, J. Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations. Atmos. Chem. Phys. 17, 9815–9836 (2017).
Zhu, Y., Rosenfeld, D. & Li, Z. Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus?. J. Geophys. Res.: Atmospheres 123, 8754–8767 (2018).
Zelinka, M. D., Smith, C. J., Qin, Y. & Taylor, K. E. Comparison of methods to estimate aerosol effective radiative forcings in climate models. Atmos. Chem. Phys. 23, 8879–8898 (2023).
Pincus, R., Forster, P. M. & Stevens, B. The Radiative Forcing Model Intercomparison Project (RFMIP): experimental protocol for CMIP6. Geoscientific Model Dev. 9, 3447–3460 (2016).
Wu, M., Su, H. & Neelin, J. D. Multi-objective observational constraint of tropical Atlantic and Pacific low-cloud variability narrows uncertainty in cloud feedback. Nat. Commun. 16, 218 (2025).
Bretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M. & Bladé, I. The Effective Number of Spatial Degrees of Freedom of a Time-Varying Field https://journals.ametsoc.org/view/journals/clim/12/7/1520-0442_1999_012_1990_tenosd_2.0.co_2.xml (1999).
Lewis, H. & Bellon, G. Contextualizing GCM Biases in Low-Cloud Coverage: The Role of Large-Scale Conditions. Geophys. Res. Lett. 52, e2025GL116330 (2025).
Zelinka, M. D. mzelinka/cloud-radiative-kernels: Nov 24, 2025 Release https://zenodo.org/records/17704420 (2025).
Gryspeerdt, E. et al. Cloud droplet number concentration, calculated from the MODIS (Moderate resolution imaging spectroradiometer) cloud optical properties retrieval and gridded using different sampling strategies https://catalogue.ceda.ac.uk/uuid/864a46cc65054008857ee5bb772a2a2b (2022).
Webb, M. Code and Data for WCRP Climate Sensitivity Assessment https://zenodo.org/records/3945276 (2020).
Zelinka, M. mzelinka/CCF_analysis: Mar 6, 2026 Release https://zenodo.org/records/18896195 (2026).
Acknowledgements
The effort of M.Z., Y.Q., L.W.C., and S.P. was supported by the U.S. Department of Energy (DOE) Office of Science Biological and Environmental Research program Regional and Global Model Analysis program area and was performed under the auspices of the DOE by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. T.M. was supported by NOAA cooperative agreement NA22OAR4320151. The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of NOAA or the U.S. Department of Commerce. P.L.M. and A.G. were supported as part of the Enabling Aerosol-cloud interactions at GLobal convection-permitting scalES (EAGLES) project (project no. 74358), funded by the U.S. DOE, Office of Science, Office of Biological and Environmental Research, Earth System Model Development (ESMD) and Regional & Global Model Analysis (RGMA) program areas. The Pacific Northwest National Laboratory is operated for the U.S. Department of Energy by the Battelle Memorial Institute under contract DE-AC05-76RL01830. C.W. is funded by the European Union (ERC, AC3S, project number 101156240). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. P.C. was supported by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding Guarantee (grant EP/Y036123/1). P.C. was additionally supported through UK Natural Environmental Research Council (NERC) grants NE/V012045/1 and NE/T006250/1. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy User Facility, using NERSC award BER-ERCAP0033047. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP and ESGF.
Author information
Authors and Affiliations
Contributions
Conceptualization: M.Z., A.G. Methodology: M.Z., T.M., C.W., P.C.; Investigation: M.Z., L.C. Visualization: M.Z. Writing - original draft: M.Z. Writing - review & editing: M.Z., T.M., Y.Q., L.C., S.K., S.P., P.M., C.W., P.C., A.G.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Communications Earth & Environment thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editors: Zijun Li, and ChenRui Diao. A peer review file is available
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Zelinka, M.D., Myers, T.A., Qin, Y. et al. Recent cloud trends and extremes reaffirm established bounds on cloud feedback and aerosol-cloud interactions. Commun Earth Environ (2026). https://doi.org/10.1038/s43247-026-03461-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s43247-026-03461-8
