publications

2025

1. Sea ice pattern effect on Earth’s energy budget is characterized by hemispheric asymmetry

   Chen Zhou, Qingming Wang, Ivy Tan, Lujun Zhang, Mark D. Zelinka, Minghuai Wang, and Jonah Bloch-Johnson

   Science Advances, Feb 2025

   Abs DOI

   Earth’s energy budget is sensitive to the spatial distribution of sea surface temperature and sea ice concentration (SIC) change, but the global radiative effect of changes in SIC spatial distribution has not been quantified. We show that SIC-induced radiation anomalies at the top of the atmosphere are sensitive to the location of SIC reduction in each season, which qualitatively explains how and why the effect of sea ice loss on Earth’s energy budget is determined by its spatial pattern. Idealized experiments indicate that SIC-induced surface warming is greater in the Arctic regions, resulting in a more negative Planck feedback. Global low-level cloud cover responses to Arctic and Antarctic SIC reduction are also distinct, leading to more negative SIC-cloud feedback in Arctic regions. SIC-induced albedo feedback is sensitive to latitude due to inhomogeneous solar radiation at the surface. As a result, the simulated radiative effect of SIC anomalies during 1980–2019 is dominated by variations in the spatial pattern of SIC.

2. Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels

   Mark D. Zelinka, Li-Wei Chao, Timothy A. Myers, Yi Qin, and Stephen A. Klein

   Atmospheric Chemistry and Physics, Feb 2025

   Abs DOI

   The cloud radiative kernel method is a popular approach to quantify cloud feedbacks and rapid cloud adjustments to increased CO2 concentrations and to partition contributions from changes in cloud amount, altitude, and optical depth. However, because this method relies on cloud property histograms derived from passive satellite sensors or produced by passive satellite simulators in models, changes in obscuration of lower-level clouds by upper-level clouds can cause apparent low-cloud feedbacks and adjustments, even in the absence of changes in lower-level cloud properties. Here, we provide a methodology for properly diagnosing the impact of changing obscuration on cloud feedbacks and adjustments and quantify these effects across climate models. Averaged globally and across global climate models, properly accounting for obscuration leads to weaker positive feedbacks from lower-level clouds and stronger positive feedbacks from upper-level clouds while simultaneously removing a mostly artificial anti-correlation between them. Given that the methodology for diagnosing cloud feedbacks and adjustments using cloud radiative kernels has evolved over several papers, and obscuration effects have only occasionally been considered in recent papers, this paper serves to establish recommended best practices and to provide a corresponding code base for community use.

3. Earth’s Energy Imbalance More Than Doubled in Recent Decades

   Thorsten Mauritsen, Yoko Tsushima, Benoit Meyssignac, Norman G. Loeb, Maria Hakuba, Peter Pilewskie, Jason Cole, Kentaroh Suzuki, Thomas P. Ackerman, Richard P. Allan, and 47 more authors

   AGU Advances, Feb 2025

   Abs DOI

   Global warming results from anthropogenic greenhouse gas emissions which upset the delicate balance between the incoming sunlight, and the reflected and emitted radiation from Earth. The imbalance leads to energy accumulation in the atmosphere, oceans and land, and melting of the cryosphere, resulting in increasing temperatures, rising sea levels, and more extreme weather around the globe. Despite the fundamental role of the energy imbalance in regulating the climate system, as known to humanity for more than two centuries, our capacity to observe it is rapidly deteriorating as satellites are being decommissioned.

4. Radiative, Hydrologic, and Circulation Responses to Warming in Cess-Potter Simulations Using the Global 3.25-km SCREAM

   C. R. Terai, N. D. Keen, P. M. Caldwell, H. Beydoun, P. A. Bogenschutz, L.-W. Chao, B. R. Hillman, H.-Y. Ma, Mark D. Zelinka, L. Bertagna, and 21 more authors

   Journal of Advances in Modeling Earth Systems, Feb 2025

   Abs DOI

   Using the global 3.25-km Simple Cloud Resolving E3SM Atmosphere Model (SCREAM 3 km), a pair of 13-month Cess-Potter simulations are performed to quantify the radiative feedbacks and the hydrologic and circulation responses to warming. Large-scale aspects of SCREAM 3 km’s top-of-atmosphere radiative fluxes, precipitation rates, and circulations are in good agreement with observations and reanalysis, with notable differences, including a drier lower free-troposphere in the Tropics, reduced precipitation and humidity over the Tropical West Pacific, and poleward shifted Southern Hemisphere midlatitude jet. In response to warming, SCREAM 3 km predicts a total radiative feedback within the top 15% of the CMIP5 and CMIP6 models, which puts it substantially higher than the feedback reported by other kilometer-scale models. SCREAM 3 km’s high radiative feedback stems from a strongly positive shortwave cloud feedback, most prominent over the mid- and high-latitudes. SCREAM 3 km’s high precipitation response also puts it among the highest of CMIP models, whereas its circulation response is within the spread of CMIP models. An ensemble of five perturbed initial condition Cess-Potter simulations with a 12 km version of SCREAM (SCREAM 12 km) is performed to characterize uncertainty and resolution sensitivity. It suggests that the uncertainty from analyzing a pair of 1-year simulations is small compared to the inter-model spread in feedbacks and precipitation response. SCREAM 12 km also produces a strong precipitation response to warming but a much lower cloud feedback and total radiative feedback. The results from these experiments suggest that the spread in climate feedbacks will likely persist in the next generation of kilometer-scale models.

5. Evaluating Mean State Cloud Properties in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM)

   Li-Wei Chao, Mark D. Zelinka, Christopher R. Terai, Hassan Beydoun, Benjamin R. Hillman, Noel D. Keen, Peter M. Caldwell, and Stephen A. Klein

   Journal of Advances in Modeling Earth Systems, Feb 2025

   Abs DOI

   Accurately simulating clouds remains a key challenge in global climate models, primarily because cloud formation involves sub-grid processes that are parameterized and crudely represented in models. This study examines the performance of DOE’s Simple Cloud-Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) in simulating cloud properties and their spatio-temporal distribution by comparing against satellite observations. Two horizontal resolutions of SCREAM (3 and 12 km) are examined, and both depict a realistic spatial structure of mean-state cloud cover but underestimate its global mean magnitude. SCREAM 3 km reasonably reproduces the distribution of mean-state cloud properties across various cloud optical thickness and cloud-top pressure regimes, with performance comparable to CMIP5 and CMIP6 ensemble and marginally outperforming SCREAM 12 km. Still, SCREAM 3 km tends to underpredict low clouds and optically thin clouds, highlighting the need for continued improvement in representing unresolved processes. This study provides a basis for confidence in the representation of clouds in SCREAM, as simulating mean-state clouds is a necessary prerequisite for trusting its cloud responses to changes in aerosols and greenhouse gases.

6. mzelinka/cloud-radiative-kernels: Nov 24, 2025 Release

   Mark D. Zelinka

   Nov 2025

   Abs DOI

   Minor updates to the attributes of the LW cloud kernel in obs_cloud_kernels4.nc and to the README file.

7. Standardising the “Gregory method” for calculating equilibrium climate sensitivity

   Anna Zehrung, Andrew D. King, Zebedee Nicholls, Mark D. Zelinka, and Malte Meinshausen

   Geoscientific Model Development, Dec 2025

   Abs DOI

   The equilibrium climate sensitivity (ECS) – the equilibrium global mean temperature response to a doubling of atmospheric CO2 – is a high-profile metric for quantifying the Earth system’s response to human-induced climate change. A widely applied approach to estimating the ECS is the “Gregory method” (Gregory et al., 2004), which uses an ordinary least squares (OLS) regression between the net radiative flux, N, and surface air temperature anomalies, ΔT, from a 150 year experiment in which atmospheric CO2 concentrations are quadrupled. The ECS is determined by extrapolating the linear fit to N=0, i.e. the ΔT-intercept, indicating the point at which the system is back in equilibrium. This method has been used to compare ECS estimates across the CMIP5 and CMIP6 ensembles and will likely be a key diagnostic for CMIP7. Despite its widespread application, there is little consistency or transparency between studies in how the climate model data is processed prior to the regression, leading to potential discrepancies in ECS estimates. We identify 32 alternative data processing pathways, varying by differences in global mean weighting, net radiative flux variable, anomaly calculation method, and linear regression fit. Using 44 CMIP6 models, we systematically assess the impact of these choices on ECS estimates and calculate uncertainty ranges using two bootstrap approaches. While the inter-model ECS range is insensitive to the data processing pathway, individual outlier models exhibit notable differences. Approximating a model’s native grid cell area (if irregular) with cosine of the latitude can decrease the ECS by 11 %, the choice of N-variable can change the ECS by 6 %, and some anomaly calculation methods can introduce spurious temporal correlations in the processed data. Beyond data processing choices, we also evaluate an alternative linear regression method – total least squares (TLS) – which has a more statistically robust basis than OLS. However, for consistency with previous literature, and given TLS may reduce the ECS compared to OLS (by up to 24 %), thereby making a known bias in the Gregory method worse, we do not feel there is sufficient clarity to recommend a transition to TLS in all cases. To improve reproducibility and comparability in future studies, we recommend a standardised Gregory method: weighting the global mean by cell area, using the top of the atmosphere (as opposed to the top of model) N-variable, and calculating anomalies by first applying a rolling average to the preindustrial control timeseries then subtracting from the raw CO2 quadrupling experiment. This approach accounts for model drift while reducing noise in the data to best meet the pre-conditions of the linear regression. While CMIP6 results of the multi-model mean ECS appear insensitive to these processing choices, similar assumptions may not hold for CMIP7, underscoring the need for standardised data preparation in future climate sensitivity assessments.

8. Global models predict clouds at the wrong time of day: Does it matter for radiation and climate?

   Travis Aerenson, Daniel McCoy, Gregory Elsaesser, Jingbo Wu, Jacqueline M. Nugent, Hunter Brown, August Mikkelsen, and Mark D. Zelinka

   Science Advances, Dec 2025

   Abs DOI

   Accurate prediction of future climate change hinges upon the ability of Earth system models (ESMs) to simulate clouds and their radiative effects. Even if an ESM can simulate the correct clouds, a systematic error in the amount of sunlight reflected by clouds (and, thus, cloud radiative effect) can exist if the clouds are simulated at the incorrect time of day. In this work, we develop an analytical model connecting diurnal cloud biases to emergent mean state radiative biases. With the use of satellite observations, we demonstrate that there are errors in the time of day that clouds are occurring in ESMs that would cause bias in shortwave cloud radiative effect (SWCRE) that is greater than 45% of the total SWCRE bias, but such errors in the cloud diurnal cycle are masked by other compensating errors, indicating that these ESMs are getting the right answer for the wrong reasons.

9. Cloud Feedback Uncertainty in the Equatorial Pacific Across CMIP6 Models

   Peter G. Hill, Declan L. Finney, and Mark D. Zelinka

   Geophysical Research Letters, Dec 2025

   Abs DOI

   Cloud feedback is the largest uncertainty in estimating Equilibrium Climate Sensitivity. In this study we focus on the equatorial Pacific, where CMIP6 model cloud feedback spread is notably large. Cloud radiative effects in this region are relevant for the global climate. Our findings show that models predict a consistent shift towards the ascent regime in response to El Nino-like sea surface warming. Models diverge in terms of the radiative impact due to differences in cloud characteristics in ascent and subsidence regimes. Using the observed relationship between circulation regime and cloud radiative effect, we find a reduction in the regional mean cloud feedback estimate from 0.77 to 0.22 }mathrmW}hspace*.5em}mathrmm^-}mathrm2}hspace*.5em}mathrmK^-}mathrm1}, though this does not substantially lessen the model spread in total feedback. Pathways to reduce this spread include: improving confidence in the regional ocean warming pattern, and using observations and models to understand cloud type and circulation interactions.

10. Impact of Turbulence Representation on the Relationship Between Cloud Feedback and Aerosol-Cloud Interaction in an E3SMv2 Perturbed Parameter Ensemble

    Yi Qin, Po-Lun Ma, Mark D. Zelinka, Stephen A. Klein, Tao Zhang, Xue Zheng, Vincent E. Larson, and Meng Huang

    Journal of Advances in Modeling Earth Systems, Dec 2025

    Abs DOI

    Recent studies reveal an anti-correlation between global cloud feedback (CF) and effective radiative forcing due to aerosol-cloud interaction (ERFaci) in Earth system models, but the physical mechanisms underlying it remain uncertain. Here we investigate how different turbulence representations contribute to this relationship over the global ocean using an ensemble of Energy Exascale Earth System Model version 2 simulations with perturbed turbulence parameters. The anti-correlation appears only in the tropical ascent regime. In the Northern Hemisphere midlatitude and high latitude regimes, there is no significant correlation, and in the tropical marine low cloud and Southern Ocean regimes, the correlation is positive. These opposite correlations are primarily driven by opposing CF responses to perturbed parameters. We find that the mean-state turbulent mixing strength affects both CF and ERFaci, enabling strong correlations in certain regimes. This study highlights the complex linkages between CF and ERFaci through turbulent processes across diverse cloud regimes.

11. Mid-latitude clouds contribute to Arctic amplification via interactions with other climate feedbacks

    David B Bonan, Jennifer E Kay, Nicole Feldl, and Mark D. Zelinka

    Environmental Research: Climate, Jan 2025

    Abs DOI

    Traditional feedback analyses, which assume that individual climate feedback mechanisms act independently and add linearly, suggest that clouds do not contribute to Arctic amplification. However, feedback locking experiments, in which the cloud feedback is disabled, suggest that clouds, particularly outside of the Arctic, do contribute to Arctic amplification. Here, we reconcile these two perspectives by introducing a framework that quantifies the interactions between radiative feedbacks, radiative forcing, ocean heat uptake, and atmospheric heat transport. We show that including the cloud feedback in a comprehensive climate model can result in Arctic amplification because of interactions with other radiative feedbacks. The surface temperature change associated with including the cloud feedback is amplified in the Arctic by the surface-albedo, Planck, and lapse-rate feedbacks. A moist energy balance model with a locked cloud feedback exhibits similar behavior as the comprehensive climate model with a disabled cloud feedback and further indicates that the mid-latitude cloud feedback contributes to Arctic amplification via feedback interactions. Feedback locking in the moist energy balance model also suggests that the mid-latitude cloud feedback contributes substantially to the intermodel spread in Arctic amplification across comprehensive climate models. These results imply that constraining the mid-latitude cloud feedback will greatly reduce the intermodel spread in Arctic amplification. Furthermore, these results highlight a previously unrecognized non-local pathway for Arctic amplification.

2024

1. Evaluating Cloud Feedback Components in Observations and Their Representation in Climate Models

   Li-Wei Chao, Mark D. Zelinka, and Andrew E. Dessler

   Journal of Geophysical Research: Atmospheres, Jan 2024

   Abs DOI

   This study quantifies the contribution of individual cloud feedbacks to the total short-term cloud feedback in satellite observations over the period 2002–2014 and evaluates how they are represented in climate models. The observed positive total cloud feedback is primarily due to positive high-cloud altitude, extratropical high- and low-cloud optical depth, and land cloud amount feedbacks partially offset by negative tropical marine low-cloud feedback. Seventeen models from the Atmosphere Model Intercomparison Project of the sixth Coupled Model Intercomparison Project are analyzed. The models generally reproduce the observed moderate positive short-term cloud feedback. However, compared to satellite estimates, the models are systematically high-biased in tropical marine low-cloud and land cloud amount feedbacks and systematically low-biased in high-cloud altitude and extratropical high- and low-cloud optical depth feedbacks. Errors in modeled short-term cloud feedback components identified in this analysis highlight the need for improvements in model simulations of the response of high clouds and tropical marine low clouds. Our results suggest that skill in simulating interannual cloud feedback components may not indicate skill in simulating long-term cloud feedback components.

2. Observational constraint on a feedback from supercooled clouds reduces projected warming uncertainty

   Grégory V. Cesana, Andrew S. Ackerman, Ann M. Fridlind, Israel Silber, Anthony D. Del Genio, Mark D. Zelinka, Hélène Chepfer, Théodore Khadir, and Romain Roehrig

   Communications Earth & Environment, Apr 2024

   Abs DOI

   The increase of carbon-dioxide-doubling-induced warming (climate sensitivity) in the latest climate models is primarily attributed to a larger extratropical cloud feedback. This is thought to be partly driven by a greater ratio of supercooled liquid-phase clouds to all clouds, termed liquid phase ratio. We use an instrument simulator approach to show that this ratio has increased in the latest climate models and is overestimated rather than underestimated as previously thought. In our analysis of multiple models, a greater ratio corresponds to stronger negative cloud feedback, in contradiction with single-model-based studies. We trace this unexpected result to a cloud feedback involving a shift from supercooled to warm clouds as climate warms, which corresponds to greater cloud amount and optical depth and weakens the extratropical cloud feedback. Better constraining this ratio in climate models – and thus this supercooled cloud feedback – impacts their climate sensitivities by up to 1 ˚C and reduces inter-model spread.

3. mzelinka/cloud-radiative-kernels: Sep 4, 2024 Release

   Mark D. Zelinka

   Sep 2024

   Abs DOI

   Substantially cleaned up the repo and provided updated backend code consistent with Zelinka et al. 2024, Technical Note: Recommendations for Diagnosing Cloud Feedbacks and Rapid Cloud Adjustments Using Cloud Radiative Kernels, submitted to ACP.

4. The Shortwave Cloud-SST Feedback Amplifies Multi-Decadal Pacific Sea Surface Temperature Trends: Implications for Observed Cooling

   Zachary I. Espinosa and Mark D. Zelinka

   Geophysical Research Letters, Sep 2024

   Abs DOI

   Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud-SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi-decadal SST variability. A heat-budget analysis reveals coupling between cloud-radiative effects, circulation, and SST gradients in driving multi-decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ∼ {\vphantom}}sim }56% on average. If models underestimate climate “noise,” as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate.

5. Implications of a Pervasive Climate Model Bias for Low-Cloud Feedback

   P. Ceppi, T. A. Myers, P. Nowack, C. J. Wall, and Mark D. Zelinka

   Geophysical Research Letters, Sep 2024

   Abs DOI

   How low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low-cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low-cloud feedback (0.45 W m−2 {\vphantom}}mathrmm^-2} K−1 {\vphantom}}mathrmK^-1}, 90% range 0.18–0.72 W m−2 {\vphantom}}mathrmm^-2} K−1 {\vphantom}}mathrmK^-1}), about twice the mean value (0.22 W m−2 {\vphantom}}mathrmm^-2} K−1 {\vphantom}}mathrmK^-1}) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean-state bias: models underestimate the low-cloud response to warming because (a) they systematically underestimate present-day tropical marine low-cloud amount, and (b) the low-cloud sensitivity to warming is proportional to this present-day low-cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

6. Relationship Between Tropical Cloud Feedback and Climatological Bias in Clouds

   Chad W. Thackeray, Mark D. Zelinka, Jesse Norris, Alex Hall, and Stephen Po-Chedley

   Geophysical Research Letters, Sep 2024

   Abs DOI

   Global climate model (GCM) projections of future climate are uncertain largely due to a persistent spread in cloud feedback. This is despite efforts to reduce this model uncertainty through a variety of emergent constraints (ECs); with several studies suggesting an important role for present-day biases in clouds. Here, we use three generations of GCMs to assess the value of climatological cloud metrics for constraining uncertainty in cloud feedback. We find that shortwave cloud radiative properties across the Southern Hemisphere extratropics are most robustly correlated with tropical cloud feedback (TCF). Using this relationship in conjunction with observations, we produce an EC that yields a TCF value of 0.52 ± 0.34 W/m2/K, which equates to a 34% reduction in uncertainty. Thus, we show that climatological cloud properties can be used to reduce uncertainty in how clouds will respond to future warming.

7. Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3

   Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, and 14 more authors

   Geoscientific Model Development, May 2024

   Abs DOI

   Systematic, routine, and comprehensive evaluation of Earth system models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize the thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) Metrics Package (PMP) is an open-source Python software package that provides quick-look objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including its extremes. The PMP comparison results are produced using all model simulations contributed to CMIP6 and earlier CMIP phases. An important objective of the PMP is to document the performance of ESMs participating in the recent phases of CMIP, together with providing version-controlled information for all datasets, software packages, and analysis codes being used in the evaluation process. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. Quantitative model evaluation provided by the PMP can assist modelers in their development priorities. In this paper, we provide an overview of the PMP, including its latest capabilities, and discuss its future direction.

8. Contributions From Cloud Morphological Changes to the Interannual Shortwave Cloud Feedback Based on MODIS and ISCCP Satellite Observations

   Ivy Tan, Mark D. Zelinka, Quentin Coopman, Brian H. Kahn, Lazaros Oreopoulos, George Tselioudis, Daniel T. McCoy, and Ninghui Li

   Journal of Geophysical Research: Atmospheres, May 2024

   Abs DOI

   The surface temperature-mediated change in cloud properties, referred to as the cloud feedback, continues to dominate the uncertainty in climate projections. A larger number of contemporary global climate models (GCMs) project a higher degree of warming than the previous generation of GCMs. This greater projected warming has been attributed to a less negative cloud feedback in the Southern Ocean. Here, we apply a novel “double decomposition method” that employs the “cloud radiative kernel” and “cloud regime” concepts, to two data sets of satellite observations to decompose the interannual cloud feedback into contributions arising from changes within and shifts between cloud morphologies. Our results show that contributions from the latter to the cloud feedback are large for certain regimes. We then focus on interpreting how both changes within and between cloud morphologies impact the shortwave cloud optical depth feedback over the Southern Ocean in light of additional observations. Results from the former cloud morphological changes reveal the importance of the wind response to warming increases low- and mid-level cloud optical thickness in the same region. Results from the latter cloud morphological changes reveal that a general shift from thick storm-track clouds to thinner oceanic low-level clouds contributes to a positive feedback over the Southern Ocean that is offset by shifts from thinner broken clouds to thicker mid- and low-level clouds. Our novel analysis can be applied to evaluate GCMs and potentially diagnose shortcomings pertaining to their physical parameterizations of particular cloud morphologies.

9. Larger Cloud Liquid Water Enhances Both Aerosol Indirect Forcing and Cloud Radiative Feedback in Two Earth System Models

   Xi Zhao, Xiaohong Liu, Lin Lin, Yi Qin, Mark D. Zelinka, Stephen A. Klein, Meng Zhang, Kai Zhang, Po-Lun Ma, Jiang Zhu, and 2 more authors

   Geophysical Research Letters, May 2024

   Abs DOI

   Previous studies have noticed that the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with a stronger cooling from aerosol-cloud interactions (ACI) also have an enhanced warming from positive cloud feedback, and these two opposing effects are counter-balanced in simulations of the historical period. However, reasons for this anti-correlation are less explored. In this study, we perturb the cloud ice microphysical processes to obtain cloud liquid of varying amounts in two Earth System Models (ESMs). We find that the model simulations with a larger liquid water path (LWP) tend to have a stronger cooling from ACI and a stronger positive cloud feedback. More liquid clouds in the mean-state present more opportunities for anthropogenic aerosol perturbations and also weaken the negative cloud feedback at middle to high latitudes. This work, from a cloud state perspective, emphasizes the influence of the mean-state LWP on effective radiative forcing due to ACI (ERFACI).

10. Causes of Reduced Climate Sensitivity in E3SM From Version 1 to Version 2

    Yi Qin, Xue Zheng, Stephen A. Klein, Mark D. Zelinka, Po-Lun Ma, Jean-Christophe Golaz, and Shaocheng Xie

    Journal of Advances in Modeling Earth Systems, May 2024

    Abs DOI

    The effective climate sensitivity in the Department of Energy’s Energy Exascale Earth System Model (E3SM) has decreased from 5.3 K in version 1 to 4.0 K in version 2. This reduction is mainly due to a weaker positive cloud feedback that leads to a stronger negative radiative feedback. Present-day atmosphere-only experiments with uniform 4 K sea surface temperature warming are used to separate the contributions of individual model modifications to the reduced cloud feedback. We find that the reduced cloud feedback is mostly driven by changes over the tropical marine low cloud regime, mainly related to a new trigger function for the deep convection scheme and modifications in the cloud microphysics scheme. The new trigger function helps weaken the low cloud reduction by increasing the cloud water detrainment at low levels from deep convection under warming. Changes to the formula of autoconversion rate from liquid to rain and an introduced minimum cloud droplet number concentration threshold in cloud microphysical calculations help sustain clouds against dissipation by suppressing precipitation generation with warming. In the midlatitudes, the increased Wegener-Bergeron-Findeisen (WBF) efficiency strongly reduces present-day liquid water and leads to a stronger negative cloud optical depth feedback. The reduced trade cumulus cloud feedback in v2 is closer to estimates from recent observational and large-eddy modeling studies but might not be due to the right physical reasons. The reduced mid-latitude cloud feedback may be more plausible because more realistic present-day mixed-phase clouds are produced through the change in the WBF efficiency.

11. The Relative Importance of Forced and Unforced Temperature Patterns in Driving the Time Variation of Low-Cloud Feedback

    Yuan-Jen Lin, Grégory V. Cesana, Cristian Proistosescu, Mark D. Zelinka, and Kyle C. Armour

    Dec 2024

    Abs DOI

    Atmospheric models forced with observed sea surface temperatures (SSTs) suggest a trend toward a more-stabilizing cloud feedback in recent decades, partly due to the surface cooling trend in the eastern Pacific (EP) and the warming trend in the western Pacific (WP). Here, we show model evidence that the low-cloud feedback has contributions from both forced and unforced feedback components and that its time variation arises in large part through changes in the relative importance of the two over time, rather than through variations in forced or unforced feedbacks themselves. Initial-condition large ensembles (LEs) suggest that the SST patterns are dominated by unforced variations for 30-yr windows ending prior to the 1980s. In general, unforced SSTs are representative of an ENSO-like pattern, which corresponds to weak low-level stability in the tropics and less-stabilizing low-cloud feedback. Since the 1980s, the forced signals have become stronger, outweighing the unforced signals for the 30-yr windows ending after the 2010s. Forced SSTs are characterized by relatively uniform warming with an enhancement in the WP, corresponding to a more-stabilizing low-cloud feedback in most cases. The time-evolving SST pattern due to this increasing importance of forced signals is the dominant contributor to the recent stabilizing shift of low-cloud feedback in the LEs. Using single-forcing LEs, we further find that if only greenhouse gases evolve with time, the transition to the domination of forced signals occurs 10–20 years earlier compared to the LEs with full forcings, which can be understood through the compensating effect between aerosols and greenhouse gases.

2023

1. mzelinka/aprp: April 7, 2023 Release

   Mark D. Zelinka

   Apr 2023

   Abs DOI

   aprp.py updated, and jupyter notebook demo now provided

2. Detailing cloud property feedbacks with a regime-based decomposition

   Mark D. Zelinka, Ivy Tan, Lazaros Oreopoulos, and George Tselioudis

   Climate Dynamics, May 2023

   Abs DOI

   Diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.

3. Comparison of methods to estimate aerosol effective radiative forcings in climate models

   Mark D. Zelinka, Christopher J. Smith, Yi Qin, and Karl E. Taylor

   Atmospheric Chemistry and Physics, Aug 2023

   Abs DOI

   Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet’s radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing due to aerosol scattering and absorption and to the indirect forcing due to aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations conducted in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and find that they are biased as a result of two large coding errors that – in most cases – fortuitously compensate. The most notable exception is the direct radiative forcing from absorbing aerosols, which is more than 40 % larger averaged across CMIP6 models in the present study. Correcting these biases eliminates the residuals and leads to better agreement with benchmark estimates derived from double calls to the radiation code. The APRP method – when properly implemented – remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available.

4. Steady global surface warming from 1973 to 2022 but increased warming rate after 1990

   B. H. Samset, C. Zhou, J. S. Fuglestvedt, M. T. Lund, J. Marotzke, and Mark D. Zelinka

   Communications Earth & Environment, Nov 2023

   Abs DOI

   The change in global mean surface temperature is a crucial and broadly used indicator of the evolution of climate change. Any decadal scale changes in warming rate are however obfuscated by internal variability. Here we show that the surface temperature increase through the recent La Nina influenced years (2022) is consistent with the 50-year trend of 0.18 °C/decade. We use an Earth System Model based tool to filter out modulations to the warming rate by sea-surface temperature patterns and find consistent warming rates in four major global temperature data series. However, we also find clear indications, in all observational series, of a step-up in warming rate since around 1990. CMIP6 models generally do not capture this observed combination of long-term warming rate and recent increase.

5. Contributions to regional precipitation change and its polar-amplified pattern under warming

   David B Bonan, Nicole Feldl, Mark D. Zelinka, and Lily C Hahn

   Environmental Research: Climate, Jul 2023

   Abs DOI

   The polar regions are predicted to experience the largest relative change in precipitation in response to increased greenhouse-gas concentrations, where a substantial absolute increase in precipitation coincides with small precipitation rates in the present-day climate. The reasons for this amplification, however, are still debated. Here, we use an atmospheric energy budget to decompose regional precipitation change from climate models under greenhouse-gas forcing into contributions from atmospheric radiative feedbacks, dry-static energy flux divergence changes, and surface sensible heat flux changes. The polar-amplified relative precipitation change is shown to be a consequence of the Planck feedback, which, when combined with larger polar warming, favors substantial atmospheric radiative cooling that balances increases in latent heat release from precipitation. Changes in the dry-static energy flux divergence contribute modestly to the polar-amplified pattern. Additional contributions to the polar-amplified response come, in the Arctic, from the cloud feedback and, in the Antarctic, from both the cloud and water vapor feedbacks. The primary contributor to the intermodel spread in the relative precipitation change in the polar region is also the Planck feedback, with the lapse rate feedback and dry-static energy flux divergence changes playing secondary roles. For all regions, there are strong covariances between radiative feedbacks and changes in the dry-static energy flux divergence that impact the intermodel spread. These results imply that constraining regional precipitation change, particularly in the polar regions, will require constraining not only individual feedbacks but also the covariances between radiative feedbacks and atmospheric energy transport.

6. Observational Constraints on the Cloud Feedback Pattern Effect

   Timothy A. Myers, Mark D. Zelinka, and Stephen A. Klein

   Aug 2023

   Abs DOI

   Model evidence for the “pattern effect” assumes that global climate models (GCMs) faithfully simulate how clouds respond to varying sea surface temperature (SST) patterns and associated meteorological perturbations. We exploit time-invariant satellite-based estimates of the sensitivity of marine low clouds to meteorological perturbations to estimate how these clouds responded to time-varying SST patterns and meteorology between 1870 and 2014. GCMs and reanalyses provide estimates of the historical meteorological changes. Observations suggest that increasing estimated inversion strength (EIS) between 1980 and 2014 produced a negative low cloud feedback, opposite to the positive feedback expected from increasing CO2. This indicates that the processes responsible for marine cloud changes from 1980 to the near present are distinct from those associated with an increase in CO2. We also observationally constrain the difference between the historical near-global marine low cloud feedback, λcloudhist, and that arising from increasing CO2, λcloud4xCO2. We find that this cloud feedback pattern effect depends strongly on time period and reanalysis dataset, and that varying changes in EIS and SST with warming explain much of its variability. Between 1980 and 2014, we estimate that λcloud4xCO2−λcloudhist=0.78±0.21 W m−2 K−1 (90% confidence) assuming meteorological changes from the Multiple Reanalysis Ensemble, implying a total pattern effect (that arising from all climate feedbacks) of 1.86 ± 0.45 W m−2 K−1. This observational evidence corroborates previous quantitative estimates of the pattern effect, which heretofore relied largely upon GCM-based cloud changes. However, disparate historical meteorological changes across individual reanalyses contribute to considerable uncertainty in its magnitude.

7. Explaining Forcing Efficacy With Pattern Effect and State Dependence

   C. Zhou, M. Wang, Mark D. Zelinka, Y. Liu, Y. Dong, and K. C. Armour

   Geophysical Research Letters, Aug 2023

   Abs DOI

   The magnitude of global surface temperature change in response to unit radiative forcing depends on the type and magnitude of forcing agent—a concept known as a “forcing efficacy.” However, the mechanisms behind the forcing efficacy are still unclear. In this study, we perform a set of simulations using CESM1 to calculate the efficacy of 10 different forcing agents defined in terms of fixed-SST effective radiative forcing, and then use a Green’s function approach to show that each forcing efficacy can be largely understood in terms of the radiative feedbacks associated with the different surface temperature patterns induced by the forcing agents (a pattern effect). We also quantify how the state dependence of feedbacks on global mean surface temperature anomalies impacts forcing efficacies. The results show that the forcing efficacy can be well reconstructed with a combination of pattern effect and state dependence.

8. Patterns of Surface Warming Matter for Climate Sensitivity

   Maria Rugenstein, Mark D. Zelinka, Kristopher Karnauskas, Paulo Ceppi, and Timothy Andrews

   Eos, Oct 2023

   Abs DOI

   Location, location, location. Surface temperature patterns play a fundamental role in Earth’s energy budget.

2022

1. Earlier emergence of a temperature response to mitigation by filtering annual variability

   B. H. Samset, C. Zhou, J. S. Fuglestvedt, M. T. Lund, J. Marotzke, and Mark D. Zelinka

   Nature Communications, Mar 2022

   Abs DOI

   The rate of global surface warming is crucial for tracking progress towards global climate targets, but is strongly influenced by interannual-to-decadal variability, which precludes rapid detection of the temperature response to emission mitigation. Here we use a physics based Green’s function approach to filter out modulations to global mean surface temperature from sea-surface temperature (SST) patterns, and show that it results in an earlier emergence of a response to strong emissions mitigation. For observed temperatures, we find a filtered 2011–2020 surface warming rate of 0.24 °C per decade, consistent with long-term trends. Unfiltered observations show 0.35 °C per decade, partly due to the El Nino of 2015–2016. Pattern filtered warming rates can become a strong tool for the climate community to inform policy makers and stakeholder communities about the ongoing and expected climate responses to emission reductions, provided an effort is made to improve and validate standardized Green’s functions.

2. Extratropical Shortwave Cloud Feedbacks in the Context of the Global Circulation and Hydrological Cycle

   Daniel T. McCoy, Paul Field, Michelle E. Frazer, Mark D. Zelinka, Gregory S. Elsaesser, Johannes Mülmenstädt, Ivy Tan, Timothy A. Myers, and Zachary J. Lebo

   Geophysical Research Letters, Mar 2022

   Abs DOI

   Shortwave (SW) cloud feedback (SWFB) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report “likely” maximum (4.5K) due to extratropical SWFB’s that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean SWFB can be predicted from the sensitivity of column-integrated liquid water mass (LWP) to moisture convergence and to surface temperature. The response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean SWFB— inconsistent with extreme ECS.

3. Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

   Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, and 32 more authors

   Geoscientific Model Development, Apr 2022

   Abs DOI

   \textlessp\textgreater\textlessstrong class="journal-contentHeaderColor"\textgreaterAbstract.\textless/strong\textgreater Realistic simulation of the Earth’s mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models’ process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.\textless/p\textgreater

4. On the Correspondence Between Atmosphere-Only and Coupled Simulations for Radiative Feedbacks and Forcing From CO2

   Yi Qin, Mark D. Zelinka, and Stephen A. Klein

   Journal of Geophysical Research: Atmospheres, Apr 2022

   Abs DOI

   Atmosphere-only experiments are widely used to investigate climate feedbacks simulated in more computationally expensive fully coupled global climate model simulations. We confirm that this remains a valid approach by comparing the radiative feedbacks and forcing between coupled and atmosphere-only simulations for the latest models taking part in the 6th phase of the Coupled Model Intercomparison Project (CMIP6). For global-mean cloud feedbacks, we find a better than previously known correspondence between these experiments, which applies even to the response of individual cloud properties (amount, altitude, and optical depth) and holds even when considering atmosphere-only simulations of only 1 yr duration. For regional cloud feedbacks, the correspondence between the two experiments is generally present at every geographic location except for the tropical Pacific but takes longer experiments to reveal. For the lapse rate and surface albedo feedbacks, the correspondence between the two experiments is weaker due to the non-uniform warming pattern and loss of sea ice in the coupled experiment. For the across-model relationship between 4xCO2 effective radiative forcing and feedback, we find a different behavior across experiments in CMIP6 than in CMIP5, casting doubt on the physical significance of previous results that highlighted an anti-correlation between the two quantities. Overall, these results confirm the utility of atmosphere-only experiments particularly to study cloud feedbacks, which are the dominant source of inter-model spread in climate sensitivity.

5. Evaluating Climate Models’ Cloud Feedbacks Against Expert Judgment

   Mark D. Zelinka, Stephen A. Klein, Yi Qin, and Timothy A. Myers

   Journal of Geophysical Research: Atmospheres, Apr 2022

   Abs DOI

   The persistent and growing spread in effective climate sensitivity (ECS) across global climate models necessitates rigorous evaluation of their cloud feedbacks. Here we evaluate several cloud feedback components simulated in 19 climate models against benchmark values determined via an expert synthesis of observational, theoretical, and high-resolution modeling studies. We find that models with smallest feedback errors relative to these benchmark values generally have moderate total cloud feedbacks (0.4–0.6 W m−2 K−1) and ECS (3–4 K). Those with largest errors generally have total cloud feedback and ECS values that are too large or too small. Models tend to achieve large positive total cloud feedbacks by having several cloud feedback components that are systematically biased high rather than by having a single anomalously large component, and vice versa. In general, better simulation of mean-state cloud properties leads to stronger but not necessarily better cloud feedbacks. The Python code base provided herein could be applied to developmental versions of models to assess cloud feedbacks and cloud errors and place them in the context of other models and of expert judgment in real-time during model development.

6. Robust Anthropogenic Signal Identified in the Seasonal Cycle of Tropospheric Temperature

   Benjamin D. Santer, Stephen Po-Chedley, Nicole Feldl, John C. Fyfe, Qiang Fu, Susan Solomon, Mark England, Keith B. Rodgers, Malte F. Stuecker, Carl Mears, and 6 more authors

   Sep 2022

   Abs DOI

   Previous work identified an anthropogenic fingerprint pattern in TAC(x, t), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite TAC(x, t) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their TAC(x, t) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3–4) intermodel and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal TAC(x, t) variability associated with the Atlantic multidecadal oscillation and El Niño–Southern Oscillation. The robustness of the seasonal cycle detection and attribution results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced TAC(x, t) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.

7. Climate simulations: recognize the ‘hot model’ problem

   Zeke Hausfather, Kate Marvel, Gavin A. Schmidt, John W. Nielsen-Gammon, and Mark D. Zelinka

   Nature, May 2022

   Abs DOI

   The sixth and latest IPCC assessment weights climate models according to how well they reproduce other evidence. Now the rest of the community should do the same.

2021

1. An underestimated negative cloud feedback from cloud lifetime changes

   Johannes Mülmenstädt, Marc Salzmann, Jennifer E. Kay, Mark D. Zelinka, Po-Lun Ma, Christine Nam, Jan Kretzschmar, Sabine Hörnig, and Johannes Quaas

   Nature Climate Change, Jun 2021

   Abs DOI

   As the atmosphere warms, part of the cloud population shifts from ice and mixed-phase (‘cold’) to liquid (‘warm’) clouds. Because warm clouds are more reflective and longer-lived, this phase change reduces the solar flux absorbed by the Earth and constitutes a negative radiative feedback. This cooling feedback is weaker in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) than in the fifth phase (CMIP5), contributing to greater greenhouse warming. Although this change is often attributed to improvements in the simulated cloud phase, another model bias persists: warm clouds precipitate too readily, potentially leading to underestimated negative lifetime feedbacks. In this study we modified a climate model to better simulate warm-rain probability and found that it exhibits a cloud lifetime feedback nearly three times larger than the default model. This suggests that model errors in cloud-precipitation processes may bias cloud feedbacks by as much as the CMIP5-to-CMIP6 climate sensitivity difference. Reliable climate model projections therefore require improved cloud process realism guided by process-oriented observations and observational constraints.

2. Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity

   Timothy A. Myers, Ryan C. Scott, Mark D. Zelinka, Stephen A. Klein, Joel R. Norris, and Peter M. Caldwell

   Nature Climate Change, Jun 2021

   Abs DOI

   Marine low clouds strongly cool the planet. How this cooling effect will respond to climate change is a leading source of uncertainty in climate sensitivity, the planetary warming resulting from CO2 doubling. Here, we observationally constrain this low cloud feedback at a near-global scale. Satellite observations are used to estimate the sensitivity of low clouds to interannual meteorological perturbations. Combined with model predictions of meteorological changes under greenhouse warming, this permits quantification of spatially resolved cloud feedbacks. We predict positive feedbacks from midlatitude low clouds and eastern ocean stratocumulus, nearly unchanged trade cumulus and a near-global marine low cloud feedback of 0.19 ± 0.12 W m−2 K−1 (90% confidence). These constraints imply a moderate climate sensitivity (~3 K). Despite improved midlatitude cloud feedback simulation by several current-generation climate models, their erroneously positive trade cumulus feedbacks produce unrealistically high climate sensitivities. Conversely, models simulating erroneously weak low cloud feedbacks produce unrealistically low climate sensitivities.

3. Greater committed warming after accounting for the pattern effect

   Chen Zhou, Mark D. Zelinka, Andrew E. Dessler, and Minghuai Wang

   Nature Climate Change, Jan 2021

   Abs DOI

   Our planet’s energy balance is sensitive to spatial inhomogeneities in sea surface temperature and sea ice changes, but this is typically ignored in climate projections. Here, we show the energy budget during recent decades can be closed by combining changes in effective radiative forcing, linear radiative damping and this pattern effect. The pattern effect is of comparable magnitude but opposite sign to Earth’s net energy imbalance in the 2000s, indicating its importance when predicting the future climate on the basis of observations. After the pattern effect is accounted for, the best-estimate value of committed global warming at present-day forcing rises from 1.31 K (0.99–2.33 K, 5th–95th percentile) to over 2 K, and committed warming in 2100 with constant long-lived forcing increases from 1.32 K (0.94–2.03 K) to over 1.5 K, although the magnitude is sensitive to sea surface temperature dataset. Further constraints on the pattern effect are needed to reduce climate projection uncertainty.

4. Using Climate Model Simulations to Constrain Observations

   Benjamin D. Santer, Stephen Po-Chedley, Carl Mears, John C. Fyfe, Nathan Gillett, Qiang Fu, Jeffrey F. Painter, Susan Solomon, Andrea K. Steiner, Frank J. Wentz, and 2 more authors

   Journal of Climate, May 2021

   Abs DOI

   Abstract We compare atmospheric temperature changes in satellite data and in model ensembles performed under phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). In the lower stratosphere, multi-decadal stratospheric cooling during the period of strong ozone depletion is smaller in newer CMIP6 simulations than in CMIP5 or satellite data. In the troposphere, however, despite forcing and climate sensitivity differences between the two CMIP ensembles, their ensemble-average global warming over 1979-2019 is very similar. We also examine four properties of tropical behavior governed by basic physical processes. The first three are ratios between trends inwater vapor (WV) and trends in sea surface temperature (SST), lower tropospheric temperature (TLT), and mid- to upper tropospheric temperature (TMT). The fourth property is the ratio between TMT and SST trends. All four ratios are tightly constrained in CMIP simulations but diverge markedly in observations. Model trend ratios between WV and temperature are closest to observed ratios when the latter are calculated with data sets exhibiting larger tropical warming of the ocean surface and troposphere. For the TMT/SST ratio, model-data consistency depends on the combination of observations used to estimate TMT and SST trends. If model expectations of these four covariance relationships are realistic, our findings reflect either a systematic low bias in satellite tropospheric temperature trends or an overestimate of the observed atmospheric moistening signal. It is currently difficult to determine which interpretation is more credible. Nevertheless, our analysis reveals anomalous covariance behavior in several observational data sets and illustrates the diagnostic power of simultaneously considering multiple complementary variables.

5. Assessing prior emergent constraints on surface albedo feedback in CMIP6

   Chad W. Thackeray, Alex Hall, Mark D. Zelinka, and Christopher G. Fletcher

   Journal of Climate, Feb 2021

   Abs DOI

   Abstract An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAFsnow) and sea ice (SAFice). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAFsnow EC is equally strong in CMIP6 as it was in past generations, while the SAFice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 ± 0.05 Wm-2K-1, or ∼61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. The NH SAF can be broken down into similar contributions from snow and sea ice over the 21st century in CMIP6. Crucially, intermodel variability in seasonal SAFsnow and SAFice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAFice, and to a lesser extent SAFsnow.

6. Natural variability contributes to model–satellite differences in tropical tropospheric warming

   Stephen Po-Chedley, Benjamin D. Santer, Stephan Fueglistaler, Mark D. Zelinka, Philip J. Cameron-Smith, Jeffrey F. Painter, and Qiang Fu

   Proceedings of the National Academy of Sciences, Mar 2021

   DOI
7. Ten new insights in climate science 2020 – a horizon scan

   Erik Pihl, Eva Alfredsson, Magnus Bengtsson, Kathryn J. Bowen, Vanesa Cástan Broto, Kuei Tien Chou, Helen Cleugh, Kristie Ebi, Clea M. Edwards, Eleanor Fisher, and 47 more authors

   Global Sustainability, Mar 2021

   Abs DOI

   Non-technical summary We summarize some of the past year’s most important findings within climate change-related research. New research has improved our understanding of Earth’s sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments. Technical summary A synthesis is made of ten fields within climate science where there have been significant advances since mid-2019, through an expert elicitation process with broad disciplinary scope. Findings include: (1) a better understanding of equilibrium climate sensitivity; (2) abrupt thaw as an accelerator of carbon release from permafrost; (3) changes to global and regional land carbon sinks; (4) impacts of climate change on water crises, including equity perspectives; (5) adverse effects on mental health from climate change; (6) immediate effects on climate of the COVID-19 pandemic and requirements for recovery packages to deliver on the Paris Agreement; (7) suggested long-term changes to governance and a social contract to address climate change, learning from the current pandemic, (8) updated positive cost–benefit ratio and new perspectives on the potential for green growth in the short- and long-term perspective; (9) urban electrification as a strategy to move towards low-carbon energy systems and (10) rights-based litigation as an increasingly important method to address climate change, with recent clarifications on the legal standing and representation of future generations. Social media summary Stronger permafrost thaw, COVID-19 effects and growing mental health impacts among highlights of latest climate science.

8. A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

   Hsi-Yen Ma, Chen Zhou, Yunyan Zhang, Stephen A. Klein, Mark D. Zelinka, Xue Zheng, Shaocheng Xie, Wei-Ting Chen, and Chien-Ming Wu

   Geoscientific Model Development, Jan 2021

   Abs DOI

   \textlessp\textgreater\textlessstrong class="journal-contentHeaderColor"\textgreaterAbstract.\textless/strong\textgreater We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model’s climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.\textless/p\textgreater

9. mzelinka/cmip56_forcing_feedback_ecs: Aug 16, 2021 Release

   Mark D. Zelinka

   Aug 2021

   Abs DOI

   This release is same as last, but comes with a zenodo doi badge.

10. mzelinka/assessed-cloud-fbks: Aug 16, 2021 Release

    Mark D. Zelinka

    Aug 2021

    Abs DOI

    Code to compare GCM and expert-assessed cloud feedback components

11. mzelinka/aprp: Sep 17, 2021 Release

    Mark D. Zelinka

    Sep 2021

    Abs DOI

    First official release.

12. Contributions to Polar Amplification in CMIP5 and CMIP6 Models

    L. C. Hahn, K. C. Armour, Mark D. Zelinka, C. M. Bitz, and A. Donohoe

    Frontiers in Earth Science, Aug 2021

    Abs DOI

    As a step towards understanding the fundamental drivers of polar climate change, we evaluate contributions to polar warming and its seasonal and hemispheric asymmetries in Coupled Model Intercomparison Project phase 6 (CMIP6) as compared with CMIP5. CMIP6 models broadly capture the observed pattern of surface- and winter-dominated Arctic warming that has outpaced both tropical and Antarctic warming in recent decades. For both CMIP5 and CMIP6, CO2 quadrupling experiments reveal that the lapse-rate and albedo feedbacks contribute most to stronger warming in the Arctic than the tropics or Antarctic. The relative strength of the polar albedo feedback in comparison to the lapse-rate feedback is sensitive to the choice of radiative kernel, and the albedo feedback contributes most to intermodel spread in polar warming at both poles. By separately calculating moist and dry atmospheric heat transport, we show that increased poleward moisture transport is another important driver of Arctic amplification and the largest contributor to projected Antarctic warming. Seasonal ocean heat storage and winter-amplified temperature feedbacks contribute most to the winter peak in warming in the Arctic and a weaker winter peak in the Antarctic. In comparison with CMIP5, stronger polar warming in CMIP6 results from a larger albedo feedback at both poles, combined with less-negative cloud feedbacks in the Arctic and increased poleward moisture transport in the Antarctic. However, normalizing by the global-mean surface warming yields a similar degree of Arctic amplification and only slightly increased Antarctic amplification in CMIP6 compared to CMIP5.

2020

1. Observed Sensitivity of Low-Cloud Radiative Effects to Meteorological Perturbations over the Global Oceans

   Ryan C. Scott, Timothy A. Myers, Joel R. Norris, Mark D. Zelinka, Stephen A. Klein, Moguo Sun, and David R. Doelling

   Journal of Climate, Sep 2020

   Abs DOI

   \textlesssection class="abstract"\textgreater\textlessh2 class="abstractTitle text-title my-1" id="d495e2"\textgreaterAbstract\textless/h2\textgreater\textlessp\textgreaterUnderstanding how marine low clouds and their radiative effects respond to changing meteorological conditions is crucial to constrain low-cloud feedbacks to greenhouse warming and internal climate variability. In this study, we use observations to quantify the low-cloud radiative response to meteorological perturbations over the global oceans to shed light on physical processes governing low-cloud and planetary radiation budget variability in different climate regimes. We assess the independent effect of perturbations in sea surface temperature, estimated inversion strength, horizontal surface temperature advection, 700-hPa relative humidity, 700-hPa vertical velocity, and near-surface wind speed. Stronger inversions and stronger cold advection greatly enhance low-level cloudiness and planetary albedo in eastern ocean stratocumulus and midlatitude regimes. Warming of the sea surface drives pronounced reductions of eastern ocean stratocumulus cloud amount and optical depth, and hence reflectivity, but has a weaker and more variable impact on low clouds in the tropics and middle latitudes. By reducing entrainment drying, higher free-tropospheric relative humidity enhances low-level cloudiness. At low latitudes, where cold advection destabilizes the boundary layer, stronger winds enhance low-level cloudiness; by contrast, wind speed variations have weak influence at midlatitudes where warm advection frequently stabilizes the marine boundary layer, thus inhibiting vertical mixing. These observational constraints provide a framework for understanding and evaluating marine low-cloud feedbacks and their simulation by models.\textless/p\textgreater\textless/section\textgreater

2. An Assessment of Earth’s Climate Sensitivity Using Multiple Lines of Evidence

   S. C. Sherwood, M. J. Webb, J. D. Annan, K. C. Armour, P. M. Forster, J. C. Hargreaves, G. Hegerl, S. A. Klein, K. D. Marvel, E. J. Rohling, and 15 more authors

   Reviews of Geophysics, Sep 2020

   Abs DOI

   We assess evidence relevant to Earth’s equilibrium climate sensitivity per doubling of atmospheric CO2, characterized by an effective sensitivity S. This evidence includes feedback process understanding, the historical climate record, and the paleoclimate record. An S value lower than 2 K is difficult to reconcile with any of the three lines of evidence. The amount of cooling during the Last Glacial Maximum provides strong evidence against values of S greater than 4.5 K. Other lines of evidence in combination also show that this is relatively unlikely. We use a Bayesian approach to produce a probability density function (PDF) for S given all the evidence, including tests of robustness to difficult-to-quantify uncertainties and different priors. The 66% range is 2.6–3.9 K for our Baseline calculation and remains within 2.3–4.5 K under the robustness tests; corresponding 5–95% ranges are 2.3–4.7 K, bounded by 2.0–5.7 K (although such high-confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent and because of greater confidence in understanding feedback processes and in combining evidence. We identify promising avenues for further narrowing the range in S, in particular using comprehensive models and process understanding to address limitations in the traditional forcing-feedback paradigm for interpreting past changes.

3. A Regime-Oriented Approach to Observationally Constraining Extratropical Shortwave Cloud Feedbacks

   Daniel T. McCoy, Paul Field, Alejandro Bodas-Salcedo, Gregory S. Elsaesser, and Mark D. Zelinka

   Journal of Climate, Oct 2020

   Abs DOI

   \textlesssection class="abstract"\textgreater\textlessh2 class="abstractTitle text-title my-1" id="d9e2"\textgreaterAbstract\textless/h2\textgreater\textlessp\textgreaterThe extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m^\textrm−2 per kelvin SST increase (35°–75°N) and 1.2–1.9 W m^\textrm−2 per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks.\textless/p\textgreater\textless/section\textgreater

4. Causes of Higher Climate Sensitivity in CMIP6 Models

   Mark D. Zelinka, Timothy A. Myers, Daniel T. McCoy, Stephen Po‐Chedley, Peter M. Caldwell, Paulo Ceppi, Stephen A. Klein, and Karl E. Taylor

   Geophysical Research Letters, Oct 2020

   Abs DOI

   Equilibrium climate sensitivity, the global surface temperature response to CO doubling, has been persistently uncertain. Recent consensus places it likely within 1.5–4.5 K. Global climate models (GCMs), which attempt to represent all relevant physical processes, provide the most direct means of estimating climate sensitivity via CO quadrupling experiments. Here we show that the closely related effective climate sensitivity has increased substantially in Coupled Model Intercomparison Project phase 6 (CMIP6), with values spanning 1.8–5.6 K across 27 GCMs and exceeding 4.5 K in 10 of them. This (statistically insignificant) increase is primarily due to stronger positive cloud feedbacks from decreasing extratropical low cloud coverage and albedo. Both of these are tied to the physical representation of clouds which in CMIP6 models lead to weaker responses of extratropical low cloud cover and water content to unforced variations in surface temperature. Establishing the plausibility of these higher sensitivity models is imperative given their implied societal ramifications.

5. Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models

   Yue Dong, Kyle C. Armour, Mark D. Zelinka, Cristian Proistosescu, David S. Battisti, Chen Zhou, and Timothy Andrews

   Journal of Climate, Sep 2020

   Abs DOI

   Abstract Radiative feedbacks depend on the spatial patterns of sea surface temperature (SST) and thus can change over time as SST patterns evolve—the so-called pattern effect. This study investigates intermodel differences in the magnitude of the pattern effect and how these differences contribute to the spread in effective equilibrium climate sensitivity (ECS) within CMIP5 and CMIP6 models. Effective ECS in CMIP5 estimated from 150-yr-long abrupt4×CO2 simulations is on average 10% higher than that estimated from the early portion (first 50 years) of those simulations, which serves as an analog for historical warming; this difference is reduced to 7% on average in CMIP6. The (negative) net radiative feedback weakens over the course of the abrupt4×CO2 simulations in the vast majority of CMIP5 and CMIP6 models, but this weakening is less dramatic on average in CMIP6. For both ensembles, the total variance in the effective ECS is found to be dominated by the spread in radiative response on fast time scales, rather than the spread in feedback changes. Using Green’s functions derived from two AGCMs shows that the spread in feedbacks on fast time scales may be primarily due to differences in atmospheric model physics, whereas the spread in feedback evolution is primarily governed by differences in SST patterns. Intermodel spread in feedback evolution is well explained by differences in the relative warming in the west Pacific warm-pool regions for the CMIP5 models, but this relation fails to explain differences across the CMIP6 models, suggesting that a stronger sensitivity of extratropical clouds to surface warming may also contribute to feedback changes in CMIP6.

6. Responses of the Hadley Circulation to Regional Sea Surface Temperature Changes

   Chen Zhou, Jian Lu, Yongyun Hu, and Mark D. Zelinka

   Journal of Climate, Jan 2020

   Abs DOI

   Abstract Idealized experiments performed with the Community Atmospheric Model 5.3 indicate that the width and strength of the Hadley circulation (HC) are sensitive to the location of sea surface temperature (SST) increases. The HC edge shifts poleward in response to SST increases over the subtropical regions near and on the equatorward flank of the HC edge, and shifts equatorward in response to warming over the tropical area except for the western Pacific Ocean and Indian Ocean. The HC is strengthened in response to SST increases over the intertropical convergence zone (ITCZ) and is weakened in response to SST increases over the subsidence branch of the HC in the subtropics. Tropical SST increases off the ITCZ tend to weaken the HC in the corresponding hemisphere and strengthen the HC in the opposite hemisphere. These results could be used to explain the simulated HC changes induced by recent SST variations, and it is estimated that more than half of the SST-induced HC widening in 1980–2014 is caused by changes in the spatial pattern of SST.

2019

1. Celebrating the anniversary of three key events in climate change science

   B. D. Santer, C. J. W. Bonfils, Q. Fu, J. C. Fyfe, G. C. Hegerl, C. Mears, J. F. Painter, S. Po-Chedley, F. J. Wentz, Mark D. Zelinka, and 1 more author

   Nature Climate Change, Jan 2019

   DOI
2. Evaluating Cloud Feedbacks and Rapid Responses in the ACCESS Model

   R. Colman, J. R. Brown, C. Franklin, L. Hanson, H. Ye, and Mark D. Zelinka

   Journal of Geophysical Research-Atmospheres, Jan 2019

   DOI
3. The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution

   J. C. Golaz, P. M. Caldwell, L. P. Van Roekel, M. R. Petersen, Q. Tang, J. D. Wolfe, G. Abeshu, V. Anantharaj, X. S. Asay-Davis, D. C. Bader, and 74 more authors

   Journal of Advances in Modeling Earth Systems, Jan 2019

   DOI
4. Evaluation of Clouds in Version 1 of the E3SM Atmosphere Model with Satellite Simulators

   Yuying Zhang, Shaocheng Xie, Wuyin Lin, Stephen A. Klein, Mark D. Zelinka, Po-Lun Ma, Philip J. Rasch, Yun Qian, Qi Tang, and Hsi-Yen Ma

   Journal of Advances in Modeling Earth Systems, Jan 2019

   DOI
5. Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations

   D. T. McCoy, P. R. Field, G. S. Elsaesser, A. Bodas-Salcedo, B. H. Kahn, Mark D. Zelinka, C. Kodama, T. Mauritsen, B. Vanniere, M. Roberts, and 7 more authors

   Atmospheric Chemistry and Physics, Jan 2019

   DOI
6. Mechanisms Behind the Extratropical Stratiform Low-Cloud Optical Depth Response to Temperature in ARM Site Observations

   C. R. Terai, Y. Zhang, S. A. Klein, Mark D. Zelinka, J. C. Chiu, and Q. Min

   Journal of Geophysical Research-Atmospheres, Jan 2019

   DOI
7. Climatology Explains Intermodel Spread in Tropical Upper Tropospheric Cloud and Relative Humidity Response to Greenhouse Warming

   Stephen Po-Chedley, Mark D. Zelinka, Nadir Jeevanjee, Tyler J. Thorsen, and Benjamin D. Santer

   Geophysical Research Letters, Jan 2019

   Abs DOI

   The response of upper tropospheric clouds and relative humidity (RH) to warming is important to the overall sensitivity of the Earth to increasing greenhouse gas concentrations. Previous research has shown that changes in hydrologic fields should closely track rising isotherms in a warming climate. Here we show that the distribution of tropical clouds and RH in general circulation models is approximately constant under greenhouse warming when using temperature as a vertical coordinate. By assuming that these fields are an invariant function of atmospheric temperature and that temperature change follows a dilute moist adiabat, we are able to accurately predict cloud fraction and RH changes in the tropical upper troposphere (150–400 hPa) in 27 general circulation models. Our results indicate that intermodel spread in changes of tropical upper tropospheric clouds and RH is closely related to differences in model climatology and could be substantially reduced if model ensembles reliably reproduced observed climatologies.

8. Quantifying stochastic uncertainty in detection time of human-caused climate signals

   Benjamin D. Santer, John C. Fyfe, Susan Solomon, Jeffrey F. Painter, Céline Bonfils, Giuliana Pallotta, and Mark D. Zelinka

   Proceedings of the National Academy of Sciences, Oct 2019

   DOI
9. Distinct Patterns of Cloud Changes Associated with Decadal Variability and Their Contribution to Observed Cloud Cover Trends

   Yong-Jhih Chen, Yen-Ting Hwang, Mark D. Zelinka, and Chen Zhou

   Journal of Climate, Nov 2019

   Abs DOI

   Abstract With the goal of understanding the relative roles of anthropogenic and natural factors in driving observed cloud trends, this study investigates cloud changes associated with decadal variability including the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO). In the preindustrial simulations of CMIP5 global climate models (GCMs), the spatial patterns and the vertical structures of the PDO-related cloud cover changes in the Pacific are consistent among models. Meanwhile, the models show consistent AMO impacts on high cloud cover in the tropical Atlantic, subtropical eastern Pacific, and equatorial central Pacific, and on low cloud cover in the North Atlantic and subtropical northeast Pacific. The cloud cover changes associated with the PDO and the AMO can be understood via the relationships between large-scale meteorological parameters and clouds on interannual time scales. When compared to the satellite records during the period of 1983–2009, the patterns of total and low cloud cover trends associated with decadal variability are significantly correlated with patterns of cloud cover trends in ISCCP observations. On the other hand, the pattern of the estimated greenhouse gas (GHG)-forced trends of total cloud cover differs from that related to decadal variability, and may explain the positive trends in the subtropical southeast Pacific, negative trends in the midlatitudes, and positive trends poleward of 50°N/S. In most models, the magnitude of the estimated decadal variability contribution to the observed cloud cover trends is larger than that contributed by GHG, suggesting the observed cloud cover trends are more closely related to decadal variability than to GHG-induced warming.

2018

1. Human influence on the seasonal cycle of tropospheric temperature

   B. D. Santer, S. Po-Chedley, Mark D. Zelinka, I. Cvijanovic, C. Bonfils, P. J. Durack, Q. Fu, J. Kiehl, C. Mears, J. Painter, and 4 more authors

   Science, Nov 2018

   DOI
2. Evaluating Emergent Constraints on Equilibrium Climate Sensitivity

   P. M. Caldwell, Mark D. Zelinka, and S. A. Klein

   Journal of Climate, Nov 2018

   DOI
3. Sources of Intermodel Spread in the Lapse Rate and Water Vapor Feedbacks

   S. Po-Chedley, K. C. Armour, C. M. Bitz, Mark D. Zelinka, B. D. Santer, and Q. Fu

   Journal of Climate, Nov 2018

   DOI
4. On the Emergent Constraints of Climate Sensitivity

   X. Qu, A. Hall, A. M. DeAngelis, Mark D. Zelinka, S. A. Klein, H. Su, B. J. Tian, and C. X. Zhai

   Journal of Climate, Nov 2018

   DOI
5. Drivers of the Low-Cloud Response to Poleward Jet Shifts in the North Pacific in Observations and Models

   Mark D. Zelinka, K. M. Grise, S. A. Klein, C. Zhou, A. M. DeAngelis, and M. W. Christensen

   Journal of Climate, Nov 2018

   DOI
6. Mixed-Phase Cloud Feedbacks

   D. T. McCoy, D. L. Hartmann, and Mark D. Zelinka

   Nov 2018

   DOI
7. The Climatic Impact of Thermodynamic Phase Partitioning in Mixed-Phase Clouds

   I. Tan, T. Storelvmo, and Mark D. Zelinka

   Nov 2018

   DOI

2017

1. Cloud feedback mechanisms and their representation in global climate models

   P. Ceppi, F. Brient, Mark D. Zelinka, and D. L. Hartmann

   Wiley Interdisciplinary Reviews-Climate Change, Nov 2017

   DOI
2. Competing Influences of Anthropogenic Warming, ENSO, and Plant Physiology on Future Terrestrial Aridity

   C. Bonfils, G. Anderson, B. D. Santer, T. J. Phillips, K. E. Taylor, M. Cuntz, Mark D. Zelinka, K. Marvel, B. I. Cook, I. Cvijanovic, and 1 more author

   Journal of Climate, Nov 2017

   DOI
3. Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green’s function approach

   C. Zhou, Mark D. Zelinka, and S. A. Klein

   Journal of Advances in Modeling Earth Systems, Nov 2017

   DOI
4. Clearing clouds of uncertainty

   Mark D. Zelinka, D. A. Randall, M. J. Webb, and S. A. Klein

   Nature Climate Change, Nov 2017
5. 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

   Y. Tsushima, F. Brient, S. A. Klein, D. Konsta, C. C. Nam, X. Qu, K. D. Williams, S. C. Sherwood, K. Suzuki, and Mark D. Zelinka

   Geoscientific Model Development, Nov 2017

   DOI
6. Clearing clouds of uncertainty

   Mark D. Zelinka, David A. Randall, Mark J. Webb, and Stephen A. Klein

   Nature Climate Change, Oct 2017

   DOI

2016

1. An observational radiative constraint on hydrologic cycle intensification (vol 528, pg 249, 2015)

   A. M. DeAngelis, X. Qu, Mark D. Zelinka, and A. Hall

   Nature, Oct 2016

   DOI
2. Quantifying the Sources of Intermodel Spread in Equilibrium Climate Sensitivity

   P. M. Caldwell, Mark D. Zelinka, K. E. Taylor, and K. Marvel

   Journal of Climate, Oct 2016

   DOI
3. Impact of decadal cloud variations on the Earth’s energy budget

   C. Zhou, Mark D. Zelinka, and S. A. Klein

   Nature Geoscience, Oct 2016

   DOI
4. Insights from a refined decomposition of cloud feedbacks

   Mark D. Zelinka, C. Zhou, and S. A. Klein

   Geophysical Research Letters, Oct 2016

   DOI
5. Positive low cloud and dust feedbacks amplify tropical North Atlantic Multidecadal Oscillation

   T. L. Yuan, L. Oreopoulos, Mark D. Zelinka, H. B. Yu, J. R. Norris, M. Chin, S. Platnick, and K. Meyer

   Geophysical Research Letters, Oct 2016

   DOI
6. Evidence for climate change in the satellite cloud record

   J. R. Norris, R. J. Allen, A. T. Evan, Mark D. Zelinka, C. W. O’Dell, and S. A. Klein

   Nature, Oct 2016

   DOI
7. On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs

   D. T. McCoy, I. Tan, D. L. Hartmann, Mark D. Zelinka, and T. Storelvmo

   Journal of Advances in Modeling Earth Systems, Oct 2016

   DOI
8. Constraining the low-cloud optical depth feedback at middle and high latitudes using satellite observations

   C. R. Terai, S. A. Klein, and Mark D. Zelinka

   Journal of Geophysical Research-Atmospheres, Oct 2016

   DOI
9. Observational constraints on mixed-phase clouds imply higher climate sensitivity

   Ivy Tan, Trude Storelvmo, and Mark D. Zelinka

   Science, Oct 2016

   DOI
10. Volcanic effects on climate

    Benjamin Santer, Susan Solomon, David Ridley, John Fyfe, Francisco Beltran, Céline Bonfils, Jeff Painter, and Mark D. Zelinka

    Nature Climate Change, Jan 2016

    DOI

2015

1. Observed multivariable signals of late 20th and early 21st century volcanic activity

   B. D. Santer, S. Solomon, C. Bonfils, Mark D. Zelinka, J. F. Painter, F. Beltran, J. C. Fyfe, G. Johannesson, C. Mears, D. A. Ridley, and 2 more authors

   Geophysical Research Letters, Jan 2015

   DOI
2. An observational radiative constraint on hydrologic cycle intensification

   A. M. DeAngelis, X. Qu, Mark D. Zelinka, and A. Hall

   Nature, Jan 2015

   DOI
3. The relationship between interannual and long-term cloud feedbacks

   C. Zhou, Mark D. Zelinka, A. E. Dessler, and S. A. Klein

   Geophysical Research Letters, Jan 2015

   DOI
4. Mixed-phase cloud physics and Southern Ocean cloud feedback in climate models

   D. T. McCoy, D. L. Hartmann, Mark D. Zelinka, P. Ceppi, and D. P. Grosvenor

   Journal of Geophysical Research-Atmospheres, Jan 2015

   DOI
5. External Influences on Modeled and Observed Cloud Trends

   K. Marvel, Mark D. Zelinka, S. A. Klein, C. Bonfils, P. Caldwell, C. Doutriaux, B. D. Santer, and K. E. Taylor

   Journal of Climate, Jan 2015

   DOI

2014

1. Volcanic contribution to decadal changes in tropospheric temperature

   Benjamin D. Santer, Celine Bonfils, Jeffrey F. Painter, Mark D. Zelinka, Carl Mears, Susan Solomon, Gavin A. Schmidt, John C. Fyfe, Jason N. S. Cole, Larissa Nazarenko, and 2 more authors

   Nature Geoscience, Jan 2014

   DOI
2. The response of the Southern Hemispheric eddy-driven jet to future changes in shortwave radiation in CMIP5

   Paulo Ceppi, Mark D. Zelinka, and Dennis L. Hartmann

   Geophysical Research Letters, Jan 2014

   DOI
3. Statistical significance of climate sensitivity predictors obtained by data mining

   Peter M. Caldwell, Christopher S. Bretherton, Mark D. Zelinka, Stephen A. Klein, Benjamin D. Santer, and Benjamin M. Sanderson

   Geophysical Research Letters, Jan 2014

   DOI
4. Diagnosing the average spatio-temporal impact of convective systems - Part 2: A model intercomparison using satellite data

   M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Raisanen, and Mark D. Zelinka

   Atmospheric Chemistry and Physics, Jan 2014

   DOI
5. Cirrus feedback on interannual climate fluctuations

   C. Zhou, A. E. Dessler, Mark D. Zelinka, P. Yang, and T. Wang

   Geophysical Research Letters, Jan 2014

   Abs DOI

   Cirrus clouds are not only important in determining the current climate but also play an important role in climate change and variability. Analysis of satellite observations shows that the amount and altitude of cirrus clouds (cloud optical depth \textless 3.6, cloud top pressure \textless 440 hPa) increase in response to interannual surface warming. Using cirrus cloud radiative kernels, the magnitude of the interannual cirrus feedback is estimated to be 0.20 ± 0.21 W/m2/°C, which represents an important component of the cloud feedback. Thus, cirrus clouds are likely to act as a positive feedback on interannual climate fluctuations, by reducing the Earth’s ability to radiate longwave radiation to space in response to planetary surface warming. Most of the cirrus feedback comes from increasing cloud amount in the tropical tropopause layer (TTL) and subtropical upper troposphere.

6. Quantifying components of aerosol-cloud-radiation interactions in climate models

   Mark D. Zelinka, Timothy Andrews, Piers M. Forster, and Karl E. Taylor

   Journal of Geophysical Research: Atmospheres, Jan 2014

   Abs DOI

   AbstractThe interaction of anthropogenic aerosols with radiation and clouds is the largest source of uncertainty in the radiative forcing of the climate during the industrial period. Here we apply novel techniques to diagnose the contributors to the shortwave (SW) effective radiative forcing (ERF) from aerosol-radiation-interaction (ERFari) and from aerosol cloud interaction (ERFaci) in experiments performed in phase 5 of the Coupled Model Intercomparison Project. We find that the ensemble mean SW ERFari+aci of −1.40±0.56 W m−2 comes roughly 25% from ERFari (−0.35±0.20 W m−2) and 75% from ERFaci (−1.04±0.67 W m−2). ERFari is made up of −0.62±0.30 W m−2 due to aerosol scattering opposed by +0.26 ± 0.12 W m−2 due to aerosol absorption and is largest near emission sources. The ERFari from nonsulfate aerosols is +0.13 ± 0.09 W m−2, consisting of −0.15±0.11 W m−2 of scattering and +0.29 ± 0.15 W m−2 of absorption. The change in clear-sky flux is a negatively biased measure of ERFari, as the presence of clouds reduces the magnitude and intermodel spread of ERFari by 40–50%. ERFaci, which is large both near and downwind of emission sources, is composed of −0.99±0.54 W m−2 from enhanced cloud scattering, with much smaller contributions from increased cloud amount and absorption. In models that allow aerosols to affect ice clouds, large increases in the optical depth of high clouds cause substantial longwave and shortwave radiative anomalies. Intermodel spread in ERFaci is dominated by differences in how aerosols increase cloud scattering, but even if all models agreed on this effect, over a fifth of the spread in ERFaci would remain due solely to differences in total cloud amount.

2013

1. The ozone hole indirect effect: Cloud-radiative anomalies accompanying the poleward shift of the eddy-driven jet in the Southern Hemisphere

   Kevin M. Grise, Lorenzo M. Polvani, George Tselioudis, Yutian Wu, and Mark D. Zelinka

   Geophysical Research Letters, Jan 2013

   DOI
2. Evaluating adjusted forcing and model spread for historical and future scenarios in the CMIP5 generation of climate models

   Piers M. Forster, Timothy Andrews, Peter Good, Jonathan M. Gregory, Lawrence S. Jackson, and Mark D. Zelinka

   Journal of Geophysical Research-Atmospheres, Jan 2013

   DOI
3. Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator

   Stephen A. Klein, Yuying Zhang, Mark D. Zelinka, Robert Pincus, James Boyle, and Peter J. Gleckler

   Journal of Geophysical Research-Atmospheres, Jan 2013

   DOI
4. Diagnosing the average spatio-temporal impact of convective systems - Part 1: A methodology for evaluating climate models

   M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, K. Wyser, and Mark D. Zelinka

   Atmospheric Chemistry and Physics, Jan 2013

   DOI
5. An Analysis of the Short-Term Cloud Feedback Using MODIS Data

   Chen Zhou, Mark D. Zelinka, Andrew E. Dessler, and Ping Yang

   Journal of Climate, Jan 2013

   DOI
6. Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5

   Mark D. Zelinka, Stephen A. Klein, Karl E. Taylor, Timothy Andrews, Mark J. Webb, Jonathan M. Gregory, and Piers M. Forster

   Journal of Climate, Jan 2013

   DOI

2012

1. Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part II: Attribution to Changes in Cloud Amount, Altitude, and Optical Depth

   Mark D. Zelinka, Stephen A. Klein, and Dennis L. Hartmann

   Journal of Climate, Jan 2012

   DOI
2. Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels

   Mark D. Zelinka, Stephen A. Klein, and Dennis L. Hartmann

   Journal of Climate, Jan 2012

   DOI
3. Climate Feedbacks and Their Implications for Poleward Energy Flux Changes in a Warming Climate

   Mark D. Zelinka and Dennis L. Hartmann

   Journal of Climate, Jan 2012

   DOI

2011

1. The observed sensitivity of high clouds to mean surface temperature anomalies in the tropics

   Mark D. Zelinka and Dennis L. Hartmann

   Journal of Geophysical Research: Atmospheres, Jan 2011

   Abs DOI

   Cloud feedback represents the source of largest diversity in projections of future warming. Observational constraints on both the sign and magnitude of the feedback are limited, since it is unclear how the natural variability that can be observed is related to secular climate change, and analyses have rarely been focused on testable physical theories for how clouds should respond to climate change. In this study we use observations from a suite of satellite instruments to assess the sensitivity of tropical high clouds to interannual tropical mean surface temperature anomalies. We relate cloud changes to a physical governing mechanism that is sensitive to the vertical structure of warming. Specifically, we demonstrate that the mean and interannual variability in both the altitude and fractional coverage of tropical high clouds as measured by CloudSat, the Moderate Resolution Imaging Spectroradiometer, the Atmospheric Infrared Sounder, and the International Satellite Cloud Climatology Project are well diagnosed by upper tropospheric convergence computed from the mass and energy budget of the clear-sky atmosphere. Observed high clouds rise approximately isothermally in accordance with theory and exhibit an overall reduction in coverage when the tropics warms, similar to their behavior in global warming simulations. Such cloud changes cause absorbed solar radiation to increase more than does outgoing longwave radiation, resulting in a positive but statistically insignificant net high cloud feedback in response to El Niño–Southern Oscillation. The results suggest that the convergence metric based on simple mass and energy budget constraints may be a powerful tool for understanding observed and modeled high cloud behavior and for evaluating the realism of modeled high cloud changes in response to a variety of forcings.

2010

1. Why is longwave cloud feedback positive?

   Mark D. Zelinka and Dennis L. Hartmann

   Journal of Geophysical Research-Atmospheres, Jan 2010

   DOI

2009

1. Response of Humidity and Clouds to Tropical Deep Convection

   Mark D. Zelinka and Dennis L. Hartmann

   Journal of Climate, Jan 2009

   DOI