quantifies how global mean surface temperature responds to changes in radiative forcing. Uncertainty
in climate sensitivity arises primarily due to uncertainty in radiative feedbacks, which can be influenced
by a large range of processes including cloud microphysics, large-scale circulation of the atmosphere and
ocean, or the pattern of surface temperature changes. This session solicits work on theory, modeling,
and observations related to Earth’s climate sensitivity, with a particular focus on recent advances in
understanding the causes and impacts of the surface temperature pattern effect. The pattern effect
describes how surface temperature changes with identical global mean values can have hugely different
effects on the radiation budget depending on their spatial distribution, having significant implications
for interpreting temperature changes from observations, paleo-climate proxies, and climate-change
projections.
We welcome contributions related, but not limited, to:
• Radiative feedbacks and their modulation by surface warming patterns
• Air-sea interactions and ocean dynamics relevant to surface temperature patterns
• Process studies of feedbacks from clouds and moist processes
• Ocean heat uptake and transient climate sensitivity
• Theoretical models of climate sensitivity
• Interbasin interactions and teleconnections spanning scales from sub-basin to global
This session serves as an exchange platform for the often more separated ocean and atmosphere communities, and we especially encourage contributions from the ocean community.
Determining the modern climate’s sensitivity to greenhouse-gas forcing has been a central challenge for over 40 years. To constrain the notoriously uncertain upper bound of climate sensitivity, we must look to the natural experiments in Earth’s past. Recent advances in climate reconstruction now provide new constraints on the spatial patterns of paleoclimate and historical temperature change. These temperature patterns play a leading role in climate sensitivity due to pattern effects.
We first investigate the cold Last Glacial Maximum and the warm Pliocene. By combining recent reconstructions with atmospheric general circulation models, we show why cloud feedbacks strongly amplify temperature changes in past climates and how this finding helps constrain the upper bound of modern climate sensitivity.
We then turn to the recent past (1850–2023) to examine the outstanding uncertainty in radiative feedbacks over the historical record. We introduce a new coupled reconstruction, which uses data assimilation to combine observational and dynamical constraints across the atmosphere and ocean. Using the reconstruction’s ensemble members in several atmospheric general circulation models, we quantify how uncertainty in SST, sea ice, and model physics leads to time-evolving uncertainty in feedbacks over the historical record. Finally, we combine results from the paleoclimate and historical records to show that accounting for pattern effects leads to stronger constraints on modern climate sensitivity and projections of 21st-century warming.
How to cite: Cooper, V.: Constraining Modern Climate Sensitivity and Pattern Effects with New Paleoclimate and Historical Reconstructions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13274, https://doi.org/10.5194/egusphere-egu26-13274, 2026.
The land–ocean warming contrast—where global land mean warms more than the global ocean mean —is one of the most prominent features of global warming. In idealized CO₂-increase experiments, although there is inter-model spread, it is known that land warming is typically about 1.6 times larger than ocean warming. However, it remains unclear what determines the magnitude of this land–ocean warming contrast. For the 1980–2014 trend, observed land warming exceeds ocean warming by more than a factor of 2.3, and such a large observed land–ocean warming contrast cannot be reproduced by CMIP6 historical simulations. It is also well known that during this period there is a mismatch in the SST trend pattern between observations and historical simulations. In this study, we investigated how differences in sea surface temperature (SST) patterns affect the magnitude of land–ocean warming contrast. Using the climate model MPI-ESM, we conducted AGCM experiments forced by (i) a globally uniform SST warming (+2 K, +4 K, and +6 K), (ii) the same global-mean SST warming superimposed with the observed 1980–2014 SST trend pattern, and (iii) the same global-mean SST warming with the sign of the 1980–2014 SST trend pattern reversed. The results show that, despite having the same global-mean SST warming, land warming differs significantly among the SST patterns, and that the observed SST trend pattern tends to enhance the global-mean land warming. Under the observed SST pattern experiments, warming tends to be amplified across the entire Eurasian continent, which is a major contributor to the enhanced global-mean land warming. The strong warming over the mid-to-high-latitude Eurasian continent is explained primarily by pronounced Atlantic warming and warming in the northwestern Pacific, whereas the cooling tendency in the eastern equatorial Pacific affects the land-warming pattern over the North America through teleconnections. This study demonstrates that SST patterns exert a substantial influence on the factors controlling the magnitude of the land–ocean warming contrast, and suggests that the coupling between ocean and land temperature changes varies markedly depending on the future SST pattern change.
How to cite: Toda, M. and Günther, M.: The magnitude of land–ocean warming contrast depends on the pattern of SST warming, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13300, https://doi.org/10.5194/egusphere-egu26-13300, 2026.
The pattern effect describes how the spatial structure of surface warming modulates Earth’s top-of-atmosphere (TOA) radiative imbalance, such that identical increases in global-mean surface temperature can produce distinct global radiative responses and distinct effective climate sensitivities. GCM studies consistently point to the tropical Pacific through changes in deep convection and low-cloud feedbacks as a dominant contributor to this sensitivity. Yet isolating the causal chain from regional SST perturbations to the global radiative response remains challenging in comprehensive GCMs.
To address this, we develop a minimal two-box model of the tropical Pacific atmosphere, partitioning it into a warm, convective box and a cooler, inversion-capped subsident box, representative of an idealized Hadley–Walker circulation. The framework retains a strict Weak Temperature Gradient (WTG) constraint in the free troposphere, quasi-equilibrium structure functions for temperature and humidity, and low-cloud radiative effects in the subsident region scale with lower-tropospheric stability (EIS), on top of a clear-sky radiative code. For a given SST and greenhouse-gas forcing, the model state is described by only six scalar variables and closed by six coupled sensible-heat and moisture conservation equations, with fixed convective/subsident fractional areas and no explicit dynamical closure.
This formulation which is purely thermodynamic (no representation of the dynamics beyond the WTG) aims to include only the processes thought to be essential for the tropical pattern effect.
This minimal set of processes is sufficient to reproduce the sign asymmetry of the pattern effect, via WTG-mediated tropospheric temperature adjustment and low-cloud sensitivity to EIS in subsident regions, but it underestimates the amplitude of local radiative sensitivities, suggesting a missing mechanism linked to the fixed-area, no-dynamics assumption.
We therefore introduce a dynamical formulation based on a linear, stationary 2D momentum balance without Coriolis and with Rayleigh damping, yielding a momentum-budget closure that links the overturning circulation strength to the boundary-layer temperature contrast. This additional constraint allows us to relax the fixed fractional-area assumption and introduces a fractional area feedback: surface warming in convective regions tends to expand the subsident fraction, whereas subsident warming contracts it weaklier. Because subsident regions radiate more effectively to space due to their dryness and high low-cloud cover, these area shifts amplify radiative sensitivities and move the model closer to GCM-inferred sensitivities.
We confirm the relevance of this mechanism in idealized atmospheric GCM experiments forced by SST fields with identical tropical-mean SST but different spatial patterns. We show that changes in convective/subsident fractional areas, account for a surprising substantial share (order 20–40%) of the resulting TOA radiative imbalance in these configurations and this contribution is asymmetric with the SST pattern. These results show that changes in the dynamics should be accounted for to explain the pattern effect.
How to cite: Lecuyer, J., Meyssignac, B., and Bellon, G.: Unravelling the mechanism of the Pattern Effect with a Two-box Model of the Tropical Atmospheric Circulation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9983, https://doi.org/10.5194/egusphere-egu26-9983, 2026.
Understanding Earth’s equilibrium sensitivity remains one of the key challenges of climate science, with cloud feedbacks representing a major source of uncertainty. High clouds associated with deep convective systems in the tropics have been shown to make a large contribution to this uncertainty. With a goal of improving our understanding of radiative properties of tropical high clouds, we investigate cloud radiative effects (CREs) of high clouds within mesoscale convective systems (MCSs) in the tropical western Pacific. The study uses a novel high-resolution (3-km), hourly dataset derived from the advanced Himawari imager onboard the Himawari-8 satellite. Cloud properties are retrieved with Optimal Retrieval of Aerosol and Cloud (ORAC) and the top-of-the-atmosphere CREs are calculated using the Broadband and Narrowband Radiative Transfer Model (BUGSrad). We identify and track MCSs during 2018–2022 using 11.2 μm brightness‑temperature data with a 233 K threshold and a minimum cloud‑top area of 1000 km², employing the ‘simple-track’ cloud-tracking algorithm. The analysis shows that, on an average, larger storms have more negative net CRE than smaller storms. Moreover, shorter-lived storms have a net CRE close to zero. Results based on all tracked MCSs across the 3-year period indicate that MCSs have a net CRE of -12.80 W m-2, though there exists a negative bias in Himawari-derived net CRE (that stems from bias in shortwave CRE) when compared to CERES-EBAF dataset. Further analysis separates clouds into low-brightness-temperature and high-brightness-temperature regimes, and show how these two cloud regimes evolve throughout the 3-year period.
How to cite: Gopalakrishnan, D., Holloway, C., Muetzelfeldt, M., Hill, P., Carboni, E., and Thomas, G.: Cloud radiative effects due to deep convective clouds in the tropics: Insights from Himawari-8 observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12772, https://doi.org/10.5194/egusphere-egu26-12772, 2026.
The vertical distribution of cloud condensates helps set precipitation efficiency, cloud fraction and cloud optical depth. Here, we examine profiles of liquid condensate in shallow convection and ice condensate in deep convection collected from in-situ and satellite observations. These observed profiles exhibit a striking similarity, which suggests they might be controlled by the same basic physical processes. We develop a simple analytical theory for these profiles based on condensation, entrainment, and conversion to precipitation. When given a few input parameters, the theory is able to quantitatively reproduce observed and simulated profiles of liquid and ice condensate. We outline how the theory could be used to interpret the anvil cloud optical depth feedback, as well as the intermodel spread in condensate seen in cloud-resolving simulations.
How to cite: McKim, B., Bony, S., Williams, A., Sokol, A., Janssens, M., and Baley, C.: Universality in Cloud Condensate Vertical Profiles and Implications for Cloud Feedbacks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1468, https://doi.org/10.5194/egusphere-egu26-1468, 2026.
Optically-thick clouds largely emit thermal radiation at their cloud top temperature across the longwave spectrum. However, the degree to which cloud top temperature dominates outgoing longwave radiation depends on how the clouds share spectral space with Earth's major greenhouse gases. In this work we leverage analytical models of spectral emission by CO2 and H2O to understand how spectral overlap between gases and clouds impacts the longwave cloud radiative effect (CRE) and all-sky feedbacks. We demonstrate that CRE is linear in the difference between surface and cloud top temperature because of water vapor's greenhouse effect and that low clouds exert a small CRE not exclusively because their temperature is close to surface temperature but primarily because they are masked by H2O and CO2. Spectral decomposition of feedbacks reveals that the changing emission temperature of greenhouse gases stabilizes the climate even in fully cloudy columns, and clouds that warm with the surface provide additional stabilization in the water vapor window. We find good agreement between our analytical expressions and both full-physics line-by-line calculations as well as output from a global storm resolving model. By understanding spectral overlap of greenhouse gases and clouds, we disentangle the effects of surface temperature, cloud top temperature, and relative humidity on Earth's longwave energy balance in cloudy columns.
How to cite: Pincus, R. and Czarnecki, P.: How Clear-Sky Spectral Overlap Shapes Radiation in Cloudy Atmospheres, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21810, https://doi.org/10.5194/egusphere-egu26-21810, 2026.
The Sherwood et al. assessment [1] of Earth's climate sensitivity to a doubling of atmospheric carbon dioxide concentration broke new ground in providing estimates of radiative feedback and its components through the use of multiple lines of evidence. The assessment combined evidence from Global Climate Models (GCMs) with evidence from observations and process models that are able to produce more defensible estimates of small-scale and poorly-understood processes. However, by treating estimates of the different components of feedbacks as independent of one another, Sherwood ignored correlations between different feedbacks, which could impact the uncertainty affecting the estimate of overall feedback. The exception to this was the well-known water vapour-lapse rate anti-correlation, which they did consider.
In this study, we first undertake a perfect model experiment with the CMIP5 and CMIP6 ensembles that demonstrates the effects of considering correlations between components of feedbacks on estimates of net radiative feedback in a Sherwood-type analysis. Second, we explore correlations between contemporary estimates of feedback components from observed climate variability and cloud controlling factor analysis. Correlations between components have a similar structure for both perfect model and contemporary estimates. It is found that introducing feedback correlations into the Sherwood framework increases the standard deviation of the net feedback uncertainty by about 30 %. Impacts on estimates of climate sensitivity are smaller, because the process-based estimate of radiative feedback is only one part of the sensitivity estimate.
Prospects for future feedback and sensitivity estimates are discussed. The caveat to our results is that Sherwood's estimates of feedback components come from different sources. Although our results suggest that at least some of these show similar correlation structures, there is a need for future work that aims to understand the physical and statistical relationships between estimates of different components of feedback.
Reference
[1] Sherwood et al., 2020, Rev. Geophys., https://doi.org/10.1029/2019RG000678.
How to cite: Lambert, H., Ceppi, P., Chao, L.-W., Ferrett, S., Webb, M., and Zelinka, M.: Relationships between feedback components alter estimates of total radiative feedback and climate sensitivity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13799, https://doi.org/10.5194/egusphere-egu26-13799, 2026.
In climate sensitivity literature, simple energy balance models provide insight into how energy moves throughout the climate system. The first-order approximation of these models assumes a linear relationship between the forcing, ocean heat uptake, and radiative response, including a constant feedback parameter. However, these linear assumptions have been shown to inaccurately estimate the effective (or equilibrium) global mean temperature response across consecutive CO2 doubling experiments, with second-order approximations required to capture climate system non-linearities such as CO2-temperature (state) dependence or the pattern effect. It is common to express these non-linearities in an energy balance model using an inconstant feedback, ocean heat uptake efficacy, or forcing efficacy factor. While these climate system non-linearities are well studied, no research has systematically assessed whether individual parameterisations differ in their ability to capture the temperature response across multiple CO2-doubling experiments – that is, whether non-linearities acting on specific components of the climate system are more effective at reproducing responses across successive forcing scenarios. Using 12 CMIP6 models for which abrupt CO2 doubling and quadrupling experiments are available (nine of which also include abrupt halving), we calibrate a two-layer energy balance model simultaneously to the surface air temperature time series from each experiment for each model. We perform multiple calibrations under both linear and non-linear assumptions. Preliminary results indicate that, for most models, a first-order approximation with a constant feedback parameter is sufficient to capture the surface air temperature response across multiple CO2 doublings. Where a constant feedback parameter is not sufficient, initial findings suggest that a state-dependent forcing is the most effective correction. Future work will consider how this work can be reconciled with the temporal evolution of the feedback parameter seen in many observation-based historical CMIP6 simulations and the implications of our findings for projections of future climate.
How to cite: Zehrung, A., Meinshausen, M., King, A., and Nicholls, Z.: Linear and non-linear energy balance model calibration across consecutive abrupt CO2 doubling experiments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4585, https://doi.org/10.5194/egusphere-egu26-4585, 2026.
Over the past decade, it has become well-established that the spatial pattern of sea surface temperature (SST) warming exerts a strong control on Earth’s radiative feedbacks at the top of atmosphere (TOA). However, the role of the spatial pattern on other parts of the climate system are less well studied. We aim to understand the role that the SST pattern, and in particular preferential warming of deep convective regions, has on the surface energy budget, noting that the surface energy budget affects the future evolution of the warming pattern.
Our primary method of investigation is through a CMIP6 multi-model analysis of the amip-piForcing experiment. Preliminary analysis with a subset of models shows large differences between the TOA and surface perspectives. e.g., in the TOA, warm pool warming drives negative TOA anomalies due to increased low cloud cover, but has positive surface anomalies from the latent heat flux.
How to cite: Kawaguchi, K. and Ceppi, P.: A surface energy balance perspective on the pattern effect, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1534, https://doi.org/10.5194/egusphere-egu26-1534, 2026.
High cloud feedbacks are a large contributor to uncertainty in estimates of equilibrium climate sensitivity. Across the CMIP6 ensemble, estimates in global longwave cloud radiative effect (LWcre) feedback (a feedback strongly tied to changes in high cloud) range from approximately -0.45 to +0.5 W m-2 K-1. HadGEM3-GC31-LL sits close to the bottom of this range and therefore we explore mechanisms for high cloud reduction with warming in HadGEM3-GC31-LL. We find that high cloud reduction in HadGEM3-GC31-LL is closely tied to the parameterized convection scheme as well as a contribution linked to a response consistent with the stability iris mechanism. To estimate the relative importance of the parameterized convection and other processes, conv-off experiments are used to capture the high cloud response in the absence of convection parameterization. In these conv-off experiments a much reduced cloud reduction is seen.
How to cite: Mutton, H., Webb, M., Andrews, T., and Ringer, M.: Mechanisms for high cloud reductions with climate warming in HadGEM3-GC3.1-LL, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4063, https://doi.org/10.5194/egusphere-egu26-4063, 2026.
Cloud feedback remains the largest source of uncertainty in projections of Earth’s climate sensitivity and future warming. Recent generations of Earth System Models (ESMs) show a trend toward more positive cloud feedback, contributing to higher estimates of effective climate sensitivity (ECS). This raises an important question: can observational constraints help rule out or support these higher values? Our work focuses on the hydrological processes that drive cloud feedback, particularly the role of large-scale moisture transport and precipitation efficiency. Both observations and models show a consistent global moisture flux pattern: moisture convergence in the tropics and extratropics, and divergence in the subtropics, maintaining a near-zero global moisture balance. As the climate warms, this pattern strengthens due to the Clausius-Clapeyron relationship, enhancing the moisture flux and driving cloud responses. These cloud responses are further shaped by how efficiently atmospheric moisture is converted into precipitation, linking hydrological and radiative processes in a warming world. Using a framework that relates cloud feedback to features of the hydrological cycle, precipitation efficiency and radiative efficiency, we constrain cloud feedback globally using satellite observations. Observations of precipitation efficiency and radiative efficiency narrow the spread of cloud feedback across the Community Atmosphere Model version 6 (CAM6) perturbed parameter.
How to cite: Werapitiya, G., Aerenson, T., McCoy, D., Brient, F., Elsaesser, G., Song, C., and Zelinka, M.: How the hydrological cycle affects the global cloud feedback, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6680, https://doi.org/10.5194/egusphere-egu26-6680, 2026.
Recent work has established how the sensitivity of tropical low clouds to patterns of SST warming influences radiative feedbacks and estimates of equilibrium climate sensitivity. This is known as the pattern effect. Central to the pattern effect is the response of low clouds in subsidence regions, which has been linked to the efficiency through which surface warming influences free-tropospheric temperature and thus changes in lower-tropospheric inversion strength.
Mechanistic understanding of this effect is underpinned by two conceptual models of the tropical atmosphere: (i) convective quasi-equilibrium (CQE) and (ii) weak free-tropospheric temperature gradients (WTG). Together, CQE and WTG imply that a quasi-uniform change in free-tropospheric temperature is set by warming in regions which are convectively coupled. The extent to which these convectively coupled regions can influence the free troposphere is partially controlled by the rate at which dry air is entrained into convective plumes, a process which is parameterized in global climate models and highly uncertain.
Here, we explore how dry-air entrainment impacts the pattern effect through idealised simulations with CESM2. Using a control entrainment parameter, we perturb an atmosphere-only model with prescribed warming and cooling SST patches at 4 locations between 100E and 220E along the equator. The simulations are then repeated for a range of entrainment parameter rates. We observe a nonlinear sensitivity of pattern effect to entrainment rate. Specifically, we find evidence that modifying the entrainment parameter influences which regions are most influential in setting free-tropospheric temperatures and affects the sensitivity of top-of-atmosphere fluxes to SST perturbations. Finally, we note contrasting responses over land and ocean when modifying the entrainment parameter, for which we describe a hypothesised mechanism.
How to cite: Dani, K., Mackie, A., and Byrne, M.: Role of entrainment in shaping the pattern effect, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14533, https://doi.org/10.5194/egusphere-egu26-14533, 2026.
Understanding the physical mechanisms governing the El Niño decay phase is fundamental for simulating accurately the duration of El Niño events. This study investigates the role of negative high cloud feedback in modulating El Niño’s decay during boreal winter and spring. Utilizing ERA5 reanalysis data from 1950 to 2024, we find that peak El Niño SST anomalies in the central-eastern Pacific during boreal winter trigger a simultaneous local increase in high cloud. These high cloud anomalies exert a cooling effect on the ocean surface by reflecting incoming shortwave radiation. There is a significant correlation between wintertime surface net cloud radiative effect (CRE) and the SST tendency from winter to the subsequent spring. Heat budget diagnostics further confirm that this intense shortwave cooling effect of high cloud accounts for a substantial proportion of the net surface heat flux anomalies, acting as a critical thermodynamic factor for the decay phase. Most Coupled Model Intercomparison Project Phase 6 (CMIP6) models capture this relationship between wintertime CRE and SST tendency, validating this mechanism. However, there is a systematic bias between simulated and observed feedback sensitivity. This discrepancy likely hinders the models' ability to accurately represent the rapid decay and realistic duration of El Niño events. Our findings suggest that improving cloud-radiation parameterizations is essential for improving the simulation and prediction of ENSO lifecycles in climate models.
How to cite: Wang, Y., Zhai, C., and Su, H.: Modulation of El Niño Decay by Negative High Cloud Feedback, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21179, https://doi.org/10.5194/egusphere-egu26-21179, 2026.
The planetary energy imbalance depends on the amount of solar energy entering and leaving the system, as well as changes in greenhouse gas concentrations. Since the start of the 21st century, the Earth’s energy imbalance (EEI) is assumed to have doubled, linked to the reduction of solar radiation reflected back to space, due to atmospheric dimming. Rapid and responsive feedback mechanisms have contributed to the accumulation of excess heat within the global oceans. The ocean warming drives the positive change in EEI and impacts the hydrological cycle, becoming more intense. Such linkage disturbs well-established weather patterns and cause their alternation. To understand these phenomena, traditionally complex state-of-the-art coupled climate models would be used. However, the strength of simpler, energy balance climate models capturing large-scale features has shown to be an alternative approach in understanding the general state of climate.
In this study, we utilise the ocean component of the newly developed novel energy balance climate model (nEBM) to examine the relationship between EEI and ocean warming. Our approach perturbs key hydrological cycle elements (e.g., precipitation, runoff, evaporation, etc) in addition to other forcing components (e.g., CO2) to show the resulting ocean response and the subsequent impacts on EEI. These results are compared to observational datasets to demonstrate the performance of the nEBM ocean model. The obtained results are compared to CMIP6, observations, and relevant literature. Finally, we discuss the ability of simpler climate models (e.g., nEBM) to quantify sensitivity in climate studies.
How to cite: Sladić, N., Trent, T., Povey, A., P. Allan, R., and Willett, K.: Energy balance climate models as a tool for investigating the linkage between the energy imbalance and the hydrological cycle , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5029, https://doi.org/10.5194/egusphere-egu26-5029, 2026.
Internal variability, particularly ENSO, plays a critical role in modulating global warming on interannual to decadal timescales. Its canonical surface temperature signature is well characterized, but the complex and non-linear relation between surface temperature and top-of-atmosphere (TOA) radiative response requires attention. Here, we use coupled atmosphere-ocean simulations to diagnose the energy redistribution and radiative feedbacks across ENSO phases. During the growth phase of El Niño, boundary-layer destabilization enhances ocean-atmosphere heat exchange in the tropical Pacific, while a positive net TOA flux anomaly amplifies surface warming, contrary to the canonical feedback perspective. This excess energy is transported poleward and zonally, with remote ocean basins exhibiting shallow heat uptake. At the El Niño peak, rapid atmospheric stabilization increases low-level cloudiness and shortwave reflection, while the subsequent decay phase is marked by net radiative cooling to space. In parallel, we find that high cloud fraction and upper-tropospheric humidity evolve in an anticorrelated manner across the tropics and extratropics. These changes are not directly tied to boundary-layer stability, and their opposing regional signatures largely cancel in the global mean. Notably, tropical drying and cloud loss co-occur with increased precipitation. Our findings clarify the role of ENSO in Earth's radiative variability and highlight key differences from CO2-forced warming.
How to cite: Yang, Q. and Fueglistaler, S.: Surface Warming Patterns, Cloud Feedbacks, and Inter-basin Energy Redistribution During ENSO, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8388, https://doi.org/10.5194/egusphere-egu26-8388, 2026.
Hydrological sensitivity, defined as the change in latent heat release per degree of global mean surface temperature increase, is a key metric for understanding future precipitation changes and the global hydrological cycle. Based on the global energy budget, hydrological sensitivity can be decomposed into three components: longwave cooling, shortwave absorption, and sensible heat flux. In this study, we analyzed hydrological sensitivity from 1980 to 2025 using ERA5 reanalysis data. A decomposition of hydrological sensitivity into three energy budget terms reveals a non-negligible residual that cannot be explained by these conventional components alone. Diagnostics of the spatiotemporal characteristics of this residual and its relationship with internal variability show a significant correlation with the Pacific Decadal Oscillation(PDO)/Interdecadal Pacific Oscillation(IPO). At the global scale, variations in precipitation dominate the hydrological sensitivity residual. These findings suggest that hydrological sensitivity is modulated by atmosphere–ocean interactions in the Pacific represented by PDO/IPO. We further examine the physical mechanisms linking internal variability to these residuals.
How to cite: Han, Y.-R. and Yeh, S.-W.: Interdecadal Pacific Oscillation Modulates Hydrological Sensitivity Residuals Derived from Energy Budget Decomposition, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9233, https://doi.org/10.5194/egusphere-egu26-9233, 2026.
Climate sensitivity and aerosol forcing are two of the most central, but uncertain, quantities in climate science - crucial for understanding past climate changes and future projections. In addition, both historical and future climate evolution has been and will be influenced by natural variability. In this study, we estimate inferred climate sensitivity (ECSinf) and aerosol forcing using observations of surface temperature and ocean heat content (OHC) combined with prior knowledge of effective radiative forcing over the industrial period, within a Bayesian framework. The global mean surface temperature set new records in 2023 and 2024. Including these years had little influence on the estimated ECSinf - due to the steadily increasing OHC - compared to previous estimates using shorter observational records. In earlier studies, where observations up to the year 2010, 2014, 2019 and 2022 were included, the ECSinf remained stable with best estimates from 1.9 to 2.2 K and the transient climate response best estimates from 1.4 to 1.6 K. A limitation in observational based estimates of climate sensitivity is the large uncertainty in the forcing of the Earth system, primarily due to the uncertain cooling effect from aerosols. The aerosol precursor emissions have declined over the past decade, but the evolution of aerosol forcing throughout the industrial period remains poorly constrained. Allowing aerosol forcing to vary more freely tends to stretch the upper tail of the ECSinf distribution toward larger values. Another limitation of observational-based estimates of climate sensitivity is that it only captures the feedbacks that have occurred over the historical period - and the historical climate is only a single realization of the Earth’s climate. To assess this limitation, the method is tested using climate model results. We use the transient ocean heat content and temperature response from fully coupled historical simulations of four CMIP6 models – with substantial differences among ensemble members – and ERF time series calculated from the individual models to estimate ECSinf. As expected, most ensemble members give posterior mean ECSinf lower than the models ECS as only feedbacks over the historical period are captured. For the individual climate models, the posterior mean ECSinf varies by 0.6 K, 1.2 K, 2.1 K and as much as 4.1 K across ensemble members. Although there are limitations within Earth System models, particularly in reproducing observed temperature patterns, this highlights the importance of natural variability in observational-based estimates of climate sensitivity.
How to cite: Skeie, R. B.: Observational-based estimates of climate sensitivity: impacts of aerosol evolution, natural variability and the recent temperature records, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10347, https://doi.org/10.5194/egusphere-egu26-10347, 2026.
Recent studies have highlighted that state-of-the-art climate models are not able to simulate the large observed trend in Earth’s energy imbalance. Here we evaluate climate models’ ability to represent both the trend and the magnitude of the imbalance, while accounting for model energy leakage and remnant drift. As reference we use satellite observations and we find that every observed annual mean energy imbalance is within the range simulated by models, including the record year 2023, and when averaged over the 2001-2024 period, 15 out of 30 models simulate magnitudes of the imbalance that are statistically consistent with the observations. Models, however, generally underestimate the positive trend in the energy imbalance, albeit barely within the range of uncertainty. We suspected that a discontinuity in volcanic forcing between the historical and future scenario in 2014-2015 could have caused the underestimated trend, but only found evidence of such artifacts for a few models. Finally, we find a weak correlation between short-term decadal warming and energy imbalance, but a surprisingly close relationship between energy imbalance and equilibrium climate sensitivity. Based on observational constraints, the relationship suggests that models with moderate climate sensitivity are most realistic.
How to cite: Bimpiri, K., Hocking, T., and Mauritsen, T.: Climate models with moderate climate sensitivity best simulate the magnitude of Earth’s energy imbalance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10667, https://doi.org/10.5194/egusphere-egu26-10667, 2026.
In this study, we revisit the widely accepted interpretation of predominantly negative lapse-rate feedback, particularly in the tropics, by applying a physics-based climate feedback framework. We perform a side-by-side comparison of TOA-based PRP (partial radiative perturbation) and EGK-centered (energy gain kernel) climate feedback analysis frameworks. The only difference between them lies in their approach to accounting for temperature feedback. Under the EGK framework, all input energy perturbations are intimately related to temperature feedback through energy amplification following a multiplication role. The vertically integrated amplified input energy perturbation by temperature feedback is always substantially greater than the vertically integrated input energy itself. Such great amplification arises from the continuous back-and-forth relay of warming-induced thermal emissions from individual layers to absorption by other layers throughout the atmosphere-surface column until the system reaches a new equilibrium state. This is the positive aspect of temperature feedback. Temperature changes predicted from EGK automatically ensures energy is balance at all layers, including the TOA, through their thermal emissions. Thermal emissions reflect the negative aspect of temperature feedback.
The perturbation energy balance equation at the TOA only involves a simple addition of vertically integrated (partial) energy perturbations associated with external forcing and non-temperature feedbacks, plus OLR perturbations due to temperature feedback. The lapse-rate feedback mainly reflects the level where input energy is placed, rather than the physical nature of air temperature feedback. Its sign changes from positive for input energy at lower levels to negative for input energy at upper levels. Because energy perturbations due to radiative processes tend to have vertically decreasing profiles, their lapse-rate feedback tends to be predominantly positive. When also considering non-radiative feedbacks, such as enhanced vertical convection, the net effect of non-temperature feedbacks tends to be weak or even negative at the surface but strongly positive in the upper atmosphere in the tropics. This explains why the lapse-rate feedback is predominantly negative in the tropics.
How to cite: Sun, J. and Cai, M.: Revisiting the Apparent Negativity of Lapse-Rate Feedback Through a Physics-Based Climate Feedback Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11982, https://doi.org/10.5194/egusphere-egu26-11982, 2026.
Understanding CO₂-induced surface warming patterns is essential for regional climate projections. Abrupt 4×CO2 experiments reveal well-documented warming holes in the subpolar North Atlantic (NA) and Southern Ocean (SO), yet a similarly robust but less recognized warming hole emerges in the Southeast Pacific (SEP). Unlike the warming holes over NA and SO, which disappear in slab ocean models without active ocean circulation, the SEP warming hole persists and intensifies, indicating the dominant role of air–sea interactions. Latitudinally constrained CO₂ forcing experiments demonstrate that off-equatorial Northern Hemisphere (NH) forcing drives the SEP warming hole by inducing an interhemispheric energy imbalance, shifting the Hadley circulation (HC) northward, and strengthening the Southern Hemisphere subtropical descent. This enhances the South Pacific Subtropical High and the associated southeasterly trade winds. Combined with a stronger cross-equatorial flow associated with the northward-shifted HC, the enhanced winds contribute to the SEP warming hole through increased latent heat flux. Inter-model spread of SEP warming hole across CMIP6 models is well explained by variations in wind-driven latent heat flux, primarily controlled by cloud-mediated interhemispheric energy asymmetry. These results identify atmospheric teleconnections as the key driver of the SEP warming hole, distinguishing it from the ocean-driven mechanisms in the NA and SO.
How to cite: Pan, X. and Kang, S.: Robust Warming Hole in the Southeast Pacific, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17261, https://doi.org/10.5194/egusphere-egu26-17261, 2026.
Global storm-resolving models (GSRMs) represent a frontier in climate change research, but their application remains limited due to high computational cost, and inter-GSRM comparisons are almost nonexistent. Moreover, a potential sensitivity of climate feedback in GSRMs of the Earth’s atmosphere to model resolution hasn’t been studied, yet.
In this study, we conducted AMIP and AMIP+4K experiments using the GSRM ICON, where the AMIP+4K experiment imposes a globally uniform sea surface temperature increase of 4 K. Each experiment was performed at three different horizontal resolutions: 20 km, 10 km, and 5 km.
Results show that for the AMIP+4K experiment, the net climate feedback parameter as well as its shortwave and longwave components all become more positive with increasing resolution. The difference in net climate feedback parameter between 20 km and 5 km resolution is comparable in magnitude to the model spread of climate feedback parameter in CMIP6 AMIP+4K experiments. The resolution dependence of the shortwave feedback in AMIP+4K experiment originates in the extratropics while the dependence of the longwave feedback is a result of tropical processes.
Regarding comparison with conventional models, the climate feedback parameter of ICON at 10km and 5km resolution falls within the model spread of CMIP6 AMIP+4K. However, over the extratropical oceans, ICON at all resolutions exhibits clearly stronger negative feedback than any of the CMIP6 models. Furthermore, the climate feedback from ICON at 5 km resolution is very close to that of another GSRM, X-SHiELD, at 3.4 km resolution. Nevertheless, the shortwave and longwave components differ significantly between the two models, indicating that even without convection parameterization—a key source of uncertainty—there is still notable inter-model variability in the representation of climate feedbacks.
How to cite: Schmidt, H., Toda, M., Peinado, A., Kang, S. M., and Stevens, B.: More positive climate feedback with higher resolution: A multi-resolution GSRM study with ICON in comparison to conventional models and other GSRMs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13152, https://doi.org/10.5194/egusphere-egu26-13152, 2026.
