Reducing uncertainties in future climate projections requires improved understanding of both the effective radiative forcing (ERF) and the climate response. The Radiative Forcing Model Intercomparison Project (RFMIP) for CMIP7 proposes a set of diagnostic experiments in global climate models to evaluate ERF in these models.
Experiments in RFMIP are run with a pre-industrial climatology of sea surface temperatures (labelled piClim) to minimize the influence of surface temperature change on the top-of-atmosphere energy budget. With an atmosphere-only configuration, as there is no slow ocean response, models equilibrate quickly to a change in forcing and do not require long run times. We use 30-year “time slice” experiments to diagnose ERF to steady-state changes to different combinations of forcing agents. We also propose a set of 251-year (1850-2100) “transient” experiments where forcings are prescribed following historical and future trajectories.
Diagnosing radiative forcing is a core model property, and therefore three previous RFMIP experiments have been selected to be included in the CMIP7 DECK:
- piClim-control (timeslice; baseline comparison for other experiments)
- piClim-4xCO2 (timeslice; quadrupling of pre-industrial CO2 concentrations)
- piClim-anthro (timeslice; present-day anthropogenic forcers)
Furthermore a set of RFMIP experiments are identified as highly societally relevant and have been included in the CMIP7 Assessment Fast Track (AFT):
- piClim-aer (timeslice; present-day aerosols)
- piClim-histaer (transient; historical and future aerosols)
- piClim-histall (transient; historical and future all forcings)
Outside of DECK and AFT, we organise RFMIP experiments into three tiers by priority and the likelihood of modelling centers’ ability to run them. All CMIP6 RFMIP experiments are present in Tiers 1 and 2. We propose novel extensions in Tier 3, including fixing land as well as sea surface temperatures (piClim-FixedTL) in order to more accurately estimate the ERF; evaluating CO2 ERF at different concentrations other than a quadrupling to assess deviation from logarithmic behaviour; changing the climatic baseline to investigate surface temperature effects; and including biogeochemically and radiatively decoupled analogues of piClim-4xCO2.
How to cite: Smith, C., Kramer, R., and Andrews, T.: The Radiative Forcing Model Intercomparison Project for CMIP7, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8007, https://doi.org/10.5194/egusphere-egu26-8007, 2026.
Previous studies showed that historical forcing changes can partly explain differences between climate model simulations of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP). With the new CMIP7 historical forcings now delivered, we investigate how forcings have changed from the CMIP5 to CMIP7 generations, and use the FaIR reduced-complexity climate model to quantify the impacts for simulated 1850-2100 global mean surface temperature.
First, we perform historical simulations using CMIP5, AR5, CMIP6, AR6, and CMIP7 forcing datasets using FaIR’s IPCC 6th Assessment Report (AR6) calibration. To quantify the impact of individual forcing change on the simulated temperatures, we run simulation ensembles changing individual forcings (CO2, CH4, N2O, other greenhouse gases, aerosol-radiation interactions, aerosol-cloud interactions, solar, volcanic, ozone, and land use forcings) for each CMIP and AR era. In particular, we show three major changes in CMIP7 relative to CMIP6: i) 1850-1900 is 0.1 K colder, largely driven by changes in stratospheric aerosol forcing; ii) 1960-1980 is 0.07 K warmer, largely driven by changes in stratospheric aerosol forcing; iii) over the 20th century, the smaller aerosol-cloud interaction forcing translates into a temperature increase of 0.04 K, whereas the solar forcing change drives colder temperatures by 0.02 K.
Second, to qualitatively assess potential impact of forcing changes on climate model tuning, we recalibrate FaIR using the different CMIP era forcings. In particular, we quantify how forcing dataset choice affects the estimates of key climate metrics (e.g. Equilibrium Climate Sensitivity or Transient Climate Response) and the distribution of FaIR parameters (e.g. carbon cycle parameters or shallow and deep ocean heat capacities). We also compare ensembles of future projections produced using the new calibrations. We show that forcing changes result in relatively small impacts on emergent parameters, e.g. ECS and TCR are up to 2.5 % higher in CMIP6 calibration compared to CMIP7. These translate in simulated temperature estimates for 2100 colder by up to 0.2 K across various SSP scenarios when using the CMIP7 calibration instead of the CMIP6 one.
Overall, our results provide a comprehensive assessment of forcing changes across CMIP eras, in particular for the new CMIP7 datasets, and their implications for simulating historical and future climate. We discuss the value of reduced-complexity models for fast sensitivity testing of new forcings datasets and establish a workflow to test future updates of inputs4MIPs forcings.
How to cite: Verkerk, M., Aubry, T., Smith, C., Naik, V., Durack, P., and Wells, C. and the CMIP Climate forcings Task Team: Assessment of forcing changes across CMIP eras using reduced-complexity climate models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-382, https://doi.org/10.5194/egusphere-egu26-382, 2026.
We present the historical anthropogenic aerosol dataset SPv2.1, produced using the Simple Plumes (SP) aerosol module (Stevens et al., 2017), for use in the Coupled Model Intercomparison Project Phase 7 (CMIP7). The dataset covers the period from 1850 to 2023 inclusive and provides updated and extended estimates of anthropogenic aerosol optical properties and their effects on clouds by incorporating the latest emission inventory and extending the temporal coverage beyond earlier versions. The SP module induces anthropogenic aerosol effects in a simplified but physically plausible way, linking emissions from major industrial and urban regions to global model grids using nine predefined plumes around the world. Present-day monthly plume profiles of anthropogenic aerosol extinction are scaled with historical time series of SO₂ and NH₃ emissions to reproduce monthly changing spatial patterns of anthropogenic aerosol forcing. Compared to the earlier CMIP6 dataset, SPv2.1 shows moderate differences. The most pronounced differences occur over Africa between approximately 1940 and 1990, where SPv2.1 exhibits higher aerosol optical depth and increased cloud droplet number concentrations. These differences arise from updates in the underlying emission inventory. Additionally, SPv2.1 extends the historical period by nine years relative to CMIP6, which ended in 2014, thereby providing a more recent representation of present-day anthropogenic aerosol forcing. The SPv2.1 dataset supports a wide range of applications related to anthropogenic aerosol effects on radiation, clouds, and atmospheric composition across multiple models and modeling centers. It is publicly available for use in CMIP7 and other applications (Fiedler and Azoulay, 2025). Ongoing work now extends the SPv2.1 dataset to future anthropogenic aerosol scenarios from ScenarioMIP for CMIP7. The SPv2.1 scenarios will be derived from seven future emission pathways, spanning from high to very low anthropogenic emissions of SO₂ and NH₃ until 2125. In addition, climate model simulations with ICON-XPP are being performed to assess the aerosol radiative forcing for both the historical period and future scenarios.
How to cite: Azoulay, A. and Fiedler, S.: Anthropogenic Aerosol Forcing for CMIP7, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19321, https://doi.org/10.5194/egusphere-egu26-19321, 2026.
The radiative forcing of CO2, which measures its impact on surface warming, is found to vary with background climate state, a phenomenon known as state dependence. Recent studies have suggested the state dependence of radiative forcing in explaining the changes in equilibrium climate sensitivity, primarily due to enhancement of instantaneous forcing in climate states of higher CO2 concentrations. However, the role of atmospheric adjustment in shaping the overall forcing and its state dependence remains vague. Here we focus on stratospheric temperature adjustment, a dominant component of atmospheric adjustment affecting the magnitude of CO2 radiative forcing. Using CMIP6 data and a radiative transfer model, we find that forcing associated with stratospheric temperature adjustment decreases in higher CO2 climate states, offsetting the increase in instantaneous forcing and leading to a smaller overall forcing change with the climate state. To elucidate the mechanisms underlying this decrease, we decompose the forcing adjustment into three multiplicative components of TOA radiative kernel, layerwise temperature Jacobian and instantaneous heating rate perturbation. We find that changes in the kernel and Jacobian contribute weakly, whereas the instantaneous heating rate response dominates the reduction in adjustment. Using a cooling-to-space approximation, we further demonstrate that the combined effects of reduced emission and increased optical depth in a higher CO₂ climate state lead to weaker stratospheric temperature adjustment and thus forcing adjustment.
How to cite: He, R. and Huang, Y.: Stratospheric Temperature Adjustment Damps the State Dependence of CO2 Radiative Forcing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3513, https://doi.org/10.5194/egusphere-egu26-3513, 2026.
Increasing concentrations of atmospheric CO2 alter the Earth's energy budget not only by interaction with radiation, but also through adjustments of the climate state. One set of such adjustments is mediated by the response of vegetation to an increase in CO2: Changes in vegetation cover and leaf area index (LAI) as well as CO2-induced plant stomatal closure alter surface fluxes of radiation, heat, and water. These changes in surface fluxes in turn affect atmospheric temperature, water vapor, and cloud cover, further affecting the Earth's energy balance. Past studies have shown that stomatal closure leads to a positive radiative forcing at the top of atmosphere (TOA), largely caused by adjustments of clouds to reduced transpiration. However, the full set of adjustments including the role of LAI changes and the surface energy balance have not been considered in investigations of the Earth's energy budget.
We aim to provide a detailed analysis of energy budget changes at the land surface and TOA by utilizing idealized simulations performed with the Max-Planck-Institute Earth System Model, and place these results in the context of a larger ensemble by analysing transient C4MIP simulations with a similar coupling. In our simulations we prescribe an abrupt doubling of CO2 concentration only seen by the land model, while its atmospheric counterpart continues to experience pre-industrial conditions. This isolates the response of vegetation and changes to the climate system resulting from it, by omitting the direct response of the atmosphere and radiation to increased CO2. To estimate which changes originate from an increase in LAI, an additional experiment is run with prescribed LAI per vegetated area.
Preliminary results show persistent decreases in near-surface relative humidity and low cloud cover over land, especially pronounced in the extra-tropics. As a result, incident shortwave radiation at the land surface increases by 0.85 Wm-2 in the global average. Together with a decreased latent heat flux, this is compensated by a greater sensible heat flux and moderate temperature increase, causing more longwave emission. Accordingly, the outgoing radiation at the TOA shows a decrease in the shortwave component, but an increase in longwave radiation. The simulation with prescribed LAI shows a much higher radiative forcing of 0.33 Wm-2 compared to 0.13 Wm-2 in the experiment with dynamically evolving LAI, suggesting that adjustments in LAI could compensate significant parts of the forcing through CO2-induced stomatal closure. However, this signal is less robust compared to the persistent changes and will require additional, dedicated experiments to be investigated thoroughly. These findings show a long term effect of stomatal closure on surface energy fluxes and suggest that considering LAI response to increased CO2 could alter estimates of radiative forcing, highlighting the need for further study.
How to cite: Behr, N., Reichstein, M., and Winkler, A. J.: The impact of vegetation response to CO2 on energy fluxes at Earth's surface and top of atmosphere, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9120, https://doi.org/10.5194/egusphere-egu26-9120, 2026.
The Amazon rainforest offers a unique experimental framework to assess aerosol effects on the radiative balance, given the interplay between a low-concentration, biogenically dominated background state and episodic, high-concentration anthropogenic perturbations or Saharan dust and smoke plume intrusions within a spatiotemporally varied aerosol population. Whereas previous studies have characterized the seasonal dynamics of the optical properties of these particles, disentangling the radiative effects of different-sized aerosols remains challenging. Our study focused on distinguishing the contributions of fine- and coarse-mode aerosols to top-of-atmosphere (TOA) radiative forcing (RF) and on evaluating a comprehensive suite of aerosol optical properties across six AERONET sites in the Amazon over 2 decades (2000-2024). This was performed by assigning labels to each data point based on the daily average of fine- and coarse-mode aerosol optical depths (AODs), using thresholds to categorize aerosol conditions as “low” (below 25th percentile) or “high” (above 75th percentile), and then evaluating each kind of event. For every site, events of low fine-mode and low coarse-mode (LL), and low fine-mode and high coarse-mode (LH) conditions usually occur during the wet season and the transition from wet to dry season. Conversely, events of high fine-mode and low coarse-mode (HL) and high fine-mode and high coarse-mode (HH) conditions usually occur during the dry season. Across all sites, under low fine-mode conditions, the AOD shows a strong dependence on the coarse-mode, with increases of approximately 131% from LL to LH. However, under high fine-mode conditions, the AOD shows a weaker dependence on the coarse-mode, with increases of approximately 12% from HL to HH. Regarding TOA RF, sites in the deforestation arc show a weak dependence on coarse-mode under both low and high fine-mode conditions (RFLL = -3.15 W/m² to RFLH = -3.05 W/m² and RFHL = -31.3 W/m² to RFHH = -33.4 W/m²). In contrast, sites in the central-north region show a stronger dependence on coarse-mode (RFLL = -4.40 W/m² to RFLH = -11.1 W/m² and RFHL = -20.0 W/m² to RFHH = -29.1 W/m²). For a multilinear regression model in the form RF = cFM AODFM + cCM AODCM, where cFM and cCM are the RF efficiencies of fine- and coarse-mode per unit of their respective AODs, we obtained cFM = -25 W/m² and cCM = -95 W/m² for the deforestation arc sites, and cFM = -39 W/m² cCM = -66 W/m² for the central-north Amazon ones. In conclusion, we have shown that coarse-mode aerosols contribute significantly to all the optical properties analyzed, particularly by increasing AOD during low fine-mode conditions and by enhancing (in magnitude) radiative forcing at sites in the central-north Amazon. Moreover, as all RF efficiencies are negative, the predominant aerosol effect in the Amazon atmosphere is always cooling, and the coarse-mode efficiency is consistently greater than the fine-mode efficiency at all sites.
How to cite: Tavares, P., Franco, M., Morais, F., and Artaxo, P.: Two decades of AERONET analysis of fine and coarse-mode aerosols impacts on radiative forcing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15081, https://doi.org/10.5194/egusphere-egu26-15081, 2026.
Black carbon (BC) aerosols are commonly treated as a uniformly warming climate forcer, yet its radiative impact depends sensitively on particle microphysics, column loading, and vertical energy redistribution. Here, we present an observation-constrained assessment of BC radiative forcing over two contrasting Asian urban agglomerations-Dhaka (Bangladesh) and Xuzhou (China), using a multi-platform remote sensing framework that integrates multi-waveband satellite and ground-based observations as constraints. Multi-waveband single-scattering albedo (SSA) from TROPOMI and AERONET/SONET is used to constrain physically admissible BC core-shell size and mixing-state ensembles, which are further filtered using aerosol optical depth (AOD) to enforce column-integrated optical feasibility. The resulting microphysical ensembles and their associated optical properties are coupled with radiative transfer simulations to quantify clear-sky atmospheric (ATM), surface (SFC), and top-of-atmosphere (TOA) forcing at high spatial and temporal resolution.
We find that BC radiative forcing exhibits pronounced regional heterogeneity and a strong vertical redistribution of energy within the atmospheric column. Contrary to the canonical assumption of BC as a strictly warming TOA agent, weighted climatological means reveal substantial net TOA cooling over both regions (-15.0 ± 1.2 Wm-2 over Dhaka and -17.4 ± 2.6 Wm-2 over Xuzhou), with occasional episodic warming events. In contrast, atmospheric absorption is markedly stronger (18.2 ± 1.3 Wm-2 and 15.5 ± 1.9 Wm-2, respectively), corresponding to localized heating rates approaching ~0.3 K day-1, while surface cooling frequently exceeds -30 Wm-2. These results indicate that BC plays a larger role in regulating boundary-layer stability and regional energy balance than implied by TOA forcing alone.
Diagnostic analysis using multivariate decomposition reveals that BC radiative impacts are organized into a limited number of physically coherent pathways. In Dhaka, forcing variability is dominated by emission-driven column loading, producing tightly coupled atmospheric heating and TOA cooling, whereas in Xuzhou, variability is primarily regulated by column-integrated optical efficiency associated with particle aging and mixing state. Local forcing extremes frequently exceed the global mean effective radiative forcing of long-lived greenhouse gases by more than an order of magnitude, underscoring the inadequacy of coarse-scale or globally averaged frameworks for assessing BC-climate interactions. Together, these findings demonstrate that regional climate responses to BC are governed by microphysically mediated energy redistribution, highlighting the need for observation-constrained, high-resolution approaches to inform mitigation strategies in polluted environments.
How to cite: Tiwari, P., Cohen, J. B., Gao, H., Guan, L., Liu, Z., Lu, L., Wang, S., Zaman, S. U., and Qin, K.: Observation-constrained estimates and diagnostic insights into black carbon radiative forcing across contrasting urban environments from multi-platform remote sensing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4639, https://doi.org/10.5194/egusphere-egu26-4639, 2026.
The Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission–Climate (GCOM-C) is a polar-orbiting satellite launched by Japan Aerospace Exploration Agency (JAXA) on 23 December 2017. SGLI is a multi-wavelength optical radiometer with 19 spectral bands ranging from the near-ultraviolet to the thermal infrared. It provides unique observation capabilities, including polarization, multi-directional, and near-ultraviolet measurements, with a spatial resolution of up to 250 m and a swath width exceeding 1,000 km.
Assessing the climate influence of wildfires requires continuous observation of aerosols released by biomass burning, as well as quantitative evaluation of their optical characteristics and radiative impacts. In this work, we investigated large wildfire events occurring since 2018 across multiple regions, including Brazil, Angola, Australia, California, Siberia, and Southeast Asia. Based on observations from SGLI, we examined temporal variations in key aerosol optical parameters—namely aerosol optical thickness (AOT), Ångström exponent (AE), and single scattering albedo (SSA)—supplemented by complementary satellite and ground-based measurements.
Examination of the relationships between SSA and AE suggests that aerosol optical behavior is strongly influenced by ambient relative humidity and the dominant vegetation types involved in combustion, in agreement with earlier findings. In addition, variations in net incoming radiation at the top of the atmosphere were evaluated during periods of intense fire activity to quantify the direct radiative effects of biomass-burning aerosols. The analysis indicates pronounced negative radiative forcing, corresponding to a cooling effect, over oceanic areas, reaching −78 W m⁻² for Australia and −96 W m⁻² for California. In contrast, radiative forcing over land remains comparatively small, with values on the order of −10 W m⁻² across all examined regions.
These findings highlight the necessity of accounting for regional differences in aerosol optical properties and surface reflectance when estimating wildfire-related radiative forcing and when evaluating the future climatic implications of this short-lived climate forcer.
How to cite: Tanada, K., Murakami, H., and Shimada, R.: The GCOM-C Mission and Eight Years of Continuous Global Observations with the SGLI: Estimation of Aerosol Optical Properties and Radiative Forcing from Large-Scale Wildfires, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6960, https://doi.org/10.5194/egusphere-egu26-6960, 2026.
Since pre-industrial times anthropogenic aerosols counteract the climate warming attributed to anthropogenic greenhouse gases through direct and indirect effects. . Within the ESA CLIMATE-SPACE cross-ECV project SATACI (SATellite observations to improve our understanding of Aerosol-Cloud Interactions), a feasibility study is conducted to demonstrate the use of global, long-term satellite data records to derive a new climate indicator for the monitoring of the cooling offset due to anthropogenic aerosols and aerosol modified clouds. This new climate indicator intends to complement the existing tableau of WMO climate indicators (e.g. surface temperature, atmospheric CO2 concentrations).
The new indicator is based on off-line (dual call) two-stream radiative transfer simulations. Baseline optical aerosol properties are taken from the MACv3 aerosol climatology, which is tied to multi-annual ground-based statistics from sun-/sky photometry and derived aerosol type contributions. Aerosol indirect effects are included based on statistical associations between relevant aerosol and cloud properties. In a stepwise approach, key aerosol properties (i.e. AOD, fine mode fraction, Dust AOD, absorbing AOD) and key aerosol/ cloud associations (i.e. fine mode AOD vs cloud droplet number concentrations, low level cloud cover) will be replaced with CCI / Copernicus Climate Change Service (C3S) (and other, such as CM-SAF) satellite retrievals. Outputs are global monthly maps and time series of aerosol impact associated radiative effects at the top of the atmosphere (TOA).
Uncertainties and diversity between different satellite datasets and aerosol cloud associations will be assessed by using different satellite data records for each variable and through uncertainty propagation of those satellite inputs through the radiative transfer code following the FIDUCEO principles. This feasibility study aims at providing an initial demonstration of a cooling indicator, assessing its potential, by exploiting the value of global, consistent, multidecadal satellite records, and identifying its limitations, such as diversity and uncertainties. To ease communication, a simple parameterization (similar to the last IPCC report) to convert TOA radiative effect changes to an equivalent surface temperature change (0.7W/m2 ~ 1 Celsius) will be applied.
This paper will discuss the methodology, the uncertainty propagation strategy and initial demonstrations of the climate indicator using MODIS aerosol retrievals between 2000 – 2021 as well as four different C3S dual view records (1996 – 2012 and 2017 – 2025) of AOD and Fine Mode AOD.
How to cite: Popp, T., Stöffelmair, U., Schall, A., Kinne, S., Luffarelli, M., and Eisinger, M.: First preliminary demonstration of a new climate indicator “aerosol and cloud cooling”, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7437, https://doi.org/10.5194/egusphere-egu26-7437, 2026.
Energy exchanges between the lower atmosphere and the shallow subsurface are fundamental to understand and quantify processes relevant to the society and ecosystems, such as extreme events, the hydrological cycle, the land carbon cycle, and the Earth heat inventory. Among these energy fluxes, Ground Heat Flux (GHF) corresponds to the conduction of heat through the subsurface. GHF is used for estimating evapotranspiration in order to ensure the conservation of energy in the applied models. Ground heat storage in the continental subsurface is estimated from GHF data, constituting the second largest term of the Earth heat inventory after the ocean. Furthermore, the increase in GHF in recent times is warming permafrost soils in the Arctic, thus enabling the thawing of permafrost and the release of additional carbon into the atmosphere.
Nevertheless, ground heat flux is the term of the surface energy balance with less measurements around the world, hindering the analysis of those processes. There are around 60 Eddy-covariance towers measuring GHF globally, with most sites containing less than a decade of records. Because of this limitation, geothermal data has been used to obtain long-term estimates of GHF. However, these estimates are only able to retrieve long-term changes in surface conditions with decadal to centennial periods, and there are not enough sampling sites to retrieve a global average after the year 2000. Although satellite observations have been recently used to bridge the gap in the heat storage evolution between 2000 and 2020 at the annual scale, data at daily and weekly temporal scales are still necessary in order to analyze the role of GHF on short-term processes such as evapotranspiration and extreme events.
Here, we develop a framework, based on machine learning models and Earth observation products, capable of estimating GHF at daily resolution across several land covers and climate zones. Our framework predicts GHF with a Root Mean Squared Error (RMSE) of 4.79 W m-2 and a Pearson’s correlation coefficient (R) of 0.65 at the global scale. The performance of the framework improves when predicting 8-day periods, achieving a RMSE of 3.31 W m-2 and a R of 0.77. A hybrid approach is also evaluated. This method predicts ground surface temperatures and uses them as forcing for a physical model that yields GHF values. Nevertheless, the performance of this hybrid method is lower than the direct approach. We identify several physical processes as the leading features driving the model performance. Given its capability to estimate GHF across several land covers and climate zones, the framework provides the basis for developing a global GHF product, thereby filling a critical gap in the datasets available to study the surface energy balance. Furthermore, this product would enable the characterization of the spatial structure of GHF, contribute directly to monitoring the land component of the Earth heat inventory, and provide a crucial observational reference for developing the land components of global climate models.
How to cite: Cuesta-Valero, F. J., Naylor, P., García-García, A., and Peng, J.: Ground heat flux at daily scale? Estimates from machine learning models and Earth observation products, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1554, https://doi.org/10.5194/egusphere-egu26-1554, 2026.
The surface energy budget of the Arctic Ocean governs sea ice growth in winter and melt in summer. Understanding the surface energy budget and 2m temperature and correctly representing them in models is a key condition for understanding and projecting Arctic climate change. Direct observations of surface fluxes are scarce, and widely used reanalysis datasets suffer from systematic biases. Here, we train a neural network with observational data to bias-correct ERA5 reanalysis surface fluxes. We achieve substantial reductions in RMSE for hourly values of net shortwave radiation (~40%), downward longwave radiation (~16%) and the total surface energy budget (~55%) as well as 2m temperature (~34%). Our bias-correction eliminates the wintertime warm bias of about 4K in ERA5, reduces wintertime surface cooling by about 50% and dampens summertime surface heating. This revised surface cooling estimate is consistent with independent satellite-observed sea ice growth rates. In contrast to ERA5 fluxes, our bias-corrected data capture the observed clear and cloudy states of the Arctic winter boundary layer and the associated bimodal distribution of net longwave radiation. The bias-corrected data provide an improved baseline for climate model evaluation, climatological and case studies and forcing to drive stand-alone sea ice and ocean models.
How to cite: Hossain, A., Keil, P., Grover, H., Brooks, I., Cox, C. J., Gallagher, M. R., Granskog, M. A., Guy, H., Hudson, S. R., Persson, P. O. G., Shupe, M. D., Tjernström, M., Vüllers, J., Walden, V. P., and Pithan, F.: Machine learning eliminates near-surface warm bias in reanalysis and reveals weaker winter surface cooling over Arctic sea ice, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19460, https://doi.org/10.5194/egusphere-egu26-19460, 2026.
Understanding why temperature trends differ across altitudes remains challenging, particularly in mountainous regions where local feedbacks and limited long-term observations make attribution difficult. Here, we analyze long-term (1940–2025) time series of surface energy balance components from ERA5 reanalysis to identify trends in surface temperature and to attribute these to trends in radiative fluxes. We then assess the robustness of these relationships using observations from Baseline Surface Radiation Network (BSRN) stations spanning different altitudes. Our results show a consistent increase in surface temperature across altitudes. While trends in absorbed solar radiation exhibit significant variability, downwelling longwave radiation increases systematically. This confirms its key role in driving surface warming. We then apply a framework that decomposes longwave radiation using the semi-empirical formulation of Brutsaert (1975), combined with thermodynamic constraints from the maximum power principle applied to the surface energy balance. This enables us to investigate the conditions under which enhanced climate sensitivity at higher altitudes may arise. This approach links observed trends in reanalysis data to a thermodynamically constrained surface energy balance, providing a basis for diagnosing the role of atmospheric emissivity and moisture changes in shaping temperature trends at different altitudes. Future work will extend this framework to higher spatial resolutions to better capture the sensitivity of surface temperature to atmospheric emissivity across complex terrain and at different altitudinal settings.
How to cite: Shukla, S. and Kleidon, A.: Attributing temperature trends across altitudes using a surface energy balance approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17301, https://doi.org/10.5194/egusphere-egu26-17301, 2026.
Rapid urbanization and climate change have markedly shifted Beijing’s climate in recent decades from cold–dry toward warm–humid conditions, raising urgent questions about the dominant controls of its surface thermal environment. Using MODIS land surface temperature (LST) observations from 2000–2024, combined with NDVI, nighttime lights, the Human Footprint index, ERA5-Land meteorology, and surface albedo, we investigate the spatiotemporal evolution of LST and quantitatively attribute its drivers across spatial scales.
Long-term LST trends were robustly identified using Theil–Sen slopes and the Mann–Kendall test, while the relative contributions of natural and anthropogenic factors were quantified through ensemble machine-learning models (Random Forest and XGBoost) coupled with SHAP-based interpretability. This integrated framework enables a scale-aware attribution of LST dynamics rather than simple correlation analysis.
Pronounced urban heat island patterns are observed in Beijing’s core districts (Dongcheng, Xicheng, Haidian, Chaoyang, Fengtai, and Shijingshan), gradually weakening toward suburban areas. Between 2000 and 2024, LST increased significantly or highly significantly across 34.67% of the city—mainly in the urban core and southeastern districts (Daxing and Tongzhou)—while 63.52% experienced cooling, particularly around the Miyun Reservoir and along the Guishui River in Yanqing. Attribution results reveal that Human Footprint intensity and nighttime light activity exert the strongest warming effects, whereas vegetation greenness (NDVI), relative humidity, and soil moisture consistently mitigate LST. The maximum cooling rate is associated with NDVI values between 0.25 and 0.55. SHAP rankings identify Human Footprint, air temperature, NDVI, and nighttime lights as the dominant drivers at the metropolitan scale, while surface albedo plays a more prominent role within the urban core.
These findings provide a quantitative and interpretable assessment of the scale-dependent drivers shaping Beijing’s surface thermal environment and offer actionable insights for urban climate adaptation, including optimized green-space allocation, high-albedo surface renovation, and land-use planning.
How to cite: Zhou, M., Cheng, Y., and Chu, L.: Evolution of land surface temperature in Beijing and its multi-source driving mechanisms, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2707, https://doi.org/10.5194/egusphere-egu26-2707, 2026.
Surface albedo plays a key role in regulating land-atmosphere energy exchange, yet its spatiotemporal variability and underlying driving mechanisms remain inadequately quantified. This study first developed a machine learning model to reconstruct land surface albedo across China from 1980 to 2020, and conducted model experiments to separate the contributions of three primary drivers (i.e., land cover change, vegetation dynamics, and climate change) to albedo variations. Results show that the machine learning model can reproduce surface albedo with high accuracy. Over the past four decades, the mean albedo across the study area decreased by 0.0101, corresponding to a linear trend of -0.0003 yr-1. Attribution analysis indicates that climate change was the dominant driver over 55.30% of the land area, followed by vegetation dynamics (24.26%) and land cover change (20.44%). Climate forcing, through its control over snow cover, temperature, precipitation, and soil moisture, primarily governed both interannual fluctuations and long-term trends in albedo. In contrast, large-scale afforestation and ecological restoration led to substantial albedo decreases, particularly in southern and southwestern China. Sensitivity analysis further reveals strong spatial heterogeneity in albedo responses to leaf area index (LAI), with pronounced negative sensitivities in arid regions and weak or even positive effects in humid zones. Our findings highlight the dominant role of climate variability in shaping albedo dynamics, while demonstrating how large-scale ecological restoration and vegetation greening modulate surface energy balance under ongoing climate change.
How to cite: Wang, J., Huang, X., Niu, H., Zhang, S., and Yuan, W.: Attribution of Land Surface Albedo Changes in China over the Last 40 Years, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4877, https://doi.org/10.5194/egusphere-egu26-4877, 2026.
Downward shortwave radiation (DSR) is the primary energy source driving Earth’s climate, hydrological, and ecological processes. While mountains occupy approximately 24% of the global land surface and exhibit complex radiative transfer processes, current global climate models and satellite products predominantly rely on plane-parallel assumptions, thereby neglecting topographic effects such as shadowing and terrain-reflected radiation.
To quantify these impacts, we developed a hybrid physical and data-driven method to generate the global, daily DSR product at 0.05° resolution, incorporating topographic effects, spanning from 2003 to 2024. By integrating a mountainous radiative transfer scheme with machine learning, we successfully captured the spatiotemporal heterogeneity of DSR over rugged terrain. Our analysis reveals that ignoring topographic effects results in substantial uncertainties across scales (from daily to annually and grid to global scales). In rough terrain hotspots, such as High Mountain Asia, the annual mean bias exceeds 30 W/m² (>20%). The slope-dependent uncertainties in the original DSR product were substantially reduced in the new DSR product with topographic considerations, i.e., the RMSE decreased globally from 21.7 to 2.2 W/m² in areas with slopes exceeding 25°. The topographically corrected DSR better explains the spatial heterogeneity of land surface temperature variations across the terrains.
These findings suggest that topography acts as a critical modulator of the Earth system's energy flow. The uncertainties of DSR in mountainous areas imply propagated biases in simulations of the cryosphere (snowmelt), carbon cycle (gross primary productivity), and hydrological processes. We underscore the necessity of integrating topographic considerations to improve the understanding of climate mechanisms in vulnerable mountain ecosystems.
How to cite: Ma, Y., Liang, S., and He, T.: Integrating Topographic Effects into Global Downward Shortwave Radiation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2407, https://doi.org/10.5194/egusphere-egu26-2407, 2026.
Outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) is a crucial parameter for understanding and interpreting the interactions between clouds, radiation, and climate. It has been one of the operational products of the Fengyun (FY) meteorological satellites. The accuracy of OLR has gradually improved due to advancements in satellite payload performance and the OLR retrieval algorithm. The Fengyun-3 (FY-3) satellite represents China's second generation of polar-orbiting meteorological satellites. Since the operational release of the OLR product from the FY-3A satellite in 2008, more than 17 years have passed. Throughout this time, the operational calibration and product retrieval algorithms have been continuously updated, resulting in variations in the accuracy of the operational products over different periods.
To address these inconsistencies, we conducted calibration consistency processing on the historical data from the Fengyun satellites and implemented a unified retrieval algorithm to reprocess the OLR products. This effort has led to the creation of a long-term dataset of outgoing longwave radiation from the top of the atmosphere for Fengyun satellites, covering the period from 2011 to the present. The dataset builds upon the original operational products and achieves multi-satellite consistency through the development of bias correction algorithms for inter-satellite discrepancies, as well as for correcting data biases caused by current orbital drifts. This dataset provides stable long-term support for climate services and scientific research, making it suitable for climate change monitoring and analysis. Furthermore, applications in monitoring climate events such as the Madden-Julian Oscillation (MJO) and the El Niño-Southern Oscillation (ENSO) are also explored.
How to cite: Zhang, W., Liu, J., Sun, L., Chen, L., and Xu, N.: Progress and Application of Outgoing Longwave Radiation Dataset from Fengyun Satellites, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6044, https://doi.org/10.5194/egusphere-egu26-6044, 2026.
The outgoing longwave radiation (OLR), which results from the combination of thermal radiation emitted by the Earth surface and each layer of the atmosphere, is of critical importance for the Earth radiative budget. Climate models are generally tuned to match the space-borne reference values of the broadband OLR derived from e.g. the CERES mission. Yet a significant inter-model spread remains, originating from differences in the simulated climate system mean state and variability, especially in terms of atmospheric water vapor and temperature, surface temperature, aerosols and clouds. Spectrally-resolved OLR observations, as derived from infrared hyperspectral sounders such as IASI (and in the near future FORUM, to be launched in 2027, which will measure for the first time the far-infrared (FIR) region (100–667 cm-1) at high spectral resolution), provide access to the spectral signature of individual climate processes and are thus valuable to identify biases in the geophysical variables of climate models. For instance, it can unveil spectral error compensations between distinct spectral ranges, beyond an apparent good match between simulated and observed broadband OLR. The present work investigates the inter-model spread of clear-sky broadband OLR of 9 CMIP6 climate models which reaches 5.6 W.m-2. To that end, clear-sky FORUM-like spectra are simulated using the fast radiative transfer solver RTTOV and atmospheric profiles and surface properties of historical amip simulations (1979–2014 period). Spectra climatologies of the ERA5 reanalysis are also computed. Significant brightness temperature (BT) and radiance discrepancies between models arise across the OLR spectrum as a consequence of differences in simulated geophysical variables. For instance, the CO2 band displays BT differences up to 16 K, which are directly linked to differences in the upper troposphere and lower stratosphere temperature. Differences as large as 3 K are also reported in the FIR H2O absorption band (100–600 cm-1) for the global annual mean BT, that can be even larger for specific latitudes. We show that the FIR H2O region accounts for half of the inter-model broadband OLR variability and is strongly correlated to differences in mid-latitude and tropical upper-tropospheric relative humidity. This suggests that upper-tropospheric relative humidity is a key driver of the radiative budget in climate models. This work also highlights that FORUM observations shall provide a strong constrain on the climate models’ spectral signatures and thus help contribute to their improvement.
How to cite: Schmitt, F., Libois, Q., and Roehrig, R.: Intercomparison of the spectrally-resolved clear-sky outgoing longwave radiation estimates from multiple climate models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19013, https://doi.org/10.5194/egusphere-egu26-19013, 2026.
Outgoing longwave radiation (OLR) at the top of the atmosphere is a fundamental component of the Earth’s radiation budget and a key observable for monitoring climate variability and change. The Meteosat Third Generation (MTG) Flexible Combined Imager (FCI) introduces a new geostationary OLR product derived from narrowband thermal infrared radiances using scene-dependent regressions. Ensuring the continuity, stability and scientific usability of this product relative to heritage datasets is therefore essential. Here we present an evaluation of the MTG FCI OLR product using comparisons with the Geostationary Earth Radiation Budget (GERB) thermal fluxes on Meteosat Second Generation (MSG) and with CERES OLR products.
The comparisons against GERB exploit the co-location of MSG and MTG to enable a detailed intercomparison between MTG FCI OLR and GERB thermal fluxes over several months spanning different seasons. Broadscale and regional differences are analysed as a function of viewing geometry, time of day and surface type, and cloud cover, and are interpreted in the context of known limitations in the GERB radiance-to-flux conversion and the MTG OLR retrieval methodology, including the use of scene-dependent regressions and plane-parallel assumptions.
Further comparisons against the CERES SYN GEO hourly and monthly mean fluxes, together with associated cloud information, provide an additional independent benchmark and allow the investigation of cloud-dependent and diurnal characteristics of the MTG OLR product. Together, these results provide a comprehensive assessment of the performance, stability and limitations of the MTG FCI OLR product and offer guidance for its application in studies of the Earth’s radiation budget and climate variability, as well as a roadmap for future product improvements.
How to cite: Flegrova, M., Russell, J., and Brindley, H.: Assessing the MTG Flexible Combined Imager Outgoing Longwave Radiation Product Using GERB and CERES Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20364, https://doi.org/10.5194/egusphere-egu26-20364, 2026.
Despite containing up to half of the Earth’s thermal emission to space, the far-infrared spectral region (FIR, defined here as 100–667cm-1 or 15–100µm) has rarely been observed from satellites. Spectrally-resolved measurements, which offer a deeper understanding of the observed physical processes, have been limited to a 9-month dataset from 1970. This has led to substantial uncertainties in the spectroscopy of water vapour, radiative properties of clouds, and the surface spectral emissivity; these in turn limit confidence in modelled FIR energy flows.
With the advent of the Polar Radiant Energy in the Far-InfraRed Experiment (PREFIRE), we have made a step towards the return of spectral measurements of the Earth in the FIR. Launched as a NASA Earth Venture mission in 2024, it consists of two polar-orbiting CubeSats equipped with uncooled grating spectrometers. The instruments offer a new perspective of the Earth with a moderate spectral resolution. However, there remains some uncertainty regarding their calibration.
To this end, we attempt to assess the accuracy of PREFIRE spectral measurements by way of a ‘ground-to-space’ closure experiment. Using zenith-viewing observations from the ground-based Far INfrarEd Spectrometer for Surface Emissivity (FINESSE), for which uncertainties have been thoroughly characterised, we gauge the representativity of atmospheric data from radiosonde launches and reanalysis. Using these data, we simulate PREFIRE measured radiances for an overflight of the field site and compare to the observations.
At the surface, simulations of the FINESSE instrument’s output are in very good agreement with observations. Observations from the PREFIRE instrument indicate some persistent biases. In the atmospheric window, a rigorous diagnosis of these biases is impeded somewhat by uncertainty in surface conditions, while instrument noise strongly impacts measurements in the FIR. By quantifying the dominant sources of uncertainty, we highlight proposed techniques for future similar experiments to aid the evaluation of satellite radiances.
How to cite: Pery, B., Brindley, H., Murray, J., L'Ecuyer, T., Michaels, T., Panditharatne, S., Mosselmans, S., and Hogan, R.: Towards ground-to-space spectral radiative closure in the thermal infrared with PREFIRE, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20760, https://doi.org/10.5194/egusphere-egu26-20760, 2026.
Climate forcing due to increases in well-mixed greenhouse gases (e.g., CO2 and methane) and the radiative response to the forcing have led to an imbalance between how much solar radiant energy is absorbed by Earth and how much thermal infrared radiation is emitted to space. Presently, Earth is absorbing »1 Wm-2 more energy from the sun than it is emitting to space as infrared radiation. A positive Earth energy imbalance (EEI) is concerning as it leads to increases in global mean temperature, sea level, heat accumulation within the ocean, and melting of snow and sea ice. Satellite and in-situ measurements indicate that EEI has more than doubled since 2000, increasing at a rate of 0.43±0.17 Wm-2 per decade. To put this into context, the cumulative planetary heating since 2000 associated with EEI is a factor of 26 larger than the global direct primary energy consumption for the same period. In this presentation, I will discuss the observations used to track changes in EEI and summarize our current understanding of the factors driving the observed changes. Of particular interest are recent EEI changes: EEI anomalies relative to the long-term average have subsided appreciably owing to an unprecedented and prolonged increase in outgoing longwave radiation. The underlying causes for this will be discussed.
How to cite: Loeb, N.: Earth’s Energy Imbalance: A Satellite Perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5505, https://doi.org/10.5194/egusphere-egu26-5505, 2026.
Earth’s Energy Imbalance (EEI) is a key metric to quantify climate change. In the long-term mean, most of this excess heat is absorbed by the ocean due to its large thermal capacity. A comparatively small fraction warms the land, melts ice and warms and moistens the atmosphere. However, this contribution shows that atmospheric storage plays a non-trivial role on shorter timescales. We investigate the balance among variations in the global flux at the top of the atmosphere (TOA), the rate of oceanic warming, and storage variations in atmosphere, land, and sea ice from year to year over 2005-2024. We find that changes in ocean warming lead the net energy flux at TOA by 2 months, and these two time-series are fairly well correlated on these interannual time scales, but the sum of atmospheric and oceanic rates of energy uptake are better correlated with a maximum correspondence at zero time lag. Further improvements of the correlation are modest when also including energy storage variations in land and sea ice. Hence the atmosphere generally plays an important role in buffering and redistributing year-to-year energy uptake by the climate system, most notably during El Niño and La Niña events. Atmospheric heat uptake played a particularly strong role in 2023, when surface temperatures increased remarkably and the global net TOA flux reach a new record high, but ocean heat uptake showed a less extreme anomaly. These results demonstrate the need to monitor energy storage variations in all compartments of the climate system to better understand variations in EEI.
How to cite: Mayer, M., Loeb, N. G., Lyman, J. M., Johnson, G. C., Winkelbauer, S., and Haimberger, L.: The Atmosphere’s Substantial Role in Interannual Variability of Earth’s Energy Imbalance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4028, https://doi.org/10.5194/egusphere-egu26-4028, 2026.
Monitoring the Earth Energy Imbalance (EEI) is of prime importance for a predictive understanding of climate change. Furthermore, monitoring of the EEI gives an early indication on how well mankind is doing in implementing the Paris Climate Agreement. EEI is defined as the small difference between the incoming energy the Earth receives from the Sun and the outgoing energy lost by Earth to space. The EEI is cumulated in the Earth climate system, particularly in the oceans, due to their substantial heat capacity, and results in global temperature rise. Currently the best estimates of the absolute value of the EEI, and of its long term variation are obtained from in situ observations, with a dominant contribution of the time derivative of the Ocean Heat Content (OHC). These in situ EEI observations can only be made over long time periods, typically a decade or longer. In contrast, with direct observations of the EEI from space, the EEI can be measured at the annual mean time scale. However, the EEI is currently poorly measured from space, due to two fundamental challenges. The first fundamental challenge is that the EEI is the difference between two opposing terms of nearly equal amplitude. Currently, the incoming solar radiation and outgoing terrestrial radiation are measured with separate instruments, which means that their calibration errors are added and overwhelm the signal to be measured. To make significant progress in this challenge, a differential measurement using identical intercalibrated instruments to measure both the incoming solar radiation and the outgoing terrestrial radiation is needed. The second fundamental challenge is that the outgoing terrestrial radiation has a systematic diurnal cycle. Currently, the outgoing terrestrial radiation is sampled from the so-called morning and afternoon Sun-synchronous orbits, complemented by narrow band geostationary imagers. Recently the sampling from the morning orbit was abandoned. The sampling of the diurnal cycle can be improved, for example, by using two orthogonal 82° inclined orbits which give both global coverage, and a statistical sampling of the full diurnal cycle at subseasonal time scale. For understanding the radiative forcing – e.g. aerosol radiative forcing - and climate feedback – e.g. ice albedo feedback - mechanisms underlying changes in the EEI, and for climate model validation, it is necessary to separate the Total Outgoing Radiation (TOR) spectrally into the two components of the Earth Radiation Budget (ERB), namely the Reflected Solar radiation (RSR) and Outgoing Longwave Radiation (OLR) and to map them at relatively high spatial resolution. The Earth Climate Observatory (ECO) mission concept was selected in 2024 by the European Space Agency as one of the 4 candidate Phase 0 Earth Explorer 12 (EE12) missions. The current presentation provides a broad overview of the ECO mission objectives, the mission requirements, the key elements of a baseline mission concept, and the demonstration of the mission feasibility. Following an EE12 Phase 0 User Consultation Meeting (UCM), to be held in June 2026, 2 out of the 4 EE12 candidate missions will be selected for further Phase A study.
How to cite: Dewitte, S., Mauritsen, T., Meyssignac, B., and August, T. and the ECO Science Team: The Earth Climate Observatory space mission concept for the monitoring of the Earth Energy Imbalance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16894, https://doi.org/10.5194/egusphere-egu26-16894, 2026.
The global mean outgoing radiation from the Earth system is typically visualised as a flow of energy in the radial direction. In the context of satellite-based observations, the picture is more complex, as each element in the field of view contributes with radiance through its own characteristic angular distribution. For instruments in low Earth orbit that are designed to observe Earth’s energy imbalance (EEI), such as the wide field-of-view cameras and radiometer onboard the proposed Earth Climate Observatory (ECO) mission, fluxes of the order of 0.1 W/m2 are significant. Under such strict requirements, it is essential to capture the complete angular distribution of the radiation that leaves each element to prevent systematic errors in the estimated imbalance. In particular, a significant portion of the outgoing irradiance leaves the Earth's atmosphere above the horizon via the atmospheric limb. In this presentation, we explore the magnitude and characteristics of the limb radiance and investigate its dependence on solar conditions, surface properties, and stratospheric aerosols by using the radiative transfer model SASKTRAN. We show that the total irradiance contribution from the atmospheric limb can reach up to 2 W/m2 and that significant signal may originate from above 30 km tangent altitude. We further investigate the influence of upper atmospheric levels to the full irradiance measurement at satellite altitude and demonstrate that contributions from the upper stratosphere may be significant for EEI monitoring.
How to cite: Linder, B., Hocking, T., Megner, L., Mauritsen, T., Zawada, D., and Bourassa, A.: From dusk till dawn: the role of the atmospheric limb in observations of Earth’s energy imbalance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17875, https://doi.org/10.5194/egusphere-egu26-17875, 2026.
The ocean, thanks to its vast heat capacity, plays a central role in the Earth’s climate system by absorbing most of the radiative imbalance caused by anthropogenic emissions. Over the past decades, more than 90% of the excess energy has been stored in the ocean, thereby moderating surface warming and influencing the global radiation budget. Understanding Ocean Heat Content (OHC), its temporal variability, and spatial distribution is essential for projecting climate evolution and associated impacts, notably sea-level rise.
Traditionally, OHC has been estimated from in-situ measurements, particularly through the ARGO network, which provides temperature and salinity profiles down to 2000 m. ARGO still suffers from incomplete spatial and temporal coverage, especially under sea ice, in marginal seas, and in the deep ocean. Algorithms have been developed to address these gaps, but they introduce significant uncertainties, particularly in dynamically active regions.
To overcome these limitations, satellite observations are used. Hybrid methods combine altimetry and in-situ data, leveraging correlations between sea surface height and OHC to improve sampling. Other approaches, referred to as geodetic methods, such as this work, combine altimetry and gravimetry to estimate thermosteric sea level and derive OHC. Here, for the first time, we combine in-situ, altimetric, and gravimetric data through an inverse approach.
Residuals between in-situ OHC and geodetic OHC are optimised and interpolated using an objective mapping algorithm to produce OHC fields along with their associated uncertainties.
The OHC product is validated in a leave-one-out approach against non-used in-situ measurements. The uncertainty of the OHC is derived from the leave-one-out approach and a synthetic data approach. In addition, we derive the Ocean Heat Uptake (OHU) by computing the tendency of the OHC and we compare it with an independent estimate computed as the radiation budget measured by CERES corrected from the atmospheric divergence (ERA5). With this comparison, we assess the capacity of the OHC product to close the Earth’s energy budget over the ocean. The OHU estimate closes the budget at the ±0.5 W/m² level on a yearly basis. This level allows tracking energy transfer at the surface of the ocean, which occurs at interannual timescales due to phenomena such as El Niño and La Niña events.
How to cite: Duvignacq, T., Fourest, S., Meyssignac, B., Oncle, V., and Armaut, S.: An Inverse Approach for Ocean Heat Content Estimation Using Altimetry, Gravimetry, and In-situ Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20034, https://doi.org/10.5194/egusphere-egu26-20034, 2026.
Recent work has shown that many observational products of sea surface temperature (SST) contain substantial biases in the early 20th century. Historical SST data is critical for estimating many key properties of the global climate system through its role in modulating global and regional temperature variability and change. The global and regional responses of the atmospheric and land surface are quantified using atmosphere-only GCMs (AGCMs) forced with historical SSTs. Here, we investigate how SST biases affect atmospheric variability and trends using an AGCM ensemble forced with SSTs from the infilledDynamically Consistent ENsemble of Temperature (DCENT-I), a recently published surface temperature product that better accounts for such biases. We compare this ensemble with an identically configured AGCM ensemble forced with ERSSTv5, a SST product with substantial early 20th-century biases. We find that DCENT-I SSTs produce more realistic terrestrial temperature trends. In addition, we explore the consequences of this updated SST dataset for estimates of climate sensitivity and pattern effects. Together, we demonstrate the critical need for accurate estimates of historical SST for understanding both the forced response and internal variability.
How to cite: Lenssen, N., Chan, D., Dong, Y., Phillips, A., and Deser, C.: Biases in Historical SSTs Propagate to Key Metrics of Radiative Balance and Global Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14365, https://doi.org/10.5194/egusphere-egu26-14365, 2026.
The poleward transport of energy through the atmosphere is a fundamental characteristic of Earth’s climate system, being consistent with both the dynamic movement of moist static energy and the atmospheric energy budget. The variability of the atmospheric energy budget must therefore be consistent with atmospheric dynamics, but to what extent the relationship holds, the relative importance of the energy budget terms, and the similarity between hemispheres remains unexamined. Here, we examine the monthly relationship between the zonal mean atmospheric heat transport (AHT) and the atmospheric energy budget across the entire globe. We find that for an AHT anomaly across a given latitude, the energetic response is limited to a ±15° latitude band. In other words, enhanced heat transport across 30°N is only associated with atmospheric energy budget anomalies between 15°N and 45°N. Furthermore, enhanced monthly poleward AHT is typically associated with anomalous latent heating on the equatorward side and increased losses of energy through radiative cooling on the poleward side. In fact, gains of energy through radiative heating is only very weakly correlated with enhanced monthly poleward AHT, demonstrating the importance of atmospheric heating from the surface turbulent heat fluxes on monthly AHT anomlies. These conclusions are consistent in both reanalysis and observationally derived data products. This research refines our understanding of monthly AHT anomalies and their connection to the local energy budget, providing a unique, robust benchmark for the representation of Earth’s energy budget within climate models.
How to cite: Prince, H., Donohoe, A., and L'Ecuyer, T.: The energetic expression of monthly atmospheric heat transport variability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8351, https://doi.org/10.5194/egusphere-egu26-8351, 2026.
Most atmospheric models treat radiation as a 1D process, creating biases called 3D radiative effects. Modeled shortwave 3D radiative effects are positive with the sun overhead (1D surface flux is artificially dim) and negative when the sun is near the horizon. Using a comprehensive sample of 3D radiative effects from shallow cumulus, deep convection, and stratocumulus LES cloud scenes, we decompose the 1D to 3D change in surface flux by cause: changes due to the amount of intercepted direct radiation and scattered light produced (cloud cover), changes due to the fate of scattered light (transmissivity), and changes due to their covariance. The decomposition reveals that cloud cover is the primary driver for how 3D cloud radiative effects change as the sun lowers. Using this framework, we develop a simple, quantitative model and find that the sign change is an inevitability: across all clouds scenes and the broader parameter space explored, 3D radiative effects always change from positive to negative as the sun lowers. The sign change occurs because transmissivity enhancement remains roughly constant with solar zenith angle while cloud cover expands super-linearly, causing diminishing positive effects to eventually be outpaced by growing negative effects. Higher cloud aspect ratios (defined height-to-width) accelerate this transition; higher initial coverage delays it due to cloud overlap. The model improves process-level understanding, revealing the importance of accurately representing how clouds interact with the direct beam.
How to cite: Powell, M., van Heerwaarden, C., Gentine, P., and Pincus, R.: How cloud geometry and solar zenith angle control 3D radiative effects, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1543, https://doi.org/10.5194/egusphere-egu26-1543, 2026.
Photosynthetically active radiation (PAR), the solar radiation absorbed by plants in the 380–710 nm wavelength range, represents a key component of the surface radiation budget and plays a central role in terrestrial carbon assimilation. Understanding long-term PAR variability is increasingly important in the context of regional climate change and shifts in radiative forcing that influence surface energy fluxes.
In Ukraine, routine PAR measurements are not performed due to the absence of standard instrumentation. Therefore, the quantification of PAR and the assessment of its multi-decadal variability require indirect reconstruction methods. This study develops a long-term PAR database for the warm season (April–October) using actinometric observations and the components of the surface radiation balance. Direct, diffuse, and total PAR were calculated using established conversion coefficients applied to measured shortwave radiation components. Spatial and temporal patterns were analysed using statistical and cartographic methods.
The primary study period is 1961–2020, complemented by several shorter sub-periods (1961–1990, 1991–2020, 1991–2000, 2001–2010, and 2011–2020) analysed comparatively to identify decadal and multi-decadal shifts in PAR components. Since the 1980s–1990s, consistent with global warming trends and associated radiative perturbations, the redistribution of solar radiation reaching the surface has been observed. These changes are linked to factors such as aerosol loadings, cloudiness variability, and large-scale circulation patterns, all of which affect the surface radiation budget.
Results indicate that direct, diffuse, and total PAR exhibit pronounced spatial gradients, increasing from western and northwestern regions, including the Ukrainian Carpathians, toward the Southern Steppe and Crimea. An increase in direct solar radiation during 2001–2010 relative to 1991–2000, and again in 2011–2020 relative to 1991–2000, resulted in marked increases in direct PAR. Conversely, declines in diffuse solar radiation resulted in reduced diffuse PAR, while heterogeneous changes in total shortwave radiation produced corresponding fluctuations in total PAR.
These findings highlight the sensitivity of PAR to long-term changes in the surface radiation budget and contribute to understanding how regional climate change is modifying the radiative environment that underpins terrestrial productivity.
How to cite: Savchuk, S., Rybchenko, L., Krakovska, S., Shpytal, T., Chyhareva, A., Kryshtop, L., and Balabukh, V.: Changes in Photosynthetically Active Radiation in Ukraine during 1961–2020 in the Context of Surface Radiation Budget Variability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2195, https://doi.org/10.5194/egusphere-egu26-2195, 2026.
Globally, hydropower is a leading source of renewable energy, however the hydroclimatic impact of the creation of hydroelectric reservoirs in northern regions is not well understood. The impoundment of hydroelectric reservoirs modifies the surface properties and the energy exchange between the earth’s surface and the atmosphere. In warm regions, due to the low albedo of water, most of the solar radiation is absorbed, and impoundment results in a positive radiative forcing. However, in cold regions, due to the presence of ice cover during several months of the year and the high albedos of snow and thick ice, the net annual radiative forcing may be negative. The magnitude of the negative radiative forcing depends on the pre-impoundment environment, as the vegetation type influences the albedo increase due to snow cover over terrestrial environments. A case study of the Romaine hydroelectric complex in Côte-Nord, Quebec (~51°N, ~63°W) is used to evaluate the net radiative forcing resulting from reservoir impoundment in the boreal region. Four-component radiometers are deployed during the open water periods on the Romaine-2 reservoir (2018-present) and year-round at two sites typical of the pre-impoundment environment, Lac Bernard (2022-present) and a forested site (2018-present). First, the radiative forcing is investigated through comparisons of in situ albedo measurements using the natural lake, Lac Bernard, and the primarily black spruce boreal forest site as proxies for post and pre-impoundment conditions. Preliminary results indicate an annual negative radiative forcing due to increased reflection during the ice cover period, as the seasonal variation of the midday albedo of the lake (~0.02 to ~0.8) is greater than that of the forest (~0.08 to ~0.2). The lake’s increased longwave emissions during the later part of the open water period also contributes to the negative radiative forcing. Second, the Canadian Small Lake Model, a 1D dynamic lake model, will be used to spatialize the analysis to the scale of the Romaine-2 reservoir and simulate the radiative forcing resulting from the impoundment under future climate conditions.
How to cite: Spearns, D., Thiboult, A., MacKay, M., Anctil, F., and Nadeau, D.: What is the net radiative forcing resulting from the impoundment of a hydroelectric reservoir in the boreal region? A case study of the Romaine Complex., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8279, https://doi.org/10.5194/egusphere-egu26-8279, 2026.
Peatland restoration has emerged as a key climate mitigation strategy due to its potential to reduce greenhouse gas emissions and improve ecosystem functioning. Beyond carbon cycling, restoration fundamentally alters surface energy partitioning and hydrological processes by modifying vegetation structure, water table dynamics, and surface-atmosphere exchanges. However, the extent to which rewetted peatlands in abandoned peat extraction areas differ from drained systems in terms of coupled energy and water balance dynamics remains poorly quantified, particularly under similar climatic forcing. Understanding these differences is essential for assessing the broader climatic and ecohydrological implications of peatland restoration. In this study, we compared the surface energy balance, water balance, and hydroclimatic controls at two contrasting peatlands in Estonia: Lavassaare, an abandoned drained peat extraction area, and Ess-soo, a recently rewetted site. Half-hourly radiation and turbulent flux measurements from 2024 were used to derive net radiation (Rn), sensible (H) and latent heat fluxes (LE), ground heat flux (G), evapotranspiration (ET), and potential evapotranspiration (PET). Monthly energy balance components exhibited strong seasonality at both sites, with LE dominating during the summer, while H increased during transitional dry periods. Annual ET totals were comparable between sites (449 mm at Ess-soo vs. 455 mm at Lavassaare), despite higher annual precipitation at Ess-soo (630 mm compared to 563 mm). As a result, Ess-soo exhibited a larger annual water surplus (P-ET = +181 mm), whereas Lavassaare operated closer to zero balance during the growing season. Hydroclimatic indices further revealed distinct functional regimes. Lavassaare showed consistently higher monthly dryness ratios (ET/P), reaching values near or above 1 during late spring, indicating temporary water limitation. In contrast, Ess-soo maintained lower ET/P values and a stronger water surplus throughout the year. Budyko analysis confirmed these patterns: Ess-soo occupied a more water-limited position (Φ = PET/P = 2.78; EI = ET/P = 0.71), whereas Lavassaare (Φ = 1.71; EI = 0.81) was closer to the energy-limited region of Budyko space. Together, these results demonstrate that the rewetted Ess-soo peatland maintains higher hydrological buffering capacity, while the abandoned Lavassaare site experiences stronger atmospheric demand relative to available water. The combined energy-water framework highlights the sensitivity of peatland surface-atmosphere exchanges to restoration status and provides a basis for understanding future ecosystem responses under changing climatic conditions.
How to cite: Yıldız, K., Wang, T., Pindus, M., and Kasak, K.: Contrasting Energy And Water Balance Regimes Between A Rewetted Peatland And An Abandoned Peat Extraction Area In Estonia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7093, https://doi.org/10.5194/egusphere-egu26-7093, 2026.
The global hydrologic cycle is a fundamental physical constraint on the atmospheric energy budget. On global scales, the net radiative cooling of the atmosphere (Ratm) must be balanced by the sum of latent heating by precipitation (P) and sensible heat flux (H), yielding the constraint: Ratm≈P+H. Despite the theoretical robustness of this equation, independent observations have historically failed to achieve exact closure, revealing a persistent residual imbalance that complicates the diagnostic use of the budget equation in physical studies.
To investigate this energy closure problem, we analyze three successive versions of the Global Precipitation Climatology Project (GPCP Versions 2.3, 3.2, and 3.3) in conjunction with the CERES data record for Ratm and the ERA5 Reanalysis for H. Although GPCP products were not developed with the explicit goal of energy budget closure, our findings reveal an unintended improvement in mean annual energy closure across these updates. The residual imbalance significantly decreases from v2.3 to v3.3, with the newest GPCP v3.3 product achieving the best mean closure, reconciling the budget to within 98%. This represents a substantial 10% improvement over the past two generations of precipitation products. Crucially, however, this improvement in the mean state is accompanied by a marked increase in the interannual variability of the residual anomalies. We hypothesize that this heightened anomaly variance is directly linked to localized adjustments in v3.3, specifically the enhanced precipitation magnitudes over the highly variable tropical Western Pacific oceanic region.
The finding that newer precipitation datasets unintentionally improve mean closure while simultaneously introducing variability in the temporal anomalies, presents a unique opportunity for physical diagnosis. This result necessitates a careful reassessment of how these global data products are utilized, particularly for studies of variability. This work provides critical observational context for understanding the partitioning of the global energy budget and highlights the imperative for continued efforts to reconcile independent satellite measurements of the Earth's energy and water cycles.
How to cite: Matus, A.: Understanding the Atmospheric Energy Budget using Global Precipitation Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4554, https://doi.org/10.5194/egusphere-egu26-4554, 2026.
The modern history of reliable Earth radiation budgets starts with the satellite era, notably be the iconic KT97 energy flow distribution. One of the cornerstone greenhouse data (“Back Radiation”, 324 Wm-2) was immediately challenged by Wild et al. (1998; 344 Wm-2). After a short interlude (TFK 2009), the magnitudes occupied their positions as we know them today in 2012. One of the pivotal studies (Stephens et al. 2012) displays both clear-sky and all-sky data in the longwave part. Today, in possession of the governing relationships (four Schwarzschild-type radiative transfer constraint equations) and their solution (as small integer ratios), we are able to reconstruct some moments in their build-up. In that work, first the exact integer positions at top-of-atmosphere (TOA) for clear-sky and all-sky outgoing LW radiation (OLR) were established: using the defined value of “Longwave cloud effect” (26.7±4 Wm-2) as the unit flux, “Clear-sky emission” was defined as 10 units (267.0 Wm-2), and “Outgoing longwave radiation” as 9 units (240.3 Wm-2). Then, a TOA imbalance of 0.6 Wm-2 was introduced; and, a reduction in OLR by the value of TOA imbalance was applied, to have the displayed values of clear-sky OLR as 266.4 Wm-2 and all-sky OLR as 239.7 Wm-2.
Wild (2020) implicitly contains the complete set of integer ratios, including the accurate albedo and greenhouse factor.
The same technique was used in the most recent comprehensive global energy budget depiction (Stephens et al. 2023, BAMS) based on 30 years of Gewex data. First, an accurate value for the longwave cloud radiative effect (LWCRE) was defined as 1 unit (26.682 Wm-2), then the exact integer positions for “Outgoing LW” (9 units, 240.14 Wm-2) and "Surface emission" (15 units, 400.24 Wm-2) were determined. Introducing an EEI of 0.54±0.3 Wm-2, a reduction in OLR and an increase in Surface emission by EEI was applied to get the displayed values of 239.5 Wm-2 and 400.7 Wm-2. TOA data were accurately tuned to the prescribed integer position of the albedo ("Reflected Solar"/"Incoming Solar" = 15/51 = 0.2941; 100.2/340.2 = 0.2945). Equation (3) [the all-sky version of the direct Schwarzschild-relationship Eq. (1), see Goody (1989), Stephens (1994) or Ramanathan (1995), for the net radiation at the surface RN(clear) = OLR(clear)/2 in the form of RN(all-sky) = (OLR(all-sky) – LWCRE)/2] is set to be valid with a difference of 0.1 Wm-2. Even the components of the convective flux (Sensible heat and Evaporation) were placed into integer multiple positions separately (compare to the ±9 Wm-2 noted ranges of uncertainty). Similarly, equation (4) for the total (SW+LW) absorbed radiation at the surface [which is the all-sky version of RT(clear)=2OLR(clear)] is valid again with the same difference (0.1 Wm-2). This required an accurate adjustment of its components. No reference to GHGs; the only numerical input parameter is Incoming Solar. This is our recent understanding of Earth's radiation budget.
The secret history of Earth radiation budget
Part 1: Data; Part 2: Theory
https://earthenergyflows.com/Secret_Data.mp4
https://earthenergyflows.com/Secret_Theory.mp4
https://ams.confex.com/ams/106ANNUAL/meetingapp.cgi/Paper/463675
AGU_GEWEX https://agu24.ipostersessions.com/default.aspx?s=26-E4-91-65-AE-83-5C-5E-2E-69-99-D2-1E-33-D1-A3&guestview=true
https://agu24.ipostersessions.com/default.aspx?s=68-C6-67-87-C2-9A-1F-66-64-57-17-86-DA-0F-9D-DC&guestview=true
https://agu25.ipostersessions.com/default.aspx?s=16-B9-40-EF-DB-A7-2A-53-AB-DC-27-A3-75-E9-A7-A3&guestview=true
https://agu25.ipostersessions.com/default.aspx?s=DE-FC-A0-F8-24-C6-C7-36-C9-6E-D9-82-42-3A-47-D1&guestview=true
https://ceres.larc.nasa.gov/documents/STM/2025-05/MP4files/30_Zagoni_EBAF-Thoery.mp4
https://earthenergyflows.com/Zagoni-EGU2024-Trenberths-Greenhouse-Geometry_Full-v03-480.mp4 (2:28:28)
https://ams.confex.com/ams/105ANNUAL/meetingapp.cgi/Paper/445222
https://ams.confex.com/ams/105ANNUAL/meetingapp.cgi/Paper/446389
How to cite: Zagoni, M.: The secret history of Earth's radiation budget, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16, https://doi.org/10.5194/egusphere-egu26-16, 2026.
The Earth’s energy imbalance (EEI), i.e. the difference between incoming solar radiation and outgoing reflected and emitted radiation, is the one quantity that ultimately controls the evolution of our climate system. Despite its importance, the exact magnitude of the energy imbalance is not well known, and because it is a small net difference of about 1 Wm−2 between two large fluxes (approximately 340 Wm−2), it is difficult to measure directly. There has recently been a renewed interest in using wide-field-of-view radiometers on board satellites to measure the outgoing radiation and hence deduce the global annual mean energy imbalance, for example as part of the EE12 candidate Earth Climate Observatory (ECO) mission.
A potential issue with wide-field-of-view radiometers, which has been the source of some concern, is the effect of anisotropic radiation, particularly anisotropic surface reflection of incoming sunlight. A wide-field-of-view radiometer does not distinguish the direction of incoming radiation, and earlier results have indicated that shortwave anisotropy could lead to substantial systematic biases in the global mean.
We simulate wide-field-of-view satellite measurements from satellites in polar, sun-synchronous and precessing orbits, as well as constellations of these orbits, and investigate how such measurements can be used to correctly determine the global annual mean imbalance. We present the results of ongoing work concerning different orbits, and how they affect the estimated global annual mean EEI, with a focus on e.g. the shortwave component and a comparison between isotropic and anisotropic shortwave reflection.
How to cite: Hocking, T., Megner, L., Hakuba, M. Z., Mauritsen, T., and Linder, B.: Sampling the Earth's energy imbalance with the Earth Climate Observatory (ECO) constellation - insights regarding shortwave anisotropy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17419, https://doi.org/10.5194/egusphere-egu26-17419, 2026.
The Earth’s Energy Imbalance (EEI) provides a measure of net energy accumulation in the climate system driven by human emissions. The cryosphere plays an important role by absorbing energy primarily through phase change associated with the melt of glaciers, ice sheets, and sea ice. Land-based ice melt is, together with thermal expansion, the major contributor to global mean sea level rise. Recent Earth Heat Inventory estimates suggest that the cryosphere contributed to approximately 4% of total heat uptake over the period 1960-2020, mostly via latent heat of fusion required to convert ice to water.
However, the total heat uptake from the cryosphere term remains uncertain due to heterogeneous data coverage, methodological inconsistencies, and incomplete accounting of some cryospheric processes. In particular, observational constraints differ strongly between glaciers, ice sheets, and sea ice, and not all relevant energy pathways have been consistently quantified in previous efforts. These current limitations hamper robust annual updates needed for operational climate indicator efforts such as the Indicators of Global Climate Change and will likely become increasingly relevant for future assessments (e.g., for upcoming IPCC AR7).
Here, we outline a framework to update the cryospheric heat uptake by compiling and harmonizing the latest observational datasets on cryosphere change, converting mass and volume losses into energetic equivalents, and assessing uncertainty propagation and methodological sensitivity. Additionally, we also explore how cryosphere heat uptake may change in the future. As such, this work aims to refine the cryospheric contribution to the EEI, clarify its temporal evolution, and improve consistency between observational and model-based global energy budget estimates.
How to cite: Zekollari, H., Van Tricht, L., and von Schuckmann, K.: Towards Reassessing the Cryosphere Contribution to Earth’s Energy Imbalance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3342, https://doi.org/10.5194/egusphere-egu26-3342, 2026.
The Arctic region is experiencing the most rapid warming on earth, significantly perturbing its surface ecosystems and energy balance. Accurately quantifying the Arctic surface radiation budget, particularly the shortwave component, is critical for understanding both regional climate change and the global energy budget. Despite ongoing advances in observational technologies and analytical methods, uncertainty in cloud fraction (CF) exerts a dominant control on the accuracy of surface shortwave radiation (SW) estimation. Existing studies indicate that Arctic clouds are dominated by low-level ice-phase and mixed-phase clouds. Daytime cloud fraction peaks in September and reaches a minimum in April, and is generally higher over ocean than over land. Most datasets suggest an overall increase in total Arctic cloudiness. However, substantial disagreements persist regarding trend magnitude, seasonal dependence, and contributions from different vertical layers, leading to SW differences of approximately 20–70 W m⁻². These discrepancies primarily arise from inconsistent CF definitions and spatiotemporal scales, sensors and sampling geometry differences, cross-calibration and processing biases, cloud detection and phase- discrimination errors over bright surfaces and during polar night, and valuation uncertainty arising from sparse and non-uniform ground-based references. Consequently, existing Arctic SW products still fall short of the requirements for energy-budget closure and climatological applications. This study synthesizes recent advances in understanding Arctic cloud fraction and its critical impact on surface SW, highlights the principal challenges, and outlines promising future research avenues. This endeavor aims to furnish a clearer scientific foundation for improving predictions of polar and global radiative energy dynamics and climate change.
How to cite: Liu, X. and He, T.: Understanding the Impact of Arctic Cloud Fraction on Surface Shortwave Radiation: Recent Progress, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8776, https://doi.org/10.5194/egusphere-egu26-8776, 2026.
The Antarctic Peninsula has undergone exceptional warming, triggering major changes in sea ice extent in the Bellingshausen and Weddell Seas and modifying the regional radiation and atmospheric energy balance. Understanding and representing air-sea-ice interaction processes remains a fundamental requirement for reliably projecting future climate change in the ice-covered Southern Ocean and its implications beyond the polar regions. As part of the SURFEIT (Surface Fluxes in Antarctica) project, airborne observations of turbulent fluxes, long and shortwave radiation, and surface characteristics are analysed to assess the role of sea ice, leads, and coastal polynyas in shaping the Antarctic atmospheric boundary layer and its radiation and energy balance. The analysis shows that variations in sea ice parameters, including albedo, temperature, and ice concentration, significantly influence both the surface energy budget and atmospheric boundary layer development. In austral summer conditions, radiative terms dominate the surface energy balance in sea-ice-covered regions, with turbulent sensible and latent heat fluxes playing a secondary role. Under warm air advection and Föhn events in the Weddell Sea, leads and polynyas exhibit an oasis effect marked by a negative Bowen ratio, consistent with enhanced snow and ice melting. Conversely, cold air advection results in positive Bowen ratio and sea ice production. The sum of sensible and latent heat fluxes (compensation fluxes) alternates between positive and negative values. In cold-air situations, variability in net radiation is compensated by turbulent fluxes, revealing a negative feedback mechanism, while such compensation breaks down under warm-air conditions. Using the observational data, we evaluated parameterizations of energy budget components and surface albedo, deriving effective atmospheric parameters needed for bulk-flux parameterisations in numerical models and for the validation of satellite and model outputs.
How to cite: Weiss, A.: The radiation and energy budget over Antarctic Sea Ice: Insights from the SURFEIT Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9729, https://doi.org/10.5194/egusphere-egu26-9729, 2026.
Explicit 3D radiative transfer captures the complex spatial variability of global horizontal irradiance (GHI) under shallow cumulus clouds, but is computationally prohibitive for real-time operational use. We address this by introducing a simulation-to-reality framework that emulates 3D radiative transfer via a neural network trained on synthetic data to translate multi-view all-sky imagery into 2D GHI maps. To produce the training data, we ran large eddy simulations at 50 m horizontal resolution for 10 selected cloud dynamic days (April to July 2022) over a 14 km x 14 km domain. The resulting cloud fields were coupled with Monte Carlo ray tracing to render synthetic all-sky images from virtual camera locations matching the Eye2Sky camera network and to compute the corresponding GHI maps. Two datasets are generated, (1) raw synthetic renderings and (2) enhanced renderings with camera-specific characteristics from the real-world. Identical image-to-image neural networks are trained on these datasets and applied to real Eye2Sky imagery, with predicted GHI maps validated against co-located pyranometers. By incorporating sensor-specific characteristics, we quantify the benefit of reducing the simulation-to-reality gap and assess whether synthetic pre-training using neural network emulations can support operational solar irradiance mapping as an alternative to computationally expensive physical simulations.
How to cite: Aragon Cerecedes, M., Saint-Drenan, Y.-M., Eissa, Y., Blanc, P., Veerman, M., van Heerwaarden, C., and Schmidt, T.: Spatial solar irradiance emulation of Monte Carlo ray tracing with multi-view all-sky imagery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13181, https://doi.org/10.5194/egusphere-egu26-13181, 2026.
The Earth’s energy budget heavily depends on the cloud radiative effect (CRE). A common approach to determine the top-of-atmosphere broadband radiative fluxes in cloudy conditions is their calculation from derived cloud properties, primarily optical thickness (COT) and effective radius (CER), which can be retrieved from passive satellite observations. In many operational retrieval algorithms simplifying 1d assumptions such as the independent pixel approximation are applied. However, accounting for 3d cloud effects is important for correctly determining the CRE and thus the Earth’s energy budget.
In our project we use the 3d Monte Carlo radiative transfer model MYSTIC in order to compare synthetic satellite radiances based on 1d or full 3d calculations. We present results for three case studies with different cloud types for which we derive COT and CER from these synthetic satellite radiances and then derive the corresponding broadband fluxes. Evaluating the derived cloud properties and broadband fluxes allows for estimating for which cloud types and viewing/illumination conditions 3d effects are more relevant and thus pose more problems for satellite-based estimates of the CRE when following the given approach. This will help us in developing strategies to better account for 3d effects and thus to potentially improve the determination of the CRE using satellite data. Our preliminary results indicate that the differences between 1d and 3d radiances and thus cloud properties and broadband fluxes are larger for cumulus clouds than for low, stratiform clouds, i.e., 3d effects are more relevant for these cases.
This work is part of the Research Unit named C3SAR (Cloud 3D Structure and Radiation, www.c3sar.de) funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), in which cloud modelling, radiative transfer as well as ground and satellite observations are complementary components for assessing the role of 3d cloud variability in estimating the Earth’s energy budget.
How to cite: Kunkel, T., Stengel, M., Wagner, J. K., Senf, F., and Mayer, B.: Assessing the impact of 3d cloud structures on broadband fluxes derived from synthetic satellite radiances, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10955, https://doi.org/10.5194/egusphere-egu26-10955, 2026.
Clouds exert a fundamental control over the Earth’s radiative balance by modulating both incoming shortwave solar radiation and outgoing longwave terrestrial radiation, resulting in a net radiative cooling of approximately 19 Wm-2. In contrast to well-mixed greenhouse gases such as CO2 and methane, the radiative impact of clouds exhibits strong spatial and temporal variability, making it intrinsically difficult to quantify and one of the dominant sources of uncertainty in contemporary climate models.
This study addresses a complementary and often overlooked aspect of this problem: the cloud–clear-sky interface, characterized by a continuous transition between cloudy and cloud-free conditions. Due to this gradual transition, defining the boundaries of a cloud region is not straightforward and depends strongly on the observational context. In numerical models, clouds are typically defined using relative humidity thresholds, whereas satellite-based cloud detection relies on radiance thresholds that vary across spectral bands.
Here, we analyze ground-based thermal infrared imagery (10–12 µm) by comparing observations with modeled clear-sky radiances. Using radiance exceedances relative to clear-sky emission, we quantify the radiative effect associated with the cloud–clear-sky transition. A preliminary analysis based on a limited subset of the available dataset indicates that the selection of cloud spectral radiance thresholds can lead to differences of approximately 0.4 Wm-2µm-1 when compared with definitions that classify clouds only under high-confidence conditions. A comprehensive analysis will be completed prior to the conference.
The data were collected at four distinct sites: the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory in Oklahoma, USA; the Federal University of São Paulo (UNIFESP), Diadema campus, located in the metropolitan region of São Paulo, Brazil; and two sites in the Amazon region—Amazonas State University (UEA), Escola Normal Superior, near downtown Manaus, Brazil, and Embrapa Amazônia Ocidental, situated in a rural area of Manaus. Measurements conducted in the Amazon region are part of the project “Measurements of cloud properties relevant to improving the prediction of intense rainfall in Manaus”, funded by Fundação de Amparo à Pesquisa do Estado do Amazonas (FAPEAM).
How to cite: Hack, E., Max Furtunato Maia, J., Klebe, D., Augusto Ferreira de Souza, R., Monteiro de Souza, J., Araújo Pereira, K., Medeiros de Oliveira, C., and Pauliquevis, T.: Quantifying radiative effects of the cloud–clear-sky transition using ground-based infrared imagery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13929, https://doi.org/10.5194/egusphere-egu26-13929, 2026.
Understanding climate-relevant radiative processes requires radiation-transfer tools that balance physical fidelity, computational efficiency, and interpretability. Existing approaches span a broad but sparse hierarchy: idealized models miss key radiative processes, operational schemes trade physical tractability for accuracy and efficiency, and although line-by-line models are physically accurate, their computational cost prohibits direct coupling to Earth system models. This leaves a critical gap for models that are physically tractable, asymptotically convergent, and efficient.
We investigate alternative representations of gas absorption, a key component for clear-sky radiation transfer. Using simple functional forms per frequency, we represent the pressure–temperature scaling of absorption. Absorption cross sections, radiative fluxes, and heating rates are evaluated for representative atmospheric profiles and compared against a benchmark line-by-line reference model. We show that these functional forms can reproduce the pressure–temperature dependence of gas absorption, thus replacing large multidimensional lookup tables. Combined with monochromatic spectral quadrature points (Czarnecki et al., 2023), this approach will enable highly efficient, physically tractable gas absorption calculations in climate models.
How to cite: Hegde, R. and Buehler, S. A.: Simple functional representations of gas absorption for efficient climate model radiation schemes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17592, https://doi.org/10.5194/egusphere-egu26-17592, 2026.
NASA’s Fast Longwave And SHortwave radiative Flux (FLASHFlux) project aims to generate low-latency operational global surface and top-of-atmosphere radiative flux data within one week of initial satellite measurements. The surface radiation budget is crucial for modulating and improving our understanding of many atmospheric, oceanic and land surface processes within the Earth system. The top-of-atmosphere (TOA) radiation budget is a key radiative forcing in the climate system. NASA’s Clouds and Earth's Radiant Energy System (CERES) is currently producing global radiation data using world-class satellite measurements. While CERES’s radiative flux products are of extremely high quality and accuracy, extensive data processing and months of validation are required to ensure their high accuracy before releasing climate-quality data. CERES data is typically released ~3 months after measurement acquisition. However, many users desire access to CERES data on a near real-time basis.
The FLASHFlux project provides a valuable resource for users who require near real-time global and regional radiative flux data. To improve efficiency, FLASHFlux has demonstrated its ability to generate high-quality radiative fluxes within a week of initial measurements while maintaining a certain level of accuracy using a simplified temporal extrapolation for CERES instrument calibration. FLASHFlux data provides daily average fluxes originally using both Terra and Aqua MODIS imagers and CERES measures. However, now FLASHFlux only uses measurements from NOAA-20 satellite VIIRS and MODIS instruments. FLASHFlux’s existing algorithms utilize meteorological and surface data from the Goddard Earth Observing System Instrument Team reanalysis (GEOS-IT), a parameterized radiative algorithm for inferring surface radiative fluxes, and a diurnal variation model for temporal interpolation to compute estimates of the daily averaged radiative fluxes gridded to 1x1 degrees. To increase the diurnal sampling of clouds and improve the flux products, FLASHFlux data will leverage NASA Langley’s SatCORPS (Satellite ClOud and Radiation retrieval System) hourly Global Cloud Composite (GCC) data. SatCORPS GCC is a comprehensive algorithm designed to obtain high spatiotemporal resolution global cloud information fusing imagery data from operational geostationary and polar-orbiting meteorological satellites. Cloud, atmospheric and surface data are integrated into the NASA Langley CERES version of radiative transfer model to calculate radiative fluxes at the surface and TOA. FLASHFlux will generate a global hourly gridded radiative flux product with an initial resolution of 1°x1°, which will be increased to 0.5°x0.5° in future versions to meet the needs of users requiring near-real-time radiative flux data. An overview of progress towards promoting this new operation system and the resulting radiative fluxes are described. Comparisons against formal CERES Ed4.2 SYN1Deg data products, current FLASHFlux products and limited sets of surface observations are presented where possible.
How to cite: Chang, F.-L., Stackhouse, P., Sawaengphokhai, P., Gopalan, A., Smith, W., Doelling, D., and Shan, B.: Deriving Hourly Synoptic FLASHFlux High-Resolution Low-Latency Global Radiative Fluxes Using NASA Langley SatCORPS Global Cloud Composite Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14671, https://doi.org/10.5194/egusphere-egu26-14671, 2026.
The radiative fluxes at the surface and at the top-of-the-atmosphere are key components of the Earth energy budget. In addition, the surface fluxes, in particular the surface solar radiation fluxes, are of high relevance for practical applications., e.g., for the planning and the monitoring of solar power systems. Data records often were designed for a certain application area like climate analyses or renewable energy, but their successful usage in a wide range of application and research areas underline their various benefits.
Three satellite-based radiation data records are available from the CM SAF: CLARA, SARAH, and HANNA. These data records provide global daily information of the surface and the top-of-the-atmosphere radiation (CLARA-A3) as well as regional high resolution (space and time) data of the surface radiation (SARAH-3, HANNA) serving climate, solar energy, and other applications.
Here we will present the three CM SAF data records and compare their suitability for certain applications. While the global CLARA data record allows the assessment of larger-scale / global phenomena incl. the surface and the top-of-the-atmosphere radiation, the SARAH and the HANNA data records allows analysis of surface irradiance at smaller spatial and temporal scales.
How to cite: Trentmann, J. and Pfeifroth, U.: Assessing changes and variability of surface and top-of-the-atmosphere shortwave and longwave radiation with satellite data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7194, https://doi.org/10.5194/egusphere-egu26-7194, 2026.
The Global Energy Balance Archive (GEBA) is an international data center for worldwide measurements of energy fluxes at the Earth’s surface, maintained at ETH Zurich (https://geba.ethz.ch). The mission of GEBA is to compile all accessible sources of directly measured surface energy fluxes into a central data archive. GEBA has been continuously expanded and updated and currently contains around 700,000 monthly mean records of various surface energy balance components measured at approximately 2,700 locations worldwide. By far the most widely represented quantity is surface shortwave irradiance, also known as global radiation. Many of the historical records of this quantity stored in GEBA extend over multiple decades, with the longest record (Stockholm) dating back to 1927.
For nearly 35 years, since its opening to the internet in the early 1990s, GEBA has served the international scientific community and is well established as a major data source for measured surface energy fluxes. GEBA data have been used in numerous publications in leading peer-reviewed journals, including Nature and Science. GEBA has played a key role in a wide range of research applications, for example in quantifying the global energy balance as presented in the 5th and 6th IPCC Assessment Reports, and in the detection of pronounced multi-decadal variations in surface solar radiation, known as “global dimming” and “brightening”. GEBA is also widely used as a reference for the evaluation of climate models, reanalyses, and satellite-derived products. On a more applied level, GEBA data are becoming increasingly important for the planning and management of solar power capacities in support of the net-zero emissions target for 2050.
Beyond regular data updates and the acquisition of new datasets, current developments focus on the introduction of a versioning system to enable a traceable documentation of the GEBA data status, as well as on the application of quality-control procedures developed at DWD/CMSAF. In particular, homogeneity tests are foreseen to detect outliers, inhomogeneities and breakpoints in the GEBA station time series data based on comparisons with multiple independent satellite-derived and reanalysis estimates (e.g., SARAH-3, CLARA-A3, and ERA5).
Since 2019, GEBA has been co-funded by the Federal Office of Meteorology and Climatology MeteoSwiss within the framework of GCOS Switzerland.
How to cite: Wild, M., Smith, P., Sedlacek, J., Trentmann, J., and Pfeifroth, U.: Current status of the Global Energy Balance Archive (GEBA), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5470, https://doi.org/10.5194/egusphere-egu26-5470, 2026.
Brown carbon (BrC) is a major organic carbonaceous aerosol fraction distinguished by its light absorption attribute, which potentially alters Earth’s radiative budget. Dark brown carbon, commonly referred to as Tar Balls (TBs), exhibits markedly stronger light absorption compared to other BrC fractions. TBs are well recognized in wildfire emissions, but their occurrence remains inadequately explored and characterized from other emission sources. This work examines the presence of strongly light-attenuating TBs in the Indo-Gangetic Plain (IGP), a globally identified air-pollution hotspot heavily influenced by biomass burning, particularly crop-residue fires post harvest.
The study encompasses three strategically selected sites across the Western, Central, and Eastern IGP, where simultaneous sampling was conducted during the early post-monsoon period. This was followed by further examination of the prevalence and occurrence patterns of TB particles, and the associated morphological and physicochemical traits using Scanning electron microscopy (SEM) and Transmission Electron Microscopy (TEM), alongside assessing the sources of PM2.5 pollution at each site using PMF model.
The TB-to-soot aggregate ratio, representing TB number concentration, increased from 0.85 in the Western IGP to 1.35 in the Central IGP. The results underscore that distinct regional particle profiles are consistent with prevailing primary and secondary pollution sources at the two sites, respectively. TB particles were scarcely detected at the Eastern IGP site, dominated by urban emissions during the study period, suggesting that their origin is primarily linked to biomass-burning. Overall, the TB number fraction in this study at Western and Central IGP, which is potentially driven by crop residue burning, was 15 times lower than previously reported for wildfire-derived TBs. TB chemistry varied spatially, with fresh biomass-derived TB particles at the Western IGP showing a higher C/O ratio of 3.60, while aged ones at the Central IGP exhibited a lower C/O ratio of 2.59. This study reported a notably lower C/O ratio and higher Nitrogen concentrations for the TBs as compared to extensively studied wildfire-derived TBs documented in past, with the ratio reaching values as high as 20–25.
The findings indicate pronounced variability in TB traits based on emission source, emphasizing the necessity of comprehensive, source-specific TB assessments across all potential origins accompanied by a thorough characterization of optical parameters to reduce uncertainties in radiative forcing effect estimates.
How to cite: Thapliyal, P. and Gupta, T.: Dark Brown Carbon over the Indo-Gangetic Plain: An Overlooked Yet Major Driver of Regional Radiative Forcing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-409, https://doi.org/10.5194/egusphere-egu26-409, 2026.
This study examines long-term trends in aerosol loading, chemical composition, and radiative effects over the northern Indian Ocean using the Maldives Climate Observatory at Hanimaadhoo (MCOH) as a receptor site for South Asian outflow. Nearly two decades (2004–2025) of in situ measurements, satellite observations, and reanalysis products are combined to assess changes in aerosol optical depth (AOD), surface solar radiation, sulfate aerosol concentrations, and associated climate-relevant feedback. AERONET observations at MCOH show a mean AOD of 0.30 ± 0.09 with a near-zero long-term trend (0.0017 ± 0.01 decade⁻¹), consistent with MODIS satellite estimates. Seasonal AOD exhibits modest increases during winter, pre-monsoon, and post-monsoon periods, and a slight decline during the monsoon. Clear-sky pyranometer measurements indicate a weak but persistent decline in surface-reaching global shortwave radiation (−3.0 ± 2.3 W m⁻²; −1.4%), consistent with regional dimming trends from MERRA-2 reanalysis (−1.6 ± 0.7 W m⁻² decade⁻¹), with the strongest dimming occurring during the pre-monsoon season. Concurrently, column-integrated water vapour increases significantly (+0.19 ± 0.07 cm decade⁻¹), suggesting potential feedback that may enhance atmospheric warming. Filter-based chemical analyses from 2006 to 2025 reveal a persistent long-term increase in sulfate aerosols concentrations (0.25 ± 0.05 µg m⁻³ yr⁻¹). Sulfate aerosols a major secondary pollutant derived from SO₂ emissions play an important role in climate-cooling agent through the scattering of solar radiation. Despite rapid socio-economic development across South Asia, emission control measures have been effective over the long term in reducing the magnitude of the increasing trend to about half of that observed in the first decade. Together, these results highlight the complexity of aerosol–radiation–water vapour interactions and emphasize the need for both sustained long-term observations and improved modelling to better constrain climate impacts of air pollution in the South Asian region.
How to cite: Remani, M., Clarke, S., Nair, H., Budhavant, K., Krishnakumari, S., and Gustafsson, Ö.: Decadal-Scale Observations of the Impact of South Asian Pollution Outflow on the Radiation over the Northern Indian Ocean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21756, https://doi.org/10.5194/egusphere-egu26-21756, 2026.
