George Tselioudis

This study analyzes the trend in Absorbed Shortwave Radiation (ASR) in the North Pacific, where an increasing ASR trend of 3.31 W/m2/dec is observed, constituting the dominant regional contributor to the global ASR increase. Multiple regression analysis shows that 1.57 W/m2/dec (47.5%) of that trend is explained by changes in cloud fraction, 1.08 W/m2/dec (32.7%) by changes in cloud optical thickness, and 0.61 W/m2/dec (18.3%) by changes in aerosol optical depth indicative of the aerosol direct effect. The pattern of cloud fraction change shows two distinct regimes: one dominated by decreases in high and middle clouds and a second dominated by decreases in low clouds. The cloud fraction contribution to the ASR trend can be broken then into a 0.88 W/m2/dec contribution from high and middle cloud fraction changes and a 0.73 W/m2/dec contribution from low cloud fraction changes. Analysis incorporating cloud controlling factors shows that the high/middle cloud fraction changes are driven by atmospheric dynamics and thermodynamics, while the low cloud fraction and optical thickness changes are driven by sea surface warming and aerosol indirect effects. High/middle cloud fraction decreases correlate with a poleward shift in the N. Pacific midlatitude storm track, pointing to a potential positive cloud feedback loop between Sea Surface Temperature increase and a poleward shift of the midlatitude storm track, mediated by the reduction in high/middle cloud fraction.

Cloud processes constitute one of the key uncertainties for climate change projections. The fourth iteration of the Cloud Feedback Model Intercomparison Project, CFMIP4, contributes to the Coupled Model Intercomparison Project phase 7 (CMIP7), by providing a set of global climate model experiments aiming to enhance our understanding of clouds, circulation and climate sensitivity, thereby informing improved projections of future climate change. CFMIP4 targets four knowledge gaps: (1) Physical mechanisms of cloud feedback and adjustment; (2) Dependence of cloud feedback and adjustment on climate base state and on the nature of the forcing; (3) Coupled mechanisms of the sea-surface temperature “pattern effect”; and (4) Coupling of clouds with circulation and precipitation. CFMIP4 contributes four CMIP7 Assessment Fast Track experiments that are central to the quantification of climate feedback and sensitivity in past, present and future climates, essential for process understanding and model evaluation. Furthermore, CFMIP4 supports the joint analysis of models and observations through a data request that includes process and satellite simulator output.

The Mediterranean region has experienced a well-documented decline in precipitation over recent decades, yet the role of cloud regimes in shaping this trend remains underexplored. This study utilizes the ISCCP-H (International Satellite Cloud Climatology Project) Weather States (WSs) classification to examine cloud regimes and their relationship with precipitation using TRMM (Tropical Rainfall Measuring Mission) data from 1998 to 2016. Cloud systems are categorized into eight distinct WSs, providing a physically grounded framework for assessing rainfall variability. The results indicate that deep convective (WS1) and frontal (WS2) regimes dominate precipitation patterns, with WS1 driving extreme rainfall and WS2 exhibiting the highest number of precipitation events. Long-term trends reveal that the observed decline in precipitation is primarily driven by a significant reduction in WS2-related precipitation frequency, particularly in moderate and heavy rainfall events, suggesting a decline in frontal system penetration. Additionally, a marked decrease in WS1 precipitation intensity signals a weakening of deep convective processes. These results are consistent with previous station-based and satellite studies reporting a widespread decline in Mediterranean precipitation, while extending them by attributing this decline to changes in precipitation characteristics within specific cloud regimes. This cloud-regime perspective offers a physically interpretable framework for assessing precipitation changes and for evaluating the representation of key precipitation-bearing regimes in climate models.

Recently, satellite observations were successfully used to constrain and quantify uncertainty in the NASA GISS ModelE Earth system model; the development and successful application of this machine-learning accelerated Bayesian parameter estimation approach has been mirrored by similar developments at Earth system modeling centers worldwide. The result of this enterprise yields what we label a "CPE": a Calibrated Physics Ensemble. It is differentiated from Perturbed Parameter Ensembles in that it contains only observationally plausible parameter and model configurations. We comment on the previous CPE, as well as the next generation of ModelE CPEs, being prepared for CMIP7. We also present a critical application of the CPE methodology towards quantifying observational information content in a method analogous to an Observing System Simulation Experiment (OSSE). In contrast to traditional data-assimilation based OSSEs, our approach quantifies the uncertainties most relevant for climatic projections and impact assessments: model physics uncertainties. We demonstrate a proof of concept focusing on the value of reduced uncertainty in PBL water vapor retrievals, toward supporting design for a future NASA Planetary Boundary Layer satellite mission currently in incubation.

Precipitation over the Mediterranean is strongly modulated by large-scale circulation and cloud-regime variability, posing persistent challenges for climate model evaluation. Standard model assessments based on aggregated precipitation metrics often mask regime-dependent errors and limit physical interpretability. Here, we present a Weather-State(WS)-based framework for evaluating Mediterranean precipitation in climate models, combining satellite observations with model simulations in a physically consistent manner.Daily precipitation from the TRMM dataset (1998-2016) is analyzed together with cloud-regime information derived from ISCCP-based Weather States. The evaluation focuses on historical simulations from CMIP climate models over the Mediterranean (30°–45°N, 10°W–40°E). As a baseline, model-observation differences in total precipitation, precipitation intensity and precipitation frequency are first assessed to identify large-scale discrepancies. WS-conditioned diagnostics are then used as a complementary layer to examine precipitation characteristics within dynamically coherent regimes.Within this framework, precipitation frequency, intensity, and spatial structure are evaluated conditional on WS occurrence, allowing regime-dependent behavior to be compared across models and observations while reducing the influence of regime mixing inherent in climatological metrics. The analysis further quantifies the contribution of individual WSs to total precipitation and examines the consistency of WS-dependent patterns and trends across models.The analysis highlights the role of Weather-State-conditioned diagnostics in structuring model evaluation and enabling physically consistent comparison in structuring model evaluation and enabling physical comparison of precipitation characteristics across regimes, supporting improved understanding of model behavior without reliance on fixed assumptions about future change.

Cloud processes constitute one of the key uncertainties for climate change projections. The fourth iteration of the Cloud Feedback Model Intercomparison Project, CFMIP4, contributes to the Coupled Model Intercomparison Project phase 7 (CMIP7), by providing a set of global climate model experiments aiming to enhance our understanding of clouds, circulation and climate sensitivity, thereby informing improved projections of future climate change. CFMIP4 targets four knowledge gaps: (1) Physical mechanisms of cloud feedback and adjustment; (2) Dependence of cloud feedback and adjustment on climate base state and on the nature of the forcing; (3) Coupled mechanisms of the sea-surface temperature "pattern effect"; and (4) Coupling of clouds with circulation and precipitation. CFMIP4 contributes four CMIP7 Assessment Fast Track experiments that are central to the quantification of climate feedback and sensitivity in past, present and future climates, essential for process understanding and model evaluation. Furthermore, CFMIP4 supports the joint analysis of models and observations through a data request that includes process and satellite simulator output.

Cloud processes constitute one of the key uncertainties for climate change projections. The fourth iteration of the Cloud Feedback Model Intercomparison Project, CFMIP4, contributes to the Coupled Model Intercomparison Project phase 7 (CMIP7), by providing a set of global climate model experiments aiming to enhance our understanding of clouds, circulation and climate sensitivity, thereby informing improved projections of future climate change. CFMIP4 targets four knowledge gaps: (1) Physical mechanisms of cloud feedback and adjustment; (2) Dependence of cloud feedback and adjustment on climate base state and on the nature of the forcing; (3) Coupled mechanisms of the sea-surface temperature "pattern effect"; and (4) Coupling of clouds with circulation and precipitation. CFMIP4 contributes four CMIP7 Assessment Fast Track experiments that are central to the quantification of climate feedback and sensitivity in past, present and future climates, essential for process understanding and model evaluation. Furthermore, CFMIP4 supports the joint analysis of models and observations through a data request that includes process and satellite simulator output.

Cloud processes constitute one of the key uncertainties for climate change projections. The fourth iteration of the Cloud Feedback Model Intercomparison Project, CFMIP4, contributes to the Coupled Model Intercomparison Project phase 7 (CMIP7), by providing a set of global climate model experiments aiming to enhance our understanding of clouds, circulation and climate sensitivity, thereby informing improved projections of future climate change. CFMIP4 targets four knowledge gaps: (1) Physical mechanisms of cloud feedback and adjustment; (2) Dependence of cloud feedback and adjustment on climate base state and on the nature of the forcing; (3) Coupled mechanisms of the sea-surface temperature "pattern effect"; and (4) Coupling of clouds with circulation and precipitation. CFMIP4 contributes four CMIP7 Assessment Fast Track experiments that are central to the quantification of climate feedback and sensitivity in past, present and future climates, essential for process understanding and model evaluation. Furthermore, CFMIP4 supports the joint analysis of models and observations through a data request that includes process and satellite simulator output.

Recent Earth energy budget observations show an increase in the sunlight absorbed by the Earth of 0.45 W/m ² per decade, caused primarily by a decrease in cloud reflection. Here we decompose the solar radiative budget trends into general circulation and cloud controlling process components. Regimes representing the midlatitude and tropical storm zones are defined, and the trends in the areal coverage of those regimes which are potentially induced by circulation changes are separated from trends in the cloud radiative effect within each regime which are potentially induced by changes in local cloud controlling processes. The regime area change component, which manifests itself as a contraction of the midlatitude and tropical storm regimes, constitutes the largest contribution to the solar absorption trend, causing decreased sunlight reflection of 0.37 W/m ² per decade. This result provides a crucial missing piece in the puzzle of the 21st century increase of the Earth's solar absorption.