@article{21013, abstract = {We have addressed convective self‐aggregation (CSA) in steady and oscillating sea surface temperature (SST) and solar radiation (SOLIN) cloud‐resolving model simulations in a non‐rotating radiative‐convective equilibrium (RCE) framework. Our experiment designs are motivated by land‐ocean heterogeneity of atmospheric convection. The steady and oscillating forcings are idealizations of ocean and land conditions, respectively, based on their differences in heat capacities. In both kinds of simulations, the diurnal mean SST and SOLIN are the same, and both SST and SOLIN are only varied in time (i.e., they are spatially homogeneous at any given time). We find that diurnally oscillating forcing accelerates CSA. Stronger long‐wave cooling in dry regions at night and during the warm SST phase (late afternoon) both allow the long‐wave feedback, known to favor aggregation, to intensify compared to steady forcing simulations. In addition to the long‐wave, reduced short‐wave warming in dry regions (during the day) further enhances radiative cooling there compared to moist regions. Overall, the radiative cooling is enhanced in dry regions compared to neighboring moist convective regions. A dry subsidence is driven by this net radiative (short‐wave plus long‐wave) cooling, consistent with earlier work on CSA. Stronger radiative cooling allows stronger subsidence which allows low‐level circulation to more efficiently transport moisture and energy up‐gradient, driving convection to aggregate faster. We also note a sensitivity of our experimental setup to initial conditions, more so at warmer SST. This stochastic behavior might be critical in reconciling the differences of opinion regarding the response of convection aggregation to oscillating SST forcing.}, author = {GOSWAMI, BIDYUT B and Lu, Ziyin and Muller, Caroline J}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {1}, publisher = {Wiley}, title = {{Convective self‐aggregation in diurnally oscillating sea surface temperature and solar forcing experiments}}, doi = {10.1029/2024ms004576}, volume = {18}, year = {2026}, } @article{21035, abstract = {According to the scientific consensus, tropical convection must decrease with global warming. This decrease is manifested by a decrease of the mass transported in the upward branch of the atmospheric overturning circulation – the convective mass flux – and a connected decrease of high clouds in the tropics, with implications for climate sensitivity. By using kilometer-scale simulations in radiative-convective equilibrium and a convective tracking algorithm, we show that no such decrease occurs in storms when taken individually and that the mass transport per storm increases instead. Storms can achieve this result by aggregating more surface of the convective cores – the inner part of the storm doing the vertical transport – so that the decrease of tropical convection is actually explained by a decrease in the total number of storms. There is little variation of the mean pressure velocity in the cores of the storms, a robust finding of this study. This remarkable invariance of the mean pressure velocity points to an emerging property of convection that should receive more attention in future studies.}, author = {Bolot, Maximilien and Roca, Rémy and Fiolleau, Thomas and Muller, Caroline J}, issn = {2397-3722}, journal = {npj Climate and Atmospheric Science}, publisher = {Springer Nature}, title = {{No decrease of tropical convection in individual deep convective systems with global warming}}, doi = {10.1038/s41612-025-01285-5}, volume = {9}, year = {2026}, } @article{21164, abstract = {Global emission inventories often fail to capture the complexities of vehicular pollution in regions with unique fuel mixes, such as Brazil’s extensive biofuel use, leading to significant uncertainties in atmospheric modeling. This study presents a century-long (1960–2100) bottom-up vehicular emission inventory for Brazil, leveraging locally derived emission factors. Our estimates reveal substantial discrepancies in magnitude, timing, and speciation of non-CO2 pollutants (CO, NMHC, PM2.5) compared to leading global inventories (EDGAR, CEDS, CAMS), highlighting critical inaccuracies in widely used data sets. More critically, future projections under Shared Socioeconomic Pathways (SSPs) uncover a novel positive feedback mechanism: rising temperatures significantly enhance vehicular evaporative nonmethane hydrocarbon (NMHC) emissions. This temperature-dependent increase and subsequent NMHC oxidation to CO2 suggest an overlooked pathway that could amplify climate warming and air pollution globally, particularly after a breakpoint around 2050 (p < 0.05). While historical emissions peaked in the 1990s–2000s, nonexhaust PM becomes increasingly important. Air quality simulations using our inventory in the MUSICA model show good regional PM2.5 agreement but highlight challenges in resolving local primary pollutant peaks. This comprehensive inventory provides crucial data for Brazil and uncovers globally relevant climate–chemistry interactions, urging a re-evaluation of regional specificities in global emission assessments.}, author = {Ibarra-Espinosa, Sergio and Dias de Freitas, Edmilson and Gaubert, Benjamin and Lichtig, Pablo and Ropkins, Karl and da Silva, Iara and Martins Pereira, Guilherme and Schuch, Daniel and Nascimento, Janaina and Hoinaski, Leonardo and Martins, Leila Droprinchinski and Gavidia-Calderón, Mario and Vara-Vela, Angel and Toledo de Almeida Albuquerque, Taciana and Ynoue, Rita Yuri and Diez, Sebastian and Mera, Zamir and Casallas Garcia, Alejandro and Vallejo, Fidel and Diaz, Valeria and Pedruzzi, Rizzieri and Abrutzky, Rosana and Franco, Marco A. and Huneeus, Nicolas and Jorquera, Hector and Belalcázar-Cerón, Luis Carlos and Rojas, Néstor Y. and de Fatima Andrade, Maria and Emmons, Louisa and Brasseur, Guy}, issn = {1520-5851}, journal = {Environmental Science & Technology}, publisher = {American Chemical Society}, title = {{A century of vehicular emissions in Brazil: Unveiling the impacts of unique fuel mix on air quality}}, doi = {10.1021/acs.est.5c08400}, year = {2026}, } @article{21217, abstract = {This study investigates the mechanisms driving clustered convection and the breakdown of the Intertropical Convergence Zone (ITCZ) over the Western Pacific Warm Pool using high‐resolution cloud‐resolving simulations and machine‐learning sensitivity experiments. Results show that ITCZ breakdown episodes, marked by spatially homogeneous convection and weakened meridional moisture gradients, are triggered primarily by anomalous moisture advection linked to the equatorial Rossby‐wave activity. While large‐scale moisture advection regulates the background convective state strongly, it is the surface and low‐level meridional winds that dominate transitions between clustered and random convection. Simulations demonstrate that moisture alone can sustain convective clustering, but breakdown episodes are more persistent and widespread when coupled with southerly meridional advection. These findings confirm that wave‐driven advection acts as a regulatory mechanism, periodically disrupting convective clustering and reshaping the meridional moisture gradient. This modulation of organization by wave‐induced breakdown events is critical for understanding tropical convection variability and its implications for the climate system.}, author = {Casallas Garcia, Alejandro and Mark Tompkins, Adrian and Muller, Caroline J}, issn = {1477-870X}, journal = {Quarterly Journal of the Royal Meteorological Society}, publisher = {Wiley}, title = {{Moisture and wind effects of Rossby waves on Western Pacific Intertropical Convergence Zone breakdown events}}, doi = {10.1002/qj.70131}, year = {2026}, } @article{21233, abstract = {Potential self-perpetuating dieback of the Amazon rain forest has been a topic of concern. The concern is that initial deforestation could critically impair the forest’s water recycling capacities, further harming the remaining forest through reduced annual precipitation. Many studies have focused on annual mean precipitation changes, due to its widespread perception as a central control on the Amazon rain forest’s stability. However, the impact of deforestation goes beyond changes in the annual mean precipitation. Yet, global coarse-resolution climate models are not well suited to investigate changes in short-duration and localized events due to their coarse resolution. Here, we circumvent these issues by analyzing a full-deforestation scenario simulated by a global storm-resolving model. We focus on changes in the tail of the hourly distribution of precipitation, temperature, and wind. Hourly precipitation becomes more extreme in the absence of the forest than in an intact forest, with an increased occurrence of both no rain and intense rainfall. These changes are driven by enhanced moisture convergence that strengthens vertical velocity. On average, the near-surface temperature rises significantly by about 3.84 °C, and the daily minimum temperature after deforestation becomes similar to the daily maximum temperature before deforestation. Except for wet-bulb temperature, human heat stress indicators shift to more severe levels, with implications for health and a significant reduction in work productivity. Finally, the mean 10 m wind speed intensifies by a factor of four, with the 99th percentile wind speed doubling. To summarize, our findings, while based on an idealized case, provide a stark warning of the effects of continuing deforestation of the Amazon.}, author = {Yoon, Arim and Hohenegger, Cathy and Bao, Jiawei and Brunner, Lukas}, issn = {2190-4987}, journal = {Earth System Dynamics}, number = {1}, pages = {167--179}, publisher = {Copernicus GmbH}, title = {{Extreme events in the Amazon after deforestation}}, doi = {10.5194/esd-17-167-2026}, volume = {17}, year = {2026}, } @article{21311, abstract = {Air pollution is a critical public health issue worldwide, South America faces unique challenges due to rapid urban growth, industrial expansion, and recurrent biomass burning. Existing studies have largely focused on regional or national scales, overlooking detailed spatio-temporal dynamics in cities. This study provides a comprehensive assessment of air pollution spatio-temporal trends from 2013 to 2023 in six major South American cities: Bogotá, Buenos Aires, Montevideo, Quito, Santiago de Chile, and São Paulo. We evaluated four key pollutants, NO2, O3, PM10, and PM2.5, using in situ monitoring networks complemented with reanalysis (boundary layer and pollution dynamics), and fire detections datasets (biomass burning). A key innovation is the use of a Lagrangian Tracker, which identifies persistent hotspots and transport pathways of pollutants, offering new insights into transboundary pollution. Results show that nearly all cities experienced reductions in particulate matter concentrations, while three of the six cities exhibited rising O3 levels, reflecting complex interactions between emissions, meteorology, and atmospheric chemistry. Santiago de Chile recorded the highest levels of NO2 and PM, strongly influenced by topography and biomass burning in JJA. Bogotá and Quito were notably impacted by regional fire emissions, whereas coastal cities such as Buenos Aires and Montevideo benefited from greater pollutant dispersion but still exceeded the World Health Organization guidelines. By integrating ground-based, satellite, and reanalysis data with advanced trajectory modeling, this research provides detailed spatio-temporal evaluations of air pollution in South America and highlights the urgent need for coordinated regional strategies to reduce health and economic burdens.}, author = {González, Yuri and Malagón, Nicolás and Benavides, Kevin and Belalcázar, Luis Carlos and Lopez-Barrera, Ellie Anne and Casallas Garcia, Alejandro}, issn = {2509-9434}, journal = {Earth Systems and Environment}, publisher = {Springer Nature}, title = {{Spatio-temporal trends of air pollution in six South American cities}}, doi = {10.1007/s41748-026-01068-9}, year = {2026}, } @article{21344, abstract = {Tropospheric ozone has the potential to become an increasingly pressing public health issue in Bogotá, Colombia, due to rising concentrations across the city driven by complex interactions among emissions, meteorology, and urban structure. This study presents a comprehensive spatiotemporal analysis of ozone levels from 2013 to 2023 and assesses the associated health burden using mortality data from the same period. Results reveal a consistent upward trend in ozone concentrations, particularly in northern, western, and southern localities, with seasonal peaks linked to biomass burning and photochemical conditions. Mortality analysis, based on the Global Exposure Mortality Model, estimates that 18.3% of all deaths among individuals aged 25 and older are attributable to long-term ozone exposure. The highest burdens are found in densely populated and socioeconomically vulnerable areas such as Kennedy, Suba, and Ciudad Bolívar, with the elderly being the most affected. Building on these findings, we developed a machine learning prediction model for ozone using a convolutional merge with a long-short term memory network architecture trained on air quality and meteorological variables. The model demonstrated strong predictive performance (mean Rho=0.86, RMSE=3.5 μg/m3) across monitoring stations (17 with at least 35000 data points), supporting its potential application in real-time early warning systems across Bogotá. This integrated approach highlights the importance of localized air quality management, combining epidemiological assessment with predictive modeling. The findings underscore the urgency of implementing region-specific mitigation strategies and improving monitoring infrastructure to reduce health risks from ozone exposure in Bogotá’s rapidly growing urban environment.}, author = {Bustos, Daniela and Garcia, Diana and Rojas, Nestor Y. and Lopez-Barrera, Ellie A. and Peña-Rincon, Carlos and Casallas Garcia, Alejandro}, issn = {2509-9434}, journal = {Earth Systems and Environment}, publisher = {Springer Nature}, title = {{Ozone trends and mortality risk: The growing need for machine learning predictions in Bogotá, Colombia}}, doi = {10.1007/s41748-026-01052-3}, year = {2026}, } @article{21657, abstract = {We compare three global kilometer-scale models (ICON, IFS and NICAM) to clarify the advantages and challenges of high-resolution global weather and climate modeling, using different approaches to represent convection, from fully parameterized to fully explicit. Our analysis focuses on tropical precipitation characteristics spanning a wide range of spatio-temporal scales—including the diurnal cycle, extreme precipitation, convective organization, and the Madden-Julian Oscillation (MJO)—along with interactions between convection and the thermodynamic environment. All three models commonly show weaker convective organization with smaller precipitation cells than observed, though the strength of the bias varies by model. This diversity is introduced by differences in the representation of (a) convective initiation affected by the convective sensitivity to moisture and (b) tropospheric moistening associated with deep convection. Models with stronger thermodynamic-convection coupling increase environmental moisture near convection, thereby enhancing convective organization. This has important upscale effects on the MJO; while IFS and NICAM capture its eastward propagation well, ICON has difficulty reproducing it. The amplitudes and phases of precipitation diurnal cycles over land show much greater disagreement among the models than over ocean, influenced by how convection is initiated. Biases in rain evaporation and cold pool formation hinder the propagation of mesoscale convection, leading to errors such as the misrepresentation of nocturnal convection moving off the coast of Sumatra in IFS and ICON. These results highlight the importance of thermodynamic-convection coupling in realistically simulating tropical convection across scales. To improve this coupling, kilometer-scale models require better representation of the interaction between resolved convection and three-dimensional turbulent mixing.}, author = {Takasuka, Daisuke and Becker, Tobias and Bao, Jiawei}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {3}, publisher = {Wiley}, title = {{Precipitation characteristics and thermodynamic-convection coupling in global kilometer-scale simulations}}, doi = {10.1029/2025MS005343}, volume = {18}, year = {2026}, } @article{21755, abstract = {Tropical shallow clouds are a major source of uncertainty in Earth's climate sensitivity, especially through their spatial arrangement, which global climate models do not represent. Efforts to understand their organization have partly relied on classifying observed scenes, identifying four patterns as archetypal regimes. Here we analyze geostationary satellite imagery of the western tropical Atlantic using the L‐function, a tool based on point pattern theory that quantifies cloud organization across spatial scales. Classical examples of the four patterns show distinct L‐function fingerprints, revealing their characteristic clustering and regularity scales and aiding physical interpretation. Yet, when evaluating many scenes at fixed spatial scales, the L‐function distribution lacks the distinct modes expected from discrete regimes. This is corroborated by analyses of other organization indices employing diverse approaches, from inter‐cloud nearest‐neighbor distances to fractal analysis. Implications for the parameterization of mesoscale cloud organization in climate models are discussed.}, author = {Biagioli, Giovanni and Mandorli, Giulio and Freischem, Lilli Johanna and Casallas Garcia, Alejandro and Tompkins, Adrian Mark}, issn = {1944-8007}, journal = {Geophysical Research Letters}, number = {8}, publisher = {Wiley}, title = {{Spatial patterns of shallow clouds: Challenging the concept of defined regimes}}, doi = {10.1029/2025gl119921}, volume = {53}, year = {2026}, } @article{18605, abstract = {The response of clouds and moist-convective processes to heat loss to space by long-wave radiative cooling is an important feedback in the Earth's atmosphere. It is known that moist convection increases roughly in equilibrium with radiative cooling, an assumption often made in simplified models of the tropical atmosphere. In this study, we use an idealised two-dimensional model of the atmosphere introduced by Vallis et. al. and incorporate a bulk-cooling term, which is an idealisation of radiative cooling in the atmosphere. We comment briefly on the static stability of the system to dry and moist convection and characteris its moist convective response to changes in the bulk cooling. We find that, while the clear-sky regions of the model respond directly to the change in the cooling term, the regions dominated by moist convective plumes are insensitive to changes in cooling. Similar to previous findings from cloud-resolving models, we too find in our idealised setting that the majority of the increase in convection occurs via an increase in the areal coverage of convection, rather than its intensity. We argue that these small-scale convective processes are an upper bound on how quickly convective intensity can change to stay in equilibrium with radiative cooling.}, author = {Agasthya, Lokahith N and Muller, Caroline J and Cheve, Mathis}, issn = {1477-870X}, journal = {Quarterly Journal of the Royal Meteorological Society}, number = {766}, publisher = {Wiley}, title = {{Moist convective scaling: Insights from an idealised model}}, doi = {10.1002/qj.4902}, volume = {151}, year = {2025}, } @inproceedings{19968, abstract = {In the dynamic arena of innovation, the relations between academia and industry are a keystone for breakthroughs and practical applications. Yet, the groundwork of these pivotal University-Industry (U-I) partnerships remains covered in complexity. This paper delves into these intricate relations, unraveling the factors that help successful collaborations. Grounded in the Resource-Based Theory, our study transcends traditional analytical boundaries, leveraging a neural network model to understand a comprehensive dataset from the UK’s Higher Education Statistics Agency, SCIMAGO Rankings, and Clarivate Publications. This novel approach helps to make clear the interplay of academic load, administrative support, scientific output, and university rank in sculpting U-I collaboration dynamics. Our findings suggest that reduced academic load and robust administrative support significantly bolster U-I collaborations. However, the influence of scientific output and university ranking is more nuanced, challenging the common belief. High scientific output, while indicative of expertise, doesn't always align with industry goals. Similarly, while higher-ranked universities could attract more collaborations, the benefits are not universal. This paper not only contributes to a deeper understanding of U-I collaborations, but also provides actionable insights for university administrators, policymakers, and industry leaders. In a world where innovation is key, understanding these collaborative dynamics is crucial for fostering partnerships that push the boundaries of research and practical application.}, author = {Plata, Carlos and Casallas Garcia, Alejandro}, booktitle = {85th Annual Meeting of the Academy of Management}, issn = {2151-6561}, location = {Copenhagen, Denmark}, number = {1}, publisher = {Academy of Management}, title = {{Machine learning analysis of the factors influencing university-industry collaborations}}, doi = {10.5465/AMPROC.2025.54bp}, volume = {2025}, year = {2025}, } @article{20098, abstract = {Climate change is causing wildfires to become more frequent and intense. While predicting burned areas using bioclimatic and anthropogenic factors is an active research area, few studies have examined what drives the economic damages of wildfires. Our study aims to fill this gap by analyzing key factors influencing global economic wildfire damages and projecting future damages under three shared socioeconomic pathways (SSPs). We apply regression analyses to identify significant predictors of economic wildfire damages at country levels and use the fitted model to project future damages under SSP126, SSP245, and SSP370. Results show that the human vulnerability index (HVI), reflecting socioeconomic conditions, is the strongest predictor of historical wildfire damages, followed by water vapor pressure deficit during the fire season and population density around forested areas. We found high population density to be associated with lower damages. These findings contrast with studies of burned areas, where climate factors are more dominant. Our model projects that by 2070, average global economic wildfire damages will be three times higher under SSP370 than SSP126. Our model also shows that following SSP126 not only reduces wildfire damages but also lessens the inequalities in damage distribution across countries. This pathway’s dual focus on equitable socioeconomic progress and climate action potentially enhances a country’s resilience that helps mitigate wildfire damages. Our analyses also indicate that strong socioeconomic development can offset wildfire damages associated with climate hazards, although this is less certain under SSP370. SSP126’s integrated approach improves both socioeconomic conditions and limits global warming, providing substantial benefits to less developed countries while still reducing damages in developed nations, despite their already low HVI scores. Our work complements existing research on burned areas and underscores the importance of sustainable development and international collaboration in reducing the economic damages of wildfires.}, author = {Hwong, Yi-Ling and Byers, Edward and Werning, Michaela and Quilcaille, Yann}, issn = {2752-5295}, journal = {Environmental Research: Climate}, number = {3}, publisher = {IOP Publishing}, title = {{Sustainable development key to limiting climate change-driven wildfire damages}}, doi = {10.1088/2752-5295/adec11}, volume = {4}, year = {2025}, } @misc{20107, abstract = {This repository contains the data and scripts required to reproduce the results of the manuscript "Sustainable Development Key to Limiting Climate Change-Driven Wildfire Damages" submitted to the Environmental Research Climate Journal (ERCL). }, author = {Hwong, Yi-Ling and Byers, Edward and Werning, Michaela and Quilcaille, Yann}, publisher = {Zenodo}, title = {{Data - Sustainable Development Key to Limiting Climate Change-Driven Wildfire Damages}}, doi = {10.5281/ZENODO.13988679}, year = {2025}, } @article{20319, abstract = {The time needed by deep convection to bring the atmosphere back to equilibrium is called convective adjustment timescale or simply adjustment timescale, typically denoted by . In the Community Atmospheric Model|Community Atmosphere Model (CAM), is the convective available potential energy (CAPE) relaxation timescale and is 1 hr, worldwide. Observational evidence suggests that is generally longer than 1 hr. Further, continental and oceanic convection are different in terms of the vigor of updrafts and can have different longevities. So using hour worldwide in CAM has two potential caveats. A longer improves the simulation of the mean climate. However, it does not address the land‐ocean heterogeneity of atmospheric deep convection. We investigate the prescription of two different CAPE relaxation timescales for land ( hr) and ocean ( to 4 hr). It is arguably an extremely crude parameterization of boundary layer control on atmospheric convection. We contrast a suite of 5‐year‐long simulations with two different for land and ocean to having one globally. The choice of longer over ocean is guided by previous studies and inspired by observational pieces of evidence. Nonetheless, to complement our variable experiments, we perform a simulation with  hr and  hrs. Most importantly, our key findings are immune to the exact values of prescribed and . The CAM model, with two values , improves convective‐stratiform rainfall partitioning and the Madden–Julian oscillation propagation characteristics.}, author = {GOSWAMI, BIDYUT B and Polesello, Andrea and Muller, Caroline J}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {9}, publisher = {Wiley}, title = {{An assessment of representing land‐ocean heterogeneity via CAPE relaxation timescale in the Community Atmospheric Model 6 (CAM6)}}, doi = {10.1029/2025ms005035}, volume = {17}, year = {2025}, } @article{20590, abstract = {Moist convection is a fundamental process occurring in the Earth's atmosphere. It plays a central role in the weather and climate of the Tropics, where, to first order, the heating of the atmosphere by convection is in balance with the cooling of the atmosphere by the emission of radiation to outer space. In this study, we use a cloud-resolving model in radiative–convective equilibrium with an imposed constant rate of radiative cooling and study the response of moist convection to varying this rate of radiative cooling. In particular, we study two types of simulation: varying air temperature (VAT) simulations, where the air temperature is allowed to adjust to the imposed radiative cooling, and constant air temperature (CAT) simulations, where the surface temperature is tuned to ensure that the atmospheric temperature profile in the domain is constant. We recover the previously known result that, in response to increasing radiative cooling, the area of convection expands rapidly, while the intensity of convection does not change. We find that this response is explained by the increased boundary-layer variability in simulations with greater radiative cooling, which compensates for the decreasing temperature by adding a larger initial velocity close to the cloud base. We also propose a fundamental scaling of the non-dimensional cumulus mass flux in moist convection, which is robust across models of different complexity. We aim to bridge the gap between highly idealised prototypes of moist convection, such as the “Rainy–Bénard convection” introduced by Vallis et al., and comprehensive cloud-resolving models.}, author = {Agasthya, Lokahith N and Muller, Caroline J}, issn = {1477-870X}, journal = {Quarterly Journal of the Royal Meteorological Society}, publisher = {Wiley}, title = {{Moist convection and radiative cooling: Dynamical response and scaling}}, doi = {10.1002/qj.70044}, year = {2025}, } @article{20685, abstract = {The Next Generation of Earth Modeling Systems (nextGEMS) project aimed to produce multidecadal climate simulations, for the first time, with resolved kilometer-scale (km-scale) processes in the ocean, land, and atmosphere. In only 3 years, nextGEMS achieved this milestone with the two km-scale Earth system models, ICOsahedral Non-hydrostatic model (ICON) and Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM). nextGEMS was based on three cornerstones: (1) developing km-scale Earth system models with small errors in the energy and water balance, (2) performing km-scale climate simulations with a throughput greater than 1 simulated year per day, and (3) facilitating new workflows for an efficient analysis of the large simulations with common data structures and output variables. These cornerstones shaped the timeline of nextGEMS, divided into four cycles. Each cycle marked the release of a new configuration of ICON and IFS-FESOM, which were evaluated at hackathons. The hackathon participants included experts from climate science, software engineering, and high-performance computing as well as users from the energy and agricultural sectors. The continuous efforts over the four cycles allowed us to produce 30-year simulations with ICON and IFS-FESOM, spanning the period 2020–2049 under the SSP3-7.0 scenario. The throughput was about 500 simulated days per day on the Levante supercomputer of the German Climate Computing Center (DKRZ). The simulations employed a horizontal grid of about 5 km resolution in the ocean and 10 km resolution in the atmosphere and land. Aside from this technical achievement, the simulations allowed us to gain new insights into the realism of ICON and IFS-FESOM. Beyond its time frame, nextGEMS builds the foundation of the Climate Change Adaptation Digital Twin developed in the Destination Earth initiative and paves the way for future European research on climate change.}, author = {Segura, Hans and Pedruzo-Bagazgoitia, Xabier and Weiss, Philipp and Müller, Sebastian K. and Rackow, Thomas and Lee, Junhong and Dolores-Tesillos, Edgar and Benedict, Imme and Aengenheyster, Matthias and Aguridan, Razvan and Arduini, Gabriele and Baker, Alexander J. and Bao, Jiawei and Bastin, Swantje and Baulenas, Eulàlia and Becker, Tobias and Beyer, Sebastian and Bockelmann, Hendryk and Brüggemann, Nils and Brunner, Lukas and Cheedela, Suvarchal K. and Das, Sushant and Denissen, Jasper and Dragaud, Ian and Dziekan, Piotr and Ekblom, Madeleine and Engels, Jan Frederik and Esch, Monika and Forbes, Richard and Frauen, Claudia and Freischem, Lilli and García-Maroto, Diego and Geier, Philipp and Gierz, Paul and González-Cervera, Álvaro and Grayson, Katherine and Griffith, Matthew and Gutjahr, Oliver and Haak, Helmuth and Hadade, Ioan and Haslehner, Kerstin and ul Hasson, Shabeh and Hegewald, Jan and Kluft, Lukas and Koldunov, Aleksei and Koldunov, Nikolay and Kölling, Tobias and Koseki, Shunya and Kosukhin, Sergey and Kousal, Josh and Kuma, Peter and Kumar, Arjun U. and Li, Rumeng and Maury, Nicolas and Meindl, Maximilian and Milinski, Sebastian and Mogensen, Kristian and Niraula, Bimochan and Nowak, Jakub and Praturi, Divya Sri and Proske, Ulrike and Putrasahan, Dian and Redler, René and Santuy, David and Sármány, Domokos and Schnur, Reiner and Scholz, Patrick and Sidorenko, Dmitry and Spät, Dorian and Sützl, Birgit and Takasuka, Daisuke and Tompkins, Adrian and Uribe, Alejandro and Valentini, Mirco and Veerman, Menno and Voigt, Aiko and Warnau, Sarah and Wachsmann, Fabian and Wacławczyk, Marta and Wedi, Nils and Wieners, Karl-Hermann and Wille, Jonathan and Winkler, Marius and Wu, Yuting and Ziemen, Florian and Zimmermann, Janos and Bender, Frida A.-M. and Bojovic, Dragana and Bony, Sandrine and Bordoni, Simona and Brehmer, Patrice and Dengler, Marcus and Dutra, Emanuel and Faye, Saliou and Fischer, Erich and van Heerwaarden, Chiel and Hohenegger, Cathy and Järvinen, Heikki and Jochum, Markus and Jung, Thomas and Jungclaus, Johann H. and Keenlyside, Noel S. and Klocke, Daniel and Konow, Heike and Klose, Martina and Malinowski, Szymon and Martius, Olivia and Mauritsen, Thorsten and Mellado, Juan Pedro and Mieslinger, Theresa and Mohino, Elsa and Pawłowska, Hanna and Peters-von Gehlen, Karsten and Sarré, Abdoulaye and Sobhani, Pajam and Stier, Philip and Tuppi, Lauri and Vidale, Pier Luigi and Sandu, Irina and Stevens, Bjorn}, issn = {1991-9603}, journal = {Geoscientific Model Development}, number = {20}, pages = {7735--7761}, publisher = {Copernicus Publications}, title = {{nextGEMS: Entering the era of kilometer-scale Earth system modeling}}, doi = {10.5194/gmd-18-7735-2025}, volume = {18}, year = {2025}, } @article{19080, abstract = {We examine mesoscale convective organisation in the tropical western Pacific using a multivariate analysis of column humidity, precipitation and sea surface temperature (SST) observations. We demonstrate that in boreal summer and autumn, convection remains spatially random despite radiative-feedbacks acting to aggregate convection, which we attribute to the high density of convective moisture sources and the role of wind shear. Instead, in winter and spring, a weak meridional SST gradient exists and convection is usually clustered over the regions of warmer SSTs, with significant meridional humidity gradients. However, this is sporadically interrupted by episodes of convection migration to the coldest SSTs and limited spatial humidity variance. These episodes are the result of westward propagating equatorial waves, which remove meridional humidity gradients. It appears that the drivers of mesoscale convective clustering and humidity variability in the Pacific warm pool are the SST gradients, shear, and equatorial wave dynamics.}, author = {Tompkins, Adrian Mike and Casallas Garcia, Alejandro and De Vera, Michie Vianca}, issn = {2397-3722}, journal = {npj Climate and Atmospheric Science}, publisher = {Springer Nature}, title = {{Drivers of mesoscale convective aggregation and spatial humidity variability in the tropical western Pacific}}, doi = {10.1038/s41612-024-00848-2}, volume = {8}, year = {2025}, } @article{19416, abstract = {Recently, Biagioli and Tompkins (2023, https://doi.org/10.1029/2022ms003231) used a simple stochastic model to derive a dimensionless parameter to predict convective self aggregation (SA) development, which was based on the derivation of the maximum free convective distance ($d_{clr}$) expected in the pre-aggregated, random state. Our goal is to test and further investigate this hypothesis, namely that $d_{clr}$ can predict SA occurrence, using an ensemble of twenty-four distinct combinations of horizontal mixing, planetary boundary layer (PBL), and microphysical parameterizations. We conclude that the key impact of parameterization schemes on SA is through their control of the number of convective cores and their relative spacing, $d_{clr}$, which itself is impacted by cold-pool (CP) properties and mean updraft core size. SA is more likely when the convective core count is small, while CPs modify convective spacing via suppression in their interiors and triggering by gust-front convergence and collisions. Each parameterization scheme emphasizes a different mechanism. Subgrid-scale horizontal turbulent mixing mainly affects SA through the determination of convective core size and thus spacing. The sensitivity to the microphysics is mainly through rain evaporation and the subsequent impact on CPs, while perturbations to the ice cloud microphysics have a limited effect. Non-local PBL mixing schemes promote SA primarily by increasing convective inhibition through inversion entrainment and altering low cloud amounts, leading to fewer convective cores and larger $d_{clr}$. }, author = {Casallas Garcia, Alejandro and Tompkins, A.M. and Muller, Caroline J and Thompson, G.}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {3}, publisher = {Wiley}, title = {{Sensitivity of self-aggregation and the key role of the free convection distance}}, doi = {10.1029/2024MS004791}, volume = {17}, year = {2025}, } @article{19585, abstract = {Air quality in northern South America faces significant challenges due to insufficient high-resolution emission inventories and sparse atmospheric studies. This study addresses these gaps by developing a novel framework that integrates high-resolution nighttime light data from SDGSAT-1 and multisource remote sensing datasets with deep learning techniques to downscale emission inventories. The refined inventories are coupled with meteorological inputs into the Weather Research and Forecasting (WRF-Chem) model, enabling precise simulation of pollutant dynamics. Validated against ground measurements from Colombia's SISAIRE monitoring network, demonstrates significant improvements in spatiotemporal accuracy, particularly for particulate matter (PM) and nitrogen dioxide (NO₂) with error reductions of 22–30 % and correlation coefficients increasing from 0.68 to 0.85. These findings underscore the critical role of satellite-enhanced inventories in resolving localized emission patterns and seasonal variability, such as dry-season PM₁₀ spikes (150 % increase from wildfires). The framework provides policymakers with actionable insights to prioritize mitigation in rapidly urbanizing regions and manage transboundary pollution. By bridging data scarcity gaps, this replicable methodology offers transformative potential for global air quality management and public health protection, advocating for expanded ground monitoring networks and real-time satellite data integration in future applications.}, author = {Antezana-Lopez, Franz and Casallas Garcia, Alejandro and Zhou, Guanhua and Zhang, Kai and Jing, Guifei and Ali, Aamir and Lopez-Barrera, Ellie and Belalcazar, Luis Carlos and Rojas, Nestor and Jiang, Hongzhi}, issn = {1879-0704}, journal = {Remote Sensing of Environment}, publisher = {Elsevier}, title = {{High-resolution anthropogenic emission inventories with deep learning in northern South America}}, doi = {10.1016/j.rse.2025.114761}, volume = {324}, year = {2025}, } @article{19662, abstract = {We investigate the effect of changes in the Coriolis force caused by changes in the rotation rate on the top-of-atmosphere (TOA) radiant energy budget of an aquaplanet general circulation model with prescribed sea surface temperatures. We analyse the effective radiative forcing caused by changes from Earth-like rotation to values between 1/32 and 8 times the Earth's rotation rate. The forcing differs by about 60 W m−2 between the fastest and slowest rotation cases, with a monotonically increasing positive forcing for faster-than-Earth-like rotations and a non-monotonically increasing negative forcing for slower rotations. The largest contributions to the forcing are due to changes in, in this order, the shortwave cloud radiative effect (SWCRE) and the clear-sky outgoing longwave radiation (OLR). From the fastest to the slowest rotation, the Hadley cell expands and the troposphere becomes drier, increasing the OLR. This contributes to negative forcing at slower-than-Earth-like rotations and to positive forcing at faster-than-Earth-like rotations. The SWCRE is influenced by changes in the low-level cloudiness within the Hadley cell and the baroclinic regime. With the expansion of the Hadley cell, the area of enhanced tropospheric stability increases, resulting in more low-level clouds, a higher SWCRE, and increased negative forcing. The non-monotonicity results from an intermediate decrease in the SWCRE caused by the disappearance of baroclinic eddies as the Hadley cell reaches global extension. At rotations faster than Earth-like, the decrease in the SWCRE, mainly due to the weakening of baroclinic eddies and storm systems, leads to an increase in positive forcing. In summary, changes in the SWCRE, driven by different circulation responses at slower-than-Earth-like and faster-than-Earth-like rotations, strongly influence the TOA radiant energy budget. These effects, along with a substantial contribution from the clear-sky OLR, could impact the habitability of Earth-like rotating planets.}, author = {Gnanaraj, Abisha Mary and Bao, Jiawei and Schmidt, Hauke}, issn = {2698-4016}, journal = {Weather and Climate Dynamics}, number = {2}, pages = {489--503}, publisher = {Copernicus Publications}, title = {{The impact of the rotation rate on an aquaplanet's radiant energy budget: Insights from experiments varying the Coriolis parameter}}, doi = {10.5194/wcd-6-489-2025}, volume = {6}, year = {2025}, }