Planning for climate change requires understanding how climate and weather interact to drive possible impacts. We developed a tool that simulates realistic monthly climate patterns and translates them into useful measures like energy needs. It captures seasonal cycles and year-to-year variations to bridges the gap between global climate predictions and local planning, making climate risk assessment faster and more accessible.

This study examines how high-energy particles develop and propagate in thunderstorm electric fields. Simulations at four high-altitude sites show that accounting for air density improves the description of particle avalanche growth across different atmospheric conditions. The study also examines how electrons and gamma rays propagate after leaving the accelerating field, providing a framework for interpreting high-energy atmospheric observations.

Coastal seas are strongly shaped by complex coastlines, shallow depths, and inputs from rivers, which influence marine life and water quality. This study introduces a new high-resolution modelling system that combines ocean circulation and marine ecosystem processes on unstructured grids. Applied to the northern Adriatic Sea, the model realistically captures seasonal changes in key biogeochemical variables, offering improved tools to support coastal environmental management.

In this work we summarize 15 years of research and developments of short-lived halogens (SLH) using the Community Earth System Model (CESM) and present a complete description of the implementation and capabilities achieved with the latest version v2. The CESM2-SLH release includes specific namelist options, input files and technical notes detailing the most important SLH updates that must be considered for the different model configurations and resolutions.

We applied a consistent modeling approach for both field and regional scales of multi-pollutants to evaluate the air-surface exchange processes contributing to regional air quality modeling biases when evaluated against observed network and satellite ammonia concentrations. This multi-resolution approach will serve the modeling and measurement community in their future development and generalization of air-surface exchange models utilizing flux, routine network and satellite observations.

Land-atmosphere interaction is an important process for the exchange of matter and energy between land and atmosphere. In this work, we incorporated the interactive Model for Air Pollution and Land Ecosystems into the European Centre Hamburg general circulation model. Compare with original configuration, the new coupling model demonstrates better performance in simulating terrestrial carbon and water fluxes. Our research provides a useful tool for studying land–atmosphere interactions.

This study develops a novel global economic model to better capture how climate change interacts with finance, innovation, employment, and public budgets. Instead of treating climate damage as a simple output loss, the model traces how rising temperatures affect investment risk, productivity, unemployment, and government spending. Large simulation ensembles show that without stronger climate action, growth slows, financial fragility rises, and welfare and debt pressures increase.

The future contribution of Antarctica to sea-level rise is strongly dependent on the melting of floating ice shelves by the underlying ocean. Here, we present version 2 of the two-dimensional ocean model LADDIE. We evaluate the model by comparing it to three-dimensional ocean models and satellite observations, showing good performance at low computational cost. With this open-source model, we hope to contribute to the evolution toward more realistic melting in ice sheet model simulations.

Some climate models still represent cities as if they were natural ground. For one of these models, we built a new way to represent cities. The update includes how reflective surfaces are, building height, stored heat, and how much ground is sealed. The novelty is to treat sealed ground not only at the surface, but also below it. Tested at twenty urban sites, the new version better represents exchanges of energy between the ground and the air, supporting more reliable urban climate studies.

Rainfall information is essential for flood studies and water management, but detailed records are often unavailable. We developed Virtual Rain, an open toolkit that generates realistic rainfall series and converts daily rainfall data into finer time scales. Using commonly available rainfall records and information on rainfall extremes, the tool reproduces key rainfall characteristics with good accuracy. It is freely available through open-source software and an interactive web platform.

Granular flows are widespread in nature and industry, yet poorly understood. Discrete particle simulations offer detailed insight into their behaviour, but only provide properties of the individual particles, such as velocity and force. To obtain bulk flow quantities relevant to science and engineering, such as pressure or strain rate, we present Pysammos: an open source, user-friendly too to process discrete particle simulation data into continuum fields.

This study presents an adaptive observation-weighting scheme for thermodynamic profile retrievals from ground-based microwave radiometers and Mie–Raman lidars. The method dynamically estimates observational contributions during the retrieval process, replacing the commonly used static weighting assumption. Evaluation using 107 heavy-precipitation cases shows improved retrieval accuracy, particularly for atmospheric moisture profiles.

This study enhances a snow model for Arctic environments by improving the heat exchanges within the snowpack and at its interfaces, revising the compaction scheme, and adding consideration of blowing snow sublimation losses. Simulations at ten Arctic, mid-latitude, and Alpine sites show significant reductions in simulated soil and snow temperature biases and improved simulated snow depth and density, which are key features to improve simulated energy, water, and carbon budgets in the Arctic.

River plumes can strongly influence coastal dynamics but are poorly resolved in global ocean models. Building on a companion study, we perform high-resolution simulations of the Mississippi–Atchafalaya (M–A) plume with the Model for Prediction Across Scales–Ocean (MPAS–O), a global model, and compare with a limited-domain Regional Ocean Modeling System configuration. MPAS–O qualitatively captures the M–A plume seasonality but fails to generate realistic eddies on the Texas–Louisiana shelf.

This study compares the model performance of the Emission and atmospheric Processes Integrated and Coupled Community Model with the two air quality models in China. The EPICC-Model excels in simulating summer ozone peaks, accurately captures pollution characteristics in highly polluted areas, and better reproduces persistent compound pollution processes. The study reveals common issues among the models and directions for improvement, providing a basis for optimizing global air quality models.

We present MONKI (Monte Carlo KNMI), an accurate and efficient Fortran radiative transfer code for simulating total and polarised sunlight in 3D planetary atmospheres. Its novelty is the derivation of Monte Carlo equations for the transfer of polarised light, fully accounting for polarisation-dependent scattering directions. This formulation gives reliable convergence even for optically thick, strongly polarising atmospheres, supporting observations of Earth, Venus, or any other planet.

Green roofs can help cool cities, but models must represent them accurately to quantify this potential. Yet few studies evaluate green roof models against real data. We evaluated two versions of EcoRoof, the green roof module in EnergyPlus, and a green roof option for WRF (Weather and Research Forecasting model) using measurements from London, Ontario. EcoRoof generally matched observed heat fluxes, surface temperature, and soil moisture, while WRF overestimated heat and underestimated cooling.

EnviFlux is a low-cost data assimilation tool to estimate trace gas fluxes at the Earth's surface. Data assimilation ideas are often first studied with "toy models", but none exists for flux estimation, hence the purpose of EnviFlux.

EnviFlux is described, and then used to show how model error and bias can influence the inferred surface flux features. This is done in two scenarios, one with no prior knowledge of a source/sink pair, and another with prior knowledge in a more realistic situation.

Geodynamic simulations of mantle flow repeatedly solve the Stokes equations at high memory and computational cost. We developed a Stokes solver for graphics processing units by coupling two open-source libraries. A single graphics processing unit solved the Stokes equations 6–11 times faster than a 32-core central processor, with the same accuracy. Two units further shortened the solution time of large problems. The doubled memory extended the maximum size of three-dimensional simulations.

This study achieves significant acceleration by developing an optimized advection module for Emission and atmospheric Processes Integrated and Coupled Community Model on Graphics Processing Unit. Through implementing thread-block indexing, minimizing Central Processing Unit and Graphics Processing Unit communication, and an parallel framework, we demonstrate speedups: 556.5× faster offline performance for the Heterogeneous Interface advection solver and 20.5× acceleration in coupled simulations.

Artificial intelligence (AI) weather models are now competing with traditional physics-based models for flood forecasting. We tested three of them and a physics-based model against observations from three flood events in Luxembourg. The AI models detected light rain and predicted temperatures better, but the physics-based model was more skilful at the heavy rainfall that actually causes floods. One AI model kept its skill on an event after its training period.

The UK Earth System Model is updated with an improved polar stratospheric cloud scheme. The performance of the scheme is evaluated against satellite data. While the model fails to form the full range of observed ice, the scheme improves its ability to represent different polar stratospheric cloud types and their variations. This brings the model closer to satellite observations and highlights the need for further development to capture the polar stratospheric clouds with high number densities.