We present the Community Fire Behavior model (CFBM) a fire behavior model designed to facilitate coupling to atmospheric models. We describe its implementation in the Unified Forecast System (UFS). Simulations of the Cameron Peak fire allowed us to verify our implementation. Our vision is to foster collaborative development in fire behavior modeling with the ultimate goal of increasing our fundamental understanding of fire science and minimizing the adverse impacts of wildland fires.

This study assesses how vertical coordinate choice shapes barotropic and baroclinic tide simulations in a high-resolution, MOM6 (Modular Ocean Model version 6) regional model. Focusing on the Yellow Sea under realistic forcing and seasonal stratification, we compare z^* and z^*-isopycnal hybrid to quantify coordinate-dependent impacts on tidal energetics and vertical structure. The results underscore that vertical representation is critical for accurately reproducing coastal stratification and tide–stratification interactions.

Landslide-Tsurrogate v1.0 is an open-source Python/MATLAB tool that create surrogate models that replace costly numerical simulations. These models estimate tsunami hazards from submarine landslides in a few seconds. Based on polynomial chaos expansions, they also enable sensitivity analyses, fast probabilistic results, and user-friendly visualization. Tested in Mayotte, Landslide-Tsurrogate v1.0 can be applied to any coastal region.

This study investigates the variability of currents in the Southwestern Atlantic Ocean using a high-resolution simulation. Particularly in the Brazil-Malvinas Confluence (BMC), it finds that the southward movement of the BMC, induced by the warming trends in the region, is balanced by northward flow from the Malvinas Current and Pacific Waves. The analysis also examines the intense northward displacement of the North Brazil Current, where inconsistencies in the simulation affect its evolution.

Land and Land Ice Theme Opportunities describe a list that contains 25 variable groups with 716 variables, which are potentially available to the broad scientific audience for performing analysis in land–atmosphere coupling, hydrological processes and freshwater systems, glacier and ice sheet mass balance and their influence on the sea levels, land use, and plant phenology.

Integrated Assessment Models are widely used by researchers to assess future emissions and the performance of climate policies. Bringing together insights from these models with information at the country level has remained difficult, as they usually provide results for a limited number of highly aggregated regions. We address this issue by presenting a novel algorithm designed to downscale regional outcomes to the country level and show the results for a current policy and a 1.5C scenario.

The percolation of liquid water down snowpacks is a complex phenomenon, and its representation can sometimes be complicated for snowpack models. The goal of this article is to transpose some state-of-the-art strategies used for modeling liquid percolation in other media (such as rocks or soil) into snowpack models. With this, snowpack models can be made more efficient, requiring less time and power to perform their computation.

Archives worldwide host vast records of observed weather data crucial for understanding climate variability. However, most of these records are still in paper form, limiting their use. To address this, we developed MeteoSaver, an open-source tool, to transcribe these records to machine-readable format. Applied to ten handwritten temperature sheets, it achieved a median accuracy of 74 %. This tool offers a promising solution to preserve records from archives and unlock historical weather insights.

We present an efficient ocean model coupled to a 3-D climate model (the Generic-PCM) that captures key features of ocean heat transport, matching well the global heat flows of more complex models. It closely reproduces Earth’s sea surface temperatures and sea ice, while influencing atmospheric circulation consistently. Balancing speed and accuracy, the model is ideal for exoplanet and paleoclimate studies, where observations are limited and broad parameter exploration is necessary.

We develop an ocean general circulation model based on heterogeneous computing architectures. The model is optimized to address a series of challenges that are particularly crucial for kilometer-scale resolution ocean modeling. We conduct a short-term global simulation test with a horizontal resolution of 2 km. The simulation demonstrates the high capacity of the model to capture the oceanic meso- to submesoscale processes.

We developed a fast and accurate computer tool that predicts how air pollution will change around the world under different climate and policy choices. Using machine learning and real model data, our tool can estimate changes in harmful fine particulate pollution in seconds instead of thousands of hours. This makes it easier for researchers and policymakers to explore future air quality and health impacts under a wide range of scenarios.

This study refines the coastal gravity anomaly model by constructing a residual terrain model using high-resolution topographic and bathymetric data. In the spatial domain, the RTM (residual terrain model) gravity forward modeling method is applied to effectively compensate for the missing high-frequency information in the XGM2019e-2159 gravity anomaly model. As a result, an RTM-corrected XGM2019e-2159 gravity anomaly model for the study area is obtained.

It is important for computational Earth system models to capture interactions between the ocean and the atmosphere accurately. Because of incredible complexity of these interactions, computational models contain simplifications, which may hinder the models' capabilities. Here we focus on detailed analysis of thermodynamic interactions between the ocean and the atmosphere in computational Earth system models. We also provide a framework to show how modeling these interactions can be improved.

This study evaluates the impact of grid resolution on long-term present and future climate runs using the Alfred Wegener Institute global model AWI-CM3. A higher-resolution setup (35 km atmosphere, eddy-permitting/resolving ocean) improves small-scale processes and long-term variability, across variables and regions, and can capture nonlinear ocean–atmosphere interactions often missed by Coupled Model Intercomparison Project (CMIP) models.

Soil moisture helps control how plants grow and how land exchanges water and energy with the atmosphere. We evaluated how well 16 Earth System Models represent soil moisture and its links to plant activity using a benchmarking system and observational data. Many models simulate surface soil moisture well but show larger errors deeper in the soil and in colder regions. Models that represent plant–soil water interactions more directly better capture how ecosystems respond to water availability.

We present Curlew, an open-source Python tool for constructing 3D geological models using machine learning. It integrates diverse spatial data and structural observations into a flexible, event-based framework. Curlew captures complex features like folds and faults, handles uncertainty, and supports learning from sparse or unlabelled data. We demonstrate its capabilities on synthetic and real-world examples.

The Aerosol and Chemistry Model Intercomparison Project phase two (AerChemMIP2) allows the community to compare results from contemporary Earth system models. AerChemMIP2 is asking modelling centres to perform experiments following the same protocol. It includes experiments for enabling new science and for tracking progress. Model output will be used for addressing research and policy questions about anthropogenic and natural drivers of climate change, and the impacts on air quality.

Soil texture varies over centimeters, which is overseen by large-scale models, likely causing simulation errors. We developed a 2-dimesional geophysical soil model (DynSoM-2D) with a resolution of 10 cm and ran it with different setups at a permafrost-affected site. Using high-resolution input, DynSoM-2D simulates a warmer soil, which thaws deeper and has an extended snow-free period in summer. These changes can impact ecosystem dynamics, but have little effect on yearly soil-air heat exchange.

The GSV-SRTS (General spectral vector-stochastic radiative transfer model for sloping terrain)  simulates radiative transfer for heterogeneous mountain forests, addressing slope-induced uncertainties in remote sensing. Validations with benchmark models and satellite data confirm its accuracy in red/NIR bands and its capability to capture canopy-terrain effects, offering a reliable tool for improved biophysical retrieval.

We develop an easy-to-use tool to estimate the per-flight climate effect of CO₂ and non-CO₂ emissions, based only on aircraft size as well as origin and destination airports. The implemented model results from a comparison of Multiple and Symbolic Regression approaches and exhibits a mean relative error of 21 % with respect to climate response model results. The simplified method is designed for climate footprint assessment and covers jet-powered passenger aircraft with over 20 seats.