Land Surface Modeling and Climate Impacts
Summary
Land surface models (LSMs) represent the exchange of energy, water and carbon between the terrestrial surface and the atmosphere, forming a critical component of Earth system models used for weather prediction and climate projection. By simulating processes such as soil moisture dynamics, evapotranspiration, snow cover evolution and vegetation growth, LSMs capture key feedbacks that influence regional and global climate patterns. Advances in high-resolution parameter datasets and process representations have revealed substantial spatial heterogeneity across topography, vegetation types and soil properties, underscoring the importance of fine‐scale information for accurate flux estimates. Improved characterisation of hydrological uncertainties and data assimilation techniques has enhanced the reliability of seasonal drought or flood forecasts, informing water resource management and agricultural planning. As societies confront a changing climate, robust land surface modelling delivers insights into carbon sequestration potential, regional heat extremes, moisture recycling and the resilience of ecosystems, thereby guiding mitigation and adaptation strategies on local to global scales.
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Land Surface Modeling and Climate Impacts publication trend
The graph below shows the total number of articles in land surface modeling and climate impacts across all publications each year (not limited to Nature Index journals).
Technical terms
Land Surface Model (LSM): A numerical scheme representing terrestrial energy, water and carbon exchanges with the atmosphere.
Earth System Model (ESM): An integrated framework coupling atmosphere, ocean, land surface and biogeochemical processes to simulate climate.
Evapotranspiration: Combined water flux from soil evaporation and plant transpiration back to the atmosphere.
Parameter uncertainty: Variability in model outputs arising from incomplete knowledge of model parameter values.
Data assimilation: The systematic integration of observations into models to improve state estimation and forecasts.
References
- Global 1 km land surface parameters for kilometer-scale Earth system modeling. Earth System Science Data (2024).
- Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States. Scientific Data (2023).
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