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Scale interaction in Land-Atmosphere (L-A) feedback

Subject Area Atmospheric Science
Physical Geography
Term since 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 514721519
 
Earth system models (ESMs) are the most important tools for global climate projections under various future emissions and land-use scenarios. Yet they feature biases, in particular with respect to turbulent heat fluxes, that could not be resolved over the last decade. These biases raise fundamental questions, but are equally relevant for very applied and urgent questions, since they are relevant in particular for heterogeneous landscapes – which include many of the world’s typical agricultural and forestry landscapes, where people live, grow food and hope to sequester CO2 as required by many climate-neutrality pathways. It remains unclear how different vegetation states and types, such as different land uses, affect the land-atmosphere coupling under realistic conditions, and how much biases in global modeling are attributable to low resolution versus other shortcomings of these models. This is why within the LAFI consortium project P8 aims at a better understanding of the role of surface heterogeneity for land-atmosphere coupling and plans to test its relevance in case studies guided by the detailed, high-quality observations of the LAFI consortium and as a key partner in the LAFI multi-model ensemble. Specifically, project P8 develops a large-eddy model based on ICON coupled to the advanced JSBACH4 land surface model. As JSBACH4 is also part of the ICON-ESM, we close the methodological gap between global Earth system and large-eddy modeling with respect to vegetation-atmosphere feedbacks. Analyzing simulations at approx. 50 m resolving land surface heterogeneities compared to simulations imitating the coarse land surface representation of ESMs allows us to assess the relevance of resolving land-atmosphere exchange at high spatial scale. With this novel tool, we will investigate if resolving the land-atmosphere interactions at high spatial detail will avoid strong known biases of ESMs like biases in turbulent heat fluxes, and how this depends on atmospheric conditions. We will investigate the relative role of radiative and non-radiative mechanisms for these biases. With the help of high-resolution simulations, we will infer conclusions about the net climate effect of land use (i.e., when water, energy and CO2 fluxes are considered together) at a level relevant for decision-making.
DFG Programme Research Units
 
 

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