The land surface, through its topography, soil moisture, temperature or vegetation activity, impacts the atmosphere from daily to seasonal time scale. An accurate assessment of the Land-Atmosphere (L-A) exchanges, and their correct representation, are therefore essential for weather and climate forecasts. However, Earth System Models (ESM) and Numerical Weather Prediction (NWP) often have large biases in their representation of surface-atmosphere flux when compared to observations. The detailed quantification and reduction of these biases are still on-going efforts in many modelling centres. The Models and Observations for Surface-Atmosphere Interactions (MOSAI) project aims at contributing to this effort, with a focus on the impact of surface heterogeneity. The first step to achieve this objective is to conduct a fair and correct evaluation of the L-A interactions simulated by ESM and NWP. This is based on (i) reliable references against which the simulated L-A exchanges can be evaluated, and, (ii) relevant comparison methods able to point out the ESM and NWP weaknesses. These points define the two first scientific objectives of MOSAI project: (1) to investigate and determine the uncertainty and representativeness of L-A exchanges measured over heterogeneous landscapes. The second scientific objective (2) is to propose and test new methods to evaluate the L-A exchanges in ESM using long-term measurements.The second step of the project concerns the improvement of the L-A exchanges simulated by the ESM and NWP. The coupling between land surface models (LSM) and atmospheric models is based on several simplifications which are different when considering Large Eddy Simulation (LES), weather or climate models. The third scientific objective (3) addresses some of these underlying simplifications in the coupling between LSM and atmospheric models, and their impacts on the simulated L-A exchanges.From an observational prospective, MOSAI is based on long-term reference surface observations of research infrastructures (ACTRIS and ICOS) and on Enhanced Observing Periods (2021-2023) on three different ACTRIS-Fr sites. From the modelling prospectives, several ESM, NWP and LES models are involved. In this presentation, we will state the objectives and strategy of MOSAI, and illustrate them with ongoing fields, works and results. The latter will notably address (1) the representativity of reference long-term measurements in a heterogeneous landscape, (2) the use of Neural Networks for the evaluation of models, (3) the impact of the heterogeneity on the boundary layer structure.
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Fabienne Lohou (2024) studied this question.
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