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Aurora viewed from space

Wave-induced transport in the atmosphere is important to a wide range of research problems, including general circulation modelling, atmospheric chemistry modelling and thermal balance calculations. However, computational cost constraints mean that it has not so far been practical to include small-scale wave transport effects directly in global models. The WAVECHASM project will bridge the gap between high-resolution regional models and global climate models in representing wave transport of constituents. It will contribute to a much deeper understanding of the key small-scale wave-induced constituent transport processes (advection, turbulent mixing, dynamical transport and chemical transport), their global characteristics and their impact on atmospheric chemistry. By making use of a recent novel theoretical approach and developing this to incorporate these transport processes into global atmospheric chemistry models, this project will significantly enhance our ability to simulate the global constituent structure of the middle atmosphere. We will focus here on the mesosphere and lower thermosphere (MLT, between 70 and 120 km), which is sensitive to perturbations from below (upward propagating atmospheric waves and dynamical forcing) and above (solar radiation and energetic particle precipitation i.e. space weather), and is where interplanetary dust particles ablate. The region is also sensitive to longer-term climate change caused by stratospheric ozone depletion and increasing levels of greenhouse gases, and it been shown that including this region in “high-top” models significantly improves long-range weather forecasting and climate prediction.

This project is jointly funded by the UK Natural Environment Research Council and the US National Science Foundation. The UK investigators are John Plane, Dan Marsh and Wuhu Feng. The US investigators are Chester Gardner (U. Illinois, Champaign-Urbana) and Xinzhao Chu (U. Colorado, Boulder). There is also 5 project partners who will provide lidar data for the project: Tao Li and Xianghui Xue (University of Science & Technology of China, Hefei), Guotao Yang (National Space Science Centre, Beijing), Satonori Nozawa (Nagoya University, Japan) and Alan Liu (Embry-Riddle University, US).