The AER team has always been open, innovative, and on the path to try something new. The team enjoys the endeavor to collaborate and pursue bold ideas, and continuously challenges themselves with new directions toward unknown territories. As a result, the projects in the AER lab can be developed and evolved relatively quickly with time. Collectively, with a goal to better understand and predict the change of our environment and atmosphere, the AER Lab has a diverse research portfolio that encompasses three research themes:
Data is the most valuable resource in the 21st century. Satellite data plays a unique role for us to observe our planet and how it is changing, and is increasingly empowered by the continuous reduction of launch cost and the rapid development of Machine Learning and Artificial Intelligence techniques. Therefore, a key aspect of AER research has been the development and application of new satellite data, and combines the observation-based data with regional (WRF-Chem) and global (GEOS-Chem) models to study atmospheric composition and climate change. AER specializes in data assimilation to improve the fidelity of predictions and emphasizes on observation-based modeling studies to better understand the processes in the atmosphere-Earth systems. AER has involved in ~10 satellite missions and developed algorithms to generate new or improve existing satellite data products. Examples include the fire light detection and fire combustion efficiency product, and the aerosol layer height product.
The AER Lab not only stresses the importance of observation and the use of observation data to advance models and our understanding of atmosphere and environment, but also strives to transfer research ideas and algorithms into application to benefit the society as well as to share the data and development with the research community. For example, the AER team runs the Earth System Modeling Complex (ESMC) in real time to predict weather and air quality for the rural communities in the Great Plains and upper mid-west region. It also develops the smart canopy sensors to help farmers to measure soil moisture, soil temperate and weather, and deliver the predictions and observations on-demand via interactive maps and phone apps. Another example is the support of community to use the research tools and algorithms developed by the AER Lab. The UNified and Liearized Vector Radiative Transfer Model (UNL-VRTM) , whose development is led by the AER Lab, has been used by 40 groups around the world. The AER team has been maintaining the public access to the UNL-VRTM since 2016.