Multiscale Wildfire Simulation Framework and Remote Sensing
Qi Tang | 22-ERD-008
Current wildfire simulation capabilities suffer from spatiotemporal resolutions that are too coarse, as well as chemistry and aerosol representations of smoke that are too simple to capture important processes needed to accurately predict the effects of wildfires. We will develop a global, multiscale, wildfire simulation framework with improved chemistry and aerosol representations and a new high-resolution wildfire emission database, which will improve remote sensing and modeling capabilities for wildfires, including their impact on climate change.
Publications, Presentations, and Patents
Chen, Yang, Stijn Hantson, Niels Andela, Shane R. Coffield, Casey A. Graff, Douglas C. Morton, Lesley E. Ott, et al. 2022. “California Wildfire Spread Derived Using VIIRS Satellite Observations and an Object-Based Tracking System.” Scientific Data 9 (1): 249. https://doi.org/10.1038/s41597-022-01343-0.
Lee, Hsiang-He. “Pyrocumulonimbus Events over British Columbia in 2017: An Ensemble Model Study on Injection Parameters and Climate Impacts of Fire Smoke in the Stratosphere.” Presented at the 102nd AMS Annual Meeting. Houston, TX. Jan. 2022.
Tang, Qi, Michael J. Prather, Juno Hsu, Hsiang-He Lee, Philip J. Cameron-Smith, Shaocheng Xie, Wuyin Lin, Mingxuan Wu, and Hailong Wang. “Initial Results from Interactive Atmospheric Chemistry in the Energy Exascale Earth System Model.” Presented at the 102nd AMS Annual Meeting. Houston, TX. Jan. 2022.