Towards seamless prediction of Earth system feedbacks to air quality under climate change: Challenges and new modeling capabilities
- 1NOAA Geophysical Fluid Dynamics Laboratory, Princeton, USA (meiyun.lin@noaa.gov)
- 2Cooperative Institute for Modeling the Earth System, Princeton University, Princeton, NJ, USA
- 3Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
With rising temperatures and shifting rainfall patterns, compound drought and heatwaves are increasing in frequency and intensity under climate change. Future air quality is vulnerable to large land-biosphere feedbacks, such as reduced ozone removal by drought-stressed vegetation, increasing wildfire and dust emissions, and varying BVOC emissions from plants amidst changing land cover. These interactions are poorly represented in the CMIP6 global chemistry-climate models, limiting our ability to accurately predict future air quality and design effective mitigation strategies. In this presentation, we will discuss recent and ongoing research at NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) to address these challenges. Specifically, we present a new variable-resolution global chemistry-climate model (AM4VR) designed for a seamless prediction of global dimensions to US climate and air quality across times scales from days to decades, with particular focus on integrating physical, chemical, and biological components. In contrast with the global models contributing to CMIP6, AM4VR features more than 10 times finer spatial resolution over the contiguous US (13 km), allowing it to better represent US climate mean patterns and variability, including hydroclimate extremes, drought, fire weather, and air pollution meteorology over complex terrain. With the resolution gradually reducing to 25-50 km over Europe and 50-100 km over Asia, we achieve multi-decadal simulations with prescribed SSTs at 50% of the computational cost for a 25 km uniform-resolution grid. With increased interactivity of atmospheric composition with vegetation dynamics and reactive nitrogen partitioning in wildfire plumes, AM4VR features much improved representation of US air quality extremes during compound events. We are conducting a suite of century-long (2000-2100) AMIP simulations under SSP1-2.6, SSP2-4.5 and the Global Methane Pledge to assess compounding climate and air pollution risks under 1.5, 2.0, and 3.0 °C of warming.
How to cite: Lin, M., Horowitz, L., Dunne, J., Ginoux, P., Malyshev, S., Shevliakova, E., Harris, L., Zhao, M., Pouyaei, A., and Smith, S.: Towards seamless prediction of Earth system feedbacks to air quality under climate change: Challenges and new modeling capabilities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10071, https://doi.org/10.5194/egusphere-egu24-10071, 2024.
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