The GFDL Variable‐Resolution Global Chemistry‐Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

Author:

Lin Meiyun1ORCID,Horowitz Larry W.1ORCID,Zhao Ming1ORCID,Harris Lucas1ORCID,Ginoux Paul1ORCID,Dunne John1ORCID,Malyshev Sergey1ORCID,Shevliakova Elena1ORCID,Ahsan Hamza2,Garner Steve1,Paulot Fabien1ORCID,Pouyaei Arman3,Smith Steven J.2ORCID,Xie Yuanyu4ORCID,Zadeh Niki1ORCID,Zhou Linjiong3ORCID

Affiliation:

1. NOAA Geophysical Fluid Dynamics Laboratory Princeton NJ USA

2. Pacific Northwest National Laboratory Joint Global Change Research Institute College Park MD USA

3. Cooperative Institute for Modeling the Earth System Princeton University Princeton NJ USA

4. Princeton School of Public and International Affairs Princeton University Princeton NJ USA

Abstract

AbstractWe present a variable‐resolution global chemistry‐climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban‐to‐rural chemical regimes, mesoscale convective systems, and land‐surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi‐decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25‐km uniform‐resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal‐to‐diurnal cycles and extremes, notably reducing the central US dry‐and‐warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process‐level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land‐biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.

Publisher

American Geophysical Union (AGU)

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