Constraining the Mechanistic Effects of Spatial Resolution on Global Air Quality Modeling

本项目的研究人员将进行一系列的化学输运模型模拟，以研究由于粗糙的水平分辨率而在模型模拟中产生的误差。许多用于研究大气化学的现代化学输运模型在计算上是昂贵的，因此许多研究小组继续依赖于相对粗糙的分辨率模拟。然而，最近的进步使更高的空间分辨率模拟成为可能，该项目的研究人员将研究不同空间分辨率产生的模型模拟中的偏差和差异。在这个项目中获得的知识将增强我们模拟和研究小尺度大气化学现象的能力，很可能在未来增加对高分辨率模型的信心和使用，并将使更多的大气化学研究与当地和区域尺度的社区相关。在这项提议的工作中，研究人员将利用GEOS-Chem （GCHP）的高性能实现，该实现最近开发了分布式内存并行化，可以实现这种类型的规模变化研究。本研究的主要目标有三个：(1)量化和解释非线性化学的分辨率依赖性机制，重点是氮氧化物、臭氧和硝酸；(2)以硝酸盐气溶胶为重点，量化和解释排放分离的分辨率依赖性机制；(3)量化和解释由于空间分辨率不足或过于粗糙而导致的模拟空气质量趋势的误差。因此，这项工作的成功可能会对GEOS-Chem、大气化学和气候化学社区以及政策制定者产生积极影响，他们可以利用这些模拟结果在自己的社区内做出有关空气质量的决策。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The investigators in this project will perform a series of chemical transport model simulations in order to study the errors that arise in model simulations due to coarse horizontal resolution. Many modern chemical transport models, which are used to study atmospheric chemistry in our atmosphere, are computationally expensive, and as such many research groups continue to rely on relatively coarse resolution simulations. However, recent advancements have enabled higher spatial resolution simulations, and the investigators in this project will study biases and differences in model simulations that arise from different spatial resolutions. The knowledge gained in this project will enhance our ability to simulate and study smaller-scale atmospheric chemistry phenomena, is likely to increase confidence in and usage of high-resolution models in the future, and would enable more atmospheric chemistry research relevant to communities at the local and regional scale. In this proposed work, the investigators will utilize a high-performance implementation of GEOS-Chem (GCHP) that has recently developed distributed-memory parallelization that enables just this type of scale-varying research. There are three primary research goals in this proposed work: (1) to quantify and interpret the mechanistic resolution-dependence of non-linear chemistry with a focus on nitrogen oxide, ozone, and nitric acid; (2) to quantify and interpret the mechanistic resolution-dependence of emission segregation with a focus on nitrate aerosols; and (3) to quantify and interpret the errors in simulated air quality trends due to inadequate or too-coarse spatial resolution. Success in this work is therefore likely to have a positive impact on the GEOS-Chem, atmospheric chemistry, and climate-chemistry communities, as well as policy makers that could use these simulation results to make decisions regarding air quality within their own communities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.