Development of UI-WRF-Chem (v1.0) for the MAIA satellite mission: case demonstration

作者：Huanxin Zhang, Jun Wang, Nathan Janechek, Cui Ge, Meng Zhou, Lorena Castro García, Tong Sha, Yanyu Wang, Weizhi Deng, Zhixin Xue, Chengzhe Li, Lakhima Chutia, Yi Wang, Sebastian Val, James McDuffie, Sina Hasheminassab, Scott Gluck, D. J. Diner, Peter R. Colarco, Arlindo da Silva, Jhoon Kim · 发表于：Geoscientific model development · 年份：2025 · DOI：10.5194/gmd-18-9061-2025 · 被引用次数：1 · 研究领域：Atmospheric chemistry and aerosols、Atmospheric aerosols and clouds、Atmospheric and Environmental Gas Dynamics

Abstract. The Multi-Angle Imager for Aerosols (MAIA) satellite mission, to be jointly implemented by NASA and the Italian Space Agency, aims to study how different types of particulate matter (PM) pollution affect human health. The investigation will primarily focus on a discrete set of globally distributed Primary Target Areas (PTAs) containing major metropolitan cities, and will integrate satellite observations, ground observations, and chemical transport model (CTM) outputs (meteorology variables and PM concentrations) to generate maps of near-surface total and speciated PM within the PTAs. In addition, the MAIA investigation will provide satellite measurements of aerosols over a set of Secondary Target Areas (STAs), which are useful for studying air quality more broadly. For the CTM, we have developed a Unified Inputs (of initial and boundary conditions) for WRF-Chem (UI-WRF-Chem) modeling framework to support the MAIA satellite mission, building upon the standard WRF-Chem model. The framework includes newly developed modules and major enhancements that aim to improve model simulated meteorology variables, total and speciated PM concentrations as well as AOD. These developments include: (1) application of NASA GEOS FP and MERRA-2 data to provide both meteorological and chemical initial and boundary conditions for performing WRF-Chem simulations at a fine spatial resolution for both forecast and reanalysis modes; (2) application of GLDAS and NLDAS data to constrain surface...