Enhanced Air Quality Forecast System Through Chemical Data Assimilation: A Co-Design Effort with Local Stakeholders in Eastern and Southern Africa

In Eastern and Southern Africa (E&SA), air pollution poses a significant public health threat, causing over 23,000 premature deaths each year and worsening respiratory conditions for millions. We present our framework and result through a project funded by NASA SERVIR. Our regional air quality prediction system is a result of co-design and co-develop in collaboration with local stakeholders. By engaging with local stakeholders through in-person interactions and surveys, the project is specifically tailored to stakeholders’ identified needs, priorities, and challenges to address local environmental conditions and support effective planning and decision-making at the regional level.

To improve forecasting accuracy in this region, where air pollution monitoring infrastructure is limited, we are developing a framework within the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and associated chemical data assimilation (WRF-DA). This framework integrates VIIRS aerosol optical depth (AOD) along with meteorological forecasts. Our estimation for the background error is through the community Gridpoint Statistical Interpolation (GSI). Our meteorological inputs are based on the Global Forecast System (GFS), monthly estimates from CAMS are used for anthropogenic emission inventory, and real-time fire emissions from the Fire Inventory from NCAR (FINN) are incorporated to generate48-hour forecasts at 15 km grid spacing. Our initial simulations, focused on June 2022, include wildfires and dust storms in addition to local anthropogenic air pollution in the region. In this presentation we will discuss our framework and design approaches, the result of data assimilation, and evaluations of base and assimilation runs with ground and satellite observations, in addition to source attribution of pollution.