Training Materials and Best Practices for Chemical Weather/Air Quality Forecasting

Atmospheric pollution is determined by emissions, chemical transformation, and removal processes, and the latter two are strongly controlled by meteorological processes. Therefore, adequate meteorological forecasting is prerequisite in AQF, and NWP is thus the key and necessary element of any AQF system. For this reason, it is a core task for the World Meteorological Organization (WMO) and NMHSs to engage in CW-AQF related activities, and examples of well-established activities include the volcanic ash advisory and assessment centers (VAACs) and the WMO Emergency Response Activities Programme for nuclear emergencies and extended to other non-nuclear airborne hazardous substances (e.g., dust, smog, volcanic ash, chemicals, bio-aerosols including pollen).

Recognizing the urgent need for the successful implementation and application of 3-D numerical models for operational CW-AQF, WMO in a collaborative effort of the Education and Training Office and the Global Atmosphere Watch Program, with the Scientific Advisory Groups on Applications (GAW SAG APP) and Urban Research Meteorology and Environment (GURME), initiated the development of guidance materials for training and demonstrating best practices for CW-AQF using 3-D numerical models in late 2017. The overarching goals of this initiative are to provide readers with the best existing experience from NMHSs and the academic community, and to build the scientific capacity of researchers and operational meteorologists in developing countries. This goal will be achieved by bridging research and operations and by making sustained contributions towards the implementation of relevant policy and decision support aimed at improving quality of life through enhancing the science-policy interface. The specific objectives are to (i) help forecasters worldwide, especially those in developing  countries, with the use of 3-D CW-AQF models and NWP for operational forecasting, early warning, policymaking, providing actionable information to reduce air pollution and associated human health effects and climate co-benefits in the most appropriate and efficient way; (ii) provide practical information about the best operational CW-AQF practices and standardized procedures for the successful deployment and application, and (iii) prepare materials that could be adapted for training by NMHSs, WMO training centers, and other users from environmental authorities and academic institutions.

The publication is developed as an effective, long-lasting educational and outreach tool to cover training materials and best practices for 3-D CW-AQF. It includes 12 chapters and 24 demonstration cases. It will target both entry-level and more experienced forecasters, and benefit the meteorological and air quality related communities, such as climate and public health communities. It includes fundamentals of CW-AQF and advanced materials such as applications of computational fluid dynamics (CFDs), chemical data assimilation (CDA), and inverse modeling for 3-D CW-AQF. This is the first version of the publication. It will be updated in the future to reflect the state-of-the-science development and advancement of CW-AQF.