Atmospheric Composition and Numerical Weather Forecasting

Co-sponsored by WMO and CAMS

Convener: Johannes Flemming | Co-conveners: Alexander Baklanov, Georg Grell, Sara Basart

The weather and atmospheric composition (AC) are closely related. Still, Numerical Weather Prediction (NWP) from from the short-range to the seasonal range often only apply simplified presentations of aerosols, greenhouse gases and reactive gases, and NWP and AC forecasting is operated independently. However, recognizing the scientific and operational benefits of combining NWP and AC forecasting and data assimilation, integrated AC-NWP systems for global, regional, and local applications have been developed.

We invite contributions on all aspects of forecasting and data assimilation of aerosols, reactive gases, greenhouse gases, and weather or stratospheric dynamics across different time scales. Our focus is on the scientific, computational, and societal advantages of such integrated approaches. Specifically, but not exclusively, we invite papers addressing the following topics:

a) Improved NWP from short timescales to seasonal scales due to feedbacks between aerosols, chemistry and radiation and cloud physics,

b) Parameterization of weather-composition feedbacks in radiation and cloud physics,

c) Impact of the uncertainty of meteorological simulations on AC predictions,

d) Advancements in designing and developing operational coupled NWP-AC prediction systems,

e) Satellite retrievals of meteorological variables in the presence of aerosols,

f) Data assimilation developments for AC and NWP,

g) Forecasting of stratospheric composition and dynamics after large volcanic eruptions such as the Hunga-Tonga,

h) Combined impact of environmental hazards on society, such as air pollution and high-impact weather, wildfires, dust storms and the underlying meteorological factors,

i) Evaluation, validation, and applications of NWP-AC predication systems.

This Session is organized in cooperation with the Copernicus Atmosphere Monitoring Service (CAMS) and the Global Air Quality Forecasting and Information Systems (GAFIS) initiative of the WMO Global Atmosphere Watch (GAW) Program.