The Goddard Earth Observing System composition forecast (GEOS-CF) system
is a high-resolution (0.25 degree) global constituent prediction system
from NASA’s Global Modeling and Assimilation Office (GMAO). GEOS-CF
offers a new tool for atmospheric chemistry research, with the goal to
supplement NASA’s broad range of space-based and in-situ observations
and to support flight campaign planning, support of satellite
observations, and air quality research. GEOS-CF expands on the GEOS
weather and aerosol modeling system by introducing the GEOS-Chem
chemistry module to provide analyses and 5-day forecasts of atmospheric
constituents including ozone (O3), carbon monoxide (CO),
nitrogen dioxide (NO2), and fine particulate matter
(PM2.5). The chemistry module integrated in GEOS-CF is identical to the
offline GEOS-Chem model and readily benefits from the innovations
provided by the GEOS-Chem community.
Evaluation of GEOS-CF against satellite, ozonesonde and surface
observations show realistic simulated concentrations of
O3, NO2, and CO, with normalized mean
biases of -0.1 to -0.3, normalized root mean square errors (NRMSE)
between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against
surface observations highlight the successful representation of air
pollutants under a variety of meteorological conditions, yet also
highlight current limitations, such as an overprediction of summertime
ozone over the Southeast United States. GEOS-CF v1.0 generally
overestimates aerosols by 20-50% due to known issues in GEOS-Chem
v12.0.1 that have been addressed in later versions.
The 5-day hourly forecasts have skill scores comparable to the analysis.
Model skills can be improved significantly by applying a bias-correction
to the surface model output using a machine-learning approach.