Tropospheric Chemistry in the Integrated Forecasting System of ECMWF

Title
Tropospheric Chemistry in the Integrated Forecasting System of ECMWF
Technical memorandum
Date Published
09/2014
Secondary Title
ECMWF Technical Memoranda
Number
730
Author
Johannes Flemming
V. Huijnen
J. Arteta
Anton Beljaars
A-M. Blechschmidt
A. Gaude
Antje Inness
Luke Jones
M.G. Schulz
O. Stein
A. Tsikerdekis
Publisher
ECMWF
Abstract A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol module of the IFS for atmospheric Composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system, in which the chemical transport model MOZART 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with IFS-MOZART. The chemical mechanism of C-IFS is an extended version of the CB05 chemical mechanism as implemented TM5 model and a parameterization for stratospheric ozone. CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning NO emissions are modelled in C-IFS using the detailed input of the IFS physics package. A one-year simulation for 2008 at a horizontal resolution of about 80 km is evaluated against ozone sondes, CO MOZAIC profiles, surface observations of ozone, CO, SO2 and NO2 as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. MACCity anthropogenic emissions and biomass burning emissions from the GFAS data set were used in the simulation. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, SO2 and upper tropospheric ozone and was of a similar accuracy for the other evaluated species. C-IFS (CB05) is about ten times more computationally efficient than IFS-MOZART.
URL https://www.ecmwf.int/en/elibrary/74497-tropospheric-chemistry-integrated-forecasting-system-ecmwf
DOI 10.21957/kkljbmrkh