Evaluating modelled tropospheric columns of CH4, CO, and O3 in the Arctic using ground-based Fourier transform infrared (FTIR) measurements
Journal article, 2024
This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model-measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0-7km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by -9.7% for CH4, -21% for CO, and -18% for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15% of the model-location comparisons.
Author
Victoria A. Flood
University of Toronto
Kimberly Strong
University of Toronto
Cynthia H. Whaley
Environment Canada
Kaley A. Walker
University of Toronto
T. Blumenstock
Karlsruhe Institute of Technology (KIT)
J. W. Hannigan
National Center for Atmospheric Research
Johan Mellqvist
Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing
J. Notholt
Universität Bremen
Mathias Palm
Universität Bremen
Amelie N. Röhling
Karlsruhe Institute of Technology (KIT)
Stephen Arnold
University of Leeds
S.R. Beagley
Environment Canada
Rong You Chien
Tickle College of Engineering
Jesper Christensen
Aarhus University
Makoto Deushi
Meteorological Research Institute
Srdjan Dobricic
Joint Research Centre (JRC), European Commission
Xinyi Dong
Tickle College of Engineering
Joshua S. Fu
Oak Ridge National Laboratory
Tickle College of Engineering
M. Gauss
Norwegian Meteorological Institute
Wanmin Gong
Environment Canada
J. Langner
SMHI
Kathy S. Law
Pierre and Marie Curie University (UPMC)
Louis Marelle
Pierre and Marie Curie University (UPMC)
Tatsuo Onishi
Pierre and Marie Curie University (UPMC)
Naga Oshima
Meteorological Research Institute
David A. Plummer
Environment Canada
Luca Pozzoli
Joint Research Centre (JRC), European Commission
Finscons Group
Jean Christophe Raut
Pierre and Marie Curie University (UPMC)
Manu Anna Thomas
Finscons Group
S. Tsyro
Norwegian Meteorological Institute
Steven Turnock
Met Office
University of Leeds
Atmospheric Chemistry and Physics
1680-7316 (ISSN) 1680-7324 (eISSN)
Vol. 24 2 1079-1118Integrated Global Observing Systems for Persistent Pollutants (IGOSP)
European Commission (EC) (EC/H2020/689443), 2017-09-01 -- 2020-08-31.
Driving Forces
Sustainable development
Subject Categories
Meteorology and Atmospheric Sciences
DOI
10.5194/acp-24-1079-2024