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Methodology for evaluating lateral boundary conditions in the regional chemical transport model MATCH (v5.5.0) using combined satellite and ground-based observations
SMHI, Research Department, Air quality.ORCID iD: 0000-0001-5695-1356
SMHI, Research Department, Atmospheric remote sensing.ORCID iD: 0000-0002-6717-8343
2015 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 8, no 11, 3747-3763 p.Article in journal (Refereed) PublishedText
Abstract [en]

Hemispheric transport of air pollutants can have a significant impact on regional air quality, as well as on the effect of air pollutants on regional climate. An accurate representation of hemispheric transport in regional chemical transport models (CTMs) depends on the specification of the lateral boundary conditions (LBCs). This study focuses on the methodology for evaluating LBCs of two moderately long-lived trace gases, carbon monoxide (CO) and ozone (O-3), for the European model domain and over a 7-year period, 2006-2012. The method is based on combining the use of satellite observations at the lateral boundary with the use of both satellite and in situ ground observations within the model domain. The LBCs are generated by the global European Monitoring and Evaluation Programme Meteorological Synthesizing Centre - West (EMEP MSC-W) model; they are evaluated at the lateral boundaries by comparison with satellite observations of the Terra-MOPITT (Measurements Of Pollution In The Troposphere) sensor (CO) and the Aura-OMI (Ozone Monitoring Instrument) sensor (O-3). The LBCs from the global model lie well within the satellite uncertainties for both CO and O-3. The biases increase below 700 hPa for both species. However, the satellite retrievals below this height are strongly influenced by the a priori data; hence, they are less reliable than at, e.g. 500 hPa. CO is, on average, underestimated by the global model, while O-3 tends to be overestimated during winter, and underestimated during summer. A regional CTM is run with (a) the validated monthly climatological LBCs from the global model; (b) dynamical LBCs from the global model; and (c) constant LBCs based on in situ ground observations near the domain boundary. The results are validated against independent satellite retrievals from the Aqua-AIRS (Atmospheric InfraRed Sounder) sensor at 500 hPa, and against in situ ground observations from the Global Atmospheric Watch (GAW) network. It is found that (i) the use of LBCs from the global model gives reliable in-domain results for O-3 and CO at 500 hPa. Taking AIRS retrievals as a reference, the use of these LBCs substantially improves spatial pattern correlations in the free troposphere as compared to results obtained with fixed LBCs based on ground observations. Also, the magnitude of the bias is reduced by the new LBCs for both trace gases. This demonstrates that the validation methodology based on using satellite observations at the domain boundary is sufficiently robust in the free troposphere. (ii) The impact of the LBCs on ground concentrations is significant only at locations in close proximity to the domain boundary. As the satellite data near the ground mainly reflect the a priori estimate used in the retrieval procedure, they are of little use for evaluating the effect of LBCs on ground concentrations. Rather, the evaluation of ground-level concentrations needs to rely on in situ ground observations. (iii) The improvements of dynamic over climatological LBCs become most apparent when using accumulated ozone over threshold 40 ppb (AOT40) as a metric. Also, when focusing on ground observations taken near the inflow boundary of the model domain, one finds that the use of dynamical LBCs yields a more accurate representation of the seasonal variation, as well as of the variability of the trace gas concentrations on shorter timescales.

Place, publisher, year, edition, pages
2015. Vol. 8, no 11, 3747-3763 p.
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
URN: urn:nbn:se:smhi:diva-1938DOI: 10.5194/gmd-8-3747-2015ISI: 000365980100014OAI: diva2:924781
Available from: 2016-04-29 Created: 2016-03-03 Last updated: 2016-04-29Bibliographically approved

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