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| Titel |
Hindcast experiments of tropospheric composition during the summer 2010 fires over western Russia |
| VerfasserIn |
V. Huijnen, J. Flemming, J. W. Kaiser, A. Inness, J. Leitão, A. Heil, H. J. Eskes, M. G. Schultz, A. Benedetti, J. Hadji-Lazaro, G. Dufour, M. Eremenko |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 9 ; Nr. 12, no. 9 (2012-05-15), S.4341-4364 |
| Datensatznummer |
250011138
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| Publikation (Nr.) |
 copernicus.org/acp-12-4341-2012.pdf |
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| Zusammenfassung |
The severe wildfires in western Russia during July–August 2010 coincided
with a strong heat wave and led to large emissions of aerosols and trace
gases such as carbon monoxide (CO), hydrocarbons and nitrogen oxides into
the troposphere. This extreme event is used to evaluate the ability of the
global MACC (Monitoring Atmospheric Composition and Climate) atmospheric
composition forecasting system to provide analyses of large-scale pollution
episodes and to test the respective influence of a priori emission
information and data assimilation on the results. Daily 4-day hindcasts were
conducted using assimilated aerosol optical depth (AOD), CO, nitrogen
dioxide (NO2) and ozone (O3) data from a range of satellite
instruments. Daily fire emissions were used from the Global Fire
Assimilation System (GFAS) version 1.0, derived from satellite fire
radiative power retrievals.
The impact of accurate wildfire emissions is dominant on the composition in
the boundary layer, whereas the assimilation system influences
concentrations throughout the troposphere, reflecting the vertical
sensitivity of the satellite instruments. The application of the daily fire
emissions reduces the area-average mean bias by 63% (for CO), 60%
(O3) and 75% (NO2) during the first 24 h with respect to
independent satellite observations, compared to a reference simulation with
a multi-annual mean climatology of biomass burning emissions. When initial
tracer concentrations are further constrained by data assimilation, biases
are reduced by 87, 67 and 90%. The forecast accuracy, quantified by the
mean bias up to 96 h lead time, was best for all compounds when using
both the GFAS emissions and assimilation. The model simulations suggest an
indirect positive impact of O3 and CO assimilation on hindcasts of
NO2 via changes in the oxidizing capacity.
However, the quality of local hindcasts was strongly dependent on the
assumptions made for forecasted fire emissions. This was well visible from a
relatively poor forecast accuracy quantified by the root mean square error,
as well as the temporal correlation with respect to ground-based CO total
column data and AOD. This calls for a more advanced method to forecast fire
emissions than the currently adopted persistency approach.
The combined analysis of fire radiative power observations, multiple trace
gas and aerosol satellite observations, as provided by the MACC system,
results in a detailed quantitative description of the impact of major fires
on atmospheric composition, and demonstrate the capabilities for the
real-time analysis and forecasts of large-scale fire events. |
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