Journal Article

PreJuSER-21129

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Hindcast experiments of tropospheric composition during the summer 2010 fires over western Russia

Huijnen, V. ; Flemming, J. ; Kaiser, J. W. ; Inness, A. ; Leitao, J. ; Heil, A.FZJ* ; Eskes, H. J. ; Schultz, M. G.FZJ* ; Benedetti, A. ; Hadji-Lazaro, J. ; Dufour, G. ; Eremenko, M.

2012
EGU Katlenburg-Lindau

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Please use a persistent id in citations: http://hdl.handle.net/2128/7465  doi:10.5194/acp-12-4341-2012

Abstract: 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 (O-3) 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% (O-3) 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 O-3 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.

Keyword(s): J

Note: We thank N. Chubarova and B. Holben and their staff for maintaining the Moscow AERONET site which provided data used in this investigation. Some of the satellite data were downloaded from the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA). We acknowledge the free use of satellite retrieval data from www.temis.nl. D. Hurtmans, P. Coheur (ULB, Belgium) and C. Clerbaux, M. George (LATMOS, France) are acknowledged for scientific development, maintenance and distribution of the CO products from IASI, available from the Ether French atmospheric database (http://ether.ipsl.jussieu.fr). The work has been carried out within the MACC project, which is funded by the European Commission under the Seventh Research Framework Programme under contract number 218793.

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Contributing Institute(s):

1. Troposphäre (IEK-8)

Research Program(s):

1. Atmosphäre und Klima (P23)
2. MACC - Monitoring Atmospheric Composition and Climate (218793) (218793)

Appears in the scientific report 2012

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Database coverage:
; ; ; ; Current Contents - Social and Behavioral Sciences ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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