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Meteorological and air quality forecasting using the WRF-STEM model during the 2008 ARCTAS field campaign

D'Allura, Alessio and Kulkarni, Sarika and Carmichael, Gregory R. and Finardi, Sandro and Adhikari, Bhupesh and Wei, Chao and Streets, David and Zhang, Qiang and Pierce, Robert B. and Al-Saadi, Jassim A. and Diskin, Glenn and Wennberg, Paul (2011) Meteorological and air quality forecasting using the WRF-STEM model during the 2008 ARCTAS field campaign. Atmospheric Environment, 45 (38). pp. 6901-6910. ISSN 1352-2310 http://resolver.caltech.edu/CaltechAUTHORS:20120103-153610191

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Abstract

In this study, the University of Iowa’s Chemical Weather Forecasting System comprising meteorological predictions using the WRF model, and off-line chemical weather predictions using tracer and full chemistry versions of the STEM model, designed to support the flight planning during the ARCTAS 2008 mission is described and evaluated. The system includes tracers representing biomass burning and anthropogenic emissions from different geographical emissions source regions, as well as air mass age indicators. We demonstrate how this forecasting system was used in flight planning and in the interpretation of the experimental data obtained through the case study of the summer mission ARCTAS DC-8 flight executed on July 9 2008 that sampled near the North Pole. The comparison of predicted meteorological variables including temperature, pressure, wind speed and wind direction against the flight observations shows that the WRF model is able to correctly describe the synoptic circulation and cloud coverage in the Arctic region The absolute values of predicted CO match the measured CO closely suggesting that the STEM model is able to capture the variability in observations within the Arctic region. The time–altitude cross sections of source region tagged CO tracers along the flight track helped in identifying biomass burning (from North Asia) and anthropogenic (largely China) as major sources contributing to the observed CO along this flight. The difference between forecast and post analysis biomass burning emissions can lead to significant changes (∼10–50%) in primary CO predictions reflecting the large uncertainty associated with biomass burning estimates and the need to reduce this uncertainty for effective flight planning.


Item Type:Article
Additional Information:© 2011 Elsevier Ltd. Received 11 August 2010; revised 12 February 2011; Accepted 14 February 2011. Available online 12 March 2011. We would like to thank the ARCTAS Measurement Team for permission in using the measurements, CGRER and the University of Iowa. This work was supported in part by NASA grant NNX08AH56G. We would like to acknowledge Space Science and Engineering Center, University of Wisconsin-Madison, WI, USA for providing the cloud cover satellite composite images centered over the Arctic region.
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Funding AgencyGrant Number
NASANNX08AH56G
Subject Keywords:ARCTAS; Arctic; Air quality forecasting; Chemical weather
Record Number:CaltechAUTHORS:20120103-153610191
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20120103-153610191
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Official Citation:Alessio D’Allura, Sarika Kulkarni, Gregory R. Carmichael, Sandro Finardi, Bhupesh Adhikary, Chao Wei, David Streets, Qiang Zhang, Robert B. Pierce, Jassim A. Al-Saadi, Glenn Diskin, Paul Wennberg, Meteorological and air quality forecasting using the WRF–STEM model during the 2008 ARCTAS field campaign, Atmospheric Environment, Volume 45, Issue 38, December 2011, Pages 6901-6910, ISSN 1352-2310, 10.1016/j.atmosenv.2011.02.073. (http://www.sciencedirect.com/science/article/pii/S1352231011002573)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:28634
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:04 Jan 2012 15:34
Last Modified:04 Jan 2012 15:34

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