Articles | Volume 15, issue 8
https://doi.org/10.5194/acp-15-4093-2015
https://doi.org/10.5194/acp-15-4093-2015
Research article
 | 
21 Apr 2015
Research article |  | 21 Apr 2015

Atmospheric transport simulations in support of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE)

J. M. Henderson, J. Eluszkiewicz, M. E. Mountain, T. Nehrkorn, R. Y.-W. Chang, A. Karion, J. B. Miller, C. Sweeney, N. Steiner, S. C. Wofsy, and C. E. Miller

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Cited articles

ACIA: Impacts of a Warming Arctic: Arctic Climate Impact Assessment, Tech. rep., Arctic Council, 140 pp., available at: http://www.amap.no/documents/download/1058/ Impacts-of-a-Warming-Arctic (last access: 15 August 2014), 2004.
Barnes, E. A.: Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes, Geophys. Res. Lett., 40, 1–6, https://doi.org/10.1002/grl.50880, 2013.
Bellinger, T. E.: Evaluating the wind data from the automated surface observing system in Oak Ridge, Tennessee Is KOQT the calmest site in the US?, in: Nuclear Utility Meteorological Data Users Group Meeting, Nuclear Utility Meteorological Data Users Group, Oak Brook, IL, available at: http://www.ornl.gov/das/web/KOQTCalm.pdf (last access: 14 August 2014), 2011.
Bergamaschi, P., Houweling, S., Segers, A., Krol, M., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Wofsy, S. C., Kort, E. A., Sweeney, C., Schuck, T., Brenninkmeijer, C., Chen, H., Beck, V., and Gerbig, C.: Atmospheric CH4 in the first decade of the 21st cen- tury: inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements, J. Geophys. Res.-Atmos., 118, 7350–7369, https://doi.org/10.1002/jgrd.50480, 2013.
Brioude, J., Angevine, W. M., McKeen, S. A., and Hsie, E.-Y.: Numerical uncertainty at mesoscale in a Lagrangian model in complex terrain, Geosci. Model Dev., 5, 1127–1136, https://doi.org/10.5194/gmd-5-1127-2012, 2012.
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This paper describes the atmospheric modeling that underlies the science analysis for the NASA Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Summary statistics of the WRF meteorological model performance on a 3.3 km grid indicate good overall agreement with surface and radiosonde observations. The high quality of the WRF meteorological fields inspires confidence in their use to drive the STILT transport model for the purpose of computing surface influence fields (“footprints”).
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