Articles | Volume 17, issue 9
https://doi.org/10.5194/acp-17-5973-2017
https://doi.org/10.5194/acp-17-5973-2017
Research article
 | 
16 May 2017
Research article |  | 16 May 2017

Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

Yinghui Liu, Matthew D. Shupe, Zhien Wang, and Gerald Mace

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Cited articles

Blanchard, Y., Pelon, J., Eloranta, E. W., Moran, K. P., Delanoë, J., and Sèze, G.: A synergistic analysis of cloud cover and vertical distribution from A-Train and ground-based sensors over the high Arctic station EUREKA from 2006 to 2010, J. Appl. Meteorol. Climatol., 53, 2553–2570, 2014.
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhan, X. Y.: Clouds and aerosols, Climate Change 2013: The Physical Science Basis, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, 571–657, https://doi.org/10.1017/CBO9781107415324.016, 2013.
Devasthale, A., Tjernstrom, M., Karlsson, K.-G., Thomas, M. A., Jones, C., Sedlar, J., and Omar, A. H.: The vertical distribution of thin features over the Arctic analysed from CALIPSO observations, Tellus B, 63, 77–85, https://doi.org/10.1111/j.1600-0889.2010.00516.x, 2011.
Devasthale, A., Tjernström, M., Caian, M., Thomas, M. A., Kahn, B. H., and Fetzer, E. J.: Influence of the Arctic Oscillation on the vertical distribution of clouds as observed by the A-Train constellation of satellites, Atmos. Chem. Phys., 12, 10535–10544, https://doi.org/10.5194/acp-12-10535-2012, 2012.
Francis, J. A. and Vavrus, S. J.: Evidence linking Arctic amplification to extreme weather in mid-latitudes, Geophys. Res. Lett., 39, L06801, https://doi.org/10.1029/2012GL051000, 2012.
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Short summary
Detailed and accurate vertical distributions of cloud properties are essential to accurately calculate the surface radiative flux and to depict the mean climate state, and such information is more desirable in the Arctic due to its recent rapid changes and the challenging observation conditions. This study presents a feasible way to provide such information by blending cloud observations from surface and space-based instruments with the understanding of their respective strength and limitations.
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