Articles | Volume 9, issue 2
https://doi.org/10.5194/amt-9-711-2016
https://doi.org/10.5194/amt-9-711-2016
Research article
 | 
29 Feb 2016
Research article |  | 29 Feb 2016

Evaluation of cloud base height measurements from Ceilometer CL31 and MODIS satellite over Ahmedabad, India

Som Sharma, Rajesh Vaishnav, Munn V. Shukla, Prashant Kumar, Prateek Kumar, Pradeep K. Thapliyal, Shyam Lal, and Yashwant B. Acharya

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Cited articles

Albrecht, B. A., Fairall, C. W., Thomson, D. W., White, A. B., Snider, J. B., and Schubert, W. H.: Surface-based remote sensing of the observed and the adiabatic liquid water content of stratocumulus clouds, Geophys. Res. Lett., 17, 89–92, 1990.
Andrejczuk, M., Gadian, A., and Blyth, A.: Numerical simulations of stratocumulus cloud response to aerosol perturbation, Atmos. Res., 140, 76–84, 2014.
Bauer, P., Auligné, T., Bell, W., Geer, A., Guidard, V., Heilliette, S., Kazumori, M., Kim, M.J., Liu, E. H. C., McNally, A. P., and Macpherson, B.: Satellite cloud and precipitation assimilation at operational NWP centres, Q. J. Roy. Meteor. Soc., 137, 1934–1951, 2011.
Bhat, G. S. and Kumar, S.: Vertical structure of cumulonimbus towers and intense convective clouds over the South Asian region during the summer monsoon season, J. Geophys. Res.-Atmos., 120, 1710–1722, 2015.
Clothiaux, E. E., Ackerman, T. P., Mace, G. G., Moran, K. P., Marchand, R. T., Miller, M. A., and Martner, B. E.: Objective determination of cloud heights and radar reflectivities using a combination of active remote sensors at the ARM CART sites, J. Appl. Meteorol., 39, 645–665, 2000.
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Short summary
Cloud base height observations from Ceilometer CL31 were extensively studied during May 2013 to January 2015 over Ahmedabad (23.03°N, 72.54°E), India. Results indicate that the ceilometer is an excellent instrument to precisely detect low- and mid-level clouds, and that the MODIS satellite provides accurate retrieval of high-level clouds over this region.