Articles | Volume 8, issue 3
https://doi.org/10.5194/amt-8-1537-2015
https://doi.org/10.5194/amt-8-1537-2015
Research article
 | 
24 Mar 2015
Research article |  | 24 Mar 2015

Cloud thermodynamic phase detection with polarimetrically sensitive passive sky radiometers

K. Knobelspiesse, B. van Diedenhoven, A. Marshak, S. Dunagan, B. Holben, and I. Slutsker

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Cited articles

Auer Jr., A. H. and Veal, D. L.: The dimension of ice crystals in natural clouds, J. Atmos. Sci., 27, 919–926, 1970.
Baran, A. J.: A review of the light scattering properties of cirrus, J. Quant. Spectrosc. Ra., 110, 1239–1260, 2009.
Barker, H. W. and Marshak, A.: Inferring optical depth of broken clouds above green vegetation using surface solar radiometric measurements, J. Atmos. Sci., 58, 2989–3006, 2001.
Bi, L., Yang, P., Liu, C., Yi, B., Baum, B. A., van Diedenhoven, B., and Iwabuchi, H.: Assessment of the accuracy of the conventional ray-tracing technique: Implications in remote sensing and radiative transfer involving ice clouds, J. Quant. Spectrosc. Ra., 146, 158–174, http://www.sciencedirect.com/science/article/pii/S0022407314001332, 2014.
Campos, E. F., Ware, R., Joe, P., and Hudak, D.: Monitoring water phase dynamics in winter clouds, Atmos. Res., 147, 86–100, 2014.
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We test if ground-based sun photometers/radiometers like those in the Aerosol Robotic Network (AERONET) can use the polarization sensitivity of some instruments for improved cloud optical property retrieval. Our radiative transfer simulations show that the direction of linear polarization indicates cloud thermodynamic phase for optically thin clouds. In practice, data analysis shows a weak response with AERONET instruments, most likely due to noise and orientation/calibration ambiguity.