P11R.12 RadOn: a new Doppler radar method to retrieve the clouds parameters

Friday, 28 October 2005
Alvarado F and Atria (Hotel Albuquerque at Old Town)
Julien Delanoë, UVSQ/CNRS/UPMC/IPSL, Guyancourt, France; and A. Protat and D. Bouniol

The knowledge of the cloud properties has been recently identified as a mandatory step to reach if the operational weather and climate change forecasts are to be improved. In the framework of the future space missions devoted to the monitoring of the microphysical, radiative, and dynamic properties of clouds at global scale using cloud radar and lidar combination (CLOUDSAT/CALIPSO as part of the Afternoon Train), there is a need for ground-based and airborne validation of the radar/lidar measurements and products from these space missions. The synergy between the two instruments is such that in moderately thick clouds the liquid/ice water content and effective radius of droplets/crystals can be accurately retrieved from these two measurements. The domain of application of the radar-lidar synergy is however limited to a given range of clouds (optical thickness less than 3, roughly). As an example, the prefrontal clouds and mixed-phase clouds, which are a very common in midlatitude regions, are never fully traversed by the lidar. In the present paper we therefore propose an original method complementary to the radar-lidar algorithm, which makes use of two measurements of a Doppler cloud radar (35 or 95 GHz), namely the radar reflectivity and the Doppler velocity in order to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction, from which the optical depth can be estimated. The RadOn method relies on the scaling of the Particle Size Distribution (PSD), N(D)=N0*F(Deq/Dm). The mean volume-weighted diameter (Dm) is derived from the terminal fall velocity of the particle (Vt), obtained using the radar Doppler velocity (Vd). N0* is derived from both the reflectivity and Dm assuming a modified gamma normalized PSD shape. Thus, knowing N (D), cloud parameters (ice water content, visible extinction, effective radius and optical depth) can be retrieved using direct relationships. Comparisons with the radar-lidar method in areas sampled by the two instruments will also be shown and discussed. This method has been systematically applied to the cloud radar measurements collected over the three instrumented sites of the European CloudNET project, in order to validate the representation of ice clouds in numerical weather prediction models and build up a cloud climatology.
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