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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 8, 1605-1616, 2015
http://www.atmos-meas-tech.net/8/1605/2015/
doi:10.5194/amt-8-1605-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
27 Mar 2015
Meso-scale modelling and radiative transfer simulations of a snowfall event over France at microwaves for passive and active modes and evaluation with satellite observations
V. S. Galligani1, C. Prigent1, E. Defer1, C. Jimenez3, P. Eriksson2, J.-P. Pinty4, and J.-P. Chaboureau4 1Laboratoire d'Etudes du Rayonnement et de la Matière en Astrophysique, CNRS, Observatoire de Paris, Paris, France
2Department of Earth and Space Sciences, Chalmers University of Technology, Gothenburg, Sweden
3Estellus, Paris, France
4Laboratoire d'Aérologie, UPS/CNRS, Toulouse, France
Abstract. Microwave passive and active radiative transfer simulations are performed with the Atmospheric Radiative Transfer Simulator (ARTS) for a mid-latitude snowfall event, using outputs from the Meso-NH mesoscale cloud model. The results are compared to the corresponding microwave observations available from MHS and CloudSat. The spatial structures of the simulated and observed brightness temperatures show an overall agreement since the large-scale dynamical structure of the cloud system is reasonably well captured by Meso-NH. However, with the initial assumptions on the single-scattering properties of snow, there is an obvious underestimation of the strong scattering observed in regions with large frozen hydrometeor quantities. A sensitivity analysis of both active and passive simulations to the microphysical parametrizations is conducted. Simultaneous analysis of passive and active calculations provides strong constraints on the assumptions made to simulate the observations. Good agreements are obtained with both MHS and CloudSat observations when the single-scattering properties are calculated using the "soft sphere" parametrization from Liu (2004), along with the Meso-NH outputs. This is an important step toward building a robust data set of simulated measurements to train a statistically based retrieval scheme.

Citation: Galligani, V. S., Prigent, C., Defer, E., Jimenez, C., Eriksson, P., Pinty, J.-P., and Chaboureau, J.-P.: Meso-scale modelling and radiative transfer simulations of a snowfall event over France at microwaves for passive and active modes and evaluation with satellite observations, Atmos. Meas. Tech., 8, 1605-1616, doi:10.5194/amt-8-1605-2015, 2015.
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