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Atmosphere 2018, 9(5), 169; https://doi.org/10.3390/atmos9050169

Evaluation of Fog and Low Stratus Cloud Microphysical Properties Derived from In Situ Sensor, Cloud Radar and SYRSOC Algorithm

1
Institut Pierre-Simon Laplace, École Polytechnique, UVSQ, Université Paris-Saclay, 91128 Palaiseau, France
2
Institut Pierre Simon Laplace, École Polytechnique, CNRS, Université Paris-Saclay, 91128 Palaiseau, France
3
Laboratoire de Météorologie Dynamique, École Polytechnique, Université Paris-Saclay, 91128 Palaiseau, France
4
Laboratoire Atmosphères, Milieux, Observations Spatiales/UVSQ/CNRS/UPMC, 78280 Guyancourt, France
5
LPC2E-CNRS/Université d’Orléans, 3A Avenue de la Recherche Scientifique, 45071 Orléans, France
6
Centre for Climate and Air Pollution Studie, National University of Ireland, Galway H91 CF50, Ireland
*
Author to whom correspondence should be addressed.
Received: 15 March 2018 / Revised: 23 April 2018 / Accepted: 23 April 2018 / Published: 2 May 2018
(This article belongs to the Section Climatology and Meteorology)
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Abstract

The microphysical properties of low stratus and fog are analyzed here based on simultaneous measurement of an in situ sensor installed on board a tethered balloon and active remote-sensing instruments deployed at the Instrumented Site for Atmospheric Remote Sensing Research (SIRTA) observatory (south of Paris, France). The study focuses on the analysis of 3 case studies where the tethered balloon is deployed for several hours in order to derive the relationship between liquid water content (LWC), effective radius (Re) and cloud droplet number concentration (CDNC) measured by a light optical aerosol counter (LOAC) in situ granulometer and Bistatic Radar System for Atmospheric Studies (BASTA) cloud radar reflectivity. The well-known relationship Z = α × (LWC)β has been optimized with α ϵ [0.02, 0.097] and β ϵ [1.91, 2.51]. Similar analysis is done to optimize the relationship Re = f(Z) and CDNC = f(Z). Two methodologies have been applied to normalize the particle-size distribution measured by the LOAC granulometer with a visible extinction closure (R² ϵ [0.73, 0.93]) and to validate the LWC profile with a liquid water closure using the Humidity and Temperature Profiler (HATPRO) microwave radiometer (R² ϵ [0.83, 0.91]). In a second step, these relationships are used to derive spatial and temporal variability of the vertical profile of LWC, Re and CDNC starting from BASTA measurement. Finally, the synergistic remote sensing of clouds (SYRSOC) algorithm has been tested on three tethered balloon flights. Generally, SYRSOC CDNC and Re profiles agreed well with LOAC in situ and BASTA profiles for the studied fog layers. A systematic overestimation of LWC by SYRSOC in the top half of the fog layer was found due to fog processes that are not accounted for in the cloud algorithm SYRSOC. View Full-Text
Keywords: fog; cloud radar; microphysical properties fog; cloud radar; microphysical properties
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Dupont, J.-C.; Haeffelin, M.; Wærsted, E.; Delanoe, J.; Renard, J.-B.; Preissler, J.; O’Dowd, C. Evaluation of Fog and Low Stratus Cloud Microphysical Properties Derived from In Situ Sensor, Cloud Radar and SYRSOC Algorithm. Atmosphere 2018, 9, 169.

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