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

Authors :
Dupont, Jean-Charles
Haeffelin, Martial
Wærsted, Eivind
Delanoe, Julien
Renard, Jean-Baptiste
Preissler, Jana
O’Dowd, Colin
Laboratoire de Météorologie Dynamique (UMR 8539) (LMD)
Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris
École normale supérieure - Paris (ENS Paris)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
SPACE - LATMOS
Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS)
Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)
Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E)
Observatoire des Sciences de l'Univers en région Centre (OSUC)
Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES)
National University of Ireland [Galway] (NUI Galway)
Source :
Atmosphere, Atmosphere, MDPI 2018, 9 (5), pp.169. ⟨10.3390/atmos9050169⟩, Atmosphere, Vol 9, Iss 5, p 169 (2018)
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

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.

Details

Language :
English
ISSN :
20734433
Database :
OpenAIRE
Journal :
Atmosphere, Atmosphere, MDPI 2018, 9 (5), pp.169. ⟨10.3390/atmos9050169⟩, Atmosphere, Vol 9, Iss 5, p 169 (2018)
Accession number :
edsair.dedup.wf.001..1e6d399f6bb677da7a5dc05259ed7bda