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

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doi:10.5194/amt-2016-262
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
02 Sep 2016
Review status
A revision of this discussion paper for further review has not been submitted.
Monitoring Aerosol–Cloud Interactions at CESAR Observatory in the Netherlands
K. Sarna and H. W. J. Russchenberg TU Delft Climate Institute, Faculty of Civil Engineering and Geotechnology, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, the Netherlands
Abstract. The representation of aerosol–cloud interactions (ACI) processes in the climate models, although long studied, still remains the source of high uncertainty. Very often there is a mismatch between the scale of observations used for ACI quantification and the ACI process itself. This can be changed by using the observations from ground-based remote sensing instruments. In this paper we presented a direct application of the Aerosol–Cloud Interactions monitoring technique (ACI monitoring). ACI monitoring is based on the standardized Cloudnet data stream, which provides measurements from ground-based remote sensing instruments working in synergy. For the dataset collected at the CESAR Observatory in the Netherlands we calculate ACI metrics. We use specifically attenuated backscatter coefficient (ATB) for the characterisation of the aerosol properties and cloud droplets effective radius (re) and number concentration (Nd) for the characterisation of the cloud properties. We calculate two metrics: ACIr = ln(re)/ln(ATB) and ACIN = ln(Nd)/ln(ATB). The calculated values of ACIr were ranging from 0.016 to 0.17, which corresponds to the values reported in previous studies. We also evaluated impact of the updraft and liquid water path (LWP) on ACI metrics. The values of ACIr were highest for the LWP between 50 and 100 g/m2 . For the higher LWP other processes, such as collision and coalescence, seem to be dominant and obscure the ACI processes. We also saw that the values of ACIr are higher when only data points located in the updraft area are considered. The method presented in this study enables monitoring aerosol–cloud interactions daily and further aggregating daily data into bigger datasets.

Citation: Sarna, K. and Russchenberg, H. W. J.: Monitoring Aerosol–Cloud Interactions at CESAR Observatory in the Netherlands, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-262, in review, 2016.
K. Sarna and H. W. J. Russchenberg
Interactive discussionStatus: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'Review', Anonymous Referee #2, 29 Sep 2016 Printer-friendly Version 
AC2: 'Response to Anonymous Referee #2', Karolina Sarna, 23 Dec 2016 Printer-friendly Version 
 
RC2: 'Review', Anonymous Referee #1, 29 Sep 2016 Printer-friendly Version 
AC1: 'Response to Anonymous Referee #1', Karolina Sarna, 22 Dec 2016 Printer-friendly Version 
K. Sarna and H. W. J. Russchenberg
K. Sarna and H. W. J. Russchenberg

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