Print Email Facebook Twitter Monitoring aerosol-cloud interactions at the CESAR Observatory in the Netherlands Title Monitoring aerosol-cloud interactions at the CESAR Observatory in the Netherlands Author Sarna, K. (TU Delft Atmospheric Remote Sensing) Russchenberg, H.W.J. (TU Delft Geoscience and Remote Sensing) Department Geoscience and Remote Sensing Date 2017-06-01 Abstract The representation of aerosol-cloud interaction (ACI) processes in 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 mitigated by using the observations from groundbased remote sensing instruments. In this paper we presented a direct application of the aerosol-cloud interaction monitoring technique (ACI monitoring). ACI monitoring is based on the standardised Cloudnet data stream, which provides measurements from ground-based remote sensing instruments working in synergy. For the data set collected at the CESAR Observatory in the Netherlands we calculate ACI metrics. We specifically use attenuated backscatter coefficient (ATB) for the characterisation of the aerosol properties and cloud droplet effective radius (re) and number concentration (Nd) for the characterisation of the cloud properties. We calculate two metrics: ACIr Dln(re)/ln(ATB) and ACIN Dln(Nd)/ln(ATB). The calculated values of ACIr range from 0.001 to 0.085, which correspond to the values reported in previous studies. We also evaluated the impact of the vertical Doppler velocity and liquid water path (LWP) on ACI metrics. The values of ACIr were highest for LWP values between 60 and 105 gm-2. For 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 updraught regime are considered. The method presented in this study allow for monitoring ACI daily and further aggregating daily data into bigger data sets. To reference this document use: http://resolver.tudelft.nl/uuid:706010a7-770d-4534-91b9-16c593c411b5 DOI https://doi.org/10.5194/amt-10-1987-2017 ISSN 1867-1381 Source Atmospheric Measurement Techniques, 10 (5), 1987-1997 Part of collection Institutional Repository Document type journal article Rights © 2017 K. Sarna, H.W.J. Russchenberg Files PDF amt_10_1987_2017.pdf 1.26 MB Close viewer /islandora/object/uuid:706010a7-770d-4534-91b9-16c593c411b5/datastream/OBJ/view