Observation of aerosol–cloud interaction over New York City using synergetic ground-based remote sensing systems

Abstract

Using UV Raman Lidar for aerosol extinction (αext), and combining microwave radiometer-derived liquid water path (LWP) with multifilter rotating shadowband radiometer-derived cloud optical depth (τcod) to retrieve cloud droplet effective radius (Reff), we observe clear signatures of the Twomey aerosol indirect effect (IE) under certain specialized conditions. The aerosol–cloud index (ACI) or IE slope relating cloud droplet radius to aerosol loading is calculated and shown to be quantitatively consistent with theoretical constraints. To demonstrate consistency, we use both a neural network multiband (default) approach and a dual-channel (DC) approach for the LWP and observe that the DC approach is generally more robust with more successful retrievals leading to a reduction of error in our regression analysis. We also perform an uncertainty analysis of the IE regression slope taking into account the major sources of error in cloud property retrieval and demonstrate that only sufficiently high values of the IE slope should be observable. Finally, based on the results of multiple cases, we observe the importance of vertical wind uptake on the IE signature.