Six years of surface remote sensing of stratiform warm clouds in marine and continental air over Mace Head, Ireland

Abstract

A total of 118 stratiform water clouds were observed by ground‐based remote sensing instruments at the Mace Head Atmospheric Research Station on the west coast of Ireland from 2009 to 2015. Microphysical and optical characteristics of these clouds were studied as well as the impact of aerosols on these properties. Microphysical and optical cloud properties were derived using the algorithm SYRSOC (SYnergistic Remote Sensing Of Clouds). Ground‐based in situ measurements of aerosol concentrations and the transport path of air masses at cloud level were investigated as well. The cloud properties were studied in dependence of the prevailing air mass at cloud level and season. We found higher cloud droplet number concentrations (CDNC) and smaller effective radii (reff) with greater pollution. Median CDNC ranged from 60 cm−3 in marine air masses to 160 cm−3 in continental air. Median reff ranged from 8 μm in polluted conditions to 10 μm in marine air. Effective droplet size distributions were broader in marine than in continental cases. Cloud optical thickness (COT) and albedo were lower in cleaner air masses and higher in more polluted conditions, with medians ranging from 2.1 to 4.9 and 0.22 to 0.39, respectively. However, calculation of COT and albedo was strongly affected by liquid water path (LWP) and departure from adiabatic conditions. A comparison of SYRSOC results with MODIS (Moderate‐Resolution Imaging Spectroradiometer) observations showed large differences for LWP and COT but good agreement for reff with a linear fit with slope near 1 and offset of −1 μm.

Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions

“…The results presented here indicate that the cloud droplet number concentration appears to be more sensitive to changes in aerosols in models than observations, and these results are in agreement with many previous studies found in the literature (e.g. Ban-Weiss et al, 2014;Quaas et al, 2004;McComiskey and Feingold, 2012;Penner et al, 2011). Some of the challenges and limitations in assessing ACI CDNC are now highlighted.…”

Linking Marine Biological Activity to Aerosol Chemical Composition and Cloud‐Relevant Properties Over the North Atlantic Ocean

“…The high‐resolution aerosol data have been averaged to hourly mean and filtered against hourly eBC mass concentration as an anthropogenic tracer in order to ensure the cleanliness of the marine air masses. The hourly averages corresponding to eBC not exceeding 15 ng m −3 was used to reliably exclude anthropogenically impacted air masses (Grigas et al, 2017; O'Dowd et al, 2015; Ovadnevaite et al, 2014; Preissler et al, 2016). The clean marine hourly aerosol data collected at MHD have been averaged daily, in order to be compared with the highest CHL time resolution of 24 hr.…”

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

“…Table 1 describes the active and passive remote-sensing instruments and the main in situ sensors deployed at the SIRTA site for the IOP and used in this study. These IOP correspond to 6 January 2015, 19 December 2016, 3 January 2017 and 17 February 2017. On the three first dates, a tethered balloon carrying an optical particle counter was deployed to document fog and low-stratus microphysical properties, while during the fog on 17 February 2017 the balloon was not used and measurements were only taken at 4 m altitude.…”

“…One possible solution comprises frequency-modulated continuous wave technique (FMCW) cloud radars that could provide continuous but indirect LWC measurements in a high temporal resolution [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. Reliable Z-LWC relationships for fog events are paramount to retrieving LWC profiles from radar reflectivity: existing procedures use empirically-derived static relationships [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22], and some are more advanced accounting for additional instrumentation such as a ceilometer [3] or microwave radiometer [14]. However, assumptions about the shape of the droplet-size distribution lead to inaccuracies in retrieved Z-LWC because Z is proportional to the sixth moment of the DSD (in Rayleigh approximation, valid for small drops i.e., for fog) while LWC is proportional to the third moment of the DSD.…”