Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)

Abstract

Abstract. Droplet size spectra measurements are crucial to obtain a quantitative microphysical description of clouds and fog. However, cloud droplet size measurements are subject to various uncertainties. This work focuses on the error analysis of two key measurement uncertainties arising during cloud droplet size measurements with a conventional droplet size spectrometer (FM-100): first, we addressed the precision with which droplets can be sized with the FM-100 on the basis of the Mie theory. We deduced error assumptions and proposed a new method on how to correct measured size distributions for these errors by redistributing the measured droplet size distribution using a stochastic approach. Second, based on a literature study, we summarized corrections for particle losses during sampling with the FM-100. We applied both corrections to cloud droplet size spectra measured at the high alpine site Jungfraujoch for a temperature range from 0 • C to 11 • C. We showed that Mie scattering led to spikes in the droplet size distributions using the default sizing procedure, while the new stochastic approach reproduced the ambient size distribution adequately. A detailed analysis of the FM-100 sampling efficiency revealed that particle losses were typically below 10 % for droplet diameters up to 10 µm. For larger droplets, particle losses can increase up to 90 % for the largest droplets of 50 µm at ambient wind speeds below 4.4 m s −1 and even to >90 % for larger angles between the instrument orientation and the wind vector (sampling angle) at higher wind speeds. Comparisons of the FM-100 to other reference instruments revealed that the total liquid water content (LWC) measured by the FM-100 was more sensitive to particle losses than to re-sizing based on Mie scattering, while the total number concentration was only marginally influenced by particle losses. Consequently, for further LWC measurements with the FM-100 we strongly recommend to consider (1) the error arising due to Mie scattering, and (2) the particle losses, especially for larger droplets depending on the set-up and wind conditions.

Enhanced extinction of visible radiation due to hydrated aerosols in mist and fog

“…This is close to 10 mg m −3 used by as a threshold to consider measurements of LWC. This is also consistent with smallest values of 8 or 9 mg m −3 observed in coastal fogs (Jiusto, 1981), and with the threshold of 5 mg m −3 to detect clouds, including thin and heterogeneous clouds (Spiegel et al, 2012). set a threshold of 2 mg m −3 for defining fog.…”

“…The default manufacturer's channels were used, which has insignificant impact on measured LWC and total droplet number concentration (Spiegel et al, 2012). The total number concentration can be estimated within ±10 % uncertainty according to Spiegel et al (2012).…”

“…The total number concentration can be estimated within ±10 % uncertainty according to Spiegel et al (2012). Following Spiegel et al (2012), a Particle Volume Monitor-100 (PVM; Gerber Scientific, Inc., Reston, Virginia, USA) was also running to check the impact of large droplet loss on LWC computations. Measurements by the PVM have a ± 15 % uncertainty (Allan et al, 2008).…”

“…The default manufacturer's channels were used, which has insignificant impact on measured LWC and total droplet number concentration (Spiegel et al, 2012). The total number concentration can be estimated within ±10 % uncertainty according to Spiegel et al (2012). Following Spiegel et al (2012), a Particle Volume Monitor-100 (PVM; Gerber Scientific, Inc., Reston, Virginia, USA) was also running to check the impact of large droplet loss on LWC computations.…”

Inversion of droplet aerosol analyzer data for long-term aerosol–cloud interaction measurements

“…The DAA can provide a direct relationship between cloud droplet size and the size of its dry residue. Other instrumentation for studying clouds, such as differential mobility particle spectrometers (DMPS), optical particle counters (OPC; Sorensen et al, 2011), the ground-based fog monitor (Spiegel et al, 2012) or the counterflow virtual impactor (CVI) that has a variable cut-off diameter for cloud droplets between 1 and 30 µm (Anderson et al, 1993;Noone et al,878 M. Berghof: Inversion of DAA data for long-term AIC measurements 2000), cannot provide such a relationship, even when used in parallel.…”