In-cloud icing of objects is caused by super-cooled microscopic water droplets carried by the wind. To estimate the icing rate of objects in such conditions, the liquid water content (LWC) of the icing cloud and the median volume diameter (MVD) of the droplets are measured. Mixed-phase clouds also contain ice crystals which must be ruled out in order to avoid overestimation of the icing rate. Typically, cloud droplet instruments are not able to do this. A particle imaging instrument ICEMET (icing condition evaluation method) was used to observe in-cloud icing conditions. This lensless device uses a computational imaging method to reconstruct the shadow images of the microscopic objects. The size, position and shape descriptors of each particle are measured. This data is then used to filter out the ice crystals. The droplet size distribution and the size of the measurement volume are used to determine the LWC and MVD. The performance of the instrument was tested under mixedphase icing conditions in a wind tunnel and on a wind turbine. The measured LWC and MVD values were used to model the ice accretion on a cylinder-shaped object according to ISO 12494:2017 icing standard. In the wind tunnel, the modeled ice mass was compared to the weighed ice mass collected by a cylinder. According to our results, ice accretion rates were overestimeted by 65.6 % on average without filtering out the ice crystals. Thus, the ability to distinguish between droplets and ice crystals is essential for estimating the icing rate properly.

An optical cloud droplet and ice crystal measurement system ICEMET (icing condition evaluation method), designed for present icing condition monitoring in field conditions, is presented. The aim in this work has been to develop a simple but precise imaging technique to measure the two often missing parameters needed in icing rate calculations caused by icing clouds-the droplet size distribution (DSD) and the liquid water content (LWC) of the air. The measurement principle of the sensor is based on lens-less digital in-line holographic imaging. Cloud droplets and ice crystals are illuminated by a short laser light pulse and the resulting hologram is digitally sampled by a digital image sensor and the digital hologram is then numerically analyzed to calculate the present DSD and LWC values. The sensor has anti-icing heating power up to 500 W and it is freely rotating by the wind for an optimal sampling direction and aerodynamics. A volume of 0.5 cm 3 is sampled in each hologram and the maximum sampling rate is 3 cm 3 /s. Laboratory tests and simulations were made to ensure the adequate operation of the measurement sensor. Computational flow dynamics simulations showed good agreement with droplet concentration distributions measured from an icing wind tunnel. The anti-icing heating of the sensor kept the sensor operational even in severe icing conditions; the most severe test conditions were the temperature − 15 °C, wind speed 20 m/s and the LWC 0.185 g/m 3. The verification measurements made using NIST traceable monodisperse particle standard glass spheres showed that the ICEMET sensor measurement median diameter 25.54 µm matched well with 25.60 µm ± 0.70 µm diameter confidence level given by the manufacturer.

Abstract. Upon a new measurement technique, it is possible to sharpen the determination of microphysical properties of cloud droplets using high resolving power imaging. The shape, size, and position of each particle inside a well-defined, three-dimensional sample volume can be measured with holographic methods without assumptions of particle properties. In-situ cloud measurements were carried out at the Puijo station in Kuopio, Finland, focusing on intercomparisons between cloud droplet analysers over the two months on September–November 2020. The novel holographic imaging instrument (ICEMET) was adapted to measure microphysical properties of liquid clouds and these values were compared to parallel measurements of cloud droplet spectrometer (FM-120) and particle measurements using a twin-inlet system. When the intercomparison was carried out during isoaxial sampling, our results showed good agreement in terms of variability between the instruments with the averaged ratios between ICEMET and FM-120 were 0.6 ± 0.2, 1.0 ± 0.5, and 1.2 ± 0.2 for total number concentration (Nd) of droplets, liquid water content (LWC), and median volume diameter (MVD), respectively. This agreement during isoaxial sampling was also confirmed by mutual information and Pearson correlation coefficients. The ICEMET observed liquid water content (LWC) was more reliably than FM-120 (without swivel-head mount), which was verified by comparing the estimated LWC to measured values whereas the twin-inlet DMPS system and FM-120 observations of Nd showed good agreement both in variability and amplitude. Field data revealed that ICEMET can detect small cloud droplets down to 5 μm via geometrical magnification.

The ICEMET-sensor is a novel cloud droplet and particle imaging instrument which measures icing conditions by determining the number and sizes of the supercooled droplets in a known air volume. The sensor captures digital holograms from 0.5 cm 3 sample volume with a maximum rate of 3.0 cm 3 /s. This lensless imaging instrument uses a computational imaging method to reconstruct the shadow images of the objects in the measurement volume. The size, position and shape descriptors of the individual particles and droplets are calculated and saved into a database. This data can be used to separate between cloud droplets and other particles. The calculated features are used to determine the two essential parameters needed for ice accretion modeling according to the ISO 12494 icing standard: liquid water content (LWC) of the air and median volume diameter (MVD) of the droplets. The basic working principle of the sensor and the image processing method are described. The performance of the sensor was tested in a wind tunnel under mixed-phase icing conditions. The measured LWC and MVD values were used to model ice accretion using the ISO 12494 icing standard for rotating cylinders. The modeled ice accretions were compared with weighed ice masses obtained from the wind tunnel with the same sized cylinder. The results show that accurate droplet size measurement and separation between droplets and ice crystals are essential for estimating the ice accretion rate properly. Without filtering out the ice crystals, the calculated accretion rates were overestimated by 65.6 % on average.

Abstract. Upon a new measurement technique, it is possible to sharpen the determination of microphysical properties of cloud droplets using high resolving power imaging. The shape, size, and position of each particle inside a well-defined, three-dimensional sample volume can be measured with holographic methods without assumptions of particle properties. In situ cloud measurements were carried out at the Puijo station in Kuopio, Finland, focusing on intercomparisons between cloud droplet analyzers over 2 months in September–November 2020. The novel holographic imaging instrument (ICEMET) was adapted to measure microphysical properties of liquid clouds, and these values were compared with parallel measurements of a cloud droplet spectrometer (FM-120) and particle measurements using a twin-inlet system. When the intercomparison was carried out during isoaxial sampling, our results showed good agreement in terms of variability between the instruments, with the averaged ratios between ICEMET and FM-120 being 0.6 ± 0.2, 1.0 ± 0.5, and 1.2 ± 0.2 for the total number concentration (Nd) of droplets, liquid water content (LWC), and median volume diameter (MVD), respectively. This agreement during isoaxial sampling was also confirmed by mutual correlation and Pearson correlation coefficients. The ICEMET-observed LWC was more reliable than FM-120 (without a swivel-head mount), which was verified by comparing the estimated LWC to measured values, whereas the twin-inlet DMPS system and FM-120 observations of Nd showed good agreement both in variability and amplitude. Field data revealed that ICEMET can detect small cloud droplets down to 5 µm via geometric magnification.