Ice Fog and Light Snow Measurements Using a High-Resolution Camera System
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Ice fog, diamond dust, and light snow usually form over extremely cold weather conditions, and they affect both visibility and Earth’s radiative energy budget. Prediction of these hydrometeors using models is difficult because of limited knowledge of the microphysical properties at the small size ranges due to measurement issues. These phenomena need to be better represented in forecast and climate models; therefore, in addition to remote sensing accurate measurements using ground-based instrumentation are required. An imaging instrument, aimed at measuring ice fog and light snow particles, has been built and is presented here. The ice crystal imaging (ICI) probe samples ice particles into a vertical, tapered inlet with an inlet flow rate of 11 L min−1. A laser beam across the vertical air flow containing the ice crystals allows for their detection by a photodetector collecting the scattered light. Detected particles are then imaged with high optical resolution. An illuminating LED flash and image capturing are triggered by the photodetector. In this work, ICI measurements collected during the fog remote sensing and modeling (FRAM) project, which took place during Winter of 2010–2011 in Yellowknife, NWT, Canada, are summarized and challenges related to measuring small ice particles are described. The majority of ice particles during the 2-month-long campaign had sizes between 300 and 800 μm. During ice fog events the size distribution measured had a lower mode diameter of 300 μm compared to the overall campaign average with mode at 500 μm.
KeywordsIce fog snow precipitation fall speed ice particle properties optical imaging
Ice fog and light snow usually form at cold temperatures below −10 °C when ice nuclei exist in a supersaturated environment with respect to ice. These conditions typically happen at higher latitudes during cold winter conditions such as over Arctic regions. Ice fog and light snow are important weather phenomena as they affect aviation and transportation through visibility reduction (Gultepe et al. 2015b). Forecasting of these weather phenomena, however, is difficult (Gultepe et al. 2009, 2015b), but better knowledge of the microphysical properties of atmospheric ice particles is essential to the development of the meteorological forecast models.
In addition to their role in aviation and transportation safety, these ice particles also influence the radiative transfer in the atmosphere; therefore they affect the Earth’s climate significantly (Gultepe et al. 2015a, 2016). Climate modelling studies suggested that ice fog can significantly affect the radiative budget in the Arctic (Girard and Blanchet 2001). Both ice fog and light snow are dominated by smaller ice particles or crystals with sizes below 1 mm. Light scattering by these particles is affected strongly by their shapes (Schlimme et al. 2005) and size distributions. Usually detailed information on particle distributions (as opposed to average or effective sizes) is required for accurate radiative transfer calculations (Mitchell et al. 2011). Thus, measurements of ice crystal shape and size, and their distribution are particularly valuable for assessing climate change issues and for aviation applications.
Parameterizations of ice particle fall speeds were determined for specific ice particles and can be found for example in the work of Locatelli and Hobbs (1974) and Kajikawa and Okuhara (1997). Although improvements of parameterizations based on field and laboratory measurements have been reported (Heymsfield and Westbrook 2010), more direct measurements of terminal velocities for a variety of particle types are needed to develop better parameterizations, so that they can be used to improve climate models and the prediction of mass and heat budget based on numerical forecasting models.
Instruments to measure snow ice particles on the ground are limited in their ability to provide detailed microphysical properties such as particle shape and size information. Disdrometers measure the drop or ice crystal size distribution and fall speed of hydrometeors making certain physical assumptions. For example, the particle size velocity, ParSiVel disdrometer (Battaglia et al. 2010) uses the intensity reduction of a horizontal light beam caused by a falling particle to determine particle size distributions and fall speed. Particle shape cannot be retrieved and the lower size limit is usually set at 250 μm. Other disdrometers or optical probes also use one-dimensional optical arrays that provide a two-dimensional shadowgraph of each particle (Gultepe et al. 2015a). The size of the smallest particle that can be detected depends on the pixel resolution (object size corresponding to one pixel of the array). For the optical spectrometer developed by ETH in Zurich the pixel resolution is 150 μm (Barthazy et al. 1998). For the hydrometeor velocity and shape detector (HVSD), horizontal pixel resolution is 0.15 mm and vertical pixel resolution depends on fall speed and is on the same order as the horizontal one for ice particles (Barthazy et al. 2004); and for the two-dimensional video disdrometer (2-DVD) pixel resolution is 200 μm (Kruger and Krajewski 2002). The snowflake video imager (SVI) uses a CCD camera to acquire images at a fixed frame rate and it has a pixel resolution of 50 and 100 μm in the two image directions, respectively (Newman et al. 2009). Another interesting new instrument is the multi-angle snowflake camera (MASC) that captures images from different angles with three higher resolution cameras and measures fall speed (Garrett et al. 2012). The cameras have different resolutions; the finest pixel resolution is 9 μm. However, only snowflakes larger than 100 μm are detected by MASC, and the resolution in falling direction is reduced by the particle’s movement to around 40 μm. Hence, all these instruments lack in accurate measurements of particle size and shape for smaller particles. Therefore, such accurate information is also missing for measurements of fall speeds.
Optical array probes that are used on aircraft have smaller pixel resolutions of 25 or 10 μm (Lawson et al. 2006b). Given the low quality and resolution of the shadowgraph images and issues with false multiple particles due to optical breakup (Field et al. 2006; Korolev et al. 1998), measuring size distributions and shape of ice fog particles with these probes are still in question. Aircraft probes with better capability of detecting smaller ice particles are scattering probes that can detect sub-micrometre particles, such as the forward scattering spectrometer probe (FSSP, Baumgardner et al. 1992), and the cloud particle imager (CPI) probe (Lawson et al. 2001). The former provides particle size distributions without direct shape information. Only indirect and very limited shape information can be retrieved based on shape dependence of light scattering detected in several directions. The latter uses optical imaging with a pixel resolution of 2.3 μm. The CPI has also been used in ground-based experiments. For example, Lawson et al. (2006a) used the CPI at Antarctica with aspirating ice particles at the inlet speed of 30 m s−1, finding that particle size distributions were dominated by particles below 200 μm for light snow fall and diamond dust. Another aircraft probe, the NCAR video ice particle sampler probe VIPS (McFarquhar and Heymsfield 1996), has a relatively good resolution and crystals larger than 5 μm can be detected. The VIPS was used in a ground-based configuration to measure in ice fog conditions in Alaska (Schmitt et al. 2013). In their work the NCAR ice crystal replicator, normally a balloon-borne instrument (Miloshevich and Heymsfield 1997), was also used for ice fog spectral measurements. After collection, the ice crystal replicas were analysed in the laboratory by microscope, thus better resolution is achieved compared to the VIPS or CPI. In their Alaska field study, Schmitt et al. (2013) found that for temperatures colder than −30 °C, most particles are below 30 μm in size with concentrations generally increasing from very low values at 100 μm to a maximum at about 10 μm. Gultepe et al. (2014) used GCIP, a ground-based version of the aircraft CIP optical array probe (Baumgardner et al. 2001) for ice fog studies. The shape measurements of ice crystals from GCIP were limited by its poorer resolution (pixel resolution of 15 μm) showing the need for a better probe to detect size, shape, and size distributions of ice crystals.
The overall goals of this work are to contribute to a better characterization of ice fog particle microphysical properties as well as small snow crystal properties for modelling and observational studies. Observations, representing ice fog and light snow crystals, were carried out during the FRAM project (fog remote sensing and modeling), which took place over Yellowknife International Airport, NWT, Canada during winter of 2010–2011 (Gultepe et al. 2014, 2015b), and are used in achieving the goals. For accomplishing this work, the following objectives are considered: (1) present a ground-based instrument, called the ice crystal imaging (ICI) probe that provides size, shape, and fall speed of small ice particles; (2) show the capability of ice crystal fall-speed (V f) measurement using ICI probe; (3) derive microphysical characteristics of small ice crystals applicable to cloud-climate studies; and (4) compare the results with other studies to validate accuracy of present measurements.
2 Field Project and Observations
A field campaign dedicated to ice fog studies called the fog remote sensing and modeling-ice fog (FRAM-IF) field project took place near the Yellowknife International Airport (62°27′46″N, 114°26′25″W), Yellowknife, NWT, Canada, from 25 November 2010 to 5 February 2011. Details of the FRAM project observations, the project site, and the instruments employed during the campaign can be found in Gultepe et al. (2014, 2015b). The main observations collected during the project were related to ice crystal size spectra and shape, aerosol spectra, visibility (Vis), temperature (T), relative humidity (RH), precipitation rate and amount (PR and PA), and 3D wind components. The ice crystal imaging (ICI) probe was installed on a pole approximately 1 m above the roof of a trailer used during the project.
During the campaign, ice fog events usually occurred related to cold high-pressure systems with clear skies and cold temperatures down to about −30 °C, which is colder than those of average weather conditions. Several ice fog, diamond dust, and often light snow conditions were observed, and these are summarized in Gultepe et al. (2014).
In this section, the ICI instrument set-up and image analysis technique to determine ice fog and light snow microphysical characteristics are described.
3.1 Instrument Set-up
The ICI probe has a vertical funnel-shaped inlet that has an upward facing opening of 25 mm in diameter. Ice crystal and snow particles that are smaller than about 100 μm are sampled efficiently at the 11-L min−1 inlet flow rate as they follow the air stream into the inlet given their low Stokes numbers (0.4 at 100 μm and lower for smaller sizes). Larger ice particles (having larger Stokes numbers) are not following the sample flow into the inlet effectively; however, they settle into the inlet opening at their own fall speed. To guide this passive collecting method of ice crystals the inlet flow rate of 11 L min−1 and inlet opening of 25 mm have been chosen so that the mean air speed across the inlet opening, about 0.4 m s−1, is within the range of typical fall speeds. In this way the sample volume determined from the inlet flow rate (see Sect. 3.2) is characteristic for both particles below and above 100 μm; however, particles settling at larger speeds will be overestimated. After entering the inlet, particles are transferred, using the principles of a virtual impactor (Gultepe et al. 2014), to a vertical tube with 12 mm inner diameter. The sampling efficiency of this virtual impactor step can be derived from the Stokes number of the flow through its nozzle and is for ICI 50 % at approximately 9 μm, and it rises quickly with increasing size to around 90 % at 10 μm according to numerical solutions presented by Rader and Marple (1985). Four lateral glass windows in this 12-mm vertical tube allow for detecting and imaging of ice crystals. Two windows are used for imaging and illumination of ice crystals, respectively. They are arranged at opposite sides of the tube wall, along the optical axis defined by the imaging system consisting of microscope objective, tube lens, and CCD camera. The optical axis is perpendicular to the vertical tube axis. The two additional windows are placed along a laser beam, which is perpendicular to both those axes. The laser light enters and leaves through these windows. Particles traversing this laser beam in the centre of the tube are detected by the scattered light intensity that is collected at 90° angle to the laser beam. The scattered light is collected by the same optics that is used for imaging, i.e. the microscope objective, and is then directed onto a photodiode detector through a beam splitter. Thereby, the sensing volume is defined by the intersection of the laser beam with the field of view (FOV) of the imaging optics. After ice crystal detection, image acquisition is triggered and the ice crystal’s image is saved for further processing in image analysis.
3.2 Image Analysis
The number concentration of ice crystals is obtained using the particle count and the corresponding sampling volume that requires an accurate flow rate parameter. All ice crystals entering the inlet are transferred to the 12-mm vertical tube. Then, a certain fraction of these ice crystals traverses the probe’s sensing volume, within the 12-mm tube, where they are detected and imaged for future processing. Hence, the effective sample flow rate used in the calculations is defined as the fraction of the inlet flow rate of 11 L min−1 that contains the detected ice crystals. This fraction is obtained from the sensing area (the cross-sectional area of the sensing volume as seen from above along the direction of flow) divided by the cross section of the 12-mm tube. The sensing area is given by the product of the width of the FOV (4.32 mm) and the sensing depth where particles are detected, which is the sum of the laser beam depth (approximately 0.5 mm) and the size of the particles. This accounts for the fact that an ice particle is detected by the laser beam even if the laser only partially hits the particle. For simplicity, it is assumed that the depth of the sensing area is 1 mm, which is the effective sensing area corresponding to a 500-μm particle size. Then, the sensing area becomes 4.32 mm2, resulting in a sample flow rate of 7.0 mL s−1. This simplification results in underestimating number concentration of smaller particles and overestimating number concentration of larger particles.
The size range, in which particles are measured, has a lower limit given by the detection through scattered light. Particles smaller than this lower size limit do not scatter enough light to be detected. The used set-up with 90° scattering allows for a simple optical set-up; however, it also has a relatively high lower size limit of around 100 μm. While it is desirable and possible to modify the set-up to allow for detecting smaller particles, this modification was not done during this study. The upper limit of the size range is given by the FOV of 4.32 mm × 3.24 mm and the vertical position of the laser beam. The laser, which is used for detecting particles and triggering the imaging, influences directly the location of particles on the images. The laser beam is located in the centre and focused vertically to a thin sheet. Hence, particles larger than approximately half the height of the FOV cannot be imaged completely. In fact, almost no particle larger than 1.5 mm is imaged without touching the upper border of the image. Particles touching any border of the image are rejected from analysis, as their size becomes uncertain. This results in an upper size limit for particles being measured of around 1.5 mm. The random horizontal location of particles yields a probability of particles touching the right or left image border, which increases with increasing particles size. This results in underestimating the number concentration of larger particles, but it is compensated by the overestimation of larger particles due to the simplification of using a constant, size-independent sampling volume. An effective correction factor for number concentration that would account for both effects would indeed be close to one for ice particle sizes between 1 and 1.5 mm. Below 1 mm this correction factor, which has not been considered in this first data analysis, increases slowly while particle size decreases, and finally reaches approximately 1.3 at 500 μm and 1.7 at 100 μm.
3.3 Set-up for Determining Fall Speed
During the campaign, the instrument was operated for 7 days in a modified set-up mode that allowed to determine the ice crystal fall speed in addition to measurements of ice crystal size, projected area, and shape. The modified set-up did not provide active sample flow rate, and the inlet as well as the 12-mm tube were removed for obtaining accurate fall speeds. The optical cell is larger in this set-up and particles are allowed to fall freely into it, so that their fall speed will not be modified. Detected particles are then captured twice on the same image by illuminating the particle with two flashes instead of one. Time difference between the two illuminating flashes was 1.64 ms. Using the vertical displacement of a particle on the image, V f is calculated. Automatic image analysis was difficult due to particles appearing twice on the same image, and sometimes, these two particle appearances were overlapping. Therefore, the outline of the particle area was traced by hand and the vertical displacement was determined during the analysis. Then, the fall speed, size, and area were retrieved from subsequent automatic analysis.
4 Results and Discussion
The ICI has been operated at its first campaign, FRAM-IF, over almost 60 days between 30 November 2010 and 30 January 2011. During this time, ice particles have been measured at temperatures between −5 and −37 °C. Gultepe et al. (2014) suggested that ice fog occurrence was more than 20 % of time during the project. Light snowfall was also measured at 30 % of the time. During the project, snow or ice particles were detected during 343 1-h periods. In general, total ice crystal number concentrations (N t) were low; more than half of this time N t was less than 0.2 L−1. The average N t during the whole period was approximately 0.6 L−1. The maximum hourly average N t during the campaign was 8 L−1. All detected particles have been considered for these number concentrations. For the rest of the analysis, particles that touch the border of an image or appear to be fragmented are excluded. The latter issue results from out-of-focus particles, leading to sizing uncertainties. Thus, 35 % of particles, because of these issues, were excluded from analysis. The remaining particles were detected during 304 1-h periods. As was to be expected, most of the excluded particles were relatively large, with an average measured size of 1.3 mm, whereas the remaining particles with a mean size of 660 μm were un-fragmented and did not touch the border.
4.1 Ice Particle Size Distributions
The PSD of ice and snow crystals for the entire campaign had a mean particle size D of 660 μm with one mode between 300 and 800 μm. During the ice fog event on 16 and 17 January 2011, ice crystal sizes are distinctly shifted towards smaller sizes, with mean D = 550 μm. However, one needs to consider that the sharp decline in N i below around 200 μm is in part caused by the lower size limit of around 100 μm. If this lower limit were decreased, the size distribution would likely shift even further towards smaller sizes, as is to be expected by comparison to the aforementioned ice fog study by Schmitt et al. (2013) with maxima in the PSDs at approximately 10 μm. However, the PSDs during that study in Alaska were observed at colder temperatures than in this study. During the light snowfall event on December 7 2010, larger sizes of ice crystals were detected, with mean D = 730 μm, i.e. larger than both for the campaign average and the ice fog event. For this snow PSD, which shows the largest sizes, N i becomes almost zero before the sizes increase to the upper size limit of 1.5 mm.
4.2 Ice Crystal Area Dependency on Size
4.3 Mass and Effective Diameter
4.4 Fall Speed Versus Size and Area
The wind speed measured was generally low (below about 3 m s−1) and did not vary significantly during the fall-speed measurements. This suggests that wind speed or near-surface turbulence did not affect the measured fall speed. This was confirmed by dividing the data set in two groups corresponding to wind speed below and above the median value, respectively. Fall speed versus D and versus A did not reveal significant differences between the two groups (not shown). While this demonstrates the ability of ICI with modified inlet to measure fall speed, more data are needed to verify fall-speed measurements and analyse them more in detail.
In this work, ice crystal and light snow characteristics are studied using ICI probe with an integrated camera system. Its observations were performed during the FRAM-IF project, which took place in Yellowknife, NWT, Canada, during winter of 2010–2011.
The specially developed ICI probe can be used to determine microphysical characteristics of small ice crystals with sizes less than about 1500 µm. When properties such as ice crystal size, shape, and fall speed are determined for these small ice crystals, new relationships for numerical model applications can be derived.
The size range considered here includes ice crystal sizes less than 500 µm, which are more important than large ice crystals for the radiative effect and heat budget due to the large number of these small ice crystals (Gultepe et al. 2014, 2015b).
The ICI probe can measure size, projected area, shape of single ice crystals, fall speeds, total number concentration, and provides PSD. The high-resolution images from the probe add valuable details on the small ice crystals and their effect on microphysical parameterizations.
The measured projected areas of ice crystals versus D during the whole campaign were approximated by the power law of A = 1.99 × 10−12 × D 1.72. Despite the large spread of data points, which represents the natural variability, a good correlation was found with R 2 = 0.88. Correlation coefficients were larger for the shorter events because of lower variability of predominant shapes and atmospheric conditions.
It was shown that a modification of ICI is well suited to measure fall speed of ice and snow crystals with sizes less than about 1500 µm. The image quality of ice crystals can allow better analysis of particle orientation effects on V f. In addition, ice crystals can easily be sorted for different shape classes to develop better V f and IWC parameterizations.
The lower size limit of the ICI probe during the campaign was approximately 100 μm and upper size limit around 1.5 mm. The upper limit did not present a problem in this study because ice fog and snow particles were much smaller than 1 mm at cold temperatures. The strength of the instrument is to provide detailed information on these small ice crystals with high-resolution optical images. However, the instrument could also be modified to allow larger particles to be measured.
With respect to the lower size limit, it is foreseen that future measurements after lowering the size threshold for particle detection below 100 µm would improve the capabilities of measuring ice fog and small crystal properties.
Overall, it is concluded that ICI probe measurements, compared to other optical sensors available, can improve the numerical model prediction of ice crystal microphysical parameters, visibility, and climate modelling through heat budget estimations. Therefore, its use for future Arctic applications, specifically for ice fog and light snow conditions (Gultepe et al. 2015a) would improve heat and moisture budgets of cold climates and our understanding of ice clouds.
We like to thank Swedish National Space Board, National Search and Rescue Secretariat (SAR) of Canada, and Environment Canada for funding this work.
- Baumgardner, D., Dye, J. E., Gandrud, B. W., & Knollenberg, R. G. (1992). Interpretation of measurements made by the forward scattering spectrometer probe (FSSP-300) during the airborne Arctic stratospheric expedition. Journal of Geophysical Research Atmospheres, 97(D8), 8035–8046.CrossRefGoogle Scholar
- Gultepe, I., et al. (2016). An overview of MATERHORN mountain ice fog project: Observations and predictability. Pure and Applied Geophysics (accepted for publication).Google Scholar
- Gultepe, I., Rabin, R., Ware, R., & Pavolonis, M. (2015a). Light snow measurements over cold climatic regions. Advances in Geophysics (submitted).Google Scholar
- Kajikawa, M., & Okuhara, K. (1997). Observations of the falling motion of plate-like snow crystals. 2. The free-fall patterns and velocity variations of rimed crystals. Journal of the Meteorological Society of Japan, 75(4), 811–818.Google Scholar
- Lawson, R. P., Baker, B. A., Zmarzly, P., O’Connor, D., Mo, Q., Gayet, J. -F., & Shcherbakov, V. (2006a). Microphysical and optical properties of atmospheric ice crystals at South Pole station. Journal of Applied Meteorology and Climatology, 45(11), 1505–1524. doi: 10.1175/JAM2421.1.CrossRefGoogle Scholar
- Lawson, R., O’Connor, D., Zmarzly, P., Weaver, K., Baker, B., Mo, Q., & Jonsson, H. (2006b). The 2D-S (Stereo) probe: Design and preliminary tests of a new airborne, high-speed, high-resolution particle Imaging probe. Journal of Atmospheric and Oceanic Technology, 23(11), 1462–1477.CrossRefGoogle Scholar
- Miloshevich, L. M., & Heymsfield, A. J. (1997). A balloon-borne continuous cloud particle replicator for measuring vertical profiles of cloud microphysical properties: Instrument design, performance, and collection efficiency analysis. Journal of Atmospheric and Oceanic Technology, 14(4), 753–768.CrossRefGoogle Scholar
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