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George A. Isaac

Abstract

Any observing program studying summer cumulus clouds should attempt to measure cloud lifetime. This parameter is important for determining whether a cloud will last long enough for precipitation to form by either natural or artificially stimulated mechanisms. When reporting cloud lifetime, the definition used and the method of calculation should be clearly specified. In North America, after a summer cumulus cloud has been identified and selected, lifetimes, at temperatures below –5°C, of approximately 10 to 12 min are being reported. This lifetime must be considered marginal for static mode seeding to produce precipitation by artificial ice nucleants.

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Alexei Korolev and George A. Isaac

Abstract

The results of in situ observations of the relative humidity in liquid, mixed, and ice clouds typically stratiform in nature and associated with mesoscale frontal systems at temperatures −45°C < Ta < −5°C are presented. The data were collected with the help of instrumentation deployed on the National Research Council (NRC) Convair-580. The length of sampled in-cloud space is approximately 23 × 103 km. The liquid sensor was calibrated in liquid clouds with the assumption that the air in liquid clouds is saturated with respect to water. It was found that the relative humidity in mixed-phase clouds is close to saturation over water in the temperature range from −5° to −35°C for an averaging scale of 100 m. In ice clouds the relative humidity over ice is not necessarily equal to 100%, and it may be either lower or higher than saturation over ice, but it is always lower than saturation over water. On average the relative humidity in ice clouds increases with a decrease of temperature. At −40°C the relative humidity over ice is midway between saturation over ice and liquid. A parameterization for the relative humidity in ice clouds is suggested. A large fraction of ice clouds was found to be undersaturated with respect to ice. The fraction of ice clouds undersaturated with respect to ice increases toward warmer temperatures.

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Alexei Korolev and George A. Isaac

Abstract

The data on cloud particle sizes and concentrations collected with the help of aircraft imaging probes [optical array probes OAP-2DC, OAP-2DP, and the High Volume Precipitation Spectrometer (HVPS)] are widely used for cloud parameterization and validation of remote sensing. The goal of the present work is to study the effect of shattering of ice particles during sampling. The shattering of ice particles may occur due to 1) mechanical impact with the probe arms prior to their entering the sample volume, and 2) fragmentation due to interaction with turbulence and wind shear generated by the probe housing. The effect of shattering is characterized by the shattering efficiency that is equal to the ratio of counts of disintegrated particles, to all counts. The shattering efficiency depends on the habit, size, and density of ice particles, probe inlet design, and airspeed. For the case of aggregates, the shattering efficiency may reach 10% or even more. The shattering of ice particles results in an overcounting of small particles and an undercounting of large ones. The number of fragments in the images of shattered particles may reach several hundreds. It was found that particles as small as 600 μm may shatter after impact with the probe arms. The effect of particle shattering should be taken into account during data analysis and carefully considered in future designs of airborne cloud particle size spectrometers.

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Stewart G. Cober and George A. Isaac

Abstract

Observations of aircraft icing environments that included supercooled large drops (SLD) greater than 100 μm in diameter have been analyzed. The observations were collected by instrumented research aircraft from 134 flights during six field programs in three different geographic regions of North America. The research aircraft were specifically instrumented to accurately measure the microphysics characteristics of SLD conditions. In total 2444 SLD icing environments were observed at 3-km resolution. Each observation had an average liquid water content (LWC) > 0.005 g m−3, drops > 100 μm in diameter, ice crystal concentrations <1 L−1, and an average static temperature ≤0°C. SLD conditions were observed approximately 5% of the in-flight time. The SLD observations were segregated into four subsets, which included conditions with maximum drop sizes <500 μm and >500 μm in diameter, each with median drop volume diameters <40 μm and >40 μm. For each SLD subset, the observations were used to develop envelopes of maximum LWC values as a function of horizontal extent and temperature. In addition, characteristic drop size distributions were developed for each SLD subset. The maximum LWC values physically represent either the 99% or 99.9% LWC values, as determined from an extreme value analysis of the data. The analysis is sufficient for simulation of SLD environments with either numerical icing accretion models or wind-tunnel icing simulations. The SLD envelopes are similar in structure and supplemental to existing aircraft icing envelopes, the difference being that the existing envelopes did not explicitly incorporate SLD conditions.

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Faisal Boudala, George A. Isaac, and Di Wu

Abstract

Light (LGT) to moderate (MOD) aircraft icing (AI) is frequently reported at Cold Lake, Alberta, but forecasting AI has been a big challenge. The purpose of this study is to investigate and understand the weather conditions associated with AI based on observations in order to improve the icing forecast. To achieve this goal, Environment and Climate Change Canada in cooperation with the Department of National Defence deployed a number of ground-based instruments that include a microwave radiometer, a ceilometer, disdrometers, and conventional present weather sensors at the Cold Lake airport (CYOD). A number of pilot reports (PIREPs) of icing at Cold Lake during the 2016/17 winter period and associated observation data are examined. Most of the AI events were LGT (76%) followed by MOD (20%) and occurred during landing and takeoff at relatively warm temperatures. Two AI intensity algorithms have been tested based on an ice accumulation rate (IAR) assuming a cylindrical shape moving with airspeed υ a of 60 and 89.4 m s−1, and the Canadian numerical weather prediction model forecasts. It was found that the algorithms IAR2 with υ a = 89.4 m s−1 and IAR1 with υ a = 60 m s−1 underestimated (overestimated) the LGT (MOD) icing events, respectively. The algorithm IAR2 with υ a = 60 m s−1 appeared to be more suitable for forecasting LGT icing. Over all, the hit rate score was 0.33 for the 1200 UTC model run and 0.6 for 0000 UTC run for both algorithms, but based on the individual icing intensity scores, the IAR2 did better than IAR1 for forecasting LGT icing events.

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Alexei V. Korolev and George A. Isaac

Abstract

A new conceptual model is proposed for enhanced cloud droplet growth during condensation. Rapid droplet growth may occur in zones of high supersaturation resulting from isobaric mixing of saturated volumes with different temperatures. Cloud volumes having a temperature different from the general cloud environment may form due to turbulent vertical motions in a temperature lapse rate that is not pseudoadiabatic. This mechanism is most effective in the vicinity of cloud-top inversions. It is also shown that the isobaric mixing of saturated and dry volumes with different temperatures may also lead to high supersaturations. The high supersaturations are associated with zones of molecular mixing, and they have a characteristic size of the order of millimeters with a characteristic lifetime near tenths of a second. Some small proportion of cloud droplets, over many supersaturation events, may grow large enough to grow effectively through collision–coalescence. This hypothesis of isobaric mixing may help explain freezing and warm drizzle formation.

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Stewart G. Cober, Andre Tremblay, and George A. Isaac

Abstract

Comparisons have been made between in situ aircraft measurements of integrated liquid water and retrievals of integrated liquid water path (LWP) from algorithms using SSM/I brightness temperatures. The aircraft measurements were made over the North Atlantic Ocean during the winter of 1992. Six case studies are presented from which trends in the LWP algorithms are discussed. SSM/I liquid water path validation has previously only been performed through comparisons with measurements from upward-looking radiometers or with calculations from radiative transfer models. The case studies presented here reflect an alternative technique for validation.

Aircraft-derived liquid water paths ranged from 0.01 to 0.09 kg m−2 for the six cases presented. The SSM/I algorithms investigated predicted LWP to within ±0.02–0.03 kg m−2, provided one accounted for systematic biases in the retrievals. These biases were systematic in the range ±0.06 kg m−2 and were presumably caused by latitudinal and seasonal influences inherent in the algorithms. Algorithms based on radiative transfer models appeared to perform better than the statistically based algorithms.

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Stewart G. Cober, George A. Isaac, and J. Walter Strapp

Abstract

Measurements of aircraft icing environments that include supercooled large drops (SLD) greater than 50 μm in diameter have been made during 38 research flights. These flights were conducted during the First and Third Canadian Freezing Drizzle Experiments. A primary objective of each project was the collection of in situ microphysics data in order to characterize aircraft icing environments associated with SLD. In total there were 2793 30-s averages obtained in clouds with temperatures less than or equal to 0°C, maximum droplet sizes greater than or equal to 50 μm, and ice crystal concentrations less than 1 L−1. The data include measurements from 12 distinct environments in which SLD were formed through melting of ice crystals followed by supercooling in a lower cold layer and from 27 distinct environments in which SLD were formed through a condensation and collision–coalescence process. The majority of the data were collected at temperatures between 0° and −14°C, in stratiform winter clouds associated with warm-frontal or low pressure regions. For in-cloud measurements with temperatures less than or equal to 0°C, the relative fraction of liquid-, mixed-, and glaciated-phase conditions were 0.4, 0.4, and 0.2, respectively. For each 30-s (3 km) measurement, integrated drop spectra that spanned 1–3000 μm were determined using measurements from forward-scattering spectrometer probes and 2D-C and 2D-P probes. The integrated liquid water content (LWC) for each drop spectrum was compared with the LWC measured with a Nevzorov total water content probe and a Rosemount icing detector. The agreement was within the errors expected for such comparisons. This provides confidence in the droplet spectra measurements, particularly in the assessment of extreme conditions. The 99.9th-percentile LWC value was 0.7 g m−3, and the 99th-percentile LWC for drops greater than 50 μm in diameter was 0.2 g m−3. The 99.5th-percentile values of LWC and droplet concentrations are determined for different horizontal length scales and droplet diameter intervals, and are used to characterize the extreme icing conditions observed. The largest median volume diameters (MVD) observed were approximately 1000 μm and represent cases in which the aircraft was flown below cloud base in freezing-rain conditions. In one case, SLD was observed to form at −21°C, and the associated icing was rated as severe. Approximately 3% of the data for which SLD were observed had LWC greater than 0.2 g m−3 and MVD greater than 30 μm. Such conditions are believed to represent conditions that have the largest potential effects on aircraft performance. The analysis is presented in a format that is suitable for several applications within the aviation community, and comparisons are made to four common icing-envelope formulations. The data should be beneficial to regulatory authorities who are currently attempting to assess certification requirements for aircraft that are expected to encounter freezing-precipitation conditions.

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Laura X. Huang, George A. Isaac, and Grant Sheng

Abstract

This study addresses the issue of improving nowcasting accuracy by integrating several numerical weather prediction (NWP) model forecasts with observation data. To derive the best algorithms for generating integrated forecasts, different integration methods were applied starting with integrating the NWP models using equal weighting. Various refinements are then successively applied including dynamic weighting, variational bias correction, adjusted dynamic weighting, and constraints using current observation data. Three NWP models—the Canadian Global Environmental Multiscale (GEM) regional model, the GEM Limited Area Model (LAM), and the American Rapid Update Cycle (RUC) model—are used to generate the integrated forecasts. Verification is performed at two Canadian airport locations [Toronto International Airport (CYYZ), in Ontario, and Vancouver International Airport (CYVR), in British Columbia] over the winter and summer seasons. The results from the verification for four weather variables (temperature, relative humidity, and wind speed and gust) clearly show that the integrated models with new refinements almost always perform better than each of the NWP models individually and collectively. When the integrated model with innovative dynamic weighting and variational bias correction is further updated with the most current observation data, its performance is the best among all models, for all the selected variables regardless of location and season. The results of this study justify the use of integrated NWP forecasts for nowcasting provided they are properly integrated using appropriate and specifically designed rules and algorithms.

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