Faisal S. Boudala

Assessing the Collection Efficiency of Natural Cloud Particles Impacting the Nevzorov Total Water Content Probe

The Nevzorov Total Water Content Probe has been used extensively for characterizing the cloud water content (ice and liquid) in clouds where airframe icing and engine related problems might occur. Because of recent work done in the ice simulating wind tunnels, where a significant fraction of ice particles were observed to be ejected from the sensor instead of captured and evaporated, it is suspected that the Nevzorov Total Water probe and other similar hot-wire sensors are providing underestimates of ice water content and possibly even liquid water content in the presence of large drops. In-flight tests were performed in December 2004 where natural ice particles (dendritic ice crystals and aggregates) and water drops were photographed impacting a specially mounted Nevzorov probe installed on the NRC Convair-580. A high speed camera captured small fragments of ice particles and water drops being swept out of the collecting cone of the total water sensor after impact. It appears that the Nevzorov probe is detecting a decreasing fraction of the mass of individual particles (solid and liquid) with increasing particle size, although this effect could not be quantified with the available data. It should be emphasized that even when ice crystal shattering was occurring with subsequent loss of mass, the Nevzorov probe was still detecting a fraction of the ice. One of the interesting observations was the apparent difference in the visual impression of natural particle impacts during the flight tests versus simulated ice impacts in the wind tunnel tests. Particles did not “bounce” out of the sensor as they appeared to in the tunnel experiments, but appeared to shatter into small fragments, some of which would be ejected from the sensor in a complicated manner. This difference is postulated to be due to the higher density of simulated ice particles in the tunnel. The current tests documented impacts with natural cloud ice particles that would be classified as “fragile” and usually with a low density. The results suggest that both wind tunnel and insitu tests are needed to fully describe probe performance in ice particle environments.

Performance of hot plate for measuring solid precipitation in complex terrain during the 2010 Vancouver winter Olympics

Solid precipitation intensity, snow density, wind speed, and temperature were collected from November 2009 to February 2010 at a naturally sheltered station located at an altitude of 1640m MSL on Whistler Mountain in British Colombia, Canada. The snowfall was measured using the instruments OTT Pluvio; the Yankee Environmental Systems, Inc., hot plate (HP); and the Vaisala FD12P (optical weather sensor). The snow amount and density were also measured manually daily. The observed wind speeds were in the range 0‐4.5ms 21 with a mean value of 0.5ms 21 . Based on this study, the HP overestimated the snow amount by about a factor of 2 as compared to the Pluvio measurements. Further data analysis using the raw output HP data suggests that this was because of false precipitations produced, particularly by the downslope flows in the complex terrain when the wind speeds were relatively stronger. This false precipitation varied from 20.9 to 1.3mmh 21 with two peaks at 0.1 and 0.3mmh 21 depending on wind speed—the larger peak being at higher wind speeds. Since the observed wind speeds were relatively calm, setting the correction factor to 0.15mmh 21 gave reasonable values as compared to the Pluvio data. The difference between the corrected HP and Pluvio accumulation data varied from 16% to 3% depending on wind speed. The observed snow density in January 2010 varied from 0.04 to 0.32gcm 23 with a mean value of 0.08gcm 23 . The snow amount measured using the corrected HP data agreed well with the manually measured values with a correlation coefficient of 0.93.

The Sensitivity of the Radiation Budget in a Climate Simulation to Neglecting the Effect of Small Ice Particles

The sensitivity of the atmospheric radiation budget to ignoring small ice particles (D 100 m) in parameterization of the mean effective size of ice particles was investigated by using the Canadian Centre for Climate Modelling and Analysis (CCCma) third-generation general atmospheric circulation model (AGCM3). The results indicate that small ice particles play two crucial roles in the radiative transfer that influence the simulated climate. First, they inhibit the IR radiation from escaping to space and, second, they enhance the scattering of solar radiation. On average, these two effects tend to partially cancel each other out. However, based on AGCM simulations, the small ice crystals make clouds more opaque to IR radiation. Generally, 5-yr seasonally averaged GCM results suggest that the strongest anomalies in outgoing longwave radiation (OLR) are found in the Tropics, reaching 15 to 25 W m 2 in areas where cold high cirrus anvil clouds are prevalent. The global average change in net cloud radiative forcing was 2.4 W m 2 in June–August (JJA) and 1.7 W m 2 in December–February (DJF). The change in globally averaged 5-yr mean cloud forcing was close to 1.9 W m 2 . When the small particles were included, the globally averaged 5-yr mean precipitation decreased by about 8%, but cloudiness increased only slightly (by 2%). The 5-yr averaged global mean surface (screen) temperature also increased slightly (about 0.2°C) when the small ice particles were included.

Parameterization of Runway Visual Range as a Function of Visibility: Implications for Numerical Weather Prediction Models

AbstractA parameterization of runway visual range (RVR) has been developed using relevant meteorological parameters such as visibility (Vk), relative humidity (RH), temperature (T), precipitation intensity (PI), and precipitation type (PT) measured in years between 2009 and 2011 at Toronto Pearson International Airport during the Canadian Airport Nowcasting Project. The FD12P probe measured PI, Vk, and PT. The observed Vk and PT were tested against data reported by hourly surface observations (SAs). The measured Vk has correlated well with the SA with a correlation coefficient (r) of 0.76 for Vk < 5 km, but the FD12P underestimated visibility by about 20% with a mean difference (MD) of about 196 m. For Vk < 2 km, the FD12P overestimated visibility by about 7% with an MD of 60 m. The SA reported slightly more snow events—22% as compared to 17%—but the FD12P reported many more snow grain cases than the SA. Both the SA and the FD12P reported rain at similar frequency—4% and 5%, respectively. Using a theoreti...

Decision Making Regarding Aircraft De-Icing and In-Flight Icing Using the Canadian Airport Nowcasting System (CAN-Now)

The Canadian Airport Nowcasting Project (CAN-Now) has developed an advanced prototype all-season weather forecasting and nowcasting system that can be used at major airports. This system uses numerical model data, pilot reports, ground in-situ sensor observations (precipitation, icing, ceiling, visibility, winds, etc), on-site remote sensing (such as vertically pointing radar and microwave radiometer) and off-site remote sensing (satellite and radar) information to provide detailed nowcasts out to approximately 6 hours. The nowcasts, or short term weather forecasts, should allow decision makers at airports such as pilots, dispatchers, deicing crews, ground personnel or air traffic controllers to make plans with increased margins of safety and improved efficiency. The system is being developed and tested at Toronto Pearson International Airport (CYYZ) and Vancouver International Airport (CYVR). A Situation Chart has been developed to allow users to have a high glance value product which identifies significant weather related problems at the airport. Some new products combining observations and numerical model output into nowcasts are being tested. This talk will describe the uses of the system for decisions regarding aircraft de-icing at the ground and in-flight icing over the airport. Some statistical verifications of forecast products regarding precipitation amount, precipitation type, in-flight icing, etc, will be given.

Performance of Emerging Technologies for Measuring Solid and Liquid Precipitation in Cold Climate as Compared to the Traditional Manual Gauges

AbstractPrecipitation amount, type, and snow depth ) have been analyzed using data collected during the 4Wing Cold Lake Research Project in northeastern Alberta, Canada. The instruments used include the Vaisala present weather detector PWD22 and present weather sensor (FS)11P, the OTT Pluvio2 automatic catchment-type gauge, the manual standard Canadian Nipher (CN) and Type B rain gauges, and a snow ruler. Both the PWD22 and FS11P performed well at detecting snow, rain, and drizzle events as compared to the human observer. The sensors predicted a higher frequency of ice pellet cases than the human observer. Segregation of precipitation phase using temperature alone appeared unrealistic at near-freezing temperatures. All the sensors agreed well at measuring liquid precipitation, but the Pluvio2 gauge with a single Alter shield underestimated the snowfall amount by 40%, mostly due to wind effects. After correcting the CN gauge catch efficiency (CE) due to wind effects, the CE of the Pluvio2 relative to the C...