The Toronto 2015 Pan and Parapan American Games Experience

Although ECCC’s mandate for the Games was to provide venue-specific forecasts and alerts, various ongoing research and development activities were aligned to take advantage of the unique opportunities provided by the Games. ECCC’s research showcase for the Games leveraged our state-of-the-art science and technologies. The goal was two-fold: support ECCC’s operations during the Games, and learn from the research and development to make a great meteorological service even better.

ECCC showcased a number of new technologies and instruments, which are described in the following sections. The research instrument platforms provided observations that supplemented the automated land- and marine-based Mesonet described in Section 5. All available observations were used to increase our understanding of meteorological and air quality science, particularly over an urban environment. ECCC will use this new scientific information to improve the accuracy and lead time of its alerts.

11.1 Doppler LiDAR

Detailed measurements of wind speed and direction are crucial for creating accurate weather forecasts. Current wind measurements use an instrument (an anemometer) to provide wind speed and direction at one location. ECCC recently acquired two remote sensing instruments, Doppler LiDAR (Light Detection and Ranging). These Doppler LiDARs are a significant improvement over anemometers, as they provide detailed measurements of the wind every 3 m along a continuous line of sight out to approximately 7 km away (depending on the weather conditions).

Doppler LiDARs are a relatively new technology that has only recently been made more affordable due to mass production techniques. The instrument uses light in the form of a pulsed laser to observe the movement of aerosols such as minute dust and other particles in the air, and to measure the direction and speed of the wind based on that movement. Near real-time observations of winds at any elevation or angle are possible using this technology, with each scan taking less than a few minutes to complete.

Two Doppler LiDARs were deployed during the Games; one at Hanlan’s Point (Toronto Centre Island) and one in the back of a pickup truck, enabling it to be mobile. The main objective of the Doppler LiDARs was to provide near real-time wind data to ECCC’s OSPC in order to provide wind fields for severe weather monitoring and characterization of lake-breeze fronts. Another objective was to measure winds over Lake Ontario to aid Games officials directing the sailboat events.

Two Doppler LiDARs successfully provided detailed mappings of wind speed and direction during severe weather events, improving our understanding of the convective and dynamic processes driving those events. Significant oscillations in wind speed were mapped across Lake Ontario. The mobile LiDAR mounted on a truck enabled researchers to position the LiDAR at areas of interest and take mobile measurements of convective wind fields during storms. This allowed researchers to study the evolution of the lake-breeze front uniquely and in significant detail when combined with measurements from the Atmospheric Mobile Meteorological Observational System (AMMOS) (see Section 11.2). The LiDAR mapped winds before, during and after lake-breeze formation; the mobile platform allowed researchers to relocate the LiDAR during lake-breeze events and to take measurements from multiple locations across the GTA, which were used to study the relationship between wind speed and wave forcing over the lake.

The Doppler LiDARs successfully provided near real-time data on wind speed and wind direction to ECCC’s forecasters. Measurements of wind speed, direction and wind field maps were uploaded in near real-time to the RSDs for analysis by forecasters and researchers, and was available to the TO2015 event coordinators through ECPASS (see Section 11.10). Measurements from both LiDARs, which mapped out wind speed and direction over Lake Ontario and Toronto’s harbour, aided in coordinating the timing and location of sailing events. These wind measurements were also useful for determining the evolution of storm systems by measuring the degree of convection (upward moving air) and the horizontal movement of air masses above the GTA; these measurements will be compared with numerical weather prediction model results and analyzed in further detail.

Analysis of lake-breeze fronts, model winds comparisons, and wind-wave relationships measured over the buoy are under way. Further evaluation of the Doppler LiDAR technology will be conducted to assess its performance in Canadian Arctic conditions. Deployment of additional Doppler LiDARs at several Arctic locations and at Toronto Pearson Airport will be completed in summer 2016.

Figure 23.

Photo: © Paul Joe

11.2 Automated Mobile Meteorological Observing System

Three hybrid vehicles equipped with AMMOS units were deployed during the Games as part of the high-resolution atmospheric monitoring network, the Mesonet. AMMOS vehicles travelled routes between the Lake Ontario shore in Toronto and suburban/rural areas to the north and west. These three mobile stations collected standard meteorological data (i.e., temperature, humidity, pressure, wind speed and direction) at one-second intervals in locations where fixed stations cannot, such as along roadways surrounded by large buildings in downtown Toronto known as “urban canyons.” AMMOS vehicles also carried fine particulate air quality sensors, and one AMMOS vehicle carried a prototype AirSENCE air quality sampling system (see Section 12.3.3).

The AMMOS mobile observations complemented those from the Mesonet, helped monitor weather and air quality conditions during the Games, and thoroughly sampled lake-breeze fronts for study post-Games. Three summer students and 6 ECCC scientists operated the 3 vehicles, mostly in pairs (1 student with 1 scientist). Nearly 10,000 km were travelled over 22 intensive observation days.

On July 28 and 29, 2015, some of the hottest weather of the summer provided an opportunity to make unique measurements of Toronto’s urban heat island. Two AMMOS units, the CRUISER mobile air quality unit (see Section 11.4), and Western University’s urban meteorology mobile unit made coordinated measurements over two periods: during peak heating on the afternoon of July 28 and during peak cooling in the early morning hours of July 29. Preliminary results suggest that some of the highest ozone (O₃) concentrations in Toronto in years were measured on the afternoon run. Temperature gradients proved equally interesting, with early morning temperatures of approximately 27°C in downtown Toronto, while outlying areas reported approximately 19°C. This unique dataset can be used to validate the performance of the high-resolution urban-scale model for this event.

AMMOS technology, as developed by ECCC, has been used in Canada and the United States since 2007 to sample severe thunderstorm and tornado environments. However, this was the first time that multiple AMMOS units had been used in a coordinated fashion in Canada, and the first time that AMMOS technology was used to gather information about heat stress and temperature in urban canyons and air quality in an urban environment, as well as to provide data in support of sporting events.

Figure 24.

Photo: © David Sills

Figure 25. Temperature, dew point and relative humidity data collected by an AMMOS-equipped vehicle on 26 July 2015

Description

Graphic plot of temperature (red line), dew point (green line) and relative humidity (purple line) data collected by an AMMOS-equipped vehicle. The measurements were made on 26 July 2015 as the AMMOS repeatedly sampled a narrow lake-breeze front along Toronto’s Dufferin Street. Data are plotted for the period from 14:35 UTC to 17:35 UTC. The plot shows that the AMMOS sampled warm, dry air while on the north (landward) side of the lake-breeze front and cool, moist air on the south (lakeward) side of the front. On the north side, the temperature was approximately 28°C, the dew point 17°C and the relative humidity 20%. On the south side, the temperature was approximately 24°C, the dew point 18.5°C and the relative humidity 28%. There are 6 passages across the lake-breeze front in total over this period.

11.3 Southern Ontario Lightning Mapping Array

A Lightning Mapping Array allows for high-resolution 3D detection of “total lightning,” meaning both cloud-to-ground and in-cloud lightning flashes. This cutting-edge technology was first implemented in the United States for lightning detection across areas with a high risk of severe thunderstorms.

The Southern Ontario Lightning Mapping Array (SOLMA), installed for the Games, was the first application of this system in Canada. It consists of 14 ground stations in the Greater Golden Horseshoe Area tied to a central computer that processes and integrates the data. SOLMA has a lightning detection efficiency of 100% within the array and has very fine temporal and spatial resolutions (on the order of tens of nanoseconds and tens of metres, respectively). Thunderstorms were detected on 9 days during the Pan Am Games in July, and on 5 days during the Parapan Am Games in August, with strong thunderstorms on 6 of those days. These data were available to the RSDs, OSPC forecasters and the 2 briefing teams.

The SOLMA was installed primarily to investigate short-term forecasting of storm intensity, or “nowcasting.” Recent studies have shown that a rapid increase in total lightning activity, termed a “lightning jump,” often precedes the occurrence of severe weather. Increasing the lead time for alerts related to severe weather is therefore possible using SOLMA data.

The SOLMA data are also used to improve scientists’ understanding of lightning development and evolution over the lifetime of a thunderstorm, to compare with Canadian Lightning Detection Network data, and in general to gain familiarity with the uses of total lightning. A new total lightning product will soon be available to scientists and meteorologists across Canada via the Geostationary Lightning Mapper aboard the National Oceanographic and Atmospheric Administration’s (NOAA) next generation of geostationary Earth observing systems, the GOES-R satellite, scheduled to be launched in October 2016.

Figure 26. 3D SOLMA data capturing full details of lightning flash

Description

Graphic showing 3D SOLMA data (left; underlying map from ©2015 Google Earth). The graphic captures full details of the actual lightning flash, including the parts hidden by cloud, in the early morning hours of July 18, 2015. The flash was generated over the western part of Lake Ontario with part of it branching off to the northwest to reach the ground near Burlington and part of it branching off along the top, anvil portion of the storm, never reaching ground level. The flash is shown as hundreds of points with different colours, with the colours indicating the passage of time (blue is oldest and red is newest). The photo on the right shows the same flash as captured by a camera, and similarities between the lightning flash captured by SOLMA and the same flash captured by the camera are clear (photo used with the permission of David Piano).

11.4 CRUISER and Related Air Quality Measurements

Air pollution in large Canadian cities such as Toronto and the surrounding Greater Golden Horseshoe Area continues to pose risks to human health. The key pollutants used to monitor this pollution and inform the public are fine particulate matter (PM_2.5), ground-level ozone (O₃) and nitrogen dioxide (NO₂), which are used to compute the Air Quality Health Index (AQHI). Transportation is an important source of these pollutants, including the large amount of car and truck traffic on the highways and roads, and transit hubs such as airports and rail yards, where considerable numbers of people and/or quantities of goods move through each day. Important scientific questions remain about the characteristics of the full mixture of gaseous and particulate pollutants associated with transportation emissions, their correlation with variations in the AQHI across both space and time, and the influence of local weather patterns on these variations, especially lake breezes caused by Lake Ontario.

Air quality researchers deployed several new pollutant measurement technologies during the Games to address these questions. ECCC’s mobile air quality laboratory (CRUISER – Canadian Regional and Urban Investigations System for Environmental Research; see Figure 27) is a specially equipped truck fitted with advanced air pollution measuring instruments. During the summer of 2015, the CRUISER was driven along various routes in the region depending upon the weather pattern. The research team also conducted unique experiments at a location adjacent to Highway 401 and in both downtown and north Toronto. A remote-sensing system was installed to measure several pollutants and atmospheric mixing along a path over Highway 401 to evaluate a new way to measure emissions. This also included highly sensitive particle detectors capable of measuring the tiniest quantities of soot coming from engines and the amount of sunlight that these particles absorbed, to better understand their impact on our climate.

The CRUISER carried the latest technology to measure NO₂, chemical components that make up PM_2.5 and gaseous pollutants, such as volatile organic compounds, that contribute to the formation of O₃ and PM_2.5 and potentially to the toxicity of the air we breathe. To date, air pollution studies have shown that the presence of Lake Ontario has a significant impact on the local weather and air quality over the greater Toronto region. The CRUISER successfully made measurements across the lake-breeze front on July 20, 24 and 28, and these data are helping to assess how well the high-resolution meteorological and air quality forecast models were able to perform. The July 28 event was also associated with a significant “urban heat island” effect, with O₃ levels exceeding 90 ppb, among the highest measurements made in recent years. On seven days, the CRUISER was driven along the remote-sensing path on Highway 401. These comparative measurements are now helping the research team assess the feasibility of longer-term remote sensing studies to better understand how much air pollution is generated from one of the busiest sections of highway in the world.

All of the data gathered on the CRUISER drives, bordered by Burlington (west), Ajax (east), Newmarket (north) and Lake Ontario (south), are being mapped to explore small-scale patterns within neighbourhoods and large-scale patterns across the entire region. This will provide the most detail ever obtained in the region, which will lead to new approaches to test and improve the air-quality prediction models and estimates of what people in this region are breathing. Ultimately, this work will support future assessments of air pollution health impacts and studies of transportation’s role in air pollutant issues. Furthermore, the experience that air quality researchers obtained in deploying new measurement technologies during the Games will pay dividends to many future air pollution studies throughout Canada, including in other cities, and downwind of large resource development activities such as the oil sands.

Figure 27.

Photo: © Jeff Brook

11.5 Ultraviolet Index Demonstration Products

ECCC has been providing one-day forecasts of the ultraviolet (UV) index for various locations in Canada since the early 1990s. The UV index forecasts mainly reflect the attenuation of the solar UV irradiance at solar noon by the atmospheric column ozone amount and the daytime averaged cloud opacity. The column ozone amount is first statistically estimated from weather forecast conditions, followed by an adjustment based on column ozone measurements from stations in the ECCC ozone network. The additional attenuation due to clouds is imposed through a scaling factor estimated from cloud opacity conditions.

ECCC has since implemented a chemical data assimilation system for ozone forecasting that is fully integrated into its NWP system. Ozone satellite measurements are assimilated for producing real-time ozone analyses, which serve as initial conditions for the forecasts. This coupled numerical system produces comprehensive UV index forecasts for all weather conditions, which take into account daily ozone and cloud variability.

Initial demonstration UV index forecasts from this experimental system were generated for the Games, to be validated against four additional ground-based UV radiometers (ultraviolet radiation instruments; see Section 5.6) installed across the region. The product made available during the Games consisted of hourly forecast maps of the all-sky UV index covering four days and updated daily. The clear-sky UV index and column ozone maps were also made available through the Université du Québec à Montréal (UQAM) website. These main products were produced with a resolution of 25 km, although a specialty UV index field was generated at a 10-km resolution over the Games footprint. An evaluation of the demonstration UV index is currently under way, as are evaluations for the various related products beyond the currently operational one-day forecasts.

11.6 Unmanned Aerial Vehicle

The Unmanned Aerial Vehicle (UAV) used during the Games was developed for atmospheric profiling of meteorological parameters, including radiosonde or upper air observations (see Section 5.7 and Figure 28). The Atmospheric Profiling-UAV (APUAV) instruments have been developed over the last three years. The APUAV has four small propellers, is lightweight (approximately 1.5 kg) and can carry an instrument “payload” of approximately 700–800 grams. Its maximum flying height can reach 3 km. It is completely controlled by a computer system and can make flight patterns similar to aircraft manoeuvres. The main meteorological observations taken by the UAV include temperature, relative humidity, pressure, wind speed and gusts, and GPS positioning information. In addition to these measurements, there were two unique air quality probes added to measure carbon dioxide (CO₂) and the total number of aerosol concentrations.

The APUAV used during the Games was unique in the way that atmospheric profiling of meteorological parameters and aerosol observations were performed. Its measurements were found to be comparable to the observations of the PUMS (Pan Am and UOIT [University of Ontario Institute of Technology] Meteorological Supersite), which was located at the UOIT Wind Farmland Campus, east of Toronto (see Section 11.7). The observations from the APUAV can be used for numerical forecast model validations, remote sensing applications, monitoring for environmental issues, and contributing to profiling performed by radiosondes.

Observations collected by the APUAV during the Games were found to be comparable to measurements collected by other platforms such as microwave radiometers and in-situ sensors. New fast-response sensors are needed for the APUAV profiling to help generate better products for atmospheric profiling and monitoring applications. Its measurements are very useful for boundary layer (i.e., lowest levels of the atmosphere) applications, including modelling, forecasting and climate assessments.

Figure 28.

Photos: © John MacPhee

11.7 Supersites

ECCC’s researchers operate an enhanced meteorological observation site at Toronto Pearson International Airport, known as the “Pearson Supersite.” Collecting data since 2007, the Supersite is home to a suite of specialized weather instruments that support research and development into short-term forecasting and nowcasting of high-impact weather at and in the vicinity of airports. Co-located with the existing staffed NAV CANADA weather observation station, the site is furnished with an icing detector, lightning sensor, multi-view camera system, specialized radar (vertically pointing X-band), horizontal visibility meter, multiple ceilometers to determine height of cloud base, and surface weather station with temperature, relative humidity and wind sampled at World Meteorological Organization standard measuring heights. The site also hosts a number of precipitation sensors including weighing gauge-type instruments and optical and radar-based systems. Multiple measurements of the same weather element allow for instrument intercomparisons, which facilitate the exploration and assessment of new observational technologies. From the Pearson Supersite, instrument data are transmitted to scientists in near real-time with a one-minute frequency for many of the instruments.

During the Games, these data were made available to support weather forecasting. Of particular interest were precipitation accumulations from the different sensors and profiles from the vertically pointing X-band radar. These radar data were used to distinguish between precipitation particle types such as ice crystals, snow, rain and drizzle at different heights in the atmosphere up to 8 km.

Beyond the Games, the Pearson Supersite will continue to be a key observational site and instrument testbed. Enhanced observations will support research and development efforts into aviation nowcasting, numerical weather prediction model verification and weather instrument performance evaluation.

A second supersite, the PUMS site (Pan Am and UOIT [University of Ontario Institute of Technology] Meteorological Supersite) was located at the UOIT Wind Farmland Campus in Oshawa, east of Toronto. This Supersite, which includes various new sensors, was designed for multi-purpose meteorological applications (see Figure 29). Its uniqueness comes from various state-of-the-art meteorological sensors. It has been developed over the last 10 years for measuring fog, visibility, precipitation, clouds, icing, radiative fluxes, wind and turbulence, and aerosol characteristics using state-of-the-art observing instruments and platforms. The PUMS measurements resemble measurements from a research aircraft. In addition to in-situ sensors, PUMS includes remote sensing platforms such as a Radiometrics Profiling Microwave Radiometer (PMWR) (a number of products relating to liquid water and water vapour in the atmosphere can be deduced from the radiation measurements), a Vaisala ceilometer (measuring the height of cloud bases), a microwave rain radar (MRR) (measuring rain rate, liquid water content and drop size distribution from near ground to several hundred metres) and an APUAV (taking meteorological measurements at different heights in the atmosphere; see Section 11.6). This site also had access to GOES-R operational weather satellite products that can be used for 3D analysis of weather processes.

The goals of this site were to: 1) compare PUMS observations with APUAV profiling flight measurements; 2) develop microphysical parameterizations for modelling applications; 3) validate satellite retrievals and modelling simulations during local meteorological events, e.g., lake-breeze effects and large-scale meteorological effects on local weather conditions; and 4) study precipitation variability over an area of about 2 km². In addition, this site provides specific observations to ECCC’s scientists and those in UOIT who facilitate research and test the instruments’ performance.

The main findings from the PUMS site will be used for model validations, new instrument development and testing, improvements in nowcasting, process studies of physical processes, and satellite validations for cloud and precipitation products.

Figure 29.

Photo: © Ismail Gultepe

11.8 Pan Am Committee Boat Meteorological Sensors

Two of the Pan Am Sailing committee boats were outfitted with meteorological sensors, which were similar to those in the land-based Mesonet (see Figure 30). These sensors provided invaluable, though infrequent, data by extending the surface data measurements over the lake. The boats (collaboration with two Toronto-area yacht clubs) were deployed about two hours prior to the start of all Pan Am sailing events, and then again during club races until the end of the sailing season in October 2015. There were no sailing events during the Parapan American Games.

The sensors were programmed to collect 1-second data of pressure, temperature, humidity, wind speed and direction. The data is processed to show 1-minute and 10-minute running averages and were available on the committee boats (10-second updates) and on the ECPASS Web display (10-minute updates) (see Section 11.10) to show very short-term and medium-term trends.

One of the remarkable observations was the fine-scale periodicity in both the wind direction and speed. The periodicity is of the order of about 6 oscillations in a 10 minute period. The wind direction and speed had variations (peak to peak difference) of about 15 degrees and about 1 m/s, respectively. This oscillation, which is critical to racing, would not have been seen with 1-minute data as with the land-based Mesonet data. This data display was quickly adopted by committee boat officials for race planning. The Doppler LiDAR was deployed to scan over the committee boats (particularly the “mobile” LiDAR) to produce Doppler wind maps for comparison and verification purposes.

Figure 30.

Photo: © Reno Sit

11.9 The Research Support Desk – “Next Generation” Forecasting, Nowcasting and Alerting Demonstration

During the Games, ECCC research meteorologists conducted a “Next Generation Forecasting, Nowcasting and Alerting Demonstration” via two Research Support Desks (RSDs) in the OSPC area. The goal was to evaluate the “MetObject” approach and its ability to better integrate observations and numerical model guidance, and to facilitate forecaster interaction with semi-automated prediction and alerting systems. Since the MetObject approach involves multiple spatial and temporal scales--from continental scale to storm scale--the “optimal human machine mix” needed for effective analysis, diagnosis and prognosis of summer convective storms (e.g., thunderstorms) was investigated at each scale. High-resolution monitoring and numerical modelling, and other science showcase technologies, were also put to full use for this demonstration. The participating scientists provided important input to the forecasters in real time and will provide valuable information to ongoing projects post-Games.

a) Forecasts to 72 hours

MetObject forecast depictions were generated at “key frame” times (every 3 hours for day one, every 6 hours for days two and three) to show areas where thunderstorms and summer severe weather were expected in Ontario and surrounding regions, with a focus on the Games domain (see Figure 31). The MetObjects at key frames were interpolated to 10-minute intervals to allow generation of animations, and time series data at various points. The MetObjects at key frames were also used to derive new integrated MetObjects for use in “convective outlook” products.

Automated “first-guess” MetObjects were generated using a variety of guidance, including numerical weather prediction model-based thunderstorm parameters. A balance between “best data” and “best form” was investigated, since such a balance will be required in order for forecasters to make effective use of first-guess MetObjects.

Figure 31. Example of an ECCC MetObject forecast depiction at a key frame time

Description

Example of an Environment and Climate Change MetObject forecast graphic depiction at a key frame time (July 19, 2015 18 UTC or 2:00 p.m. local time). The map covers the area of southern Manitoba, Ontario, southern and central Quebec, western New Brunswick and neighboring U.S. states.
The maps can be used to depict:

• positions of fronts (lake-breeze, land-breeze, gust, other (e.g. cold, warm, occluded, quasistationary)), jets (upper, lower) and trofs (surface, upper level).
• wind barbs (depicting wind speed and direction)
• shaded areas representing different levels of occurrence risks for thunderstorms and severe storms

For this map, a cold front stretches northeast from southern Lake Huron to southwest Quebec with a warm front southeast through New York to the Atlantic Ocean. An occluded front stretches north-northwest from southwest Quebec into James Bay.
Lake breeze frontal positions are shown along western Lakes Superior and Michigan; southern Lake Huron and Georgian Bay; and north and south shores of Lakes Erie and Ontario.

There are four low-level jets:

• West-east through southern Manitoba (35 kts)
• West-east from South Dakota to eastern Lake Superior (35 kts)
• West-east through central Michigan (35 kts)
• Southeast-northwest from central Quebec to Hudson Bay (35 kts)

There are three upper-level jets:

• West-east from southern South Dakota to southern Georgian Bay to New York state (95 kts)
• Southeast from Lake Winnipegosis, Manitoba to just south of Lake Superior (110 kts)
• West-east from just south of Labrador (speed not given)

There are three upper-level trofs:

• Northwest to southeast west of James Bay
• Southwest to northeast through northern Lake Winnipegosis to northern Lake Winnipeg
• Northwest to southeast from western Gulf of St. Lawrence to the Atlantic Ocean

There are two surface trofs:

• Southwestern Ontario northeast to Toronto
• Central New York State north to St. Lawrence River

Thunderstorms are shown as being likely near the occluded front, across the northeastern United States, and in southwestern Ontario. Otherwise there is a chance of thunderstorms ahead of the cold and warm fronts in southern Ontario, southwestern Quebec and the northeastern United States. Severe storms are probable in two smaller areas embedded within these areas in eastern Ontario and central New York State/western New Hampshire.

Collaboration between the two RSDs was evaluated, with each working at different temporal/spatial scales, then sharing resulting MetObjects to create collaborative products.

Subjective and objective near-real-time verification products were created so that forecasters could gauge their performance after the end of each shift and use that information to calibrate their efforts for the next shift.

b) Hourly Analyses/1–2 hour Nowcasts

Analyses of mesoscale features (for example, lake-breeze fronts) that positively influence the development or intensification of thunderstorms and related severe weather were performed hourly using the enhanced Mesonet monitoring data as well as operational radar and satellite data (see Figure 32).

Nowcasts of the development of new thunderstorms one to two hours into the future were made using data from the hourly analyses as well as rapid update cycle numerical model data.

Figure 32. Hourly meteorological analysis in the Games region

Description

Map showing the meteorological analysis in the Games region over the Greater Golden Horseshoe Area of southern Ontario, valid for 18:00 UTC or 2:00 p.m. local on July 19, 2015. Magenta lines indicate estimated positions of lake-breeze fronts. The yellow outline indicates an area where thunderstorms are expected to develop in the next one to two hours. Surface weather observations are plotted and show a generally southwesterly flow between 5 and 15 knots. Weather radar returns indicate that thunderstorms have developed to the west of Kitchener, and speckled green areas indicate insects detected by the radar. These lines of insects can be used to identify lake-breeze fronts. Lastly, clouds from visible-channel satellite imagery are also overlaid. Cumulus clouds are present over land and the sky is mostly cloud-free over the lakes. Cloud is more developed where thunderstorms are beginning to form west of Kitchener.

c) Storm-scale Nowcasting to 30 minutes

A new semi-automated approach for thunderstorm tracking, intensity trending and threat alerting was tested. It is anticipated that nowcasts of thunderstorm intensity will allow greater lead time for alerts.

11.10 Environment Canada Pan Am Science Showcase

An externally accessible, password-protected website was created to showcase science initiatives during the Games. The site, known as ECPASS (Environment Canada Pan Am Science Showcase) can be found at http://ecpass.ca. The website allowed real-time access to data from the following science initiatives:

• Next Generation Forecasting, Nowcasting and Alerting Demonstration;
• Automated nowcasts (lightning, INTW point forecasts, URP radar nowcasts);
• High-resolution urban scale meteorology model;
• Air quality model;
• Wave model;
• SOLMA 3D total lightning observations;
• Supersite observations at Pearson Airport and UOIT in Oshawa;
• Mesonet observations;
• AMMOS vehicle-based observations; and
• Doppler LiDAR.

ECPASS also served as the communications hub for science activities, with a blog (daily posts) and forum (real-time communication). More than 250 blogs and forum posts were written over the period covering both Games.