The Pan and Parapan American Games (PA15) are the third largest sporting event in the world and were held in Toronto in the summer of 2015 (10–26 July and 7–15 August). This was used as an opportunity to coordinate and showcase existing innovative research and development activities related to weather, air quality (AQ), and health at Environment and Climate Change Canada. New observational technologies included weather stations based on compact sensors that were augmented with black globe thermometers, two Doppler lidars, two wave buoys, a 3D lightning mapping array, two new AQ stations, and low-cost AQ and ultraviolet sensors. These were supplemented by observations from other agencies, four mobile vehicles, two mobile AQ laboratories, and two supersites with enhanced vertical profiling. High-resolution modeling for weather (250 m and 1 km), AQ (2.5 km), lake circulation (2 km), and wave models (250-m, 1-km, and 2.5-km ensembles) were run. The focus of the science, which guided the design of the observation network, was to characterize and investigate the lake breeze, which affects thunderstorm initiation, air pollutant transport, and heat stress. Experimental forecasts and nowcasts were provided by research support desks. Web portals provided access to the experimental products for other government departments, public health authorities, and PA15 decision-makers. The data have been released through the government of Canada’s Open Data Portal and as a World Meteorological Organization’s Global Atmospheric Watch Urban Research Meteorology and Environment dataset.
ABSTRACT: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), 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 h. The nowcasts, or short term weather forecasts, should allow decision makers such as pilots, dispatchers, de-icing crews, ground personnel or air traffic controllers to make plans with increased margins of safety and improved efficiency. The system has been 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. New products combining observations and numerical model output into nowcasts have been tested. Some statistical verifications of forecast products, with comparisons to persistence, covering both a winter (2009/2010) and summer (2010) period have been made. Problems with the prediction of relative humidity and wind direction are outlined. The ability to forecast categorical variables such as ceiling, visibility, as well as precipitation rate and type accurately are discussed. Overall, for most variables, the nowcast systems can outperform persistence after the first 1 or 2 h, and provide more accurate forecasts than individual Numerical Weather Prediction models out to 6 h.
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.
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.
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