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Published on May 2, 2008

Author: Reginaldo

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MESOSCALE SURFACE OBSERVING NETWORK for the VANCOUVER 2010 WINTER OLYMPICS. World Weather research Program Symposium on Nowcasting and Very Short Range Forecasting, Toulouse, France. Sept 5-9 2005 C. Doyle, Environment Canada, Suite 201, 401 Burrard Street, Vancouver, Canada, V6C 3S1:  MESOSCALE SURFACE OBSERVING NETWORK for the VANCOUVER 2010 WINTER OLYMPICS. World Weather research Program Symposium on Nowcasting and Very Short Range Forecasting, Toulouse, France. Sept 5-9 2005 C. Doyle, Environment Canada, Suite 201, 401 Burrard Street, Vancouver, Canada, V6C 3S1 Slide2:  The overall venue for the 2010 Games will be held in a landscape ranging from coastal plains to complex mountainous terrain. The existing weather observing network in this area has many gaps and may not detect small scale, yet intense, weather systems that could significantly affect public safety and security, and the operation of the Olympic Games. New surface weather data sources may contribute to a number of meteorological objectives. Besides informing current weather conditions, surface data can be used to validate NWP, populate surface weather analyses, and to construct UMOS - Updateable Model Output Statistics - forecast equations. Good results will depend, in part, on high quality model output. The requirement for an enhanced density of surface weather observations over southwestern British Columbia is based on the need for meteorologists to have a detailed and precise understanding of weather at the outdoor venues, highway routes to Whistler, the city of Vancouver and local transportation corridors during the Olympic period. In an ideal world, observations are readily available, taken where and when needed, meet every requirement and all at minimum cost. Deciding where to place new observing systems depends on the accessibility of locations and what contribution they are expected to make to the validation of very high resolution numerical weather prediction models Other complicating issues include the acquisition of appropriate permits and the conduct of Environmental Assessments. In short, the design of an optimal observing network may not be possible. Nevertheless, with the results of some simulations from a high resolution model (originally designed for wind-energy prospecting) some clues as to the best locations for instrument placements were obtained. Slide3:  Since the installation of our observing network and and planning are bounded both in time and resources, criteria from which to prioritize the allocation of monitoring resources were necessary. Figure 1 indicates the current surface observing network and topography of the region. Slide4:  In the case of 2010, the surface network design team had the serendipitous advantage of being able to review data newly produced by the Canadian Wind Energy Atlas. The atlas is based on numerical simulations, run at 5 km resolution, representing average wind speed and wind-energy generation potential across Canada. Its basic climatology was derived from the NCAR/NCEP reanalysis (Kalnay et al., 1996). Mesoscale simulations were performed with the Mesoscale Compressible Community (MC2) model (Benoit et al., 1997), a research model widely used by Environment Canada, Canadian Universities, and others. Output was generated on a Polar Stereographic grid with 5 km resolution at latitude 60 N. There are 28 unevenly distributed vertical levels with the two lowest model levels for wind calculations at 50 and 150 m. The roughness field was determined entirely from the land use data. A simplified physics scheme without radiation, condensation or diurnal cycle was used in order to accelerate model convergence to the final state. The time step is 120 seconds and there is a nine-hour adaptation period for the initial flow to the surface geophysical properties. Figure 2 illustrates the calculated 10-meter ASL average wind field over southwestern British Columbia. It should be noted that orography and land use data were interpolated to the model resolution from the U.S. Geological Survey data base at 900 m resolution. This point alone ensured that whatever data is developed will not be entirely reflective of the complexity of the terrain in the area. Figure 2 –Wind model output: 10 m average wind speed at 5 km resolution with 5 km topography:  Figure 2 –Wind model output: 10 m average wind speed at 5 km resolution with 5 km topography Slide6:  An examination of the 10 m (above sea-level) average wind field indicated a number of salient points: Over water, the average wind speeds are significantly higher that that calculated over land, which one would expect due to the influence of the roughness field. Howe Sound, for example, is a relatively open estuary where the Squamish River empties into Georgia Strait. It is often windy due to outflow from the interior, especially when surface high pressure predominates east of the Coast Ranges. Data from Pam Rocks, a station located on a small island in the entrance to Howe Sound, shows good correspondence with the wind map. Its calculated average wind speed is approximately 5.0 m/s and the wind model indicates 4-5 m/s in the area. Relatively high average wind speeds are more often found over higher elevations than lower elevations, also as one would expect. Since, however, the scale of significant topographical variation in the region is often much less than 5 km, areas where quite high average wind speeds have been recorded are not always captured by the model. Wind data from an inland station, Lytton, BC, located in the deep and narrow Fraser river canyon, north of Hope, BC, indicates the effect of topography. The model indicates a wind maxima in the Lytton area of 3-4 m/s. The calculated average annual wind speed at the Lytton automatic weather station is 7.9 m/s. As the actual width of the canyon is 1-3 km in the area, the model topography does not resolve the feature. Figure 3 illustrates the proposed surface network: Figure 2: proposed additions to the Environment Canada Observing network on behalf of the 2010 Winter Games:  Figure 2: proposed additions to the Environment Canada Observing network on behalf of the 2010 Winter Games Slide8:  A number of the new stations are actually existing stations that will be upgraded to 24 hours a day, seven days-a-week observations, with an expanded weather-element observing program. In addition, Environment Canada has installed, on behalf of the Vancouver Olympic Committee, five new automatic weather stations…three in the Whistler region, one in the Callaghan Valley and one at Cypress Bowl. These are the outdoor venues for 2010. All together there will be 14 new, 6 upgraded and 23 existing surface weather stations within a 150 km radius of Squamish, one-half of the way between Whistler and Vancouver, for a total of 43 in the network. Other meteorological data sources exist in the region courtesy of the British Columbia Government and the Greater Vancouver regional municipality. As the Games approach, NWP with resolution in the order of 1-2 km will be developed and validated. Environment Canada’s wind prospecting model has helped to confirm the importance of increasing model resolution to a fine enough scale to reflect weather consistent with the topographic nature of the region. The high resolution surface weather data network being created at this time will help to validate model output. Most of the stations will be concentrated in the topographically constrained canyon environment on the route between Whistler and Vancouver, and in the Whistler area itself. References: 1. Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woolen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetma, R. Reynolds, R. Jenne, and D. Joseph, 1996: The NCEP/NCAR 40-year reanalysis project. Bullet. Amer. Meteorol. Soc., 77, 437-471). 2. Benoit,R.,M. Desgagne,P. Pellerin,S. Pellerin,Y. Chartier and S. Desjardins, 1997: The Canadian MC2: A semi-lagrangian, semi-implicit wide-band atmospheric model suited for fine-scale process studies and simulation. Mon. Wea. Rev., Vol 125.

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