Severe weather studies using data from the OQ-Net VHF Wind-Profiler Network

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With CFI and OIF support we (York University, University of Western Ontario and McGill) have now completed the installation of a unique regional scale network of ten VHF wind profilers (the O-QNet) in Ontario and southern Quebec. These are providing a valuable data set of hourly and three-hourly winds from about 400 m to 15 km above the surface. At York, our work has so far focused on issues of performance monitoring and quality control. This raised some initial concerns but these have been addressed and we have full confidence in the reliability and accuracy of the data. We plan to use the data to study spatial variations in winds throughout the troposphere in conjunction with meso-scale (WRF for example) meteorological models. We can also use the data to monitor the performance of operational weather forecast models for wind analyses and predictions and develop a climatology of tropospheric winds. A central theme of the proposed research will be to take advantage of the network to look at spatial features of the wind field. One approach will involve using triangles of three wind profilers, typically about 200 km apart, to estimate vorticity and divergence fields. This can be simply done by assuming linear variations of the velocity components in the horizontal coordinates at each geopotential height. Vorticity and divergence are important diagnostic parameters for synoptic and meso-scale meteorology. Integration of divergence will give an estimate of vertical velocity which can be linked to precipitation and severe weather. The profilers will also measure vertical velocity directly. Vorticity and upper level divergence are key quantities in the identification of conditions liable to spawn tornadoes and other severe summer weather. We will look at any nearby profiler data on all recent occasions where strong and damaging winds have occurred (resulting from tornadoes, sting jets or derechos for example) to investigate wind field structure and to see if timely distribution and use of the profiler data could be an aid in short term forecasting of similar events in the future.