5 0 RESULTS PART II Synoptic Evolution Timing

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5. 0 RESULTS PART II: Synoptic Evolution & Timing of Peak Emergence Composite Evolution:

5. 0 RESULTS PART II: Synoptic Evolution & Timing of Peak Emergence Composite Evolution: Composite Time-Series: • • MSLP & Tmax Individual daily composites were constructed for a 7 day period centered around the composite for peak emergence. The evolution of the synoptic conditions is depicted in the daily time series of the composite reanalysis fields for the grid cell nearest to Prince George (below) and the composite surface pressure patterns two days preceding, and 2 days after the composite for peak emergence (right). DAY-2 COMPOSITE 7 -DAY TIME-SERIES (YXS Reanalysis Cell) Timing of Peak Emergence: • The results suggest peak emergence coincides with a regional scale drop in atmospheric pressure and a relative maximum in atmospheric instability, associated with the movement of weak surface troughs of low pressure from the north, while the center of the 500 h. Pa ridge is directly above the region. Synoptic Evolution: • • • DAY-0 Periods of fair-weather are triggered by a ridge of high pressure building into BC from the Pacific High that leads to clearing skies and increasing surface pressure over the region. Increased solar radiation contributes to intense surface heating that is accompanied by a building of an upper level ridge to the west Temperatures continue to warm as the upper level ridge intensifies and moves eastward. The end of the heating cycle is typically triggered by the passage of low pressure systems from the west that are steered around the surface ridge. Pressure begins to fall as the trough approaches, and temperature continues to increase due to an intensification of the south-north pressure gradient, temporarily advecting warm continental air into the region. A trough of low pressure extending southward from the surface low gradually approaches BC from the north, bringing a shift in wind direction and cooler air. DAY+2 6. 0 COMPOSITE VALIDATION: Comparison to Actual Emergence Events REANALYSIS 7 -DAY TIME-SERIES (YXS Grid Cell) STATION 8 -DAY TIME-SERIES (UNBC/YXS) Validation Data: • • Historical emergence monitoring data documented in the scientific literature, and monitoring data collected by forest licensees, are currently being collected analyzed to corroborate the timing of peak emergence relative to the synoptic evolution. Additionally, a daily emergence monitoring campaign was undertaken in a forested area near UNBC between June 22 and July 22, 2004. Preliminary Results: • • A period of rapid emergence was recorded near UNBC between July 12 and July 19 (see left), and peak emergence occurred on July 15. The modelled reanalysis, and observed station trends, are similar to the composite time-series. The heating cycle is characterized by 4 days of consecutive warming. Peak emergence coincides with the center of the 500 h. Pa ridge over the region, and a drop in station pressure on the order of 3 h. Pa per day. Temperature reaches a maximum as the pressure reaches a relative minimum. The daily maximum temperature and station pressure closely follow the trends in the reanalysis data, providing an additional justification of the appropriateness of using the NCEP/NCAR Reanalysis data set, and supports the synoptic climatology approach adopted in this analysis. 7. 0 CONCLUSION: Expected Benefits & Future Work Conclusion: • • • Understanding the relationship between the synoptic and surface environment brings order to the observed variability of winds above the forest canopy. Mesoscale modelling will allow these relationships to be extrapolated at a higher spatial resolution than could be attained by surface measurements alone. The trends in the synoptic time-series will allow historical rapid emergence events to be identified from weekly monitoring by licensees, and thereby allow the timing of peak emergence to be identified with greater confidence. The fact that peak emergence occurs under a developing and propagating upper level ridge highlights the importance of determining whether above canopy transport is behavioural, or a random meteorological interaction. The answer to this question is beyond the scope our investigations, however, future work may provide further insight into this issue. Field Monitoring Campaigns & Case Studies Future Work: • • • Ongoing and planned future work will examine in more detail, the fundamental relationships between movement patterns and topography. An examination of historical spread patterns and a series of idealistic simulations under the prevailing synoptic conditions, will explore the role of topographically driven wind systems in explaining medium range transport. The fact that favourable conditions for flight may exist through the depth of the atmospheric boundary layer, poses considerable challenges for modelling the above canopy transport component. Continued emergence monitoring and a possible above canopy capture field study, in conjunction with radar imagery and case studies, may provide guidance on this issue. Finally, the realistic simulation of multi-year events will allow for the development of probabilistic pathways (ensemble trajectories) of long range transport. Idealistic Simulations & Landscape Level Spread Patterns Realistic Simulations & Development of Probabilistic Trajectories Expected Benefits: • • This multi-phase atmospheric project will provide a better understanding of the between stand spread component of the mountain pine beetle infestation. It is anticipated that by incorporating this above canopy component into the current provincial population model, this work will contribute to a better understanding of past and future redistributions of the mountain pine beetle population. ACKNOWLEDGEMENTS: NCEP Reanalysis data provided by the NOAA-CIRES Climate Diagnostics Center, Boulder, Colorado, USA, from their Web site at http: //www. cdc. noaa. gov/ UNBC Research Assistants, Vera Lindsay and Janice Allen, performed the manual map-pattern classification and together with Ben Burkholder and Gail Roth assisted with the beetle emergence monitoring campaign. Funding for this work is provided by the Natural Resources Canada / Canadian Forest Service Mountain Pine Beetle Initiative. REFERENCES Gray, B. ; R. F. Billings, R. L. Gara, and R. L. Johnsey, 1972. On the emergence and initial flight behaviour of the Mountain Pine Beetle, Dendroctonus ponderosae, in Eastern Washington 71: 250 -259. Kalnay, E. , M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, A. Leetmaa, R. Reynolds (NCEP Environmental Modeling Center), M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang (NCEP Climate Prediction Center), R. Jenne, and D. Joseph (NCAR), 1996. The NCEP/NCAR 40 -Year Reanalysis Project. Bulletin of the American Meteorological Society 77(3), 437 -471. Kinter III, J. L. , B. Doty, 1993. The Grid Analysis and Display System: A practical desktop tool for anaylzing geophysical data. Information Systems Newsletter, 27, NASA, OSSA, JPL, Pasadena, CA. Logan, J. A. ; B. J. , Bentz, 1999. Model analysis of mountain pine beetle (Coleoptera: Scolytidae). Environmental Entomology 28(6): 924 -934. Mc. Cambridge, W. F. 1964. Emergence Period of Black Hills beetles from ponderosa pine in the Central Rocky Mountains. USDA For. Serv. Roc. Mountain For. and Range Exp. Stn. Res. Note RM-32. Safranyik, L. , and D. A. Linton, 1993. Relationships between catches in flight and emergence traps of the mountain pine beetle, Dendroctonus ponderosae (Col. : Scolytidae). Journal of the Entomology Society of British Columbia 90, 53 -61.