5.0%20RESULTS%20PART%20II:%20Synoptic%20Evolution%20

1
5.0 RESULTS PART II Synoptic Evolution Timing
of Peak Emergence
Composite Evolution MSLP Tmax

• Composite Time-Series
• 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

• 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 hPa ridge is directly above the
  region.
• Synoptic Evolution
• 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.

COMPOSITE 7-DAY TIME-SERIES (YXS Reanalysis Cell)
DAY-0
DAY2
6.0 COMPOSITE VALIDATION Comparison to Actual
Emergence Events

• Validation Data
• Historical emergence monitoring data documented
  in the scientific literature, and monitoring data
  collected by forest licensees, are currently
  being collected and 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 hPa ridge over the
  region, and a drop in station pressure on the
  order of 3 hPa 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.

REANALYSIS 7-DAY TIME-SERIES (YXS Grid Cell)
STATION 8-DAY TIME-SERIES (UNBC/YXS)
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.
• 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.
• Expected Benefits
• This multi-phase atmospheric project will provide
  a better understanding of the between stand
  spread component of the mountain pine beetle
  infestation.

Field Monitoring Campaigns Case Studies
Idealistic Simulations Landscape Level Spread
Patterns
Realistic Simulations Development of
Probabilistic Trajectories
ACKNOWLEDGEMENTS
NCEP Reanalysis data provided by the NOAA-CIRES
Climate Diagnostics Center, Boulder, Colorado,
USA, from their Web site at http//www.cdc.noaa.go
v/
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 71250-259. 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. McCambridge, 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.
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.