Effects of topography upon mountain pine beetle (Dendroctonus ponderosae) transport and dispersion as indicated by mesoscale meteorological models. Brenda L. Moore & P. L. Jackson Environmental Science and Engineering Program, University of Northern British Columbia, Prince George, B.C. V2N 4Z9 _________________________________________________________________________________________________________________ Acknowledgements: Funding for this work is provided by the Natural Resources Canada / Canadian Forest Service Mountain Pine Beetle Initiative. Introduction: The mountain pine beetle (MPB, Dendroctonus ponderosae) is a natural part of western North American forested ecosystems at low population levels The current epidemic has been reached due to: Recent weather conditions (warmer and drier) Abundance of mature lodgepole pine (Pinus contorta) (fire suppression and forestry practices Within B.C., the current outbreak stretches 4.2 million hectares MPB spread is currently documented through: Aerial surveys (to assess the extent of the previous year’s population) Ground data collection – “beetle probing” (to assess the spatial extent of newly infested stands) Rationale: Production of a predictive MPB dispersion model has the potential to direct ground surveys and therefore reduce costs Current MPB modeling endeavors focus on the single tree to stand level and rarely include meteorological variables, although they are noted as important to MPB ecology Use of atmospheric models to determine extent of MPB dispersal over longer distances (between stands) should provide a regional visualization of spatial infestation extent which could be used by resource managers As a preliminary step in the full MPB dispersal model, this research seeks to validate the models used and explore fundamental relationships between MPB dispersal and local topography Background photograph from: Model Initialization: 2 atmospheric models used: RAMS (preliminary results shown) and HYPACT (to be used later) RAMS initialized horizontally homogeneously at 12 UTC Representative soundings from Prince George (ZXS) upper-air station were found based upon a synoptic climatology of MPB emergence days (see Murphy and Jackson P1.12)  RMSE (Root Mean Square Error) and RMSVE (Root Mean Square Vector Error) used to rank and determine the most representative soundings Artificial Topography:  3 landscapes used: flat (control), E-W sinusoidal terrain (Figure 2a), N-S sinusoidal terrain (Figure 2b)  Grids centered at Prince George upper-air station (53.9 lat., long., 601 masl)  Wavelength and amplitude for sine wave obtained by averaging measurements from Tweedsmuir Park (large MPB infestation) (Figure 1) Future Work:  Realistic simulations of Prince George SO2 concentrations will be used to validate RAMS/HYPACT at simulating real-life situations  Further qualitative study of RAMS output (comparison to published literature)  Use HYPACT (Lagrangian particle dispersion model) to insert, advect and disperse MPB using RAMS meteorological output  Quantitative comparison between control (flat) and variable (sinusoidal) topographies to determine if an effect is present and/or which landscapes offer the greatest forcing on MPB dispersal Discussion: Model output shows anabatic/katabatic flows dominating local wind circulations Night-time down-slope (katabatic) winds cause pooling of cool air and subsequent inversion conditions In the mid-morning, inversion breaks down and differential heating of slopes brings up-slope (anabatic) winds Afternoon brings convective conditions (Figure 3b and 4b) with variable wind directions and substantial mixing Anabatic flows during the day may act to advect MPB up slopes and aloft along ridge lines Subsidence in mid-valleys may act as fallout regions for MPB Results: Figures 3 and 4 show a sampling of RAMS model output for artificial topography simulations 22 UTC (3:00 pm PST) used to illustrate convective meteorological conditions At this time, wind direction is highly variable, but speeds generally low (fair-weather conditions) (Figure 3b and 4b) High temperatures in valley bottoms, with a gradient of approx. 15 degrees Celsius from valley to peak (Figures 3a and 4a) Figure 1: Landscape-level MPB infestation near Tweedsmuir, B.C. ( 1.jpg) a b Figure 2: Artificial topography contours for N-S simulation (a) and E-W simulation (b) Figure 3: Sample RAMS output for E-W topography simulation: temperature (a) and wind speed and direction (b) ab Figure 4: Sample RAMS output for E-W topography simulation: temperature (a) and wind speed and direction (b) ab