Tuesday, 12 January 2016: 11:00 AM
Room 346/347 ( New Orleans Ernest N. Morial Convention Center)
Melinda Marquis, NOAA, Boulder, CO; and R. M. Banta, L. A. Benjamin, S. Benjamin, L. K. Berg,
L. Bianco, J. Bickford, A. Brewer,
A. Choukulkar, K. L. Clawson, A. Clifton, J. W. Cline, D. Cook, I. V. Djalalova, R. M. Eckman, H. J. S. Fernando, K. Friedrich, J. Kenyon, B. Kosovic, C. W. King, K. Lantz, C. Long,
J. K. Lundquist, J. McCaa,
K. McCaffrey, V. R. Morris, J. Olson, Y. Pichugina, J. Sharp, W. J. Shaw, K. Wade, S. Wharton, and J. M. Wilczak
WFIP2 aims to improve model physics and bridge models that describe multiple scales in complex flow. Observations collected during a 12-18 month field campaign in the Columbia River Gorge and Basin in the Pacific Northwest will be used for model verification and assimilation. Physical phenomena of particular interest include frontal passages, gap flows, convective outflows, mountain waves, topographic wakes, and marine pushes. The field campaign will begin in the autumn of 2015. Instrumentation for the field campaigns includes radar wind profilers, sodars, lidar wind profilers, scanning Doppler lidars, microwave radiometers, sonic anemometers, a ceilometer, high resolution microbarographs, and surface radiation sensors. NOAA's 13-km Rapid Refresh (RAP) and the 3-km High-Resolution Rapid Refresh (HRRR) will be the primary forecast models for this study. A 750-m HRRR nest developed for WFIP2, covering the field campaign region, will also be used. Other WFIP2 partners will develop improvements in the WRF. Improvements in each model will be shared across the team and made available to the public.
The WFIP2 team will use the special WFIP2 observations to verify the operational RAP and HRRR forecasts and identify cases that are not well forecasted and that are important to wind farm operations and utility integration of wind power. Case studies will be be re-simulated with modifications to key physical parameterizations (e.g., turbulence, etc.) in an attempt to improve upon the forecast errors. The most significant model improvements as well as the sum of all model improvements will further be tested in retrospective data denial experiments involving the full RAP domains and full data assimilation of standard and special WFIP 2.0 observations in order to ensure robust improvements for general weather prediction as well as the complex flows of focus in this project.
The WFIP2 team will produce decision support tools to provide greater situational awareness and reduced decision-making time on the part of electric power system operators and wind power producers. These tools will allow for the best use of the mesoscale models and not interfere with the private company roles related to individual wind plant decision-making.
This presentation will discuss the goals of the project and how they will be met, including information about the field campaign, instrumentation choices, validation strategy, and expected contribution to improved weather models.
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