WRF Hub-Height Wind Forecast Sensitivity to PBL Scheme, Grid Length, and Initial Condition Choice in Complex Terrain

被引:52
作者
Siuta, David [1 ]
West, Gregory [1 ]
Stull, Roland [1 ]
机构
[1] Univ British Columbia, Vancouver, BC, Canada
关键词
BOUNDARY-LAYER; TEMPERATURE PROFILES; VERTICAL DIFFUSION; WEATHER RESEARCH; RADIX LAYER; MODEL; ENSEMBLE; PARAMETERIZATION; BOTTOM;
D O I
10.1175/WAF-D-16-0120.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This study evaluates the sensitivity of wind turbine hub-height wind speed forecasts to the planetary boundary layer (PBL) scheme, grid length, and initial condition selection in the Weather Research and Forecasting (WRF) Model over complex terrain. Eight PBL schemes available for the WRF-ARW dynamical core were tested with initial conditions sources from the North American Mesoscale (NAM) model andGlobal Forecast System (GFS) to produce short-term wind speed forecasts. The largest improvements in forecast accuracy primarily depended on the grid length or PBL scheme choice, although the most important factor varied by location, season, time of day, and bias-correction application. Aggregated over all locations, the Asymmetric Convective Model, version 2 (ACM2) PBL scheme provided the best forecast accuracy, particularly for the 12-km grid length. Other PBL schemes and grid lengths, however, did perform better than the ACM2 scheme for individual seasons or locations.
引用
收藏
页码:493 / 509
页数:17
相关论文
共 60 条
  • [1] Knowledge Is Power
    Ahlstrom, Mark
    Bartlett, Drake
    Collier, Craig
    Duchesne, Jacques
    Edelson, David
    Gesino, Alejandro
    Keyser, Marc
    Maggio, David
    Milligan, Michael
    Mohrlen, Corinna
    O'Sullivan, Jonathan
    Sharp, Justin
    Storck, Pascal
    de la Torre Rodriguez, Miguel
    [J]. IEEE POWER & ENERGY MAGAZINE, 2013, 11 (06): : 45 - 52
  • [2] [Anonymous], 2012, An Introduction to Boundary Layer Meteorology
  • [3] [Anonymous], 2011, INT GEOPHYS, DOI DOI 10.1016/B978-0-12-385022-5.00008-7
  • [4] [Anonymous], 2009, Argonne National Laboratory, DOI DOI 10.2172/968212
  • [5] [Anonymous], DOEGO1020082567
  • [6] Arya P.S., 2001, Introduction to Micrometeorology London, England
  • [7] Reliable probabilistic forecasts from an ensemble reservoir inflow forecasting system
    Bourdin, Dominique R.
    Nipen, Thomas N.
    Stull, Roland B.
    [J]. WATER RESOURCES RESEARCH, 2014, 50 (04) : 3108 - 3130
  • [8] A New Moist Turbulence Parameterization in the Community Atmosphere Model
    Bretherton, Christopher S.
    Park, Sungsu
    [J]. JOURNAL OF CLIMATE, 2009, 22 (12) : 3422 - 3448
  • [9] Canadian Wind Energy Association, 2008, WIND VIS 2025 POW CA
  • [10] The impact of model physics on numerical wind forecasts
    Cheng, William Y. Y.
    Liu, Yubao
    Liu, Yuewei
    Zhang, Yongxin
    Mahoney, William R.
    Warner, Thomas T.
    [J]. RENEWABLE ENERGY, 2013, 55 : 347 - 356