Improved quality gridded surface wind speed datasets for Australia

被引:0
|
作者
Hong Zhang
Stephen Jeffrey
John Carter
机构
[1] Queensland Government,Science and Technology Division, Department of Environment and Science
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Gridded near-surface (2 and 10 m) daily average wind datasets for Australia have been constructed by interpolating observational data collected by the Australian Bureau of Meteorology (BoM). The new datasets span Australia at 0.05 × 0.05° resolution with a daily time step. They are available for the period 1 January 1975 to present with daily updates. The datasets were constructed by blending observational data collected at various heights using local surface roughness information. Error detection techniques were used to identify and remove suspect data. Statistical performances of the spatial interpolations were evaluated using a cross-validation procedure, by sequentially applying interpolations after removing the observed weather station data. The accuracy of the new blended 10 m wind datasets were estimated through comparison with the Reanalysis ERA5-Land 10 m wind datasets. Overall, the blended 10 m wind speed patterns are similar to the ERA5-Land 10 m wind. The new blended 10 m wind datasets outperformed ERA5-Land 10 m wind in terms of spatial correlations and mean absolute errors through validations with BoM 10 m wind weather station data for the period from 1981 to 2020. Average correlation (R2) for blended 10 m wind is 0.68, which is 0.45 for ERA5-Land 10 m wind. The average of the mean absolute error is 1.15 m/s for blended 10 m wind, which is lower than that for ERA5-Land 10 m wind (1.61 m/s). The blending technique substantially improves the spatial correlations for blended 2 m wind speed.
引用
收藏
相关论文
共 50 条
  • [41] Statistical approach for improved wind speed forecasting for wind power production
    Pearre, Nathaniel S.
    Swan, Lukas G.
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2018, 27 : 180 - 191
  • [42] A new E-OBS gridded dataset for daily mean wind speed over Europe
    de Baar, Jouke H. S.
    Van der Schrier, Gerard
    Van den Besselaar, Else J. M.
    Garcia-Marti, Irene
    de Valk, Cees
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2023, 43 (13) : 6083 - 6100
  • [43] Effects of wind farms on near-surface wind speed
    Zhang Xin
    Yin Ruiping
    Xu Ronghui
    Liu Jing
    He Jingli
    Liu Yanping
    Wu Yongsheng
    Sun Xu
    Wang Lixia
    2018 INTERNATIONAL CONFERENCE ON CONSTRUCTION, AVIATION AND ENVIRONMENTAL ENGINEERING, 2019, 233
  • [44] Dependence of the Friction Speed on the Wind Speed in the Surface Air Layer
    Gladkikh, V. A.
    Mamyshev, V. P.
    Nevzorova, I., V
    Odintsov, S. L.
    ATMOSPHERIC AND OCEANIC OPTICS, 2021, 34 (05) : 507 - 512
  • [45] Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic
    Hughes, Sarah L.
    Holliday, N. Penny
    Colbourne, Eugene
    Ozhigin, Vladimir
    Valdimarsson, Hedinn
    Osterhus, Svein
    Wiltshire, Karen
    ICES JOURNAL OF MARINE SCIENCE, 2009, 66 (07) : 1467 - 1479
  • [46] Dependence of the Friction Speed on the Wind Speed in the Surface Air Layer
    V. A. Gladkikh
    V. P. Mamyshev
    I. V. Nevzorova
    S. L. Odintsov
    Atmospheric and Oceanic Optics, 2021, 34 : 507 - 512
  • [47] Long-Term Wind Speed Trends over Australia
    Troccoli, Alberto
    Muller, Karl
    Coppin, Peter
    Davy, Robert
    Russell, Chris
    Hirsch, Annette L.
    JOURNAL OF CLIMATE, 2012, 25 (01) : 170 - 183
  • [48] Evaluation of Near-Surface Wind Speed Changes during 1979 to 2011 over China Based on Five Reanalysis Datasets
    Yu, Jiang
    Zhou, Tianjun
    Jiang, Zhihong
    Zou, Liwei
    ATMOSPHERE, 2019, 10 (12)
  • [49] A STOCHASTIC-MODEL OF SURFACE WIND-SPEED FOR AIR-QUALITY CONTROL PURPOSES
    FINZI, G
    BONELLI, P
    BACCI, G
    JOURNAL OF CLIMATE AND APPLIED METEOROLOGY, 1984, 23 (09): : 1354 - 1361
  • [50] Improved prediction of wind speed using machine learning
    Senthil Kumar P.
    EAI Endorsed Transactions on Energy Web, 2019, 19 (23):