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Volume 2 Issue S1
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Article Navigation >  SOUTHERN ENERGY CONSTRUCTION  > 2015  >  2(S1): 187-192

CAI Yanfeng, ZHANG Canheng, HUANG Yong. Study on the Comparison of Spatial Interpolation Methods Used to Estimate Extreme Wind Speed Spatial Distribution Using Irregularly Distributed Station Data in Guangdong Coastal Area[J]. SOUTHERN ENERGY CONSTRUCTION, 2015, 2(S1): 187-192. doi: 10.16516/j.gedi.issn2095-8676.2015.S1.042
Citation: CAI Yanfeng, ZHANG Canheng, HUANG Yong. Study on the Comparison of Spatial Interpolation Methods Used to Estimate Extreme Wind Speed Spatial Distribution Using Irregularly Distributed Station Data in Guangdong Coastal Area[J]. SOUTHERN ENERGY CONSTRUCTION, 2015, 2(S1): 187-192. doi: 10.16516/j.gedi.issn2095-8676.2015.S1.042
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Study on the Comparison of Spatial Interpolation Methods Used to Estimate Extreme Wind Speed Spatial Distribution Using Irregularly Distributed Station Data in Guangdong Coastal Area

doi: 10.16516/j.gedi.issn2095-8676.2015.S1.042

  • 1. China Energy Enginering Group Guangdong Electric Power Design Institute, Co., Ltd., Guangzhou 510663, China;

  • 2. Electric Powr Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China

  • Received Date: 2014-12-01
  • Data from 26 national reference weather stations, 101 regional automatic weather stations and 6 ocean observation stations in Guangdong coastal area are collected. Inverse Distance Weighting scheme, Cressman Interpolation scheme, Radial Basis Function scheme and Kriging method are then empolyed to study the continuous extreme wind speed distribution spatial interpolation experiment of 10 min averaged extreme wind speed at 10 meters above ground with a return peroid of 50 years. Cross-validation shows that the Mean Absolute Error of Cressman Interpolation is least while Universe Kriging interpolation lead to the least Root-Mean-Square Error and the best correlation coefficient. It is indicated that Universe Kriging interpolation is more appropriate for extreme wind speed spatial interpolation in Guangdong coastal area.
    • 通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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Study on the Comparison of Spatial Interpolation Methods Used to Estimate Extreme Wind Speed Spatial Distribution Using Irregularly Distributed Station Data in Guangdong Coastal Area

doi: 10.16516/j.gedi.issn2095-8676.2015.S1.042
  • 1. China Energy Enginering Group Guangdong Electric Power Design Institute, Co., Ltd., Guangzhou 510663, China;
  • 2. Electric Powr Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
  • Received Date: 2014-12-01

Abstract: Data from 26 national reference weather stations, 101 regional automatic weather stations and 6 ocean observation stations in Guangdong coastal area are collected. Inverse Distance Weighting scheme, Cressman Interpolation scheme, Radial Basis Function scheme and Kriging method are then empolyed to study the continuous extreme wind speed distribution spatial interpolation experiment of 10 min averaged extreme wind speed at 10 meters above ground with a return peroid of 50 years. Cross-validation shows that the Mean Absolute Error of Cressman Interpolation is least while Universe Kriging interpolation lead to the least Root-Mean-Square Error and the best correlation coefficient. It is indicated that Universe Kriging interpolation is more appropriate for extreme wind speed spatial interpolation in Guangdong coastal area.

CAI Yanfeng, ZHANG Canheng, HUANG Yong. Study on the Comparison of Spatial Interpolation Methods Used to Estimate Extreme Wind Speed Spatial Distribution Using Irregularly Distributed Station Data in Guangdong Coastal Area[J]. SOUTHERN ENERGY CONSTRUCTION, 2015, 2(S1): 187-192. doi: 10.16516/j.gedi.issn2095-8676.2015.S1.042
Citation: CAI Yanfeng, ZHANG Canheng, HUANG Yong. Study on the Comparison of Spatial Interpolation Methods Used to Estimate Extreme Wind Speed Spatial Distribution Using Irregularly Distributed Station Data in Guangdong Coastal Area[J]. SOUTHERN ENERGY CONSTRUCTION, 2015, 2(S1): 187-192. doi: 10.16516/j.gedi.issn2095-8676.2015.S1.042
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