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闽东北沿海港湾岛屿测站风分布特征及预报指标站的选取

曾瑾瑜 高聪晖 叶冬云 王金萍

海洋预报2017,Vol.34Issue(4):42-51,10.
海洋预报2017,Vol.34Issue(4):42-51,10.DOI:10.11737/j.issn.1003-0239.2017.04.005

闽东北沿海港湾岛屿测站风分布特征及预报指标站的选取

Wind distribution characteristics and the selection of forecast indicator station in the northeast coastal islands of Fujian

曾瑾瑜 1高聪晖 1叶冬云 2王金萍2

作者信息

  • 1. 福建省气象台,福建福州350001
  • 2. 福建省宁德市气象局,福建宁德352100
  • 折叠

摘要

Abstract

Based on wind data from automatic station at Ningde harbour Island during 2011-2013,the temporal and spatial distribution characteristics of wind power are analyzed statistically.The results shows that the spatial distribution of each station is very uneven,with obvious regional differences,and the local characteristics are prominent.The main wind direction at the station is dominated by northeasterly wind,with an obvious differences of wind direction at different stations.Seasonal variation of wind speed is relatively gentle,and with an unremarkable seasonal difference.As for seasonal variation of wind direction,the prevailing wind direction in winter,autumn and spring is north-easterly,while in summer is dominated by the southwest wind.Through the in-depth analysis of factors such as the integrity and availability of the data,importance of service,the geographical distribution and the relevance of sites,by comparing the representative and applicability of the automatic station wind detection data,24 representative station of the automatic station of the wind forecast area at Ningde harbor island is determined as the indicator station for forecasting the wind power of harbor island.The automatic station will be integrated into the weather forecasting index system,so as to fine-tune the harbor island wind forecast.

关键词

港湾岛屿/最大风/空间分布/代表站

Key words

harbor island/the most strong winds/spatial distribution/representative station

分类

海洋科学

引用本文复制引用

曾瑾瑜,高聪晖,叶冬云,王金萍..闽东北沿海港湾岛屿测站风分布特征及预报指标站的选取[J].海洋预报,2017,34(4):42-51,10.

基金项目

福建省气象局自研项目(2015z02) (2015z02)

福建省气象局青年科技专项(2015q26) (2015q26)

福建省自然科学基金社会发展引导性(重点)项目(2017Y-008). (重点)

海洋预报

OA北大核心CSTPCD

1003-0239

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