JOURNAL ARTICLE

Climatology of sea breeze over Jiangsu coast: An overview from the ERA5 reanalysis.

  • Published In: International Journal of Climatology, 2024, v. 44, n. 11. P. 3821 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Cui, Zhiqiang; Mei, Shuying; Li, Xin; Wang, Shizhang; Zeng, Mingjian 3 of 3

Abstract

The sea breeze characteristics for 30 years of summer (1981–2010) in the coastal region of Jiangsu Province were analysed in this study, using the four‐step filter method based on ECMWF Fifth‐Generation Reanalysis (ERA5) data. The results showed that the filtering method reasonably identified three types of sea breeze. Additionally, approximately 23% of the total summer days remained; the corkscrew type dominates the three types of sea breeze; and the backdoor sea breeze was the least common. Except for the type of backdoor sea breeze, the other two types had relatively fixed dominant weather types on three coastlines. The synoptic weather patterns in the 500‐hPa level corresponding to each sea breeze type were different. Further, the details of the diurnal cycle of lower tropospheric circulation indicated the strength of the onshore wind and the location of the large potential temperature gradient at noon being influenced by sea breeze type and coastal location. The wind strength for the three types of sea breeze on the middle coastline was stronger than that on the other two coastlines. On the three coastlines, strong onshore winds were concentrated in areas near the coastline, where they reached their maximum strengths around noon. On the southern coastline, strong onshore winds moved further inland. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Climatology. 2024/09, Vol. 44, Issue 11, p3821
  • Document Type:Article
  • Subject Area:Earth and Atmospheric Sciences
  • Publication Date:2024
  • ISSN:0899-8418
  • DOI:10.1002/joc.8552
  • Accession Number:180411074
  • Copyright Statement:Copyright of International Journal of Climatology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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