Python数据分析技术在海雾过程中的应用

Chenyu Zhang, Bingyu Liu, Haoye Liu, Chengyu Yan
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摘要

Python的特点是相对容易学习的语法,大量的标准库和第三方数据库支持,以及良好的兼容性。它已被应用于理论研究、实际案例,并具有工具集广泛的优势。Python已经渗透到科学计算、大数据处理、数据分析等专业和领域。本文通过脚本请求并下载ERA5再分析数据,通过Python Xarray工具包读取ERA5再分析数据网格点数据,对数据时间维度和空间维度进行处理,将气象数据读入格式化数组,并使用Metpy对数据进行气象方程计算。随后,利用Matplotlib和Cartopy对2020年2月9日至14日一次高影响海雾过程的气象和海洋资料进行分析投影到地图上并进行制图,并对产品批二维制图进行高效并行优化,研究辽东湾海雾形成机制,提高海雾预报预警水平。
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Application of Data Analysis by Python Technology in a Sea Fog Process
Python is characterized by a relatively easy-to-learn syntax, a large number of standard libraries and third-party database support, and good compatibility. It has been applied to theoretical research, practical cases, and also has the advantage of a wide variety of toolsets. Python has penetrated into scientific computing, big data processing, data analysis and other professions and fields. In this paper, we requested and downloaded ERA5 reanalysis data by script, and read ERA5 reanalysis data grid point data by Python Xarray toolkit, processed data time dimension and space dimension to read meteorological data into formatted array, and used Metpy to calculate meteorological equation on data. After that, the meteorological and marine data of a high impact sea fog process from February 9th to 14th, 2020 were analyzed and projected onto the map and plotted by Matplotlib and Cartopy, and the product batch 2D mapping was efficiently parallel optimized to study the formation mechanism of sea fog in Liaodong Bay and improve the forecast and warning level of sea fog.
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