在佛罗里达州的16年 (2005-2020年) 无间隙的日下地表气象观测
Julie A Peeling1, Jasmeet Judge2, Vasubandhu Misra3
1University of Florida, Center for Remote Sensing, Department of Agricultural and Biological Engineering, Gainesville, FL, 32611, USA. juliepeeling@ufl.edu.
Scientific data
|December 16, 2023
概括
这项研究使用先进的数据归算技术为佛罗里达州开发了一个无差距的气象数据集. 来自佛罗里达自动天气网络 (FAWN) 的15分钟观测结果增强了气候研究和资源管理.
科学领域:
- 大气科学与气象学
- 气候科学 气候科学
- 环境科学 环境科学
背景情况:
- 佛罗里达州的亚热带气候容易发生极端天气事件,影响农业,公共卫生和自然资源.
- 高分辨率的气象数据对于了解日间气候变化至关重要,但现有的数据集往往存在差距.
- 数据缺口限制了气候模型的验证和详细的观测分析.
研究的目的:
- 为佛罗里达州开发一个无差距,高时间分辨率 (15分钟) 的气象数据集.
- 为了解决对亚热带地区现有的气象数据的局限性.
- 为研究和管理提供连续的,公开可访问的数据集.
主要方法:
- 在佛罗里达州自动天气网络 (FAWN) 的气象数据上应用了一套数据填补策略.
- 使用线性插值,趋势延续,外部数据引用和基于差距范围的最近站替换.
- 处理了30个FAWN站的数据,涵盖了2005-2020年期间.
主要成果:
- 成功生成了一个连续的,没有空隙的表面气象数据集,每隔15分钟.
- 该数据集涵盖了15年 (2005-2020年) 的时间,覆盖了佛罗里达州的30个FAWN站.
- 归算方法有效地填补了数据空白,提高了数据的实用性.
结论:
- 开发的无差距数据集为佛罗里达州提供了有价值的高分辨率气象观测.
- 该资源支持改善气候建模,农业规划,公共卫生准备和自然资源管理.
- 持续的数据增强了对亚热带气候动态和极端天气影响的理解.
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