气象数据源比较 - - 关于纳瓦霍民族废弃矿场地潜在环境暴露的地理空间建模的案例研究
Christopher Girlamo1, Yan Lin1, Joseph Hoover2
1Department of Geography and Environmental Studies, UNM Center for the Advancement of Spatial Informatics Research and Education (ASPIRE), University of New Mexico, Albuquerque, NM, 87131, USA.
Environmental monitoring and assessment
|June 11, 2023
概括
当地气象数据,包括METAR和气象站,提供比再分析数据更准确的环境暴露预测. 这一发现改善了对废弃的矿等地点的风险评估.
科学领域:
- 环境科学 环境科学
- 地理空间分析的研究.
- 数据科学数据科学数据科学
背景情况:
- 气象学 (MET) 数据对于环境暴露模型至关重要.
- 地理空间技术通常用于曝光建模,但输入数据的不确定性往往被忽视.
- 评估MET数据源对模型不确定性的影响对于准确的预测至关重要.
研究的目的:
- 评估不同MET数据源对潜在暴露易感性预测的影响.
- 来自北美区域再分析 (NARR),气象机场报告 (METAR) 和当地MET气象站的风力数据进行比较.
- 确定最准确的数据源来预测暴露在废弃的矿场所的情况.
主要方法:
- 使用机器学习 (ML) 驱动的GIS多标准决策分析 (GIS-MCDA) 地缘空间模型.
- 来自NARR,METAR和当地MET气象站的输入风数据.
- 使用国家资源评估 (NURE) 数据库和地理加权回归 (GWR) 验证的模型输出.
主要成果:
- 在不同风力数据源中观察到预测结果的显著差异.
- 在验证后,METAR和当地MET气象站数据的组合产生了最高的准确性 (平均R2为0.74).
- 基于当地直接测量的数据比其他来源更准确.
结论:
- 与NARR相比,本地MET数据 (METAR和MET气象站) 提供了更准确的暴露预测.
- 这项研究强调了为环境暴露建模选择适当的MET数据的重要性.
- 结果可以指导未来的数据收集策略,以改善风险评估和政策决策.
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