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一个基于NARX网络的新型优化模型,用于预测热浪期间波兰湖泊的热异常,特别参考2018年的热浪
Senlin Zhu1, Fabio Di Nunno2, Mariusz Ptak3
1College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, China.
The Science of the total environment
|September 17, 2023
概括
2018年欧洲热浪显著增加了波兰湖泊表面水温超过2°C. 一个新的贝叶斯优化非线性自回归网络与外源输入和贝叶斯规则化 (BO-NARX-BR) 模型准确地捕获了这些极端的湖泊热事件.
科学领域:
- 环境科学 环境科学
- 气候科学 气候科学
- 水文学的水文学
背景情况:
- 2018年欧洲的热浪是一个严重的极端气候事件.
- 它对波兰湖面水温 (LSWT) 的影响以前没有得到量化.
- 了解这些影响对于水球运行至关重要.
研究的目的:
- 调查2018年热浪对波兰24个湖泊LSWT的影响.
- 开发和评估一种用于捕捉湖泊热浪动态的新型模型.
- 与现有方法对比,评估新模型的准确性.
主要方法:
- 利用LSWT (1987-2020) 的长期观察数据集.
- 开发了一个新的BO-NARX-BR模型,结合了贝叶斯优化,NARX神经网络和贝叶斯规范化.
- 将BO-NARX-BR模型的性能与空气2水模型进行比较.
主要成果:
- 在2018年热浪期间,平均和最大的LSWT分别为2.35°C和3.38°C更热.
- 与air2water.com相比,BO-NARX-BR模型在校准和验证方面表现出卓越的性能.
- 该模型准确地复制了湖泊热浪的持续时间和强度,与现场数据密切匹配.
结论:
- 该BO-NARX-BR模型有效地捕捉了极端高温事件期间的LSWT动态.
- LSWT异常显著影响湖泊热浪特征.
- 开发的模型显示了适应其他地区的潜力,有助于预测极端气候事件的影响.
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