一个0.1°每月潜在蒸发透气数据集,基于全球植被区的最佳模型
Zaoying Bi1, Shanlei Sun2, Qianrong Ma3
1State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster, Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China.
Scientific data
|March 3, 2026
概括
准确的潜在蒸发透气 (PET) 估计是至关重要的. 这项研究使用全球数据对PET模型进行了校准,确定了最佳模型,并为研究创建了一个新的可靠的PET数据集.
科学领域:
- 水文学的水文学
- 气候学 气候学 气候学
- 生态生态学 生态生态学
- 农业学是一种农业学.
背景情况:
- 准确的潜在蒸发透气 (PET) 估计对于各种科学学科至关重要.
- 现有的PET产品经常使用默认模型参数,导致研究不确定性.
研究的目的:
- 通过全球旋共变点点观测,校准五种广泛使用的PET模型.
- 确定最佳的PET模型并生成一个高分辨率的全球PET数据集.
主要方法:
- 五个PET模型的校准参数使用来自124个旋共变点的数据.
- 在多种生物群中评估模型性能.
- 使用最佳模型和气象数据生成0.1°分辨率的每月PET数据集 (1992-2022年).
主要成果:
- 校准的普里斯特利-泰勒和米莉-恩模型在整个生物群中表现出卓越的性能.
- 在0.1°分辨率下生成了一个新的月度全球PET数据集 (1992-2022年).
- 新的数据集与全球土地蒸发阿姆斯特丹模型 (GLEAM) V4.2a PET.相对验证.
结论:
- 校准的PET模型为研究提供了更高的准确性.
- 生成的PET数据集为科学研究提供了有价值的替代资源.
- 这项工作提高了PET估计在气候学,生态学,水文学和农学方面的可靠性.
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