论文
论文题目: Global near real-time daily apparent temperature and heat wave dataset
第一作者: Yin Cong, Yang Yaping, Chen Xiaona, Yue Xiafang etc.
联系作者:
发表年度: 2022
摘  要: Temperature is the most concerned factor in the human-environment interactions. Apparent temperature accounting for other meteorological variables, such as humidity, wind speed and solar radiation, is the equivalent temperature, and it is a more accurate indicator to reflect human's environmental temperature perception. High-quality apparent temperature data are urgently needed for the further research on human-environment interactions. At the same time, as global heat waves continue to increase in frequency, duration and intensity, understanding the impact of heat waves on human health needs human perception-based heat wave data. Using ERA5 hourly data on single levels of 2 m temperature, wind speed, dewpoint temperature and solar radiation, this study developed a global apparent temperature and heat wave (GATHW) toolbox based on the Climate Data Store (CDS) online platform. This toolbox allows using three methods to calculate daily apparent temperature and heat wave at three spatial resolutions of 0.25 degrees, 0.5 degrees and 1 degrees respectively. It can realize online calculation, display and real-time download and is updated in near real-time. The global daily apparent temperature and annual heat wave dataset from 2006 to 2020 calculated by the toolbox can be obtained from . After evaluation, this dataset can well reflect the typical extreme temperatures and heat wave events, and is more accurate, with higher resolution and faster update frequency than similar data products, which can provide data support for the study of human-environmental interactions and extreme climate events.
英文摘要:
刊物名称: GEOSCIENCE DATA JOURNAL
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论文类别: SCI