Articles | Volume 18, issue 1
https://doi.org/10.5194/essd-18-371-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-371-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
14 Jan 2026
Data description article |
| 14 Jan 2026
| 14 Jan 2026
An hourly 0.02° total precipitable water dataset for all-weather conditions over the Tibetan Plateau through the fusion of observations of geostationary and multi-source microwave satellites
Qixiang Sun
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Yongqian Wang
College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China
Peng Zhang
Meteorological Observation Center, China Meteorological Administration, Beijing, 100081, China
State Key Laboratory of Environment Characteristics and Effects for Near-space, Beijing 10081, China
Hong Liang
Meteorological Observation Center, China Meteorological Administration, Beijing, 100081, China
Chong Shi
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Shuai Yin
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Jiancheng Shi
National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
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Earth Syst. Sci. Data, 14, 1413–1432, https://doi.org/10.5194/essd-14-1413-2022, https://doi.org/10.5194/essd-14-1413-2022, 2022
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Air temperature is an important parameter reflecting climate change, and the current method of obtaining daily temperature is affected by many factors. In this study, we constructed a temperature model based on weather conditions and established a correction equation. The dataset of daily air temperature (Tmax, Tmin, and Tavg) in China from 1979 to 2018 was obtained with a spatial resolution of 0.1°. Accuracy verification shows that the dataset has reliable accuracy and high spatial resolution.
Yungang Wang, Liping Fu, Fang Jiang, Xiuqing Hu, Chengbao Liu, Xiaoxin Zhang, Jiawei Li, Zhipeng Ren, Fei He, Lingfeng Sun, Ling Sun, Zhongdong Yang, Peng Zhang, Jingsong Wang, and Tian Mao
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Lin Tian, Lin Chen, Peng Zhang, and Lei Bi
Atmos. Chem. Phys., 21, 11669–11687, https://doi.org/10.5194/acp-21-11669-2021, https://doi.org/10.5194/acp-21-11669-2021, 2021
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The result shows dust aerosols from the Taklimakan Desert have higher aerosol scattering during dust storm cases of this paper, and this caused higher negative direct radiative forcing efficiency (DRFEdust) than aerosols from the Sahara.
The microphysical properties and particle shapes of dust aerosol significantly influence DRFEdust. The satellite-based equi-albedo method has a unique advantage in DRFEdust estimation: it could validate the results derived from the numerical model directly.
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Short summary
The Tibetan Plateau plays a vital role in Asia’s water cycle, but tracking water vapor in this mountainous region is difficult, especially under cloudy conditions. We developed a new satellite-based method to generate hourly water vapor data at 0.02-degree resolution from 2016 to 2022, now available at https://doi.org/10.11888/Atmos.tpdc.301518, which improves accuracy and reveals fine-scale moisture transport critical for understanding rainfall and extreme weather.
The Tibetan Plateau plays a vital role in Asia’s water cycle, but tracking water vapor in this...
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