Articles | Volume 15, issue 10
https://doi.org/10.5194/essd-15-4571-2023
© Author(s) 2023. 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-15-4571-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
17 Oct 2023
Data description paper |
| 17 Oct 2023
| 17 Oct 2023
ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins
Jinghua Xiong
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei 430072, China
Abhishek
Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India
Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
Hrishikesh A. Chandanpurkar
Centre for Sustainability, Environment, and Climate Change, FLAME University, Pune, India
James S. Famiglietti
Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
Global Futures Laboratory, Arizona State University, Tempe, AZ 85281, United States
Chong Zhang
Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
Gionata Ghiggi
Environmental Remote Sensing Laboratory (LTE), EPFL, 1005 Lausanne, Switzerland
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei 430072, China
Yun Pan
CORRESPONDING AUTHOR
Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
Bramha Dutt Vishwakarma
Interdisciplinary Centre for Water Research, Indian Institute of Science, Bengaluru 560012, India
Centre for Earth Sciences, Indian Institute of Science, Bengaluru 560012, India
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The Universal Thermal Climate Index (UTCI) plays a pivotal role in gauging how the human adapts to meteorological conditions and copes with thermal and cold stress. We produced the GloUTCI-M, a monthly UTCI dataset boasting global coverage, an extensive time series spanning from March 2000 to October 2022, and a high spatial resolution of 1 km. We analyzed the global spatiotemporal characteristics and pattern evolution of UTCI based on GloUTCI-M.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
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We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Yinghong Jing, Xinghua Li, and Huanfeng Shen
Earth Syst. Sci. Data, 14, 3137–3156, https://doi.org/10.5194/essd-14-3137-2022, https://doi.org/10.5194/essd-14-3137-2022, 2022
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Snow variation is a vital factor in global climate change. Satellite-based approaches are effective for large-scale environmental monitoring. Nevertheless, the high cloud fraction seriously impedes the remote-sensed investigation. Therefore, a recent 20-year cloud-free snow cover collection in China is generated for the first time. This collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues.
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Short summary
To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
To overcome the shortcomings associated with limited spatiotemporal coverage, input data...
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