Articles | Volume 14, issue 12
https://doi.org/10.5194/essd-14-5513-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-14-5513-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
15 Dec 2022
Data description article |
| 15 Dec 2022
| 15 Dec 2022
A dataset of 10-year regional-scale soil moisture and soil temperature measurements at multiple depths on the Tibetan Plateau
Pei Zhang
Faculty of Geo-Information Science and Earth Observation (ITC),
University of Twente, Enschede 7514AE, the Netherlands
State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of
Sciences, Beijing 100101, China
State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of
Sciences, Beijing 100101, China
Rogier van der Velde
Faculty of Geo-Information Science and Earth Observation (ITC),
University of Twente, Enschede 7514AE, the Netherlands
Jun Wen
College of Atmospheric Sciences, Chengdu University of Information
Technology, Chengdu 610225, China
Yaoming Ma
State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of
Sciences, Beijing 100101, China
Yijian Zeng
Faculty of Geo-Information Science and Earth Observation (ITC),
University of Twente, Enschede 7514AE, the Netherlands
Xin Wang
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Zuoliang Wang
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Jiali Chen
State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of
Sciences, Beijing 100101, China
College of Earth and Environmental Sciences, Lanzhou University,
Lanzhou 730000, China
Zhongbo Su
CORRESPONDING AUTHOR
Faculty of Geo-Information Science and Earth Observation (ITC),
University of Twente, Enschede 7514AE, the Netherlands
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Shijie Jiang, Georgios Blougouras, Tuya Wulan, Yijian Zeng, and Jialiang Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2026-3294, https://doi.org/10.5194/egusphere-2026-3294, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Land surface models simulate how plants and soils exchange water and carbon with the atmosphere, but they rely on many parameters that are hard to measure. We built a model that combines physics with machine learning so these parameters can be learned from observations, checked for reliability, and mapped from a few measurement sites across whole regions. Over Europe it improved predictions and produced coherent parameter maps, offering a foundation for land models that learn from data.
Matthias Cuntz, Stephan Thober, Anne Verhoef, Yijian Zeng, Aaron Boone, Agnès Ducharne, Sujan Koirala, David M. Lawrence, Philipp de Vrese, Carsten Montzka, Sonia I. Seneviratne, Harry Vereecken, Dani Or, Salma Tafasca, Naoki Mizukami, Rich Ellis, Patrick C. McGuire, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2026-4223, https://doi.org/10.5194/egusphere-2026-4223, 2026
Preprint archived
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Land surface models (LSMs) are essential tools to analyze future climate change. Here we pushed state-of-the-art LSMs out of their comfort zone revealing hidden connections between processes encoded into the models. The LSMs reacted differently due to complex, sometimes counter-intuitive interactions of different water fluxes. We identified surface runoff and soil evaporation as the two main reasons behind model differences, which should be improved by using more mechanistic descriptions.
Rong Liu, Xin Wang, Zuoliang Wang, Yongjie Pan, and Yan Song
EGUsphere, https://doi.org/10.5194/egusphere-2025-5814, https://doi.org/10.5194/egusphere-2025-5814, 2026
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Wetland soils on the Qinghai–Tibetan Plateau have layered pore structures that influence how water drains, is retained, and is stored. Using soil measurements, evaporation experiments, and model analysis, we show how surface, middle, and deep layers respond differently to moisture changes and control daily heat exchange. These results improve understanding of how alpine wetlands regulate water and energy and help make land surface simulations more realistic.
Binbin Wang, Yaoming Ma, Zeyong Hu, Xuan Li, Weiqiang Ma, Xuelong Chen, Cunbo Han, Zhipeng Xie, Yuyang Wang, Maoshan Li, Bin Ma, Xingdong Shi, Weimo Li, and Zhengling Cai
Earth Syst. Sci. Data, 18, 1147–1164, https://doi.org/10.5194/essd-18-1147-2026, https://doi.org/10.5194/essd-18-1147-2026, 2026
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This study reveals distinct patterns in water, heat, and carbon exchange over the Tibetan Plateau. Heat transfer peaks in spring, while water vapor release is highest in summer. Most stations act as carbon sinks, but one in a forested valley is a carbon source, likely due to vegetation loss and human activity. The findings highlight the strong connections between water, heat, and carbon fluxes, offering valuable insights into climate change and weather forecasting.
Qianqian Han, Yijian Zeng, Yunfei Wang, Fakhereh Alidoost, Francesco Nattino, Yang Liu, and Bob Su
Earth Syst. Sci. Data, 17, 7101–7117, https://doi.org/10.5194/essd-17-7101-2025, https://doi.org/10.5194/essd-17-7101-2025, 2025
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Understanding how land interacts with the atmosphere is crucial for studying climate change, yet global high-resolution data on energy, water, and carbon exchanges remain limited. This study introduces a new dataset FluxHourly that estimates these exchanges hourly from 2000 to 2020 by combining physical process model, field measurements, and machine learning with satellite and meteorological data. Fluxhourly enables analysis of ecosystem responses to climate extremes.
Haipeng Yu, Guantian Wang, Zeyong Hu, Yaoming Ma, Maoshan Li, Weiqiang Ma, Lianglei Gu, Fanglin Sun, Hongchun Gao, Shujin Wang, and Fuquan Lu
Earth Syst. Sci. Data, 17, 6871–6888, https://doi.org/10.5194/essd-17-6871-2025, https://doi.org/10.5194/essd-17-6871-2025, 2025
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The Nagqu Observation Network, located in Central Tibetan Plateau (CTP), has functioned as the primary source of land-atmosphere interaction observations and published a near-surface meteorological observational dataset which spans a period of nine years (2014–2022) with hourly temporal resolution. This dataset will contribute to the understanding of the mechanism of land-atmosphere interactions on the TP and support comprehensive research of the energy-water cycle and climate change.
Cunbo Han, Yaoming Ma, Weiqiang Ma, Fanglin Sun, Yunshuai Zhang, Wei Hu, Hanying Xu, Chunhui Duan, and Zhenhua Xi
EGUsphere, https://doi.org/10.5194/egusphere-2025-4642, https://doi.org/10.5194/egusphere-2025-4642, 2025
Preprint archived
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Wind speed spectra analysis is very important for understanding boundary layer turbulence characteristics, atmospheric numerical model development, and wind energy assessment. However, wind speed spectra studies in mountainous areas are extremely scarce. In this study, using a 15-year time series of wind speed observed by a PBL tower and eddy-covariance tower at a site on the north slope of Mt. Everest, we investigated the characteristics of wind speed and wind speed spectrum.
Mostafa Gomaa Daoud, Fakhereh Alidoost, Yijian Zeng, Bart Schilperoort, Christiaan Van der Tol, Maciek W. Lubczynski, Mhd Suhyb Salama, Eric D. Morway, Christian D. Langevin, Prajwal Khanal, Zengjing Song, Lianyu Yu, Hong Zhao, Gualbert Oude Essink, Victor F. Bense, Michiel van der Molen, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2025-4179, https://doi.org/10.5194/egusphere-2025-4179, 2025
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This study investigates the groundwater role in soil-plant-atmosphere continuum. An integrated ecohydrological modelling approach was developed by coupling STEMMUS-SCOPE to MODFLOW 6 and applied at three sites over 8 years. The coupled model improved simulations of soil moisture and temperature, evapotranspiration, carbon fluxes and fluorescence. The findings highlight the groundwater critical role in ecosystem dynamics and its contribution to advancing water, energy and carbon cycle modelling.
Minqiang Zhou, Yilong Wang, Minzheng Duan, Xiangjun Tian, Jinzhi Ding, Jianrong Bi, Yaoming Ma, Weiqiang Ma, and Zhenhua Xi
Atmos. Meas. Tech., 18, 4311–4324, https://doi.org/10.5194/amt-18-4311-2025, https://doi.org/10.5194/amt-18-4311-2025, 2025
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The Qinghai–Tibetan Plateau is a key system that impacts the global carbon balance. This study presents the greenhouse gas (GHG) mole fraction measurement campaign in May 2022 at Mt. Qomolangma station, including ground-based remote sensing and in situ measurements. The GHG measurements are carried out in this region for the first time and used for satellite validation.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
Hydrol. Earth Syst. Sci., 29, 465–483, https://doi.org/10.5194/hess-29-465-2025, https://doi.org/10.5194/hess-29-465-2025, 2025
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The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two endmembers of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented supersites.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
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This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Zengjing Song, Yijian Zeng, Yunfei Wang, Enting Tang, Danyang Yu, Fakhereh Alidoost, Mingguo Ma, Xujun Han, Xuguang Tang, Zhongjing Zhu, Yao Xiao, Debing Kong, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2024-2940, https://doi.org/10.5194/egusphere-2024-2940, 2024
Preprint archived
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The exchange of water and carbon between the plant and the atmosphere is affected under water stress conditions. In this study, a leaf-water-potential-based water stress factor is considered in the STEMMUS-SCOPE (hereafter STEMMUS-SCOPE-PHS), to replace the conventional soil-moisture-based water stress factor. The results show that leaf water potential reflects the plant water stress well, and the STEMMUS-SCOPE-PHS outperforms STEMMUS-SCOPE in the dynamics of the water, energy and carbon fluxes.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
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Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Cunbo Han, Yaoming Ma, Weiqiang Ma, Fanglin Sun, Yunshuai Zhang, Wei Hu, Hanying Xu, Chunhui Duan, and Zhenhua Xi
EGUsphere, https://doi.org/10.5194/egusphere-2024-1963, https://doi.org/10.5194/egusphere-2024-1963, 2024
Preprint archived
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Wind speed spectra analysis is very important for understanding boundary layer turbulence characteristics, atmospheric numerical model development, and wind energy assessment. However, wind speed spectra studies in mountainous areas are extremely scarce. In this study, using a 15-year time series of wind speed observed by a PBL tower and eddy-covariance tower at a site on the north slope of Mt. Everest, we investigated the characteristics of wind speed and wind speed spectrum.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaomin Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, https://doi.org/10.5194/essd-16-3017-2024, 2024
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Current models and satellites struggle to accurately represent the land–atmosphere (L–A) interactions over the Tibetan Plateau. We present the most extensive compilation of in situ observations to date, comprising 17 years of data on L–A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region, and it enables new investigations of fine-scale L–A processes and their mechanistic drivers.
Yunfei Wang, Yijian Zeng, Zengjing Song, Danyang Yu, Qianqian Han, Enting Tang, Henk de Bruin, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2024-1321, https://doi.org/10.5194/egusphere-2024-1321, 2024
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Various methods were proposed to estimate irrigation water requirements (IWR). However, the simulated IWR exhibits large differences. This study evaluates six potential evapotranspiration (PET) methods and proposes a practical approach to estimate IWR. The radiation-based methods show promise in approximating daily PET accurately, and the STEMMUS-SCOPE model can reliably estimate IWR. This research enhances our understanding of different PET methods and their implications for water management.
Enting Tang, Yijian Zeng, Yunfei Wang, Zengjing Song, Danyang Yu, Hongyue Wu, Chenglong Qiao, Christiaan van der Tol, Lingtong Du, and Zhongbo Su
Biogeosciences, 21, 893–909, https://doi.org/10.5194/bg-21-893-2024, https://doi.org/10.5194/bg-21-893-2024, 2024
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Our study shows that planting shrubs in a semiarid grassland reduced the soil moisture and increased plant water uptake and transpiration. Notably, the water used by the ecosystem exceeded the rainfall received during the growing seasons, indicating an imbalance in the water cycle. The findings demonstrate the effectiveness of the STEMMUS–SCOPE model as a tool to represent ecohydrological processes and highlight the need to consider energy and water budgets for future revegetation projects.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
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Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Qianqian Han, Yijian Zeng, Lijie Zhang, Calimanut-Ionut Cira, Egor Prikaziuk, Ting Duan, Chao Wang, Brigitta Szabó, Salvatore Manfreda, Ruodan Zhuang, and Bob Su
Geosci. Model Dev., 16, 5825–5845, https://doi.org/10.5194/gmd-16-5825-2023, https://doi.org/10.5194/gmd-16-5825-2023, 2023
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Using machine learning, we estimated global surface soil moisture (SSM) to aid in understanding water, energy, and carbon exchange. Ensemble models outperformed individual algorithms in predicting SSM under different climates. The best-performing ensemble included K-neighbours Regressor, Random Forest Regressor, and Extreme Gradient Boosting. This is important for hydrological and climatological applications such as water cycle monitoring, irrigation management, and crop yield prediction.
Peizhen Li, Lei Zhong, Yaoming Ma, Yunfei Fu, Meilin Cheng, Xian Wang, Yuting Qi, and Zixin Wang
Atmos. Chem. Phys., 23, 9265–9285, https://doi.org/10.5194/acp-23-9265-2023, https://doi.org/10.5194/acp-23-9265-2023, 2023
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In this paper, all-sky downwelling shortwave radiation (DSR) over the entire Tibetan Plateau (TP) at a spatial resolution of 1 km was estimated using an improved parameterization scheme. The influence of topography and different radiative attenuations were comprehensively taken into account. The derived DSR showed good agreement with in situ measurements. The accuracy was better than six other DSR products. The derived DSR also provided more reasonable and detailed spatial patterns.
Kai-Gao Ouyang, Xiao-Wei Jiang, Gang Mei, Hong-Bin Yan, Ran Niu, Li Wan, and Yijian Zeng
Hydrol. Earth Syst. Sci., 27, 2579–2590, https://doi.org/10.5194/hess-27-2579-2023, https://doi.org/10.5194/hess-27-2579-2023, 2023
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Our knowledge on sources and dynamics of rock moisture is limited. By using frequency domain reflectometry (FDR), we monitored rock moisture in a cave. The results of an explainable deep learning model reveal that the direct source of rock moisture responsible for weathering in the studied cave is vapour, not infiltrating precipitation. A physics-informed deep learning model, which uses variables controlling vapor condensation as model inputs, leads to accurate rock water content predictions.
Lianyu Yu, Yijian Zeng, Huanjie Cai, Mengna Li, Yuanyuan Zha, Jicai Zeng, Hui Qian, and Zhongbo Su
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-221, https://doi.org/10.5194/gmd-2022-221, 2023
Revised manuscript not accepted
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We developed a coupled soil water-groundwater (SW-GW) model, which is verified as physically accurate and applicable in large-scale groundwater problems. The role of vadose zone processes, coupling approach, and spatiotemporal heterogeneity of SW-GW interactions were highlighted as essential to represent the SW-GW system. Given the relevant dataset, the developed SW-GW modeling framework has the potential to portray the processes "from bedrock to atmosphere" in a physically consistent manner.
Rogier van der Velde, Harm-Jan F. Benninga, Bas Retsios, Paul C. Vermunt, and M. Suhyb Salama
Earth Syst. Sci. Data, 15, 1889–1910, https://doi.org/10.5194/essd-15-1889-2023, https://doi.org/10.5194/essd-15-1889-2023, 2023
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From 2009, a network of 20 profile soil moisture and temperature monitoring stations has been operational in the Twente region, east of the Netherlands. In addition, field campaigns have been conducted covering four growing seasons during which soil moisture was measured near 12 monitoring stations. We describe the monitoring network and field campaigns, and we provide an overview of open third-party datasets that may support the use of the Twente datasets.
Hong Zhao, Yijian Zeng, Jan G. Hofste, Ting Duan, Jun Wen, and Zhongbo Su
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-333, https://doi.org/10.5194/hess-2022-333, 2022
Revised manuscript not accepted
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This paper demonstrated the capability of our developed platform for simulating microwave emission and backscatter signals at multi-frequency. The results of associated investigations on impacts of vegetation water (VW) and temperature (T) imply the need to first disentangle the impact of T for the use of high-frequency signals as its variation is more due to dynamic T. Estimated vegetation optical depth is frequency-dependent, while its diurnal variation depends on that of VW despite frequency.
Maoshan Li, Wei Fu, Na Chang, Ming Gong, Pei Xu, Yaoming Ma, Zeyong Hu, Yaoxian Yang, and Fanglin Sun
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-257, https://doi.org/10.5194/acp-2022-257, 2022
Revised manuscript not accepted
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Compared with the plain area, the land-atmosphere interaction on the Tibetan Plateau (TP) is intense and complex, which affects the structure of the boundary layer. The observed height of the convective boundary layer on the TP under the influence of the southern branch of the westerly wind was higher than that during the Asian monsoon season. The height of the boundary layer was positively correlated with the sensible heat flux and negatively correlated with latent heat flux.
Shaoning Lv, Clemens Simmer, Yijian Zeng, Jun Wen, Yuanyuan Guo, and Zhongbo Su
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-369, https://doi.org/10.5194/tc-2021-369, 2022
Preprint withdrawn
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The freeze-thaw of the ground is an interesting topic to climatology, hydrology, and other earth sciences. The global freeze-thaw distribution is available by passive microwave remote sensing technique. However, the remote sensing technique indirectly detects freeze-thaw states by measuring the brightness temperature difference between frozen and unfrozen soil. Thus, we present different interprets of the brightness signals to the FT-state by using its sub-daily character.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Geosci. Model Dev., 14, 7345–7376, https://doi.org/10.5194/gmd-14-7345-2021, https://doi.org/10.5194/gmd-14-7345-2021, 2021
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We developed an integrated soil–snow–atmosphere model (STEMMUS-UEB) dedicated to the physical description of snow and soil processes with various complexities. With STEMMUS-UEB, we demonstrated that the snowpack affects not only the soil surface moisture conditions (in the liquid and ice phase) and energy-related states (albedo, LE) but also the subsurface soil water and vapor transfer, which contributes to a better understanding of the hydrothermal implications of the snowpack in cold regions.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Yunshuai Zhang, Qian Huang, Yaoming Ma, Jiali Luo, Chan Wang, Zhaoguo Li, and Yan Chou
Atmos. Chem. Phys., 21, 15949–15968, https://doi.org/10.5194/acp-21-15949-2021, https://doi.org/10.5194/acp-21-15949-2021, 2021
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The source region of the Yellow River has an important role in issues related to water resources, ecological environment, and climate changes in China. We utilized large eddy simulation to understand whether the surface heterogeneity promotes or inhibits the boundary-layer turbulence, the great contribution of the thermal circulations induced by surface heterogeneity to the water and heat exchange between land/lake and air. Moreover, the turbulence in key locations is characterized.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
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The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Lian Liu, Yaoming Ma, Massimo Menenti, Rongmingzhu Su, Nan Yao, and Weiqiang Ma
Hydrol. Earth Syst. Sci., 25, 4967–4981, https://doi.org/10.5194/hess-25-4967-2021, https://doi.org/10.5194/hess-25-4967-2021, 2021
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Albedo is a key factor in land surface energy balance, which is difficult to successfully reproduce by models. Here, we select eight snow events on the Tibetan Plateau to evaluate the universal improvements of our improved albedo scheme. The RMSE relative reductions for temperature, albedo, sensible heat flux and snow depth reach 27%, 32%, 13% and 21%, respectively, with remarkable increases in the correlation coefficients. This presents a strong potential of our scheme for modeling snow events.
Zhipeng Xie, Yaoming Ma, Weiqiang Ma, Zeyong Hu, and Genhou Sun
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-260, https://doi.org/10.5194/tc-2021-260, 2021
Preprint withdrawn
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Wind-driven snow transport greatly influences spatial-temporal distribution of snow in mountainous areas. Knowledge of the spatiotemporal variability of blowing snow is in its infancy because of inaccuracies in satellite-based blowing snow algorithms and the absence of quantitative assessments. Here, we present the spatiotemporal variability and magnitude of blowing snow events, and explore the potential links with ambient meteorological conditions using near surface blowing snow observations.
Cited articles
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Short summary
Soil moisture and soil temperature (SMST) are important state variables for quantifying the heat–water exchange between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements at multiple depths are scarce on the Tibetan Plateau (TP). The presented dataset would be valuable for the evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change.
Soil moisture and soil temperature (SMST) are important state variables for quantifying the...
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