Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-4959-2023
© 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-15-4959-2023
© 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
| 
10 Nov 2023
Data description paper |
| 10 Nov 2023
| 10 Nov 2023
A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin
Shaomin Liu
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Ziwei Xu
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Xin Li
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Tongren Xu
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Zhiguo Ren
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Yang Zhang
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Junlei Tan
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Lisheng Song
Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze–Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241000, China
Ji Zhou
School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China
Zhongli Zhu
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Xiaofan Yang
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Rui Liu
Institute of Urban Study, School of Environmental and Geographical Sciences (SEGS), Shanghai Normal University, Shanghai 200234, China
Yanfei Ma
Hebei Technology Innovation Centre for Remote Sensing Identification of Environmental Change, Hebei Key Laboratory of Environmental Change and Ecological Construction, School of Geographical Sciences, Hebei Normal University, Shijiazhuang 050024, China
Related authors
Xufeng Wang, Tao Che, Jingfeng Xiao, Tonghong Wang, Junlei Tan, Yang Zhang, Zhiguo Ren, Liying Geng, Haibo Wang, Ziwei Xu, Shaomin Liu, and Xin Li
Earth Syst. Sci. Data, 17, 1329–1346, https://doi.org/10.5194/essd-17-1329-2025, https://doi.org/10.5194/essd-17-1329-2025, 2025
Short summary
Short summary
In this study, carbon flux and auxiliary meteorological data are post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River basin. Overall, 18 sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1513 site months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.
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
Short summary
Short summary
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.
Yibo Sun, Bilige Sude, Xingwen Lin, Bing Geng, Bo Liu, Shengnan Ji, Junping Jing, Zhiping Zhu, Ziwei Xu, Shaomin Liu, and Zhanjun Quan
Atmos. Meas. Tech., 16, 5659–5679, https://doi.org/10.5194/amt-16-5659-2023, https://doi.org/10.5194/amt-16-5659-2023, 2023
Short summary
Short summary
Unoccupied aerial vehicles (UAVs) provide a versatile platform for eddy covariance (EC) flux measurements at regional scales with low cost, transport, and infrastructural requirements. This study evaluates the measurement performance in the wind field and turbulent flux of a UAV-based EC system based on the data from a set of calibration flights and standard operational flights and concludes that the system can measure the georeferenced wind vector and turbulent flux with sufficient precision.
Xinlei He, Yanping Li, Shaomin Liu, Tongren Xu, Fei Chen, Zhenhua Li, Zhe Zhang, Rui Liu, Lisheng Song, Ziwei Xu, Zhixing Peng, and Chen Zheng
Hydrol. Earth Syst. Sci., 27, 1583–1606, https://doi.org/10.5194/hess-27-1583-2023, https://doi.org/10.5194/hess-27-1583-2023, 2023
Short summary
Short summary
This study highlights the role of integrating vegetation and multi-source soil moisture observations in regional climate models via a hybrid data assimilation and machine learning method. In particular, we show that this approach can improve land surface fluxes, near-surface atmospheric conditions, and land–atmosphere interactions by implementing detailed land characterization information in basins with complex underlying surfaces.
Wangyipu Li, Zhaoyuan Yao, Yifan Qu, Hanbo Yang, Yang Song, Lisheng Song, Lifeng Wu, and Yaokui Cui
Earth Syst. Sci. Data, 17, 3835–3855, https://doi.org/10.5194/essd-17-3835-2025, https://doi.org/10.5194/essd-17-3835-2025, 2025
Short summary
Short summary
Due to shortcomings such as extensive data gaps and limited observation durations in current ground-based latent heat flux (LE) datasets, we developed a novel gap-filling and prolongation framework for ground-based LE observations, establishing a benchmark dataset for global evapotranspiration (ET) estimation from 2000 to 2022 across 64 sites at various timescales. This comprehensive dataset can strongly support ET modeling, water–carbon cycle monitoring, and long-term climate change analysis.
Yuan He and Xiaofan Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1983, https://doi.org/10.5194/egusphere-2025-1983, 2025
Short summary
Short summary
This study introduces HyLake, a hybrid lake model that embeds a deep-learning surrogate for the water temperature module within a process-based backbone. HyLake simulates lake surface temperature and the latent and sensible heat fluxes in Lake Taihu more accurately than traditional process-based models and other hybrid experiments across different forcing datasets. The proposed coupling strategy provides a reliable tool for quantifying the impacts of climate change on aquatic ecosystems.
Xufeng Wang, Tao Che, Jingfeng Xiao, Tonghong Wang, Junlei Tan, Yang Zhang, Zhiguo Ren, Liying Geng, Haibo Wang, Ziwei Xu, Shaomin Liu, and Xin Li
Earth Syst. Sci. Data, 17, 1329–1346, https://doi.org/10.5194/essd-17-1329-2025, https://doi.org/10.5194/essd-17-1329-2025, 2025
Short summary
Short summary
In this study, carbon flux and auxiliary meteorological data are post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River basin. Overall, 18 sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1513 site months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.
Xia Wang, Tao Che, Xueyin Ruan, Shanna Yue, Jing Wang, Chun Zhao, and Lei Geng
Geosci. Model Dev., 18, 651–670, https://doi.org/10.5194/gmd-18-651-2025, https://doi.org/10.5194/gmd-18-651-2025, 2025
Short summary
Short summary
We employed the WRF-Chem model to parameterize atmospheric nitrate deposition in snow and evaluate its performance in simulating snow cover, snow depth, and concentrations of dust and nitrate using new observations from northern China. The results generally exhibit reasonable agreement with field observations in northern China, demonstrating the model's capability to simulate snow properties, including concentrations of reservoir species.
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
Short summary
Short summary
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.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
Short summary
Short summary
This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
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
Short summary
Short summary
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.
Wenbin Tang, Ji Zhou, Jin Ma, Ziwei Wang, Lirong Ding, Xiaodong Zhang, and Xu Zhang
Earth Syst. Sci. Data, 16, 387–419, https://doi.org/10.5194/essd-16-387-2024, https://doi.org/10.5194/essd-16-387-2024, 2024
Short summary
Short summary
This paper reported a daily 1 km all-weather land surface temperature (LST) dataset for Chinese land mass and surrounding areas – TRIMS LST. The results of a comprehensive evaluation show that TRIMS LST has the following special features: the longest time coverage in its class, high image quality, and good accuracy. TRIMS LST has already been released to the scientific community, and a series of its applications have been reported by the literature.
Yibo Sun, Bilige Sude, Xingwen Lin, Bing Geng, Bo Liu, Shengnan Ji, Junping Jing, Zhiping Zhu, Ziwei Xu, Shaomin Liu, and Zhanjun Quan
Atmos. Meas. Tech., 16, 5659–5679, https://doi.org/10.5194/amt-16-5659-2023, https://doi.org/10.5194/amt-16-5659-2023, 2023
Short summary
Short summary
Unoccupied aerial vehicles (UAVs) provide a versatile platform for eddy covariance (EC) flux measurements at regional scales with low cost, transport, and infrastructural requirements. This study evaluates the measurement performance in the wind field and turbulent flux of a UAV-based EC system based on the data from a set of calibration flights and standard operational flights and concludes that the system can measure the georeferenced wind vector and turbulent flux with sufficient precision.
Xinlei He, Yanping Li, Shaomin Liu, Tongren Xu, Fei Chen, Zhenhua Li, Zhe Zhang, Rui Liu, Lisheng Song, Ziwei Xu, Zhixing Peng, and Chen Zheng
Hydrol. Earth Syst. Sci., 27, 1583–1606, https://doi.org/10.5194/hess-27-1583-2023, https://doi.org/10.5194/hess-27-1583-2023, 2023
Short summary
Short summary
This study highlights the role of integrating vegetation and multi-source soil moisture observations in regional climate models via a hybrid data assimilation and machine learning method. In particular, we show that this approach can improve land surface fluxes, near-surface atmospheric conditions, and land–atmosphere interactions by implementing detailed land characterization information in basins with complex underlying surfaces.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
Short summary
Short summary
Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Huadong Wang, Xueliang Zhang, Pengfeng Xiao, Tao Che, Zhaojun Zheng, Liyun Dai, and Wenbo Luan
The Cryosphere, 17, 33–50, https://doi.org/10.5194/tc-17-33-2023, https://doi.org/10.5194/tc-17-33-2023, 2023
Short summary
Short summary
The geographically and temporally weighted neural network (GTWNN) model is constructed for estimating large-scale daily snow density by integrating satellite, ground, and reanalysis data, which addresses the importance of spatiotemporal heterogeneity and a nonlinear relationship between snow density and impact variables, as well as allows us to understand the spatiotemporal pattern and heterogeneity of snow density in different snow periods and snow cover regions in China from 2013 to 2020.
Hui Guo, Xiaoyan Wang, Zecheng Guo, Gaofeng Zhu, Tao Che, Jian Wang, Xiaodong Huang, Chao Han, and Zhiqi Ouyang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-229, https://doi.org/10.5194/tc-2022-229, 2022
Revised manuscript not accepted
Short summary
Short summary
Snow phenology is a seasonal pattern in snow cover and snowfall. In this review, we found that during the past 50 years in the Northern Hemisphere, the snow cover end date has shown a significantly advanced change trend. Eurasia contributes more to the snow phenology in the Northern Hemisphere than does North America. Snow phenology is related to climate and atmospheric circulation, and the response to vegetation phenology depends on geographical regions, temperature and precipitation gradients.
Liyun Dai, Tao Che, Yang Zhang, Zhiguo Ren, Junlei Tan, Meerzhan Akynbekkyzy, Lin Xiao, Shengnan Zhou, Yuna Yan, Yan Liu, Hongyi Li, and Lifu Wang
Earth Syst. Sci. Data, 14, 3509–3530, https://doi.org/10.5194/essd-14-3509-2022, https://doi.org/10.5194/essd-14-3509-2022, 2022
Short summary
Short summary
An Integrated Microwave Radiometry Campaign for Snow (IMCS) was conducted to collect ground-based passive microwave and optical remote-sensing data, snow pit and underlying soil data, and meteorological parameters. The dataset is unique in continuously providing electromagnetic and physical features of snowpack and environment. The dataset is expected to serve the evaluation and development of microwave radiative transfer models and snow process models, along with land surface process models.
Yijie Sui, Min Feng, Chunling Wang, and Xin Li
Earth Syst. Sci. Data, 14, 3349–3363, https://doi.org/10.5194/essd-14-3349-2022, https://doi.org/10.5194/essd-14-3349-2022, 2022
Short summary
Short summary
High-latitude water bodies differ greatly in their morphological and topological characteristics related to their formation, type, and vulnerability. In this paper, we present a water body dataset for the North American high latitudes (WBD-NAHL). Nearly 6.5 million water bodies were identified, with approximately 6 million (~90 %) of them smaller than 0.1 km2.
Shu Fang, Kebiao Mao, Xueqi Xia, Ping Wang, Jiancheng Shi, Sayed M. Bateni, Tongren Xu, Mengmeng Cao, Essam Heggy, and Zhihao Qin
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
Short summary
Short summary
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.
Yanxing Hu, Tao Che, Liyun Dai, Yu Zhu, Lin Xiao, Jie Deng, and Xin Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-63, https://doi.org/10.5194/essd-2022-63, 2022
Preprint withdrawn
Short summary
Short summary
We propose a data fusion framework based on the random forest regression algorithm to derive a comprehensive snow depth product for the Northern Hemisphere from 1980 to 2019. This new fused snow depth dataset not only provides information about snow depth and its variation over the Northern Hemisphere but also presents potential value for hydrological and water cycle studies related to seasonal snowpacks.
Youhua Ran, Xin Li, Guodong Cheng, Jingxin Che, Juha Aalto, Olli Karjalainen, Jan Hjort, Miska Luoto, Huijun Jin, Jaroslav Obu, Masahiro Hori, Qihao Yu, and Xiaoli Chang
Earth Syst. Sci. Data, 14, 865–884, https://doi.org/10.5194/essd-14-865-2022, https://doi.org/10.5194/essd-14-865-2022, 2022
Short summary
Short summary
Datasets including ground temperature, active layer thickness, the probability of permafrost occurrence, and the zonation of hydrothermal condition with a 1 km resolution were released by integrating unprecedentedly large amounts of field data and multisource remote sensing data using multi-statistical\machine-learning models. It updates the understanding of the current thermal state and distribution for permafrost in the Northern Hemisphere.
Donghang Shao, Hongyi Li, Jian Wang, Xiaohua Hao, Tao Che, and Wenzheng Ji
Earth Syst. Sci. Data, 14, 795–809, https://doi.org/10.5194/essd-14-795-2022, https://doi.org/10.5194/essd-14-795-2022, 2022
Short summary
Short summary
The temporal series and spatial distribution discontinuity of the existing snow water equivalent (SWE) products in the pan-Arctic region severely restricts the use of SWE data in cryosphere change and climate change studies. Using a ridge regression machine learning algorithm, this study developed a set of spatiotemporally seamless and high-precision SWE products. This product could contribute to the study of cryosphere change and climate change at large spatial scales.
Xiaohua Hao, Guanghui Huang, Tao Che, Wenzheng Ji, Xingliang Sun, Qin Zhao, Hongyu Zhao, Jian Wang, Hongyi Li, and Qian Yang
Earth Syst. Sci. Data, 13, 4711–4726, https://doi.org/10.5194/essd-13-4711-2021, https://doi.org/10.5194/essd-13-4711-2021, 2021
Short summary
Short summary
Long-term snow cover data are not only of importance for climate research. Currently China still lacks a high-quality snow cover extent (SCE) product for climate research. This study develops a multi-level decision tree algorithm for cloud and snow discrimination and gap-filled technique based on AVHRR surface reflectance data. We generate a daily 5 km SCE product across China from 1981 to 2019. It has high accuracy and will serve as baseline data for climate and other applications.
Guoqing Zhang, Youhua Ran, Wei Wan, Wei Luo, Wenfeng Chen, Fenglin Xu, and Xin Li
Earth Syst. Sci. Data, 13, 3951–3966, https://doi.org/10.5194/essd-13-3951-2021, https://doi.org/10.5194/essd-13-3951-2021, 2021
Short summary
Short summary
Lakes can be effective indicators of climate change, especially over the Qinghai–Tibet Plateau. Here, we provide the most comprehensive lake mapping covering the past 100 years. The new features of this data set are (1) its temporal length, providing the longest period of lake observations from maps, (2) the data set provides a state-of-the-art lake inventory for the Landsat era (from the 1970s to 2020), and (3) it provides the densest lake observations for lakes with areas larger than 1 km2.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
Short summary
Short summary
The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Jiahua Zhang, Lin Liu, Lei Su, and Tao Che
The Cryosphere, 15, 3021–3033, https://doi.org/10.5194/tc-15-3021-2021, https://doi.org/10.5194/tc-15-3021-2021, 2021
Short summary
Short summary
We improve the commonly used GPS-IR algorithm for estimating surface soil moisture in permafrost areas, which does not consider the bias introduced by seasonal surface vertical movement. We propose a three-in-one framework to integrate the GPS-IR observations of surface elevation changes, soil moisture, and snow depth at one site and illustrate it by using a GPS site in the Qinghai–Tibet Plateau. This study is the first to use GPS-IR to measure environmental variables in the Tibetan Plateau.
Zhe Jin, Xiangjun Tian, Rui Han, Yu Fu, Xin Li, Huiqin Mao, and Cuihong Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-210, https://doi.org/10.5194/essd-2021-210, 2021
Manuscript not accepted for further review
Short summary
Short summary
Here we present a global and regional resolved terrestrial ecosystem and ocean carbon flux dataset during 2015–2019. The dataset was generated using the Tan-Tracker inversion system by absorbing satellite CO2 observations. The posterior 5-year annual mean global net carbon emissions were 5.35 PgC yr−1; the terrestrial ecosystem and ocean sinks were −4.07 and −3.33 PgC yr−1, respectively. This dataset can help understand global and regional carbon cycle, and support climate policy formulation.
Mengmeng Cao, Kebiao Mao, Yibo Yan, Jiancheng Shi, Han Wang, Tongren Xu, Shu Fang, and Zijin Yuan
Earth Syst. Sci. Data, 13, 2111–2134, https://doi.org/10.5194/essd-13-2111-2021, https://doi.org/10.5194/essd-13-2111-2021, 2021
Short summary
Short summary
We constructed a temperature depth and observation time correction model to eliminate the sampling depth and temporal differences among different data. Then, we proposed a reconstructed spatial model that filters and removes missing pixels and low-quality pixels contaminated by clouds from raw SST images and retrieves real sea surface temperatures under cloud coverage based on multisource data to generate a high-quality unified global SST product with long-term spatiotemporal continuity.
Jin Ma, Ji Zhou, Frank-Michael Göttsche, Shunlin Liang, Shaofei Wang, and Mingsong Li
Earth Syst. Sci. Data, 12, 3247–3268, https://doi.org/10.5194/essd-12-3247-2020, https://doi.org/10.5194/essd-12-3247-2020, 2020
Short summary
Short summary
Land surface temperature is an important parameter in the research of climate change and many land surface processes. This article describes the development and testing of an algorithm for generating a consistent global long-term land surface temperature product from 20 years of NOAA AVHRR radiance data. The preliminary validation results indicate good accuracy of this new long-term product, which has been designed to simplify applications and support the scientific research community.
Cited articles
Bai, Y., Liu, Y. L., Kueppers, L. M., Feng, X., Yu, K. L., Yang, X. F., Li, X. Y., and Huang, J. P.: The coupled effect of soil and atmospheric constraints on stress-responses of desert riparian species, Agr. Forest Meteorol., 311, 108701, https://doi.org/10.1016/j.agrformet.2021.108701, 2021.
Che, T., Dai, L. Y., Wang, J., Zhao, K., and Liu, Q: Estimation of snow depth and snow water equivalent distribution using airborne microwave radiometry in the Binggou Watershed, the upper reaches of the Heihe River basin, Int. J. Appl. Earth Obs., 17, 23–32, https://doi.org/10.1016/j.jag.2011.10.014, 2012.
Che, T., Li, X., Liu, S., Li, H., Xu, Z., Tan, J., Zhang, Y., Ren, Z., Xiao, L., Deng, J., Jin, R., Ma, M., Wang, J., and Yang, X.: Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China, Earth Syst. Sci. Data, 11, 1483–1499, https://doi.org/10.5194/essd-11-1483-2019, 2019.
Cheng, G. D., Xiao, D. N., and Wang, G. X.: On the characteristics and building of landscape ecology in arid area, Adv. Geosci., 14, 11–15, 1999 (in Chinese with English abstract).
Cheng, G. D., Li, X., Zhao, W., Xu, Z., Feng, Q., Xiao, S., and Xiao, H.: Integrated study of the water-ecosystem-economy in the Heihe River Basin, Natl. Sci. Rev., 1, 413–428, https://doi.org/10.1093/nsr/nwu017, 2014.
Chu, P. C., Lu, S., and Chen, Y.: A numerical modeling study on desert oasis self-supporting mechanisms, J. Hydrol., 312, 256–276, https://doi.org/10.1016/j.jhydrol.2005.02.043, 2005.
Crétaux, J. F., Calmant, S., Romanovski, V., Shabunin, A., Lyard, F., Bergé-Nguyen, M., Cazenave, A., Hernandez, F., and Perosanz, F.: An absolute calibration site for radar altimeters in the continental domain: Lake issykkul in the central asia, J. Geodesy, 83, 723–735, https://doi.org/10.1007/s00190-008-0289-7, 2009.
Dregne, H. E.: Global status of desertification, Ann. Arid Zone, 30, 179–185, 1991.
Georgescu, M., Moustaoui, M., Mahalov, A., and Dudhia, J.: An alternative explanation of the semiarid urban area “oasis effect”, J. Geophys. Res.-Atmos., 116, D24113, https://doi.org/10.1029/2011JD016720, 2011.
He, X. L., Liu, S. M., Xu, T. R., Yu, K. L., Gentine, P., Zhang, Z., Xu, Z. W., Jiao, D. D., and Wu, D. X.: Improving predictions of evapotranspiration by integrating multi-source observations and land surface model, Agr. Water Manage., 272, 107827, https://doi.org/10.1016/j.agwat.2022.107827, 2022.
Hommeltenberg, J., Mauder, M., Drosler, M., Heidbach, K., Werle, P., and Schmid, H. P.: Ecosystem scale methane fluxes in a natural temperature bog-pine forest in southern Germany, Agr. Forest Meteorol., 198–199, 273–284, https://doi.org/10.1016/j.agrformet.2014.08.017, 2014.
Huang, J. P., Yu, H. P., Guan, X. D., Wang, G. Y., and Guo, R. X.: Accelerated dryland expansion under climate change, Nature Clim. Change, 6, 166–171, https://doi.org/10.1038/nclimate2837, 2016.
Li, M. S., Zhou, J., Peng, Z. X., Liu, S. M., Göttsche, F. M., Zhang, X. D., and Song, L. S.: Component radiative temperatures over sparsely vegetated surfaces and their potential for upscaling land surface temperature, Agr. Forest Meteorol., 276–277, 107600, https://doi.org/10.1016/j.agrformet.2019.05.031, 2019.
Li, X., Li, X. W., Li, Z. Y., Ma, M. G., Wang, J., Xiao, Q., Liu, Q., Che, T., Chen, E. X., Yan, G. J., Hu, Z. Y., Zhang, L. X., Chu, R. Z., Su, P. X., Liu, Q. H., Liu, S. M., Wang, J. D., Niu, Z., Chen, Y., Jin, R., Wang, W. Z., Ran, Y. H., and Xin, X.: Watershed Allied Telemetry Experimental Research, J. Geophys. Res.-Atmos., 114, D22103, https://doi.org/10.1029/2008JD011590, 2009.
Li, X., Cheng, G. D., Liu, S. M., Xiao, Q., Ma, M. G., Jin, R., Che, T., Liu, Q. H., Wang, W. Z., Qi, Y., Wen, J. G., Li, H. Y., Zhu, G. F., Guo, J. W., Ran, Y. H., Wang, S. G., Zhu, Z. L., Zhou, J., Hu, X. L., and Xu, Z. W.: Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific Objectives and Experimental Design, B. Am. Meteorol. Soc., 94, 1145–1160, https://doi.org/10.1175/BAMS-D-12-00154.1, 2013.
Li, X., Yang, K., and Zhou, Y.: Progress in the study of oasis-desert interactions, Agr. Forest Meteorol., 230, 1–7, https://doi.org/10.1016/j.agrformet.2016.08.022, 2016.
Li, X., Liu, S. M., Xiao, Q., Ma, M. G., Jin, R., Che, T., Wang, W. Z., Hu, X. L., Xu, Z. W., Wen, J. G., and Wang, L. X.: A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system, Sci. Data, 4, 170083, https://doi.org/10.1038/sdata.2017.83, 2017a.
Li, X., Zheng, Y., Sun, Z., Tian, Y., Zheng, C. M., Liu, J., Liu, S. M., and Xu, Z. W.: An integrated ecohydrological modeling approach to exploring the dynamic interaction between groundwater and phreatophytes, Ecol. Model., 356, 127–140, https://doi.org/10.1016/j.ecolmodel.2017.04.017, 2017b.
Li, X., Liu, S. M., Li, H. X., Ma, Y. F., Wang, J. H., Zhang, Y., Xu, Z. W., Xu, T. R., Song, L. S., Yang, X. F., Lu, Z., Wang, Z. Y., and Guo, Z. X.: Intercomparison of six upscaling evapotranspiration methods: from site to the satellite pixel, J. Geophys. Res.-Atmos., 123, 6777–6803, https://doi.org/10.1029/2018JD028422, 2018.
Li, X., Liu, S. M., Yang, X. F., Ma, Y. F., He, X. L., Xu, Z. W., Xu, T. R., Song, L. S., Zhang, Y., Hu, X., Qu, Q., and Zhang, X. D.: Upscaling evapotranspiration from a single-site to satellite pixel scale, Remote Sens., 13, 4072, https://doi.org/10.3390/rs13204072, 2021.
Liebethal, C., Huwe, B., and Foken, T.: Sensitivity analysis for two ground heat flux calculation approaches, Agr. Forest Meteorol., 132, 253–262, https://doi.org/10.1016/j.agrformet.2005.08.001, 2005.
Liu, R., Sogachev, A., Yang, X. F., Liu, S. M., Xu, T. R., and Zhang, J. J.: Investigating microclimate effects in an oasis-desert interaction zone, Agr. Forest Meteorol., 290, 107992, https://doi.org/10.1016/j.agrformet.2020.107992, 2020.
Liu, S., Xu, Z., Che, T., Li, X., Xu, T., Ren, Z., Zhang, Y., Tan, J., Song, L., Zhou, J., Zhu, Z., Yang, X., Liu, R., and Ma, Y.: Energy, water vapor and carbon exchange observations in oasis-desert areas of Heihe river basin (2012–2021), National Tibetan Plateau/Third Pole Environment Data Center, https://doi.org/10.11888/Terre.tpdc.300441, 2023.
Liu, S. M., Xu, Z. W., Wang, W. Z., Jia, Z. Z., Zhu, M. J., Bai, J., and Wang, J. M.: A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem, Hydrol. Earth Syst. Sci., 15, 1291–1306, https://doi.org/10.5194/hess-15-1291-2011, 2011.
Liu, S. M., Xu, Z. W., Song, L. S., Zhao, Q. Y., Ge, Y., Xu, T. R., Ma, Y. F., Zhu, Z. L., Jia, Z. Z., and Zhang, F.: Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces, Agr. Forest Meteorol., 230–231, 97–113, https://doi.org/10.1016/j.agrformet.2016.04.008, 2016.
Liu, S. M., Li, X., Xu, Z. W., Che, T., Xiao, Q., Ma, M. G., Liu, Q. H., Jin, R., Guo, J. W., Wang, L. X., Wang, W. Z., Qi, Y., Li, H. Y., Xu, T. R., Ran, Y. H., Hu, X. L., Shi, S. J., Zhu, Z. L., Tan, J. L., Zhang, Y., and Ren, Z. G.: The Heihe Integrated Observatory Network: A basin-scale land surface processes observatory in China, Vadose Zone J., 17, 180072, https://doi.org/10.2136/vzj2018.04.0072, 2018.
Ma, Y. F., Liu, S. M., Song, L. S., Xu, Z. W., Liu, Y. L., Xu, T. R., and Zhu, Z. L.: Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data, Remote Sens. Environ., 216, 715–734, https://doi.org/10.1016/j.rse.2018.07.019, 2018.
Mao, D., Wang, Z., Wu, B., Zeng, Y., Luo, L., and Zhang, B.: Land degradation and restoration in the arid and semiarid zones of China: Quantified evidence and implications from satellites, Land Degrad. Dev., 29, 3841–3851, https://doi.org/10.1002/ldr.3135, 2018.
Meng, X., Lv, S., Zhang, T., Guo, J., Gao, Y., Bao, Y., Wen, L., Luo, S., and Liu, Y.: Numerical simulations of the atmospheric and land conditions over the jinta oasis in northwestern China with satellite-derived land surface parameters, J. Geophys. Res.-Atmos., 114, 605–617, https://doi.org/10.1029/2008JD010360, 2009.
Potchter, O., Goldman, D., Kadish, D., and Iluz, D.: The oasis effect in an extremely hot and arid climate: The case of southern Israel, J. Arid Environ., 72, 1721–1733, https://doi.org/10.1016/j.jaridenv.2008.03.004, 2008.
Qu, Y. H., Zhu, Y. Q., Han, W. C., Wang, J. D., and Ma, M. G: Crop leaf area index observations with a wireless sensor network and its potential for validating remote sensing products, IEEE J-STARS., 7, 431–444, https://doi.org/10.1109/JSTARS.2013.2289931, 2014.
Scanlon, B. R., Keese, K. E., Flint, A. L., Flint, L. E., Gaye, C. B., Edmunds, W. M., and Simmers, I.: Global synthesis of groundwater recharge in semiarid and arid regions, Hydrol. Process., 20, 3335–3370, https://doi.org/10.1002/hyp.6335, 2006.
Song, L. S., Liu, S. M., Kustas, W. P., Nieto, H., Sun, L., Xu, Z. W., Skaggs, T. H., Yang, Y., Ma, M. G., Xu, T. R., Tang, X. G., and Li, Q. P.: Monitoring and validating spatially and temporally continuous daily evaporation and transpiration at river basin scale, Remote Sens. Environ., 219, 72–88, https://doi.org/10.1016/j.rse.2018.10.002, 2018.
Stanev, E., Staneva, J., Bullister, J., and Murray, J.: Ventilation of the black sea pycnocline. Parameterization of convection, numerical simulations and validations against observed chlorofluorocarbon data, Deep-Sea Res. Pt. I, 51, 2137–2169, https://doi.org/10.1016/j.dsr.2004.07.018, 2004.
Stone, K. B.: Burke-Litwin organizational assessment survey: reliability and validity, Organization Development Journal, 33, 33–50, 2015.
Stoy, P. C., Mauder, M., Foken, T., Marcolla, B., Boegh, E., Ibrom, A., Arain, M., Arneth, A., Aurela, M., Bernhofer, C., Cescatti, A., Dellwik, E., Duce, P., Gianelle, D., Gorsel, E., Kiely, G., Knohl, A., Margolis, H., McCaughey, H., Merbold, L., Montagnanti, L., Papale, D., Reichstein, M., Saunders, M., Serrano-Ortiz, P., Sottocornola, M., Spano, D., Vaccari, F., and Varlagin, A.: A data-driven analysis of energy balance closure across FLUXNET research sites: The role of landscape scale heterogeneity, Agr. Forest Meteorol., 171–172, 137–152, https://doi.org/10.1016/j.agrformet.2012.11.004, 2013.
Tagesson, T., Fensholt, R., Cappelaere, B., Mougin, E., Horion, S., Kergoat, L., Nieto, H., Mbow, C., Ehammer, A., Demarty, J., and Ardö, J.: Spatiotemporal variability in carbon exchange fluxes across the Sahel, Agr. Forest Meteorol., 226–227, 108–118, https://doi.org/10.1016/j.agrformet.2016.05.013, 2016.
Taha, H., Akbari, H., and Rosenfeld, A.: Heat island and oasis effects of vegetative canopies, Theor. Appl. Climatol., 44, 123–138, https://doi.org/10.1007/BF00867999, 1991.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R., Meyers, T. P., Prueger, J. H., Starks, P. J., and Wesely, M. L.: Correcting eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol., 103, 279–300, https://doi.org/10.1016/S0168-1923(00)00123-4, 2000.
Wang, G. X. and Cheng, G. D.: Water resource development and its influence on the environment in arid areas of China-the case of the Hei River basin, J. Arid Environ., 43, 121–131, https://doi.org/10.1006/jare.1999.0563, 1999.
Wang, H. B., Li, X., Xiao, J. F., Ma, M. G., Tan, J. L., Wang, X. F., and Geng, L. Y.: Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability, Sci. Total Environ., 697, 133978, https://doi.org/10.1016/j.scitotenv.2019.133978, 2019.
Wang, J. M. and Mitsuta, Y.: Evaporation from the desert: some preliminary results of HEIFE, Bound.-Lay. Meteorol., 59, 413–418, https://doi.org/10.1007/BF02215461, 1992.
Wen, X., Lv, S., and Jin, J.: Integrating remote sensing data with WRF for improved simulations of oasis effects on local weather processes over an arid region in northwestern China, J. Hydrometeorol., 13, 573–587, https://doi.org/10.1175/JHM-D-10-05001.1, 2012.
Wu, D. X., Liu, S. M., Wu, X. C., Xu, T. R., Xu, Z. W., He, X. L., and Shi, H. Y.: Evaluation of the intrinsic temperature sensitivity of ecosystem respiration in typical ecosystems of an endorheic river basin, Agr. Forest Meteorol., 333, 109393, https://doi.org/10.1016/j.agrformet.2023.109393, 2023.
Xu, Z. W., Liu, S. M., Li, X., Shi, S. J., Wang, J. M., Zhu, Z. L., Xu, T. R., Wang, W. Z., and Ma, M. G.: Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE, J. Geophys. Res.-Atmos., 118, 13140–13157, https://doi.org/10.1002/2013JD020260, 2013.
Xu, Z. W., Ma, Y. F., Liu, S. M., Shi, W. J., and Wang, J. M.: Assessment of the energy balance closure under advective conditions and its impact using remote sensing data, J. Appl. Meteorol. Clim., 56, 127–140, https://doi.org/10.1175/JAMC-D-16-0096.1, 2017.
Xu, Z. W., Liu, S. M., Zhu, Z. L., Zhou, J., Shi, W. J., Xu, T. R., Yang, X. F., Zhang, Y., and He, X. L.: Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network, Agr. Forest Meteorol., 290, 108010, https://doi.org/10.1016/j.agrformet.2020.108010, 2020.
Xue, J., Gui, D., Lei, J., Sun, H., Zeng, F., Mao, D., Zhang, Z., Jin, Q., and Liu, Y.: Oasis microclimate effects under different weather events in arid or hyper arid regions: A case analysis in southern Taklimakan desert and implication for maintaining oasis sustainability, Theor. Appl. Climatol., 137, 89–101, https://doi.org/10.1007/s00704-018-2567-5, 2019.
Zhang, Q., Sun, R., Jiang, G. Q., Xu, Z. W., and Liu, S. M.: Carbon and energy flux from a Phragmites australis wetland in Zhangye oasis-desert area, China, Agr. Forest Meteorol., 230–231, 45–57, https://doi.org/10.1016/j.agrformet.2016.02.019, 2016.
Zhang, Y. Y. and Zhao, W. Z.: Vegetation and soil property response of short-timefencing in temperate desert of the Hexi Corridor northwestern China, Catena, 133, 43–51, https://doi.org/10.1016/j.catena.2015.04.019, 2015.
Zhang, X. Y., Arimoto, R., Zhu, G. H., Chen, T., and Zhang, G. Y.: Concentration, size-distribution and deposition of mineral aerosol over Chinese desert regions, Tellus B, 50, 317–330, https://doi.org/10.3402/tellusb.v50i4.16131, 2016.
Zhang, Y., Zhao, W., He, J., and Fu, L.: Soil susceptibility to macropore flow across a desert-oasis ecotone of the Hexi Corridor, Northwest China, Water Resour. Res., 54, 1281–1294, https://doi.org/10.1002/2017WR021462, 2018.
Zhang, Y., Liu, S. M., Song, L. S., Li, X., Jia, Z. Z., Xu, T. R., Xu, Z. W., Ma, Y. F., Zhou, J., Yang, X. F., He, X. L., Yao, Y. J., and Hu, G. C.: Integrated Validation of Coarse Remotely Sensed Evapotranspiration Products over Heterogeneous Land Surfaces, Remote Sens., 14, 3467, https://doi.org/10.3390/rs14143467, 2022.
Zhang, Z., Poulter, B., Knox, S., Stavert, A., McNicol, G., Fluet-Chouinard, E., Feinberg, A., Zhao, Y., Bousquet, P., Canadell, J., Ganesan, A., Hugelius, G., Jackson, R., Patra, P., Saunois, M., Höglund-Isaksson, L., Huang, C., Chatterjee, A., and Li, X.: Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993–2017, Natl. Sci. Rev., 9, nwab200, https://doi.org/10.1093/nsr/nwab200, 2022.
Zhao, R., Chen, Y., Shi, P., Zhang, L., Pan, J., and Zhao, H.: Land use and land cover change and driving mechanism in the arid inland river basin: a case study of Tarim River, Xinjiang, China, Environ. Earth Sci., 68, 591–604, https://doi.org/10.1007/s12665-012-1763-3, 2013.
Zheng, C., Liu, S. M., Song, L. S., Xu, Z. W., Guo, J. X., Ma, Y. F., Ju, Q., and Wang, J. M.: Comparison of sensible and latent heat fluxes from optical-microwave scintillometers and eddy covariance systems with respect to surface energy balance closure, Agr. Forest Meteorol., 331, 109345, https://doi.org/10.1016/j.agrformet.2023.109345, 2023.
Zhou, Y. and Li, X.: Energy balance closures in diverse ecosystems of an endorheic river basin, Agr. Forest Meteorol., 274, 118–131, https://doi.org/10.1016/j.agrformet.2019.04.019, 2018.
Zhou, Y., Liao, W., and Li, X.: The contributions of individual factors to the oasis cold island effect intensity in the Heihe River Basin, Agr. Forest Meteorol., 312, 108706, https://doi.org/10.1016/j.agrformet.2021.108706, 2022.
Short summary
We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
We present a suite of observational datasets from artificial and natural oases–desert systems...
Altmetrics
Final-revised paper
Preprint