Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2937-2020
© Author(s) 2020. 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-12-2937-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
18 Nov 2020
Data description paper |
| 18 Nov 2020
| 18 Nov 2020
A long-term (2005–2016) dataset of hourly integrated land–atmosphere interaction observations on the Tibetan Plateau
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100101, China
University of Chinese Academy of Sciences, Beijing, 100049, China
Zeyong Hu
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100101, China
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Weiqiang Ma
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100101, China
Binbin Wang
CORRESPONDING AUTHOR
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Xuelong Chen
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Maoshan Li
School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610025, China
Lei Zhong
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China
CAS Center for Excellence in Comparative Planetology, USTC, Hefei, 230026, China
Fanglin Sun
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
Lianglei Gu
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
Cunbo Han
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Lang Zhang
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Xin Liu
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Zhangwei Ding
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Genhou Sun
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, 510275, China
Shujin Wang
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
Yongjie Wang
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
Zhongyan Wang
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
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X. Chen, Z. Su, Y. Ma, S. Liu, Q. Yu, and Z. Xu
Atmos. Chem. Phys., 14, 13097–13117, https://doi.org/10.5194/acp-14-13097-2014, https://doi.org/10.5194/acp-14-13097-2014, 2014
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R. van der Velde, M. S. Salama, T. Pellarin, M. Ofwono, Y. Ma, and Z. Su
Hydrol. Earth Syst. Sci., 18, 1323–1337, https://doi.org/10.5194/hess-18-1323-2014, https://doi.org/10.5194/hess-18-1323-2014, 2014
C. Xu, Y. M. Ma, A. Panday, Z. Y. Cong, K. Yang, Z. K. Zhu, J. M. Wang, P. M. Amatya, and L. Zhao
Atmos. Chem. Phys., 14, 3133–3149, https://doi.org/10.5194/acp-14-3133-2014, https://doi.org/10.5194/acp-14-3133-2014, 2014
Y. Ma, Z. Zhu, L. Zhong, B. Wang, C. Han, Z. Wang, Y. Wang, L. Lu, P. M. Amatya, W. Ma, and Z. Hu
Atmos. Chem. Phys., 14, 1507–1515, https://doi.org/10.5194/acp-14-1507-2014, https://doi.org/10.5194/acp-14-1507-2014, 2014
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Short summary
Short summary
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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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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.
Cunbo Han, Corinna Hoose, Martin Stengel, Quentin Coopman, and Andrew Barrett
Atmos. Chem. Phys., 23, 14077–14095, https://doi.org/10.5194/acp-23-14077-2023, https://doi.org/10.5194/acp-23-14077-2023, 2023
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Cloud phase has been found to significantly impact cloud thermodynamics and Earth’s radiation budget, and various factors influence it. This study investigates the sensitivity of the cloud-phase distribution to the ice-nucleating particle concentration and thermodynamics. Multiple simulation experiments were performed using the ICON model at the convection-permitting resolution of 1.2 km. Simulation results were compared to two different retrieval products based on SEVIRI measurements.
Chuanxi Zhao, Wei Yang, Evan Miles, Matthew Westoby, Marin Kneib, Yongjie Wang, Zhen He, and Francesca Pellicciotti
The Cryosphere, 17, 3895–3913, https://doi.org/10.5194/tc-17-3895-2023, https://doi.org/10.5194/tc-17-3895-2023, 2023
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This paper quantifies the thinning and surface mass balance of two neighbouring debris-covered glaciers in the southeastern Tibetan Plateau during different seasons, based on high spatio-temporal resolution UAV-derived (unpiloted aerial
vehicle) data and in situ observations. Through a comparison approach and high-precision results, we identify that the glacier dynamic and debris thickness are strongly related to the future fate of the debris-covered glaciers in this region.
Wei Yang, Zhongyan Wang, Baosheng An, Yingying Chen, Chuanxi Zhao, Chenhui Li, Yongjie Wang, Weicai Wang, Jiule Li, Guangjian Wu, Lin Bai, Fan Zhang, and Tandong Yao
Nat. Hazards Earth Syst. Sci., 23, 3015–3029, https://doi.org/10.5194/nhess-23-3015-2023, https://doi.org/10.5194/nhess-23-3015-2023, 2023
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We present the structure and performance of the early warning system (EWS) for glacier collapse and river blockages in the southeastern Tibetan Plateau. The EWS warned of three collapse–river blockage chain events and seven small-scale events. The volume and location of the collapses and the percentage of ice content influenced the velocities of debris flows. Such a study is helpful for understanding the mechanism of glacier hazards and for establishing similar EWSs in other high-risk regions.
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.
Wei Yang, Huabiao Zhao, Baiqing Xu, Jiule Li, Weicai Wang, Guangjian Wu, Zhongyan Wang, and Tandong Yao
The Cryosphere, 17, 2625–2628, https://doi.org/10.5194/tc-17-2625-2023, https://doi.org/10.5194/tc-17-2625-2023, 2023
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There is very strong scientific and public interest regarding the snow thickness on Mountain Everest. Previously reported snow depths derived by different methods and instruments ranged from 0.92 to 3.5 m. Our measurements in 2022 provide the first clear radar image of the snowpack at the top of Mount Everest. The snow thickness at Earth's summit was averaged to be 9.5 ± 1.2 m. This updated snow thickness is considerably deeper than values reported during the past 5 decades.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yaoming Ma, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 14, 5513–5542, https://doi.org/10.5194/essd-14-5513-2022, https://doi.org/10.5194/essd-14-5513-2022, 2022
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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.
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.
Chuanxi Zhao, Wei Yang, Matthew Westoby, Baosheng An, Guangjian Wu, Weicai Wang, Zhongyan Wang, Yongjie Wang, and Stuart Dunning
The Cryosphere, 16, 1333–1340, https://doi.org/10.5194/tc-16-1333-2022, https://doi.org/10.5194/tc-16-1333-2022, 2022
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On 22 March 2021, a ~ 50 Mm 3 ice-rock avalanche occurred from 6500 m a.s.l. in the Sedongpu basin, southeastern Tibet. It caused temporary blockage of the Yarlung Tsangpo river, a major tributary of the Brahmaputra. We utilize field investigations, high-resolution satellite imagery, seismic records, and meteorological data to analyse the evolution of the 2021 event and its impact, discuss potential drivers, and briefly reflect on implications for the sustainable development of the region.
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.
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.
Cunbo Han, Yaoming Ma, Binbin Wang, Lei Zhong, Weiqiang Ma, Xuelong Chen, and Zhongbo Su
Earth Syst. Sci. Data, 13, 3513–3524, https://doi.org/10.5194/essd-13-3513-2021, https://doi.org/10.5194/essd-13-3513-2021, 2021
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Actual terrestrial evapotranspiration (ETa) is a key parameter controlling the land–atmosphere interaction processes and water cycle. However, the spatial distribution and temporal changes in ETa over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ETa and its spatial distribution on the TP by a combination of meteorological data and satellite products. Results have been validated at six eddy-covariance monitoring sites and show high accuracy.
Zhipeng Xie, Weiqiang Ma, Yaoming Ma, Zeyong Hu, Genhou Sun, Yizhe Han, Wei Hu, Rongmingzhu Su, and Yixi Fan
Hydrol. Earth Syst. Sci., 25, 3783–3804, https://doi.org/10.5194/hess-25-3783-2021, https://doi.org/10.5194/hess-25-3783-2021, 2021
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Ground information on the occurrence of blowing snow has been sorely lacking because direct observations of blowing snow are sparse in time and space. In this paper, we investigated the potential capability of the decision tree model to detect blowing snow events in the European Alps. Trained with routine meteorological observations, the decision tree model can be used as an efficient tool to detect blowing snow occurrences across different regions requiring limited meteorological variables.
Yanbin Lei, Tandong Yao, Kun Yang, Lazhu, Yaoming Ma, and Broxton W. Bird
Hydrol. Earth Syst. Sci., 25, 3163–3177, https://doi.org/10.5194/hess-25-3163-2021, https://doi.org/10.5194/hess-25-3163-2021, 2021
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Lake evaporation from Paiku Co on the TP is low in spring and summer and high in autumn and early winter. There is a ~ 5-month lag between net radiation and evaporation due to large lake heat storage. High evaporation and low inflow cause significant lake-level decrease in autumn and early winter, while low evaporation and high inflow cause considerable lake-level increase in summer. This study implies that evaporation can affect the different amplitudes of lake-level variations on the TP.
Maoshan Li, Xiaoran Liu, Lei Shu, Shucheng Yin, Lingzhi Wang, Wei Fu, Yaoming Ma, Yaoxian Yang, and Fanglin Sun
Hydrol. Earth Syst. Sci., 25, 2915–2930, https://doi.org/10.5194/hess-25-2915-2021, https://doi.org/10.5194/hess-25-2915-2021, 2021
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In this study, using MODIS satellite data and site atmospheric turbulence observation data in the Nagqu area of the northern Tibetan Plateau, with the Massman-retrieved model and a single height observation to determine aerodynamic surface roughness, temporal and spatial variation characteristics of the surface roughness were analyzed. The result is feasible, and it can be applied to improve the model parameters of the land surface model and the accuracy of model simulation in future work.
Ziyu Huang, Lei Zhong, Yaoming Ma, and Yunfei Fu
Geosci. Model Dev., 14, 2827–2841, https://doi.org/10.5194/gmd-14-2827-2021, https://doi.org/10.5194/gmd-14-2827-2021, 2021
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Spectral nudging is an effective dynamical downscaling method used to improve precipitation simulations of regional climate models (RCMs). However, the biases of the driving fields over the Tibetan Plateau (TP) would possibly introduce extra biases when spectral nudging is applied. The results show that the precipitation simulations were significantly improved when limiting the application of spectral nudging toward the potential temperature and water vapor mixing ratio over the TP.
María P. González-Dugo, Xuelong Chen, Ana Andreu, Elisabet Carpintero, Pedro J. Gómez-Giraldez, Arnaud Carrara, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 755–768, https://doi.org/10.5194/hess-25-755-2021, https://doi.org/10.5194/hess-25-755-2021, 2021
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Drought is a devastating natural hazard and difficult to define, detect and quantify. Global meteorological data and remote-sensing products present new opportunities to characterize drought in an objective way. In this paper, we applied the surface energy balance model SEBS to estimate monthly evapotranspiration (ET) from 2001 to 2018 over the dehesa area of the Iberian Peninsula. ET anomalies were used to identify the main drought events and analyze their impacts on dehesa vegetation.
Genhou Sun, Zeyong Hu, Yaoming Ma, Zhipeng Xie, Jiemin Wang, and Song Yang
Hydrol. Earth Syst. Sci., 24, 5937–5951, https://doi.org/10.5194/hess-24-5937-2020, https://doi.org/10.5194/hess-24-5937-2020, 2020
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We investigate the influence of soil conditions on the planetary boundary layer (PBL) thermodynamics and convective cloud formations over a typical underlying surface, based on a series of simulations on a sunny day in the Tibetan Plateau, using the Weather Research and Forecasting (WRF) model. The real-case simulation and sensitivity simulations indicate that the soil moisture could have a strong impact on PBL thermodynamics, which may be favorable for the convective cloud formations.
Felix Nieberding, Christian Wille, Gerardo Fratini, Magnus O. Asmussen, Yuyang Wang, Yaoming Ma, and Torsten Sachs
Earth Syst. Sci. Data, 12, 2705–2724, https://doi.org/10.5194/essd-12-2705-2020, https://doi.org/10.5194/essd-12-2705-2020, 2020
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We present the first long-term eddy covariance CO2 and H2O flux measurements from the large but underrepresented alpine steppe ecosystem on the central Tibetan Plateau. We applied careful corrections and rigorous quality filtering and analyzed the turbulent flow regime to provide meaningful fluxes. This comprehensive data set allows potential users to put the gas flux dynamics into context with ecosystem properties and potential flux drivers and allows for comparisons with other data sets.
Meixin Zhang, Chun Zhao, Zhiyuan Cong, Qiuyan Du, Mingyue Xu, Yu Chen, Ming Chen, Rui Li, Yunfei Fu, Lei Zhong, Shichang Kang, Delong Zhao, and Yan Yang
Atmos. Chem. Phys., 20, 5923–5943, https://doi.org/10.5194/acp-20-5923-2020, https://doi.org/10.5194/acp-20-5923-2020, 2020
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Analysis of multiple numerical experiments over the Himalayas and Tibetan Plateau (TP) shows that the complex topography results in 50 % stronger overall cross-Himalayan transport during the pre-monsoon season primarily due to the strengthened efficiency of near-surface meridional transport towards the TP, enhanced wind speed in some valleys and deeper valley channels associated with larger transported BC mass volume, which leads to 30–50 % stronger BC radiative heating over the TP.
Yanbin Lei, Tandong Yao, Kun Yang, Zhu La, Yaoming Ma, and Broxton W. Bird
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-421, https://doi.org/10.5194/hess-2019-421, 2019
Revised manuscript not accepted
X. Chen, Z. Su, and Y. Ma
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1729–1733, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1729-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1729-2019, 2019
Lei Zhong, Yaoming Ma, Zeyong Hu, Yunfei Fu, Yuanyuan Hu, Xian Wang, Meilin Cheng, and Nan Ge
Atmos. Chem. Phys., 19, 5529–5541, https://doi.org/10.5194/acp-19-5529-2019, https://doi.org/10.5194/acp-19-5529-2019, 2019
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Fine-temporal-resolution turbulent heat fluxes at the plateau scale have significant importance for studying diurnal variation characteristics of atmospheric boundary and weather systems in the Tibetan Plateau (TP) and its surroundings. Time series of land surface heat fluxes with high temporal resolution over the entire TP were derived. The derived surface heat fluxes proved to be in good agreement with in situ measurements and were superior to GLDAS flux products.
Xintong Chen, Shichang Kang, Zhiyuan Cong, Junhua Yang, and Yaoming Ma
Atmos. Chem. Phys., 18, 12859–12875, https://doi.org/10.5194/acp-18-12859-2018, https://doi.org/10.5194/acp-18-12859-2018, 2018
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To understand the impact of transboundary atmospheric black carbon on the Mt. Everest region and depict the transport pathways in different spatiotemporal scales, we first investigated the concentration level, temporal variation, and sources of black carbon based on high-resolution (2-year) measurements at Qomolangma (Mt. Everest) Station (4276 m a.s.l.). Next, the WRF-Chem simulations were used to reveal the transport mechanisms of black carbon from southern Asia to the Mt. Everest region.
Xiufeng Yin, Shichang Kang, Benjamin de Foy, Yaoming Ma, Yindong Tong, Wei Zhang, Xuejun Wang, Guoshuai Zhang, and Qianggong Zhang
Atmos. Chem. Phys., 18, 10557–10574, https://doi.org/10.5194/acp-18-10557-2018, https://doi.org/10.5194/acp-18-10557-2018, 2018
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Total gaseous mercury concentrations were measured at Nam Co Station on the inland Tibetan Plateau for ~ 3 years. The mean concentration of TGM during the entire monitoring period was 1.33 ± 0.24 ngm-3, ranking it the lowest in China and indicating the pristine atmospheric environment of the inland Tibetan Plateau. Variation of TGM at Nam Co was affected by regional surface reemission, vertical mixing and long-range transported atmospheric mercury, which was associated with the Indian monsoon.
Xiufeng Yin, Shichang Kang, Benjamin de Foy, Zhiyuan Cong, Jiali Luo, Lang Zhang, Yaoming Ma, Guoshuai Zhang, Dipesh Rupakheti, and Qianggong Zhang
Atmos. Chem. Phys., 17, 11293–11311, https://doi.org/10.5194/acp-17-11293-2017, https://doi.org/10.5194/acp-17-11293-2017, 2017
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We presented 5-year surface ozone measurements at Nam Co in the inland Tibetan Plateau and made a synthesis comparison of diurnal and seasonal patterns on regional and hemispheric scales. Surface ozone at Nam Co is mainly dominated by natural processes and is less influenced by stratospheric intrusions and human activities than on the rim of the Tibetan Plateau. Ozone at Nam Co is representative of background that is valuable for studying ozone-related effects on large scales.
Bin Liu, Zhiyuan Cong, Yuesi Wang, Jinyuan Xin, Xin Wan, Yuepeng Pan, Zirui Liu, Yonghong Wang, Guoshuai Zhang, Zhongyan Wang, Yongjie Wang, and Shichang Kang
Atmos. Chem. Phys., 17, 449–463, https://doi.org/10.5194/acp-17-449-2017, https://doi.org/10.5194/acp-17-449-2017, 2017
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The first observation net of background atmospheric aerosols of the Himalayas and Tibetan Plateau were conducted in 2011–2013, and the aerosol mass loadings were especially illustrated in this paper. Consequently, these terrestrial aerosol masses were strongly ecosystem-dependent, with various seasonality and diurnal cycles at these sites. These findings implicate that regional characteristics and fine-particle emissions need to be treated sensitively when assessing their climatic effects.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
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The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
C. Xu, Y. M. Ma, C. You, and Z. K. Zhu
Atmos. Chem. Phys., 15, 12065–12078, https://doi.org/10.5194/acp-15-12065-2015, https://doi.org/10.5194/acp-15-12065-2015, 2015
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Different monthly variation patterns of aerosol optical depth are observed over the southern and northern Tibetan Plateau (TP). A dividing line of higher dust occurrence in the northern TP and lower dust occurrence in the southern TP can be observed clearly at an altitude of 6-8km. The different seasonal variation patterns between the northern and southern TP are due to many factors, including the emission sources, high-altitude terrain and atmospheric circulation.
T. Gerken, W. Babel, M. Herzog, K. Fuchs, F. Sun, Y. Ma, T. Foken, and H.-F. Graf
Hydrol. Earth Syst. Sci., 19, 4023–4040, https://doi.org/10.5194/hess-19-4023-2015, https://doi.org/10.5194/hess-19-4023-2015, 2015
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Surface moisture is an important control for the development of clouds and precipitation on the Tibetan Plateau. While dry surface conditions do not provided enough water for the development of precipitation and convection, wet surface conditions lead to increased cloud cover and a decrease in solar irradiation, which also reduces convection development. It was found that intermediate soil moistures are associated with the strongest convection.
W. Yu, L. Tian, Y. Ma, B. Xu, and D. Qu
Atmos. Chem. Phys., 15, 10251–10262, https://doi.org/10.5194/acp-15-10251-2015, https://doi.org/10.5194/acp-15-10251-2015, 2015
F. Salerno, N. Guyennon, S. Thakuri, G. Viviano, E. Romano, E. Vuillermoz, P. Cristofanelli, P. Stocchi, G. Agrillo, Y. Ma, and G. Tartari
The Cryosphere, 9, 1229–1247, https://doi.org/10.5194/tc-9-1229-2015, https://doi.org/10.5194/tc-9-1229-2015, 2015
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Climate-trends data in Himalaya are completely absent at high elevation. We explore the south slopes of Mt Everest though time series reconstructed from 7 stations (2660-5600m) during 1994-2013. The main increase in temp is concentrated outside of the monsoon, minimum temp increased far more than maximum, while we note a precipitation weakening. We contribute to change the perspective on which climatic drivers (temperature vs. precipitation) led mainly the glacier responses in the last 20 yr.
X. Chen, Z. Su, Y. Ma, S. Liu, Q. Yu, and Z. Xu
Atmos. Chem. Phys., 14, 13097–13117, https://doi.org/10.5194/acp-14-13097-2014, https://doi.org/10.5194/acp-14-13097-2014, 2014
W. Babel, T. Biermann, H. Coners, E. Falge, E. Seeber, J. Ingrisch, P.-M. Schleuß, T. Gerken, J. Leonbacher, T. Leipold, S. Willinghöfer, K. Schützenmeister, O. Shibistova, L. Becker, S. Hafner, S. Spielvogel, X. Li, X. Xu, Y. Sun, L. Zhang, Y. Yang, Y. Ma, K. Wesche, H.-F. Graf, C. Leuschner, G. Guggenberger, Y. Kuzyakov, G. Miehe, and T. Foken
Biogeosciences, 11, 6633–6656, https://doi.org/10.5194/bg-11-6633-2014, https://doi.org/10.5194/bg-11-6633-2014, 2014
R. van der Velde, M. S. Salama, T. Pellarin, M. Ofwono, Y. Ma, and Z. Su
Hydrol. Earth Syst. Sci., 18, 1323–1337, https://doi.org/10.5194/hess-18-1323-2014, https://doi.org/10.5194/hess-18-1323-2014, 2014
C. Xu, Y. M. Ma, A. Panday, Z. Y. Cong, K. Yang, Z. K. Zhu, J. M. Wang, P. M. Amatya, and L. Zhao
Atmos. Chem. Phys., 14, 3133–3149, https://doi.org/10.5194/acp-14-3133-2014, https://doi.org/10.5194/acp-14-3133-2014, 2014
Y. Ma, Z. Zhu, L. Zhong, B. Wang, C. Han, Z. Wang, Y. Wang, L. Lu, P. M. Amatya, W. Ma, and Z. Hu
Atmos. Chem. Phys., 14, 1507–1515, https://doi.org/10.5194/acp-14-1507-2014, https://doi.org/10.5194/acp-14-1507-2014, 2014
M. Li, W. Babel, K. Tanaka, and T. Foken
Atmos. Meas. Tech., 6, 221–229, https://doi.org/10.5194/amt-6-221-2013, https://doi.org/10.5194/amt-6-221-2013, 2013
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Pantelis Georgiades, Theo Economou, Yiannis Proestos, Jose Araya, Jos Lelieveld, and Marco Neira
Earth Syst. Sci. Data, 17, 1153–1171, https://doi.org/10.5194/essd-17-1153-2025, https://doi.org/10.5194/essd-17-1153-2025, 2025
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Climate change is posing increasing challenges in the dairy cattle farming sector, as heat stress adversely affects the animals' health and milk production. To accurately assess these impacts, we developed a machine learning model to downscale daily climate data to hourly Temperature Humidity Index (THI) values. We utilized historical weather data to train our model and applied them to future climate projections, under two climate scenarios.
Qi Zhang, Chiyuan Miao, Jiajia Su, Jiaojiao Gou, Jinlong Hu, Xi Zhao, and Ye Xu
Earth Syst. Sci. Data, 17, 837–853, https://doi.org/10.5194/essd-17-837-2025, https://doi.org/10.5194/essd-17-837-2025, 2025
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Our study introduces CHM_Drought, an advanced meteorological drought dataset covering mainland China, offering detailed insights from 1961 to 2022 at a spatial resolution of 0.1°. This dataset incorporates six key drought indices, including multi-scale versions, facilitating early detection and monitoring of droughts. Through the provision of consistent and reliable data, CHM_Drought enhances our understanding of drought patterns, aiding in effective water management and agricultural planning.
Zhiqi Xu, Jianping Guo, Guwei Zhang, Yuchen Ye, Haikun Zhao, and Haishan Chen
Earth Syst. Sci. Data, 16, 5753–5766, https://doi.org/10.5194/essd-16-5753-2024, https://doi.org/10.5194/essd-16-5753-2024, 2024
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Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we generate a global long-term TC size and intensity reconstruction dataset, covering a time period from 1959 to 2022, with a 3 h temporal resolution, using machine learning models. These can be valuable for filling observational data gaps and advancing our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.
Matilde García-Valdecasas Ojeda, Feliciano Solano-Farias, David Donaire-Montaño, Emilio Romero-Jiménez, Juan José Rosa-Cánovas, Yolanda Castro-Díez, Sonia Raquel Gámiz-Fortis, and María Jesús Esteban-Parra
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-522, https://doi.org/10.5194/essd-2024-522, 2024
Revised manuscript accepted for ESSD
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This work aims to present a series of climate datasets for Sierra Nevada, a region especially vulnerable to climate change in Southern Spain. The database consists of primary climate variables such as precipitation, temperature, radiation, wind speed, pressure, and atmospheric humidity, but also bioclimatic variables and extreme indices, both useful information for assessing the impact of climate change in this region. These datasets are only available on https://doi.org/10.5281/zenodo.14364865
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
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This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant
Earth Syst. Sci. Data, 16, 5579–5602, https://doi.org/10.5194/essd-16-5579-2024, https://doi.org/10.5194/essd-16-5579-2024, 2024
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We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
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The energy reaching Earth's surface from the Sun is a quantity of great importance for the climate system and for many applications. SARAH-3 is a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 covers more than 4 decades and provides a high spatial and temporal resolution, and its validation shows good accuracy and stability.
Yanyi He, Kaicun Wang, Kun Yang, Chunlüe Zhou, Changkun Shao, and Changjian Yin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-493, https://doi.org/10.5194/essd-2024-493, 2024
Revised manuscript accepted for ESSD
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To address key gaps in data availability and homogeneity of sunshine duration, we compiled raw data and made a homogenization protocol to produce a homogenized daily observational dataset of sunshine duration from 1961 to 2022 in China. The dataset avoids a sharp drop in zero-value frequency after 2019, caused by the instrument upgrade, but also is more continuous for various periods. This dataset is crucial for accurately assessing the dimming and brightening, and supporting other applications.
Xinyan Liu, Tao He, Qingxin Wang, Xiongxin Xiao, Yichuan Ma, Yanyan Wang, Shanjun Luo, Lei Du, and Zhaocong Wu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-458, https://doi.org/10.5194/essd-2024-458, 2024
Revised manuscript accepted for ESSD
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This study addresses the challenge of how clouds affect the Earth's energy balance, which is vital for understanding climate change. We developed a new method to create long-term cloud radiative kernels to improve the accuracy of sunlight reaching the surface, which significantly reduces errors. Findings suggest that prior estimates of cloud cooling effects may have been overstated, emphasizing the need for better strategies to manage climate change impacts in the Arctic.
Susana Barbosa, Nuno Dias, Carlos Almeida, Guilherme Amaral, António Ferreira, António Camilo, and Eduardo Silva
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-245, https://doi.org/10.5194/essd-2024-245, 2024
Revised manuscript accepted for ESSD
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The electric field present in the Earth's atmosphere reflects global planetary conditions. It is influenced by both atmospheric processes (thunderstorms, pollution, aerosols) and space weather. Marine measurements of the electric field are rare. Here, a unique dataset of atmospheric electric field measurements performed over the Atlantic Ocean is presented. This dataset is relevant not only for atmospheric electricity studies but also for climate and space-Earth interaction studies.
Thomas Fiolleau and Rémy Roca
Earth Syst. Sci. Data, 16, 4021–4050, https://doi.org/10.5194/essd-16-4021-2024, https://doi.org/10.5194/essd-16-4021-2024, 2024
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This paper presents a database of tropical deep convective systems over the 2012–2020 period, built from a cloud-tracking algorithm called TOOCAN, which has been applied to homogenized infrared observations from a fleet of geostationary satellites. This database aims to analyze the tropical deep convective systems, the evolution of their associated characteristics over their life cycle, their organization, and their importance in the hydrological and energy cycle.
Bing Li, Shunlin Liang, Han Ma, Guanpeng Dong, Xiaobang Liu, Tao He, and Yufang Zhang
Earth Syst. Sci. Data, 16, 3795–3819, https://doi.org/10.5194/essd-16-3795-2024, https://doi.org/10.5194/essd-16-3795-2024, 2024
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This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
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During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
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.
Zijiang Song, Zhixiang Cheng, Yuying Li, Shanshan Yu, Xiaowen Zhang, Lina Yuan, and Min Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-137, https://doi.org/10.5194/essd-2024-137, 2024
Revised manuscript accepted for ESSD
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It is hard to access long-time series and high-resolution meteorological data for historical years. In this paper, we proposed a geopotential-guide attention network (GeoAN) for downscaling, which can produce high-resolution data from the given low-resolution data. Quantitative and visual comparisons reveal our GeoAN producing better results in most metrics. Using GeoAN, historical meteorological data called MDG625 has been produced daily since 1940.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Francesca Lappin, Gijs de Boer, Petra Klein, Jonathan Hamilton, Michelle Spencer, Radiance Calmer, Antonio R. Segales, Michael Rhodes, Tyler M. Bell, Justin Buchli, Kelsey Britt, Elizabeth Asher, Isaac Medina, Brian Butterworth, Leia Otterstatter, Madison Ritsch, Bryony Puxley, Angelina Miller, Arianna Jordan, Ceu Gomez-Faulk, Elizabeth Smith, Steven Borenstein, Troy Thornberry, Brian Argrow, and Elizabeth Pillar-Little
Earth Syst. Sci. Data, 16, 2525–2541, https://doi.org/10.5194/essd-16-2525-2024, https://doi.org/10.5194/essd-16-2525-2024, 2024
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This article provides an overview of the lower-atmospheric dataset collected by two uncrewed aerial systems near the Gulf of Mexico coastline south of Houston, TX, USA, as part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. The data were collected through boundary layer transitions, through sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu
Earth Syst. Sci. Data, 16, 2407–2424, https://doi.org/10.5194/essd-16-2407-2024, https://doi.org/10.5194/essd-16-2407-2024, 2024
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We produced a monthly Universal Thermal Climate Index dataset (GloUTCI-M) boasting global coverage and an extensive time series spanning March 2000 to October 2022 with a high spatial resolution of 1 km. This dataset is the product of a comprehensive approach leveraging multiple data sources and advanced machine learning models. GloUTCI-M can enhance our capacity to evaluate thermal stress experienced by the human, offering substantial prospects across a wide array of applications.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
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A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Christopher J. Cox, Janet M. Intrieri, Brian Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-158, https://doi.org/10.5194/essd-2024-158, 2024
Revised manuscript accepted for ESSD
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Snow is an essential water resource in the intermountain western United States and predictions are made using models. We made observations to validate, constrain, and develop the models. The data is from the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in Colorado’s East River Valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
Nele Reyniers, Qianyu Zha, Nans Addor, Timothy J. Osborn, Nicole Forstenhäusler, and Yi He
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-132, https://doi.org/10.5194/essd-2024-132, 2024
Revised manuscript accepted for ESSD
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We present two sets of bias-corrected UK Climate Projections 2018 (UKCP18) regional projections of temperature, precipitation and potential evapotranspiration for 1981–2080. All 12 members of the UKCP18 regional ensemble were bias-corrected using (1) empirical quantile mapping and (2) a change-preserving variant. The two methods were evaluated and compared to guide dataset application. The datasets improve the usability of UKCP18 and serve as a reference for selecting bias correction methods.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
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Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
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This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
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We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Leah Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer
Earth Syst. Sci. Data, 16, 1301–1316, https://doi.org/10.5194/essd-16-1301-2024, https://doi.org/10.5194/essd-16-1301-2024, 2024
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The vertical structure of clouds has a major impact on global energy flows, air circulation, and the hydrologic cycle. Two satellite instruments, CloudSat radar and CALIPSO lidar, have taken complementary measurements of cloud vertical structure for over a decade. Here, we present the 3S-GEOPROF-COMB product, a globally gridded satellite data product combining CloudSat and CALIPSO observations of cloud vertical structure.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
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We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
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This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
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.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
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The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Raghavendra Krishnamurthy, Gabriel García Medina, Brian Gaudet, William I. Gustafson Jr., Evgueni I. Kassianov, Jinliang Liu, Rob K. Newsom, Lindsay M. Sheridan, and Alicia M. Mahon
Earth Syst. Sci. Data, 15, 5667–5699, https://doi.org/10.5194/essd-15-5667-2023, https://doi.org/10.5194/essd-15-5667-2023, 2023
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Our understanding and ability to observe and model air–sea processes has been identified as a principal limitation to our ability to predict future weather. Few observations exist offshore along the coast of California. To improve our understanding of the air–sea transition zone and support the wind energy industry, two buoys with state-of-the-art equipment were deployed for 1 year. In this article, we present details of the post-processing, algorithms, and analyses.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
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The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
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We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
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Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
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CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
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We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
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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.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
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Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
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This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
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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.
Boyang Jiao, Yucheng Su, Qingxiang Li, Veronica Manara, and Martin Wild
Earth Syst. Sci. Data, 15, 4519–4535, https://doi.org/10.5194/essd-15-4519-2023, https://doi.org/10.5194/essd-15-4519-2023, 2023
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This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica) SSRIH station. This is interpolated into a 5° × 5° SSRIH grid and reconstructed into a long-term (1955–2018) global land (except for Antarctica) 5° × 2.5° SSR anomaly dataset (SSRIH20CR) by an improved partial convolutional neural network deep-learning method. SSRIH20CR yields trends of −1.276 W m−2 per decade over the dimming period and 0.697 W m−2 per decade over the brightening period.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
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The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
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Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Christian Borger, Steffen Beirle, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3023–3049, https://doi.org/10.5194/essd-15-3023-2023, https://doi.org/10.5194/essd-15-3023-2023, 2023
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This study presents a long-term data set of monthly mean total column water vapour (TCWV) based on measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. We describe how the TCWV values are retrieved from UV–Vis satellite spectra and demonstrate that the OMI TCWV data set is in good agreement with various different reference data sets. Moreover, we also show that it fulfills typical stability requirements for climate data records.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
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A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Santiago Beguería, Dhais Peña-Angulo, Víctor Trullenque-Blanco, and Carlos González-Hidalgo
Earth Syst. Sci. Data, 15, 2547–2575, https://doi.org/10.5194/essd-15-2547-2023, https://doi.org/10.5194/essd-15-2547-2023, 2023
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A gridded dataset on monthly precipitation over mainland Spain between spans 1916–2020. The dataset combines ground observations from the Spanish National Climate Data Bank and new data rescued from meteorological yearbooks published prior to 1951, which almost doubled the number of weather stations available during the first decades of the 20th century. Geostatistical techniques were used to interpolate a regular 10 x 10 km grid.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
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We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
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The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
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Short summary
In comparison with other terrestrial regions of the world, meteorological observations are scarce over the Tibetan Plateau.
This has limited our understanding of the mechanisms underlying complex interactions between the different earth spheres with heterogeneous land surface conditions.
The release of this continuous and long-term dataset with high temporal resolution is expected to facilitate broad multidisciplinary communities in understanding key processes on the
Third Pole of the world.
In comparison with other terrestrial regions of the world, meteorological observations are...
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