Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2635-2020
© 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-12-2635-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
31 Oct 2020
Data description article |
| 31 Oct 2020
| 31 Oct 2020
A dataset of microclimate and radiation and energy fluxes from the Lake Taihu eddy flux network
Zhen Zhang
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Mi Zhang
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
NUIST-Wuxi Research Institute, Wuxi, Jiangsu Province, China
Chang Cao
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Wei Xiao
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
NUIST-Wuxi Research Institute, Wuxi, Jiangsu Province, China
Chengyu Xie
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Haoran Chu
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Jiao Wang
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Jiayu Zhao
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Lei Jia
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Qiang Liu
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Wenjing Huang
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Wenqing Zhang
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Yang Lu
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Yanhong Xie
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Yi Wang
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Yini Pu
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Yongbo Hu
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Zheng Chen
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Zhihao Qin
Yale-NUIST Center on Atmospheric Environment, International Joint
Laboratory on Climate and Environment Change (ILCEC), Nanjing University of
Information Science and Technology, Nanjing, Jiangsu Province, China
Key Laboratory of Meteorological Disaster, Ministry of Education and
Collaborative Innovation Center on Forecast and Evaluation of Meteorological
Disasters, Nanjing University of Information Science and Technology,
Nanjing, Jiangsu Province, China
Xuhui Lee
CORRESPONDING AUTHOR
School of the Environment, Yale University, New Haven, CT 06511, USA
Viewed
Total article views: 3,988 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Jun 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,795 | 1,039 | 154 | 3,988 | 176 | 211 |
- HTML: 2,795
- PDF: 1,039
- XML: 154
- Total: 3,988
- BibTeX: 176
- EndNote: 211
Total article views: 3,447 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 31 Oct 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,536 | 785 | 126 | 3,447 | 137 | 173 |
- HTML: 2,536
- PDF: 785
- XML: 126
- Total: 3,447
- BibTeX: 137
- EndNote: 173
Total article views: 541 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Jun 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 259 | 254 | 28 | 541 | 39 | 38 |
- HTML: 259
- PDF: 254
- XML: 28
- Total: 541
- BibTeX: 39
- EndNote: 38
Viewed (geographical distribution)
Total article views: 3,988 (including HTML, PDF, and XML)
Thereof 3,652 with geography defined
and 336 with unknown origin.
Total article views: 3,447 (including HTML, PDF, and XML)
Thereof 3,165 with geography defined
and 282 with unknown origin.
Total article views: 541 (including HTML, PDF, and XML)
Thereof 487 with geography defined
and 54 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
26 citations as recorded by crossref.
- Can the atmospheric boundary layer-based potential evaporation model increase the accuracy of generalized complementary functions? W. Liu & B. Gao https://doi.org/10.2166/nh.2024.092
- 多时间尺度湖库二氧化碳通量环境驱动因子研究 相. 贺 et al. https://doi.org/10.1360/N072025-0320
- Dominant environmental influencing factors of carbon dioxide fluxes in lakes and reservoirs at different time scales X. He et al. https://doi.org/10.1007/s11430-025-1752-7
- Quantifying the difference between surface temperature and surface waterbulk temperature and its influencing factors at Lake Taihu with <i>in-situ</i> observation L. Yuzhu et al. https://doi.org/10.18307/2023.0543
- Effects of temporal and spatial variability in energy fluxes on phytoplankton J. Zhou et al. https://doi.org/10.1002/lno.70271
- Development of a 60-year high-resolution water body evaporation dataset in China P. Bai & X. Guo https://doi.org/10.1016/j.agrformet.2023.109428
- The Land Wet‐Bulb Temperature Increases Faster Than the Sea Surface Temperature H. Chu et al. https://doi.org/10.1029/2023GL106617
- Evaporative water loss of 1.42 million global lakes G. Zhao et al. https://doi.org/10.1038/s41467-022-31125-6
- Evaporation From Six Water Bodies of Various Sizes in East Asia: An Analysis on Size Dependency S. Han & F. Guo https://doi.org/10.1029/2022WR032650
- The Importance of Heat Storage for Estimating Lake Evaporation on Different Time Scales: Insights From a Large Shallow Subtropical Lake P. Bai & Y. Wang https://doi.org/10.1029/2023WR035123
- Long-term carbon dioxide dynamics variability at submerged macrophyte habitat of a subtropical shallow lake L. Hong et al. https://doi.org/10.1016/j.jhydrol.2025.133950
- Seasonal Characteristics of Air–Sea Exchanges over the South Coast of Matara, Sri Lanka X. Lu et al. https://doi.org/10.3390/jmse12111903
- 湖泊表层溶解氧对热浪的响应及其生态反馈调控机制 智. 欧阳 et al. https://doi.org/10.1360/N072025-0097
- Sensitivity of surface downward longwave radiation to aerosol optical depth over the Lake Taihu region, China C. Liu et al. https://doi.org/10.1016/j.atmosres.2024.107444
- Ecological feedbacks modulate lake surface oxygen responses to heatwaves Z. Ouyang et al. https://doi.org/10.1007/s11430-025-1840-6
- Aerosol interference with open-path eddy covariance measurement in a lake environment L. Jia et al. https://doi.org/10.1016/j.agrformet.2024.110104
- Coupling satellite imagery and numerical models to advance understanding and modelling of diel cyanobacterial blooms in shallow eutrophic lakes J. Li et al. https://doi.org/10.1016/j.watres.2025.124744
- Quantification of phytoplankton primary production from space: A revisit based on high-frequency observations with the aid of Himawari-8/AHI Z. Li et al. https://doi.org/10.1016/j.rse.2026.115238
- N2O emissions from a multi-habitat lake: Patterns and controls F. Yang et al. https://doi.org/10.1016/j.jhydrol.2025.133209
- Sigmoid Generalized Complementary Equation for Evaporation Over Wet Surfaces: A Nonlinear Modification of the Priestley‐Taylor Equation S. Han et al. https://doi.org/10.1029/2020WR028737
- Understanding the performance of three 1-D lake models in simulating thermal dynamics of diverse water bodies in the Yangtze River Basin O. Obulkasim et al. https://doi.org/10.1016/j.jhydrol.2025.133094
- Hybrid Lake Model (HyLake) v1.0: unifying deep learning and physical principles for simulating lake-atmosphere interactions Y. He & X. Yang https://doi.org/10.5194/gmd-18-9257-2025
- In Situ Observation of Near-Surface Wind Seasonal Variation on the Southern Coast of Sri Lanka X. Lu et al. https://doi.org/10.3390/jmse11091721
- Quantifying the contribution of evaporation from Lake Taihu to precipitation with an isotope-based method Y. Hu et al. https://doi.org/10.1080/10256016.2022.2056599
- A benchmark dataset of diurnal- and seasonal-scale radiation, heat, and CO2 fluxes in a typical East Asian monsoon region Z. Duan et al. https://doi.org/10.5194/essd-14-4153-2022
- Estimating the sensitivity of the Priestley–Taylor coefficient to air temperature and humidity Z. Liu et al. https://doi.org/10.5194/hess-28-4349-2024
26 citations as recorded by crossref.
- Can the atmospheric boundary layer-based potential evaporation model increase the accuracy of generalized complementary functions? W. Liu & B. Gao https://doi.org/10.2166/nh.2024.092
- 多时间尺度湖库二氧化碳通量环境驱动因子研究 相. 贺 et al. https://doi.org/10.1360/N072025-0320
- Dominant environmental influencing factors of carbon dioxide fluxes in lakes and reservoirs at different time scales X. He et al. https://doi.org/10.1007/s11430-025-1752-7
- Quantifying the difference between surface temperature and surface waterbulk temperature and its influencing factors at Lake Taihu with <i>in-situ</i> observation L. Yuzhu et al. https://doi.org/10.18307/2023.0543
- Effects of temporal and spatial variability in energy fluxes on phytoplankton J. Zhou et al. https://doi.org/10.1002/lno.70271
- Development of a 60-year high-resolution water body evaporation dataset in China P. Bai & X. Guo https://doi.org/10.1016/j.agrformet.2023.109428
- The Land Wet‐Bulb Temperature Increases Faster Than the Sea Surface Temperature H. Chu et al. https://doi.org/10.1029/2023GL106617
- Evaporative water loss of 1.42 million global lakes G. Zhao et al. https://doi.org/10.1038/s41467-022-31125-6
- Evaporation From Six Water Bodies of Various Sizes in East Asia: An Analysis on Size Dependency S. Han & F. Guo https://doi.org/10.1029/2022WR032650
- The Importance of Heat Storage for Estimating Lake Evaporation on Different Time Scales: Insights From a Large Shallow Subtropical Lake P. Bai & Y. Wang https://doi.org/10.1029/2023WR035123
- Long-term carbon dioxide dynamics variability at submerged macrophyte habitat of a subtropical shallow lake L. Hong et al. https://doi.org/10.1016/j.jhydrol.2025.133950
- Seasonal Characteristics of Air–Sea Exchanges over the South Coast of Matara, Sri Lanka X. Lu et al. https://doi.org/10.3390/jmse12111903
- 湖泊表层溶解氧对热浪的响应及其生态反馈调控机制 智. 欧阳 et al. https://doi.org/10.1360/N072025-0097
- Sensitivity of surface downward longwave radiation to aerosol optical depth over the Lake Taihu region, China C. Liu et al. https://doi.org/10.1016/j.atmosres.2024.107444
- Ecological feedbacks modulate lake surface oxygen responses to heatwaves Z. Ouyang et al. https://doi.org/10.1007/s11430-025-1840-6
- Aerosol interference with open-path eddy covariance measurement in a lake environment L. Jia et al. https://doi.org/10.1016/j.agrformet.2024.110104
- Coupling satellite imagery and numerical models to advance understanding and modelling of diel cyanobacterial blooms in shallow eutrophic lakes J. Li et al. https://doi.org/10.1016/j.watres.2025.124744
- Quantification of phytoplankton primary production from space: A revisit based on high-frequency observations with the aid of Himawari-8/AHI Z. Li et al. https://doi.org/10.1016/j.rse.2026.115238
- N2O emissions from a multi-habitat lake: Patterns and controls F. Yang et al. https://doi.org/10.1016/j.jhydrol.2025.133209
- Sigmoid Generalized Complementary Equation for Evaporation Over Wet Surfaces: A Nonlinear Modification of the Priestley‐Taylor Equation S. Han et al. https://doi.org/10.1029/2020WR028737
- Understanding the performance of three 1-D lake models in simulating thermal dynamics of diverse water bodies in the Yangtze River Basin O. Obulkasim et al. https://doi.org/10.1016/j.jhydrol.2025.133094
- Hybrid Lake Model (HyLake) v1.0: unifying deep learning and physical principles for simulating lake-atmosphere interactions Y. He & X. Yang https://doi.org/10.5194/gmd-18-9257-2025
- In Situ Observation of Near-Surface Wind Seasonal Variation on the Southern Coast of Sri Lanka X. Lu et al. https://doi.org/10.3390/jmse11091721
- Quantifying the contribution of evaporation from Lake Taihu to precipitation with an isotope-based method Y. Hu et al. https://doi.org/10.1080/10256016.2022.2056599
- A benchmark dataset of diurnal- and seasonal-scale radiation, heat, and CO2 fluxes in a typical East Asian monsoon region Z. Duan et al. https://doi.org/10.5194/essd-14-4153-2022
- Estimating the sensitivity of the Priestley–Taylor coefficient to air temperature and humidity Z. Liu et al. https://doi.org/10.5194/hess-28-4349-2024
Saved (final revised paper)
Latest update: 28 May 2026
Short summary
Inland lakes play an important role in regulating local climate. In this paper, we describe a dataset on microclimate and eddy covariance variables measured at a network of sites across Lake Taihu. The dataset, which appears to be the first of its kind for lake systems, can be used for validation of lake–air flux parameterizations, investigation of climatic controls on lake evaporation, evaluation of remote-sensing surface data products and global synthesis on lake–air interactions.
Inland lakes play an important role in regulating local climate. In this paper, we describe a...
Altmetrics
Final-revised paper
Preprint