Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2023.0055.zh
Tao Wang, Z. Deng, Yonghong Xie, Feng Li
With considerable carbon sequestration potential, lakes are active channels of terrestrial carbon cycle. As the second largest freshwater lake in China, Dongting Lake has huge annual water level fluctuations (12–14 m), and the unique hydrological situation is a major challenge and of significance to the study of the carbon and water cycle processes at Dongting Lake, the control mechanism and its response to environmental changes. Miscanthus sacchariflorus is widely distributed at Dongting Lake and is a perennial tall bamboo-like herb with well-developed rhizomes and high carbon sequestration potential. Targeting the Miscanthus sacchariflorus ecosystem of Dongting Lake as the research object, we used the eddy-correlation (EC) system in the study to conduct long-term localized observations of carbon fluxes in the Miscanthus sacchariflorus ecosystem. As the first Dongting Lake ecosystem research station in China, National Field Scientific Observation and Research Station of Dongting Lake Wetland Ecosystem in Hunan Province (Dongting Lake National Station) collated the fluxes and conventional meteorological data of the Dongting Lake Miscanthus sacchariflorus ecosystem from June 2014 to December 2016 based on the data processing system of the China Flux Observation and Research Network (ChinaFLUX). The dataset includes the data files of net ecosystem carbon exchange, ecosystem respiration, ecosystem carbon exchange, latent heat flux, sensible heat flux, air temperature, relative air humidity, water vapor pressure, net radiation, and soil temperature at half-hourly, daily, monthly, and yearly scales. It can provide a strong data base for scientific understanding of the spatial and temporal dynamics of carbon, water and heat in the Miscanthus sacchariflorus ecosystem, material and energy cycles, estimation of global carbon sequestration potential, as well as response and adaptation to global climate change.
{"title":"A dataset of carbon dioxide flux observation of the Miscanthus sacchariflorus ecosystem of Dongting Lake Wetland from 2014 to 2016","authors":"Tao Wang, Z. Deng, Yonghong Xie, Feng Li","doi":"10.11922/11-6035.csd.2023.0055.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0055.zh","url":null,"abstract":"With considerable carbon sequestration potential, lakes are active channels of terrestrial carbon cycle. As the second largest freshwater lake in China, Dongting Lake has huge annual water level fluctuations (12–14 m), and the unique hydrological situation is a major challenge and of significance to the study of the carbon and water cycle processes at Dongting Lake, the control mechanism and its response to environmental changes. Miscanthus sacchariflorus is widely distributed at Dongting Lake and is a perennial tall bamboo-like herb with well-developed rhizomes and high carbon sequestration potential. Targeting the Miscanthus sacchariflorus ecosystem of Dongting Lake as the research object, we used the eddy-correlation (EC) system in the study to conduct long-term localized observations of carbon fluxes in the Miscanthus sacchariflorus ecosystem. As the first Dongting Lake ecosystem research station in China, National Field Scientific Observation and Research Station of Dongting Lake Wetland Ecosystem in Hunan Province (Dongting Lake National Station) collated the fluxes and conventional meteorological data of the Dongting Lake Miscanthus sacchariflorus ecosystem from June 2014 to December 2016 based on the data processing system of the China Flux Observation and Research Network (ChinaFLUX). The dataset includes the data files of net ecosystem carbon exchange, ecosystem respiration, ecosystem carbon exchange, latent heat flux, sensible heat flux, air temperature, relative air humidity, water vapor pressure, net radiation, and soil temperature at half-hourly, daily, monthly, and yearly scales. It can provide a strong data base for scientific understanding of the spatial and temporal dynamics of carbon, water and heat in the Miscanthus sacchariflorus ecosystem, material and energy cycles, estimation of global carbon sequestration potential, as well as response and adaptation to global climate change.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49018798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2023.0001.zh
Mi Zhang, W. Xiao, Jiayu Zhao, L. Jia, Pei Ge, H. Bao, Jili Qiu, Zhen Zhang, R. Zhao, Jiao Wang, Xiu-Fang Zhang, Hao Zhang, Jian Yang, Shoudong Liu, Chang Cao, N. Hu
Aquaculture ponds are inland small water bodies subject to human activities. They are not only carbon sources, but important sources of regional water evaporation. Accurate observation of carbon and water fluxes in aquaculture ponds is the basis for quantifying carbon emission and evaporation contribution of inland water. Nanjing University of Information Science and Technology set up an atmospheric environment experiment site to observe the carbon and water flux over aquaculture water bodies in Guandu Village of Quanjiao County, Anhui Province. This dataset includes the CO2 flux data (measured by the multi-channel closed dynamic floating chamber method), CH4 flux data (measured by the eddy covariance method, multi-channel closed dynamic floating chamber method, and inverted funnel method), latent heat and sensible heat fluxes data (measured by the eddy covariance method), as well as key environmental factors data, such as air temperature, water temperature, and radiation. All data were processed by standardized procedures. Moreover, data quality controls were performed. This dataset can provide important data for accurately estimating carbon emission and evaporation contribution in regional and global inland small water bodies.
{"title":"A dataset of carbon and water flux observed in aquaculture ponds in Quanjiao, Anhui Province from 2016 to 2020","authors":"Mi Zhang, W. Xiao, Jiayu Zhao, L. Jia, Pei Ge, H. Bao, Jili Qiu, Zhen Zhang, R. Zhao, Jiao Wang, Xiu-Fang Zhang, Hao Zhang, Jian Yang, Shoudong Liu, Chang Cao, N. Hu","doi":"10.11922/11-6035.csd.2023.0001.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0001.zh","url":null,"abstract":"Aquaculture ponds are inland small water bodies subject to human activities. They are not only carbon sources, but important sources of regional water evaporation. Accurate observation of carbon and water fluxes in aquaculture ponds is the basis for quantifying carbon emission and evaporation contribution of inland water. Nanjing University of Information Science and Technology set up an atmospheric environment experiment site to observe the carbon and water flux over aquaculture water bodies in Guandu Village of Quanjiao County, Anhui Province. This dataset includes the CO2 flux data (measured by the multi-channel closed dynamic floating chamber method), CH4 flux data (measured by the eddy covariance method, multi-channel closed dynamic floating chamber method, and inverted funnel method), latent heat and sensible heat fluxes data (measured by the eddy covariance method), as well as key environmental factors data, such as air temperature, water temperature, and radiation. All data were processed by standardized procedures. Moreover, data quality controls were performed. This dataset can provide important data for accurately estimating carbon emission and evaporation contribution in regional and global inland small water bodies.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49122593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2023.0009.zh
Weinan Chen, Song Wang, S. Niu
With abundant and widespread carbon, Alpine meadow boasts one of the most important ecosystems on Qinghai-Tibet Platea. It is essential to observe the carbon, water and heat fluxes in alpine meadow ecosystem for understanding and predicting the dynamics of carbon storage in alpine regions. This dataset includes the observation data of carbon, water and heat fluxes in Zoige alpine meadow from 2015 to 2020. The data collection work was carried out at the Field Scientific Observation and Research Station of Hongyuan alpine meadow ecosystem on the eastern edge of the Qinghai-Tibet Plateau. Based on the open-circuit vorticity correlation system, the observation work also covers the carbon dioxide flux, methane flux, water and heat flux. The data of this station has been sorted out a set of long-term, continuous and standardized datasets of ecosystem carbon and water fluxes and key meteorological elements through the data processing system of China Flux Observation and Research Network (ChinaFLUX). This dataset is of great significance for accurately evaluating the position and role of carbon and water fluxes in the regional and global carbon and water cycles of the alpine meadow ecosystem in the Qinghai-Tibet Plateau.
{"title":"A dataset of carbon, water and heat fluxes of Zoige alpine meadow from 2015 to 2020","authors":"Weinan Chen, Song Wang, S. Niu","doi":"10.11922/11-6035.csd.2023.0009.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0009.zh","url":null,"abstract":"With abundant and widespread carbon, Alpine meadow boasts one of the most important ecosystems on Qinghai-Tibet Platea. It is essential to observe the carbon, water and heat fluxes in alpine meadow ecosystem for understanding and predicting the dynamics of carbon storage in alpine regions. This dataset includes the observation data of carbon, water and heat fluxes in Zoige alpine meadow from 2015 to 2020. The data collection work was carried out at the Field Scientific Observation and Research Station of Hongyuan alpine meadow ecosystem on the eastern edge of the Qinghai-Tibet Plateau. Based on the open-circuit vorticity correlation system, the observation work also covers the carbon dioxide flux, methane flux, water and heat flux. The data of this station has been sorted out a set of long-term, continuous and standardized datasets of ecosystem carbon and water fluxes and key meteorological elements through the data processing system of China Flux Observation and Research Network (ChinaFLUX). This dataset is of great significance for accurately evaluating the position and role of carbon and water fluxes in the regional and global carbon and water cycles of the alpine meadow ecosystem in the Qinghai-Tibet Plateau.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43145255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2023.0031.zh
Fan Liu, Yanjun Shen, Jian-sheng Cao, Yucui Zhang
The winter wheat-summer maize double-cropping agro-ecosystem holds the largest planting area in the North China Plain. The carbon and water flux observation data of the croplands are crucial to understanding regional carbon and water cycles and their regulation mechanism. Located in the piedmont Plain of Taihang Mountain, Luancheng Agro-ecosystem Experimental Station (Luancheng Station) is the typical groundwater irrigation district. We have been using the eddy covariance technology to carry out the observation work of the winter-summer maize croplands since October 2007. This is the dataset of water, heat, and carbon fluxes over the winter wheat-summer maize croplands in Luancheng from October 2013 to September 2017 (covering four complete growing seasons). The dataset includes latent heat flux (or evapotranspiration), sensible heat flux, net ecosystem exchange of CO2, solar radiation, photosynthetically active radiation, air temperature/humidity, precipitation, soil temperature and volumetric soil water content at the half-hourly, daily, crop-season, and crop-year scales. The network observation, quality control and storage process of this dataset strictly abide by ChinaFLUX data management technology system to ensure data reliability. This dataset can provide solid data support for deeply understanding the processes of water, heat and carbon exchange, and improving the management of water resource to relieve the overdraft of groundwater in North China.
{"title":"A dataset of water, heat, and carbon fluxes over the winter wheat-summer maize croplands in Luancheng during 2013–2017","authors":"Fan Liu, Yanjun Shen, Jian-sheng Cao, Yucui Zhang","doi":"10.11922/11-6035.csd.2023.0031.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0031.zh","url":null,"abstract":"The winter wheat-summer maize double-cropping agro-ecosystem holds the largest planting area in the North China Plain. The carbon and water flux observation data of the croplands are crucial to understanding regional carbon and water cycles and their regulation mechanism. Located in the piedmont Plain of Taihang Mountain, Luancheng Agro-ecosystem Experimental Station (Luancheng Station) is the typical groundwater irrigation district. We have been using the eddy covariance technology to carry out the observation work of the winter-summer maize croplands since October 2007. This is the dataset of water, heat, and carbon fluxes over the winter wheat-summer maize croplands in Luancheng from October 2013 to September 2017 (covering four complete growing seasons). The dataset includes latent heat flux (or evapotranspiration), sensible heat flux, net ecosystem exchange of CO2, solar radiation, photosynthetically active radiation, air temperature/humidity, precipitation, soil temperature and volumetric soil water content at the half-hourly, daily, crop-season, and crop-year scales. The network observation, quality control and storage process of this dataset strictly abide by ChinaFLUX data management technology system to ensure data reliability. This dataset can provide solid data support for deeply understanding the processes of water, heat and carbon exchange, and improving the management of water resource to relieve the overdraft of groundwater in North China.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43298109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2023.0041.zh
Cuihai You, Yanbing Wang, Shiping Chen
Grassland is an important terrestrial ecosystem for the exchange of mass and energy between land and atmosphere, playing an important role in global carbon cycle. However, the direction and size of its carbon sink are still in dispute. The eddy covariance technique can be sued to continuously determine ecosystem-level carbon, water and energy exchanges between vegetation and atmosphere. The long-term observations of carbon and water fluxes can help quantify the carbon sequestration capability of grassland ecosystems and its response to climate change. This dataset consists of two half-hourly data files, including the carbon, water and heat fluxes data file and the meteorological variables data file. All of the flux data were processed according to the flux data processing procedure specified by ChinaFLUX. The observational quality of this dataset is good, with a complete data observation integrity of over 95% throughout the year and a high energy balance ratio (1.04 ± 0.07). This decadal flux dataset from 2006 to 2015 provides a high-quality and continuous long-term eddy flux observation data valuable for the research of diurnal dynamics, seasonal and interannual variations of carbon and water fluxes, which is significant for evaluating the role of China’s temperate typical grasslands in regional and global carbon and water cycles.
{"title":"A dataset of carbon and water fluxes of the typical grasslands in Duolun County, Inner Mongolia during 2006-2015","authors":"Cuihai You, Yanbing Wang, Shiping Chen","doi":"10.11922/11-6035.csd.2023.0041.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0041.zh","url":null,"abstract":"Grassland is an important terrestrial ecosystem for the exchange of mass and energy between land and atmosphere, playing an important role in global carbon cycle. However, the direction and size of its carbon sink are still in dispute. The eddy covariance technique can be sued to continuously determine ecosystem-level carbon, water and energy exchanges between vegetation and atmosphere. The long-term observations of carbon and water fluxes can help quantify the carbon sequestration capability of grassland ecosystems and its response to climate change. This dataset consists of two half-hourly data files, including the carbon, water and heat fluxes data file and the meteorological variables data file. All of the flux data were processed according to the flux data processing procedure specified by ChinaFLUX. The observational quality of this dataset is good, with a complete data observation integrity of over 95% throughout the year and a high energy balance ratio (1.04 ± 0.07). This decadal flux dataset from 2006 to 2015 provides a high-quality and continuous long-term eddy flux observation data valuable for the research of diurnal dynamics, seasonal and interannual variations of carbon and water fluxes, which is significant for evaluating the role of China’s temperate typical grasslands in regional and global carbon and water cycles.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42550959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The transport of electromagnetic energy in the polar upper atmosphere and its spatial and temporal distribution are current hot issues and important topics for studying the polar upper atmospheric environment and space weather forecasting models. Researchers usually adopted the observations from low-altitude polar-orbiting satellites to estimate the magnitude and direction of electromagnetic energy. The continuous accumulation of electromagnetic energy data will be beneficial to the study on the transmission and variation characteristics of electromagnetic energy in the polar ionosphere in China. In this paper, we estimated the distribution of field-aligned Poynting flux, horizontal convection electric field and magnetic field perturbation in the dayside polar cap based on the plasma velocity and magnetic field data of DMSP F17 satellite in the northern hemisphere during 2014-2016. The initial DMSP F17 satellite data included in this dataset are of high quality. The estimation process is rigorous and reasonable, and the data records are complete. The dataset can provide important data support for the study on energy transport and dissipation in the ionosphere/thermosphere in the polar region.
{"title":"A dataset of field-aligned Poynting flux in the dayside polar cap of the northern hemisphere during 2014-2016","authors":"Jianping Wang, Beichen Zhang, Chunming Huang, Rui-yuan Liu, Yonghua Liu, Zejun Hu, Jianjun Liu","doi":"10.11922/11-6035.csd.2022.0096.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0096.zh","url":null,"abstract":"The transport of electromagnetic energy in the polar upper atmosphere and its spatial and temporal distribution are current hot issues and important topics for studying the polar upper atmospheric environment and space weather forecasting models. Researchers usually adopted the observations from low-altitude polar-orbiting satellites to estimate the magnitude and direction of electromagnetic energy. The continuous accumulation of electromagnetic energy data will be beneficial to the study on the transmission and variation characteristics of electromagnetic energy in the polar ionosphere in China. In this paper, we estimated the distribution of field-aligned Poynting flux, horizontal convection electric field and magnetic field perturbation in the dayside polar cap based on the plasma velocity and magnetic field data of DMSP F17 satellite in the northern hemisphere during 2014-2016. The initial DMSP F17 satellite data included in this dataset are of high quality. The estimation process is rigorous and reasonable, and the data records are complete. The dataset can provide important data support for the study on energy transport and dissipation in the ionosphere/thermosphere in the polar region.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44515603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2022.0024.zh
Lisha Qu, Qiu'an Zhu, Chaofan Zhu, Jiang Zhang
Precipitation data are greatly valuable in theoretical research and practical application, and have been widely used in hydrological forecasting, agricultural production, ecological protection and other fields. China has a vast territory with large topographic fluctuations, and most meteorological stations are located in densely populated plain areas. Due to the low density of stations, there is a lack of precipitation observation data in some areas such as mountainous areas. Therefore, it is necessary to use the interpolation method to establish high-precision precipitation datasets. Based on the precipitation monitoring data from more than 2,400 meteorological stations on the ground from 1960 to 2020, we used the climate data spatial interpolation software ANUSPLIN to obtain a dataset of monthly precipitation interpolation with a resolution of 1 km in China. According to the comparison between the dataset and the measured precipitation data as well as the hydrological yearbook data in China released by the CRU and Northwest University of agriculture and forestry science and technology, this dataset has the characteristics of high accuracy, high resolution and long time series, with great potential in scientific research and application.
{"title":"A dataset of monthly precipitation with resolution of 1 km in China from 1960 to 2020","authors":"Lisha Qu, Qiu'an Zhu, Chaofan Zhu, Jiang Zhang","doi":"10.11922/11-6035.csd.2022.0024.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0024.zh","url":null,"abstract":"Precipitation data are greatly valuable in theoretical research and practical application, and have been widely used in hydrological forecasting, agricultural production, ecological protection and other fields. China has a vast territory with large topographic fluctuations, and most meteorological stations are located in densely populated plain areas. Due to the low density of stations, there is a lack of precipitation observation data in some areas such as mountainous areas. Therefore, it is necessary to use the interpolation method to establish high-precision precipitation datasets. Based on the precipitation monitoring data from more than 2,400 meteorological stations on the ground from 1960 to 2020, we used the climate data spatial interpolation software ANUSPLIN to obtain a dataset of monthly precipitation interpolation with a resolution of 1 km in China. According to the comparison between the dataset and the measured precipitation data as well as the hydrological yearbook data in China released by the CRU and Northwest University of agriculture and forestry science and technology, this dataset has the characteristics of high accuracy, high resolution and long time series, with great potential in scientific research and application.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46331359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2023.0040.zh
Huichan Liu, G. He, Yan Peng, Gui-zhou Wang, R. Yin
The Tibetan Plateau is known as the Asian Water Tower. The distribution of surface water and its changes are closely related to global change, biodiversity and water-related ecosystems. Based on the collection of high-precision land surface water samples, we used the random forest classification algorithm in machine learning to extract land surface water information from Landsat series satellite images and produced a dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau based on satellite remote sensing images in 2022. According to data quality assessment, the overall accuracy of the dataset is 92.9%, and the Kappa coefficient is 0.84. This dataset can provide foundational data support for water resource monitoring, ecosystem services, and global change research on the Qinghai-Tibet Plateau.
{"title":"A dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau in 2022","authors":"Huichan Liu, G. He, Yan Peng, Gui-zhou Wang, R. Yin","doi":"10.11922/11-6035.csd.2023.0040.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0040.zh","url":null,"abstract":"The Tibetan Plateau is known as the Asian Water Tower. The distribution of surface water and its changes are closely related to global change, biodiversity and water-related ecosystems. Based on the collection of high-precision land surface water samples, we used the random forest classification algorithm in machine learning to extract land surface water information from Landsat series satellite images and produced a dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau based on satellite remote sensing images in 2022. According to data quality assessment, the overall accuracy of the dataset is 92.9%, and the Kappa coefficient is 0.84. This dataset can provide foundational data support for water resource monitoring, ecosystem services, and global change research on the Qinghai-Tibet Plateau.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45065700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2023.0059.zh
Yanbing Wang, Cuihai You, Shiping Chen
Grassland is one of the most widely distributed vegetation types around the world, and play an important role in the global carbon and water cycle. As a common type of land use in Inner Mongolia, mowing has profoundly affected plant growth and ecosystem functioning of grasslands. However, the influences of mowing on the carbon and water cycle processes in grassland ecosystems are still unclear. A lack of long-term and continuous observation flux data is one of the important reasons. According to the flux data processing procedure by ChinaFLUX, we collected the carbon and water fluxes and conventional meteorological data of typical grassland ecosystems in Xilinhot, Inner Mongolia from 2006 to 2015. This dataset provides a high-quality and continuous long-term eddy flux observation valuable for the research of temporal variations and mechanisms of carbon and water fluxes. Meanwhile, it is important for optimizing grassland management practices and evaluating the role of grassland in regional and global carbon and water cycles.
{"title":"A dataset of carbon and water fluxes of mowing grasslands in Xilinhot, Inner Mongolia during 2006-2015","authors":"Yanbing Wang, Cuihai You, Shiping Chen","doi":"10.11922/11-6035.csd.2023.0059.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0059.zh","url":null,"abstract":"Grassland is one of the most widely distributed vegetation types around the world, and play an important role in the global carbon and water cycle. As a common type of land use in Inner Mongolia, mowing has profoundly affected plant growth and ecosystem functioning of grasslands. However, the influences of mowing on the carbon and water cycle processes in grassland ecosystems are still unclear. A lack of long-term and continuous observation flux data is one of the important reasons. According to the flux data processing procedure by ChinaFLUX, we collected the carbon and water fluxes and conventional meteorological data of typical grassland ecosystems in Xilinhot, Inner Mongolia from 2006 to 2015. This dataset provides a high-quality and continuous long-term eddy flux observation valuable for the research of temporal variations and mechanisms of carbon and water fluxes. Meanwhile, it is important for optimizing grassland management practices and evaluating the role of grassland in regional and global carbon and water cycles.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47637434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.11922/11-6035.csd.2022.0068.zh
Ruiyang Ma, D. Zheng
Thunderstorm clouds yield lightning discharges and are often accompanied by damaging weather; therefore, they are important concerns for weather monitoring and forecasting. At present, the research on the thunderstorm activity in China is deficient; and available thunderstorm cloud datasets with high temporal-spatial resolution and big spatial coverage are rare. We established the thunderstorm feature dataset (TFD) by using the black body temperature (TBB) and the cloud classification (CLC) products from the Fengyun-2E (FY-2E) satellite and the lightning location data from the World-Wide Lightning Location Network (WWLLN). Thunderstorm cloud is defined in accordance with the criterion that at least one WWLLN lightning is in the area with TBB ≤ −32°C or its fitted ellipse. We obtained the parameters including time, location, structure, and lightning activities to prepare the TFD. This dataset extends from 2010 to 2018, with a temporal resolution of 1 hour and wide spatial coverage of the FY-2E full-disc observation area, especially including the mainland and adjacent sea areas of China. This TFD can play an important role in the study of thunderstorm activities.
{"title":"A dataset of thunderstorm features of the FY-2E full-disc observation area from 2010 to 2018","authors":"Ruiyang Ma, D. Zheng","doi":"10.11922/11-6035.csd.2022.0068.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0068.zh","url":null,"abstract":"Thunderstorm clouds yield lightning discharges and are often accompanied by damaging weather; therefore, they are important concerns for weather monitoring and forecasting. At present, the research on the thunderstorm activity in China is deficient; and available thunderstorm cloud datasets with high temporal-spatial resolution and big spatial coverage are rare. We established the thunderstorm feature dataset (TFD) by using the black body temperature (TBB) and the cloud classification (CLC) products from the Fengyun-2E (FY-2E) satellite and the lightning location data from the World-Wide Lightning Location Network (WWLLN). Thunderstorm cloud is defined in accordance with the criterion that at least one WWLLN lightning is in the area with TBB ≤ −32°C or its fitted ellipse. We obtained the parameters including time, location, structure, and lightning activities to prepare the TFD. This dataset extends from 2010 to 2018, with a temporal resolution of 1 hour and wide spatial coverage of the FY-2E full-disc observation area, especially including the mainland and adjacent sea areas of China. This TFD can play an important role in the study of thunderstorm activities.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47777387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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