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- Author or Editor: Jian Ma x
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A major research plan entitled “Integrated research on the ecohydrological process of the Heihe River Basin” was launched by the National Natural Science Foundation of China in 2010. One of the key aims of this research plan is to establish a research platform that integrates observation, data management, and model simulation to foster twenty-first-century watershed science in China. Based on the diverse needs of interdisciplinary studies within this research plan, a program called the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) was implemented. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system, and to enhance the applicability of remote sensing in integrated ecohydrological studies and water resource management at the basin scale. This paper introduces the background, scientific objectives, and experimental design of HiWATER. The instrumental setting and airborne mission plans are also outlined. The highlights are the use of a flux observing matrix and an eco-hydrological wireless sensor network to capture multiscale heterogeneities and to address complex problems, such as heterogeneity, scaling, uncertainty, and closing water cycle at the watershed scale. HiWATER was formally initialized in May 2012 and will last four years until 2015. Data will be made available to the scientific community via the Environmental and Ecological Science Data Center for West China. International scientists are welcome to participate in the field campaign and use the data in their analyses.
A major research plan entitled “Integrated research on the ecohydrological process of the Heihe River Basin” was launched by the National Natural Science Foundation of China in 2010. One of the key aims of this research plan is to establish a research platform that integrates observation, data management, and model simulation to foster twenty-first-century watershed science in China. Based on the diverse needs of interdisciplinary studies within this research plan, a program called the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) was implemented. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system, and to enhance the applicability of remote sensing in integrated ecohydrological studies and water resource management at the basin scale. This paper introduces the background, scientific objectives, and experimental design of HiWATER. The instrumental setting and airborne mission plans are also outlined. The highlights are the use of a flux observing matrix and an eco-hydrological wireless sensor network to capture multiscale heterogeneities and to address complex problems, such as heterogeneity, scaling, uncertainty, and closing water cycle at the watershed scale. HiWATER was formally initialized in May 2012 and will last four years until 2015. Data will be made available to the scientific community via the Environmental and Ecological Science Data Center for West China. International scientists are welcome to participate in the field campaign and use the data in their analyses.
Abstract
Surface downward solar radiation compositions (SSRC), including photosynthetically active radiation (PAR), ultraviolet-A (UVA), ultraviolet-B (UVB), and shortwave radiation (SWR), with high spatial–temporal resolutions and precision are essential for applications including solar power, vegetation photosynthesis, and environmental health. In this study, an optimal algorithm was developed to calculate SSRC, including their direct and diffuse components. Key features of the algorithm include combining the radiative transfer model with machine learning techniques, including full consideration of the effects of aerosol types, cloud phases, and gas components. A near-real-time monitoring system was developed based on this algorithm, with SSRC products generated from Himawari-8/9 and Fengyun-4 series data. Validation with ground-based data shows that the accuracy of the SWR and PAR compositions (daily mean RMSEs of 19.7 and 9.2 W m−2, respectively) are significantly better than those of state-of-the-art products from CERES, ERA5, and GLASS. The accuracy of UVA and UVB measurements is comparable with CERES. Characteristics of aerosols, clouds, gases, and their impacts on SSRC are investigated before, during, and post COVID-19; in particular, significant SSRC variations due to the reduction of aerosols and increase of ozone are identified in the Chinese central and eastern areas during that period. The spatial–temporal resolution of data products [up to 0.05° (10 min)−1 for the full-disk region] is one of the most important advantages. Data for the East Asia–Pacific region during 2016–20 is available from the CARE home page (www.slrss.cn/care/sp/pc/).
Abstract
Surface downward solar radiation compositions (SSRC), including photosynthetically active radiation (PAR), ultraviolet-A (UVA), ultraviolet-B (UVB), and shortwave radiation (SWR), with high spatial–temporal resolutions and precision are essential for applications including solar power, vegetation photosynthesis, and environmental health. In this study, an optimal algorithm was developed to calculate SSRC, including their direct and diffuse components. Key features of the algorithm include combining the radiative transfer model with machine learning techniques, including full consideration of the effects of aerosol types, cloud phases, and gas components. A near-real-time monitoring system was developed based on this algorithm, with SSRC products generated from Himawari-8/9 and Fengyun-4 series data. Validation with ground-based data shows that the accuracy of the SWR and PAR compositions (daily mean RMSEs of 19.7 and 9.2 W m−2, respectively) are significantly better than those of state-of-the-art products from CERES, ERA5, and GLASS. The accuracy of UVA and UVB measurements is comparable with CERES. Characteristics of aerosols, clouds, gases, and their impacts on SSRC are investigated before, during, and post COVID-19; in particular, significant SSRC variations due to the reduction of aerosols and increase of ozone are identified in the Chinese central and eastern areas during that period. The spatial–temporal resolution of data products [up to 0.05° (10 min)−1 for the full-disk region] is one of the most important advantages. Data for the East Asia–Pacific region during 2016–20 is available from the CARE home page (www.slrss.cn/care/sp/pc/).
