1. A quality-assured dataset of nine radiation components observed at the Shangdianzi regional GAW station in China (2013-2022).
- Author
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Weijun Quan, Zhenfa Wang, Lin Qiao, Xiangdong Zheng, Junli Jin, Yinruo Li, Xiaomei Yin, Zhiqiang Ma, and Wild, Martin
- Subjects
SOLAR radiation ,ATMOSPHERIC radiation ,SOLAR spectra ,SPECTRAL irradiance ,ATMOSPHERIC composition ,RADIATION ,DATA loggers - Abstract
A New Baseline Surface Radiation (NBSR) system was established at the Shangdianzi (SDZ) regional Global Atmosphere Watch (GAW) station in 2013 to observe nine broadband radiation components, i.e., the global-, direct-, diffuse-, and upwelling-shortwave irradiance (GSWI, DSWI, DifSWI, and UpSWI) as well as the photosynthetically active radiation (PAR), ultraviolet irradiance (UVAI; UVBI), down- and up-welling long-wave irradiance (DnLWI; UpLWI). To test the 1-min raw radiometric data, a Hybrid Algorithm for Radiation Data Quality Control (HARDQC) is presented in this study based on well-established methods together with the solar irradiance dataset and the spectral features of the instrument bands. Subsequently, an NBSR dataset, which consists of multi-time scale (i.e. 1-min, hourly, daily, monthly, monthly average hourly, and monthly average daily) radiation datasets over 2013-2022, is established and evaluated. Results show that more than 98.7% of all radiation components passed the physical possibility test. The percentages passed the extremely rare test are greater than 98.6% for all radiation components except for the DnLWI (97.1%). The percentages passed the comparison test are greater than 83.3% (GSWI), 78.3% (DSWI), 81.7% (DifSWI), 93.1% (UpSWI), 88.9% (PARI), 95.6% (UVAI), 96.3% (UVBI), 99.8% (DnLWI), and 99.7% (UpLWI), respectively. Due to data logger faults, removal of the instruments for calibration, and lightning strokes, some apparent data gaps in the upwelling radiation components (January 2015-August 2017) and all radiation components (December 2018; July to September 2021) were detected. Despite the existence of a few imperfections in the NBSR dataset, it is still reliable to apply in many fields such as the validation of satellite products and numerical models, investigation of relationships between radiation and atmospheric composition, and the detection of changes in the surface fluxes. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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