Development of a 50-year daily surface solar radiation dataset over China

Tang, Wenjun; Yang, Kun; Qin, Jun; Min, Min

doi:10.1007/s11430-012-4542-9

Cited by 53 publications

(52 citation statements)

References 37 publications

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“…The spatial distribution characteristics of Fig. 11 are consistent with the result of Tang et al (2013), which was derived based on the SSR estimations at 716 CMA stations. The SSR values are the highest in summer and lowest in winter, and spring and autumn are in the middle.…”

Section: Applications In Chinasupporting

confidence: 84%

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

et al. 2016

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Abstract. Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporalresolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m −2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m −2 (or 3.5 %) and 98.5 W m −2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m −2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m −2 (or 19.1 %) and 22.1 W m −2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

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Section: Applications In Chinasupporting

confidence: 84%

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

et al. 2016

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“…7. This distribution is similar to the distributions of photosynthetically active radiation and surface solar radiation reconstructed by Tang et al (2013aTang et al ( , 2013b.…”

Section: Sample Description Of the Observed Uv Radiation Valuessupporting

confidence: 78%

Two ultraviolet radiation datasets that cover China

Liu

Wang

et al. 2017

Adv. Atmos. Sci.

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Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes. The dataset consists of two compressed files, with the file names "observed uv radiation.zip" and "reconstructed uv radiation.zip". 1. The file "observed uv radiation.zip" contains the in situ-measured UV radiation dataset and comprises 40Excel worksheets. Each file contains the data collected at a single station. 2. The file "reconstructed uv radiation.zip" contains the reconstructed UV radiation dataset, which consists of 725 .txt files. The file named "station information.txt" contains information on the site locations, and the other 724 file names correspond to the station codes.

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“…CN05.1 (Wu and Gao, 2013) and MWR (Xu et al, 2017) data are available upon request to the corresponding author. CMA shortwave radiation data are provided by the Data Assimilation and Modeling Center for Tibetan Multi-spheres (http://dam.itpcas.ac.cn/data/daily_solar_radiation_dataset_over_ China_readme.htm; Tang et al, 2013). Shortwave radiation data from CERN are provided by the Chinese Ecosystem Research Network through http://cerndis1.cern.ac.cn/data/meta?id=17046 (Su et al, 2005).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China

Yang

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during [2008][2009][2010][2011][2012][2013][2014]. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the spatial distribution, but estimates from CLDAS and GLDAS are systematically higher than those from CMFD over most of mainland China. Based on our evaluation metrics, CLDAS slightly outperforms GLDAS. CLDAS is also closer than GLDAS to CMFD with respect to temporal variations in shortwave radiation anomalies, with substantial differences among the time series. Differences in temporal variations are especially pronounced south of 34 • N. Our findings provide valuable guidance for a variety of stakeholders, including land-surface modelers and data providers.

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Development of a 50-year daily surface solar radiation dataset over China

Cited by 53 publications

References 37 publications

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

Two ultraviolet radiation datasets that cover China

Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China

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