
Proceedings Paper
A method to compute solar radiation at surface in any time interval based on NCEP re-analysisFormat | Member Price | Non-Member Price |
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Paper Abstract
Diurnal variation of solar radiation at surface is of importance to data assimilation, weather and climate model
assessment. However, the shortage of solar radiation data has limited full use of other meteorological data. Solar
radiation at surface can not be simply calculated by interpolation in any time interval because it is heavily influenced by
solar hour angle, cloud, water vapor and aerosols etc., which brings great troubles to model applications. This paper
presents a method to compute mean solar radiation at surface in any time interval and develops a data set of hourly mean
solar radiation that can be used to assess models by use of NCEP 6-hourly mean of downward solar radiation flux at
surface. Also, while comparing to measured hourly mean of solar radiation, results show that the calculated hourly mean
solar radiation agrees closely with observation in numerical value and variation trend, which illuminates that the method
is efficient. The calculated hourly-mean solar radiation reflects the diurnal variation all over the world and it can be used
as land model forcing, It is helpful to simulation, validation and assessment of the weather and climate model and can
make up the shortage of measured solar radiation data.
Paper Details
Date Published: 9 October 2007
PDF: 7 pages
Proc. SPIE 6679, Remote Sensing and Modeling of Ecosystems for Sustainability IV, 66790R (9 October 2007); doi: 10.1117/12.730626
Published in SPIE Proceedings Vol. 6679:
Remote Sensing and Modeling of Ecosystems for Sustainability IV
Wei Gao; Susan L. Ustin, Editor(s)
PDF: 7 pages
Proc. SPIE 6679, Remote Sensing and Modeling of Ecosystems for Sustainability IV, 66790R (9 October 2007); doi: 10.1117/12.730626
Show Author Affiliations
Lanjun Zou, Shanghai Meteorological Bureau (China)
China Meteorological Administration (China)
Nanjing Univ. of Information Science and Technology (China)
Wei Gao, Nanjing Univ. of Information Science and Technology (China)
Colorado State Univ. (United States)
China Meteorological Administration (China)
Nanjing Univ. of Information Science and Technology (China)
Wei Gao, Nanjing Univ. of Information Science and Technology (China)
Colorado State Univ. (United States)
Tongwen Wu, China Meteorological Administration (China)
Xiaofeng Xu, China Meteorological Administration (China)
Xiaofeng Xu, China Meteorological Administration (China)
Published in SPIE Proceedings Vol. 6679:
Remote Sensing and Modeling of Ecosystems for Sustainability IV
Wei Gao; Susan L. Ustin, Editor(s)
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