Computational Fluid Dynamics Analysis on Radiation Error of Surface Air Temperature Measurement

  • Jie YangEmail author
  • Qing-Quan Liu
  • Ren-Hui Ding


Due to solar radiation effect, current air temperature sensors inside a naturally ventilated radiation shield may produce a measurement error that is 0.8 K or higher. To improve air temperature observation accuracy and correct historical temperature of weather stations, a radiation error correction method is proposed. The correction method is based on a computational fluid dynamics (CFD) method and a genetic algorithm (GA) method. The CFD method is implemented to obtain the radiation error of the naturally ventilated radiation shield under various environmental conditions. Then, a radiation error correction equation is obtained by fitting the CFD results using the GA method. To verify the performance of the correction equation, the naturally ventilated radiation shield and an aspirated temperature measurement platform are characterized in the same environment to conduct the intercomparison. The aspirated temperature measurement platform serves as an air temperature reference. The mean radiation error given by the intercomparison experiments is 0.23 K, and the mean radiation error given by the correction equation is 0.2 K. This radiation error correction method allows the radiation error to be reduced by approximately 87 %. The mean absolute error and the root mean square error between the radiation errors given by the correction equation and the radiation errors given by the experiments are 0.036 K and 0.045 K, respectively.


Computational fluid dynamics Naturally ventilated radiation shield Radiation error Surface air temperature 



This work was supported by the Special Scientific Research Fund of Meteorological Public Welfare Profession of China (GYHY200906037 and GYHY201306079), the National Natural Science Foundation of China (41275042) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD-II).


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological AdministrationNanjingChina
  2. 2.School of Atmospheric PhysicsNanjing University of Information Science and TechnologyNanjingChina
  3. 3.Jiangsu Key Laboratory of Meteorological Observation and Information ProcessingNanjingChina
  4. 4.Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment TechnologyNanjingChina
  5. 5.Jiangsu Meteorological Observation CenterNanjingChina

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