Gappy POD-based reconstruction of the temperature field in Tibet

  • Basang Tsering-xiao
  • Qinwu XuEmail author
Original Paper


Meteorological observations in Tibet are poor in quality with a severe amount of missing data; this is mostly caused by extreme climatological conditions and higher maintenance costs. This paper focuses on the imputation of missing data and the reconstruction of the regional temperature field. Due to insufficient observation stations and complicated topography, we employ the weather research and forecasting (WRF) model to produce the proper orthogonal decomposition (POD) basis for the study region. We then develop the gappy POD method for the imputation of missing data. Both methods are compared and tested for various missing data cases, and the results show that the gappy POD method dramatically outperforms the regularized EM algorithm when the amount of missing spatial data is not severe. Furthermore, between the two methods, only the gappy POD method is capable of reconstructing the temperature field at locations where the data are absent. The gappy POD method can also be generalized for data assimilation with the assumption that the data across all model grids have missing values.


Reconstruction Gappy POD Tibet Missing value 



We are immensely grateful to Prof. Pingwen Zhang at School of Mathematical Sciences of PKU and Prof. Yun Chen at National Meteorological Center of CMA for their helpful discussion and valuable suggestions. We would also like to extent our gratitude to the anonymous reviewer for their comments that greatly improved the manuscript.


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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Mathematical Department of Tibet UniversityLhasaPeople’s Republic of China
  2. 2.Department of MathematicsNanjing UniversityNanjingPeople’s Republic of China

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