| 光谱学与光谱分析 |
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| The Application of the L-Curve Method in the Retrieval of Temperature Profiles Using Ground-Based Hyper-Spectral Infrared Radiance |
| HUANG Wei, LIU Lei*, GAO Tai-chang, LI Shu-lei, HU Shuai |
| College of Meteorology and Oceanography, the PLA University of Science and Technology, Nanjing 211101, China |
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Abstract The thermodynamic profiles of Planetary Boundary Layer could be retrieved by using ground-based hyper-spectral infrared radiance. The AERIoe algorithm has a better performance at the dependency of initial profiles than the “onion peeling” method which was originally applied in the Atmospheric Emitted Radiance Interferometer. The regularization parameter is the key to the AERIoe algorithm, and the strategy for choosing the regularization parameter in the retrieval algorithm is based on the empirical method, which requires too much time for computation while the empirical method needs many iteration steps. A L-curve criterion is proposed to calculate the regularization parameter in AERIoe algorithm. The L-curve criterion is based on a log-log plot of corresponding values of the residual and solution norms, and the optimal regularization parameter corresponds to a point on the curve near the “corner” of the L-shaped region. Therefore, the L-curve criterion has better theoretical basis than the traditional empirical method. The result of retrieval experiment using the observed data collected at the SGP site of the year 2011 shows that, the L-curve method has a good performance in terms of stability, convergence and accuracy of the retrieval. Compared with empirical method, L-curve algorithm converges more quickly which saves much computation time when retrieving the temperature profiles. When considering the retrieval accuracy, the L-curve method has a better behavior at the middle and top of the boundary layer, with an improvement of 0.2 K of RMSE at the altitude of 1～3 km than the empirical method. Therefore, the L-curve algorithm has a better performance compared with the empirical method when choosing the regularization parameter in the retrieval of temperature profiles using the ground-based hyper-spectral infrared radiance.
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Received: 2016-02-22
Accepted: 2016-05-16
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Corresponding Authors:
LIU Lei
E-mail: liuleidll@gmail.com
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