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Applications of random balance design Fourier amplitude sensitivity test and extended Fourier amplitude sensitivity test in the parameter sensitivity analysis of land surface process model
Author(s) -
Hongqi Li
Publication year - 2015
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.64.069201
Subject(s) - sensitivity (control systems) , amplitude , fourier transform , surface roughness , fourier analysis , environmental science , latent heat , meteorology , physics , optics , mathematics , mathematical analysis , electronic engineering , engineering , quantum mechanics
In this paper, we discuss the applications of random balance design Fourier amplitude sensitivity test (RBD-FAST) and extended Fourier amplitude sensitivity test (EFAST) in the parameter sensitivity analysis of land surface process model. We use the common land model and data of Tongyu station, which is a reference site of CEOP in the semi-arid regions, use five model outputs (sensible heat flux, latent heat flux, surface temperature, temperature of air at 2 m over surface, moisture of air at 2 m over surface) as focus output, and use 11 model parameter (soil depth, the soil proportion of 1-5 layers of soil, the porosity of soil, the max dew depth, the roughness of the air between surface and the canopy, and the drag coefficient under the canopy) as the parameters to be analyzed. After the 10 RBD-FAST experiments, we obtain the first-order sensitivity results, and we gain not only first-order sensitivity but also the total sensitivity after the EFAST experiment. The first-order results of two methods show their consistency. The RBD-FAST takes less computing time and is easy to implemente, while the EFAST also has a more comprehensive and reasonable total sensitivity result. All results above illustrate the applications of both RBD-FAST and EFAST in the parameter sensitivity analysis of land surface model. Researchers can choose the suitable one to solve the different problems.

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