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A Novel Calibration Method for Pure Rotational Raman Lidar Temperature Profiling
Author(s) -
He Jingxi,
Chen Siying,
Zhang Yinchao,
Guo Pan,
Chen He
Publication year - 2018
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2018jd029062
Subject(s) - lidar , calibration , profiling (computer programming) , raman spectroscopy , inversion (geology) , backscatter (email) , materials science , remote sensing , temperature measurement , computational physics , environmental science , biological system , computer science , optics , physics , geology , mathematics , statistics , thermodynamics , paleontology , telecommunications , structural basin , wireless , operating system , biology
We propose a new calibration method for pure rotational Raman (PRR) lidar temperature profiling based on the different temperature sensitivities of Stocks and anti‐Stocks PRR lines. This method reconstructs the expression of the differential backscatter cross section according to the temperature dependencies of each component and forms a temperature factor and a calibration factor in the intensity ratio. With these factors, the temperature is retrievable from the lidar return. The effectiveness and accuracy of the proposed method have been verified through simulations and experiments. The inversion error can be reduced by ~50% compared with the commonly used calibration methods in weak signal‐to‐noise situations.