Abstract
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.
Original language | English |
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Pages (from-to) | 10,925-10,934 |
Journal | Journal of Geophysical Research: Atmospheres |
Volume | 123 |
Issue number | 19 |
DOIs | |
Publication status | Published - 16 Oct 2018 |
Keywords
- atmospheric temperature
- pure rotational Raman lidar
- remote sensing