A Novel Calibration Method for Pure Rotational Raman Lidar Temperature Profiling

Jingxi He, Siying Chen*, Yinchao Zhang, Pan Guo, He Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

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 languageEnglish
Pages (from-to)10,925-10,934
JournalJournal of Geophysical Research: Atmospheres
Volume123
Issue number19
DOIs
Publication statusPublished - 16 Oct 2018

Keywords

  • atmospheric temperature
  • pure rotational Raman lidar
  • remote sensing

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