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Estimation of a lidar's overlap function and its calibration by nonlinear regression
Adam C Povey1, Roy G Grainger, Daniel M Peters
1Department of Atmospheric, Oceanic, and Planetary Physics, University of Oxford, Clarendon Laboratory, Oxford, UK. povey@atm.ox.ac.uk
Applied Optics
|August 4, 2012
Summary
This study retrieves the Raman lidar overlap function using nonlinear regression, improving aerosol profile accuracy. The method enhances measurements by reducing discrepancies between calibrated and commercial lidar instruments.
Area of Science:
- Atmospheric Science
- Optical Remote Sensing
Background:
- Accurate lidar measurements are crucial for atmospheric research.
- The overlap function is a critical parameter for Raman lidar calibration.
- Deviations in aerosol profiles can impact lidar data quality.
Purpose of the Study:
- To develop and validate a method for retrieving the Raman lidar overlap function.
- To assess the performance of the retrieval scheme with simulated and real aerosol data.
- To improve the accuracy of attenuated backscatter coefficient measurements.
Main Methods:
- Nonlinear regression analysis was employed.
- An analytic description of the optical system was used.
- A simplified extinction profile model, constrained by aerosol optical thickness, was applied.
Main Results:
- The retrieval scheme proved successful with simulated data, even with significant aerosol profile deviations.
- Application to real data reduced the root-mean-square difference by a factor of 1.4-2.0.
- The method improved agreement between calibrated and commercial lidar instruments.
Conclusions:
- The developed nonlinear regression method effectively retrieves the Raman lidar overlap function.
- This approach enhances the reliability and accuracy of lidar-derived atmospheric measurements.
- The findings contribute to improved aerosol characterization using lidar technology.
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