Related Experiment Video
Updated: May 19, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
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
Abstract:
The overlap function of a Raman channel for a lidar system is retrieved by nonlinear regression using an analytic description of the optical system and a simple model for the extinction profile, constrained by aerosol optical thickness. Considering simulated data, the scheme is successful even where the aerosol profile deviates significantly from the simple model assumed. Application to real data is found to reduce by a factor of 1.4-2.0 the root-mean-square difference between the attenuated backscatter coefficient as measured by the calibrated instrument and a commercial instrument.
Related Concept Videos
Calibration Curves: Linear Least Squares
For data that follow a straight line, the standard method for fitting is the linear...
Calibration Curves: Correlation Coefficient
Application of Linearization and Approximation
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Linearization and Approximation
Plotting and Calibrating the Root Locus
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is observed...

