Dr Adam Povey FRMetSoc FHEA

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. Applicationto real dataisfound 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. © 2012 Optical Society of America.

Abstract:

The overlap function of a Raman channel for a lidar system is retrieved by non-linear 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.

Abstract:

Lidars are ideally placed to investigate the effects of aerosol and cloud on the climate system due to their unprecedented vertical and temporal resolution. Dozens of techniques have been developed in recent decades to retrieve the extinction and backscatter of atmospheric particulates in a variety of conditions. These methods, though often very successful, are fairly ad hoc in their construction, utilising a wide variety of approximations and assumptions that makes comparing the resulting data products with independent measurements difficult and their implementation in climate modelling virtually impossible. As with its application to satellite retrievals, the methods of non-linear regression can improve this situation by providing a mathematical framework in which the various approximations, estimates of experimental error, and any additional knowledge of the atmosphere can be clearly defined and included in a mathematically ‘optimal’ retrieval method, providing rigorously derived error estimates. In addition to making it easier for scientists outside of the lidar field to understand and utilise lidar data, it also simplifies the process of moving beyond extinction and backscatter coefficients and retrieving microphysical properties of aerosols and cloud particles. Such methods have been applied to a prototype Raman lidar system. A technique to estimate the lidar’s overlap function using an analytic model of the optical system and a simple extinction profile has been developed. This is used to calibrate the system such that a retrieval of the profile extinction and backscatter coefficients can be performed using the elastic and nitrogen Raman backscatter signals.