Abstract
Atmospheric lidar observations provide a unique capability to directly observe the vertical profile of cloud and aerosol scattering properties and have proven to be an important capability for the atmospheric science community. For this reason NASA and ESA have put a major emphasis on developing both space and ground based lidar instruments. Measurement noise (solar background and detector noise) has proven to be a significant limitation and is typically reduced by temporal and vertical averaging. This approach has significant limitations as it results in significant reduction in the spatial information and can introduce biases due to the non-linear relationship between the signal and the retrieved scattering properties. This paper investigates a new approach to de-noising and retrieving cloud and aerosol backscatter properties from lidar observations that leverages a technique developed for medical imaging to de-blur and de-noise images; the accuracy is defined as the error between the true and inverted photon rates. Hence non-linear bias errors can be mitigated and spatial information can be preserved.
Highlights
The scatter properties of cloud and aerosol particulates can be inverted through an atmospheric lidar system, and are of great use to the atmospheric science community
NASA has invested in several lidar instruments, eg
The backscatter volume coefficient - or backscatter in short, is one of the scatter properties that can be inverted from HSRL photon rate observations, without making a priori assumptions about the backscatter phase function
Summary
The scatter properties of cloud and aerosol particulates can be inverted through an atmospheric lidar system, and are of great use to the atmospheric science community. The backscatter volume coefficient - or backscatter in short, is one of the scatter properties that can be inverted from HSRL photon rate observations, without making a priori assumptions about the backscatter phase function. Nonlinear bias errors are introduced into the retrievals whenever averaging is performed over a region of a cloud which is non-homogenous. This is especially true when the scattering volume coefficient change several orders in magnitude over a short period of time. This paper makes a contribution by demonstrating that an accurate backscatter profile, relative to the standard retrieval, can be inverted from HSRL measured photon rates. For the quantitative approach a simulation is used to quantify the performance of the backscatter estimates
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