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Inverse problem and the pseudoempirical orthogonal function method of solution. 2: Use.

A Ben-David, B M Herman, J A Reagan

|June 10, 2010

Summary

This summary is machine-generated.

Determining aerosol size distributions from backscattered radiation requires additional constraints. The accuracy of these solutions depends on the validity of applied constraints, impacting objective analysis.

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Area of Science:

Atmospheric Science
Aerosol Physics
Remote Sensing

Background:

Tropospheric rural aerosol size distributions are crucial for climate and air quality.
Retrieving these distributions from backscattered radiation measurements is an inverse problem.
Existing methods often lack sufficient information for accurate solutions without additional data.

Purpose of the Study:

To investigate the information content obtainable for aerosol size distributions from backscattered radiation.
To demonstrate the necessity and impact of additional information (constraints) in solving this inverse problem.
To evaluate the influence of different constraint types on the accuracy and objectivity of the solutions.

Main Methods:

Analysis of information content from backscattered radiation measurements.
Application of pseudo-empirical orthogonal functions (PEOF).
Implementation of two constraint types: positivity and positivity combined with smoothing.

Main Results:

Measurements alone provide limited information about aerosol size distributions.
Additional constraints are essential for obtaining meaningful solutions.
The choice and validity of constraints significantly influence the accuracy and objectivity of the retrieved size distributions.
Positivity and smoothing constraints affect the functional form and moments of the solutions.

Conclusions:

Objective determination of aerosol size distributions from backscattered radiation is challenging without constraints.
The accuracy of retrieved aerosol size distributions is directly linked to the validity of imposed constraints.
Future research should focus on developing robust and physically meaningful constraints for aerosol remote sensing.