On the accuracy of covariance matrix: Hessian versus Gauss-Newton methods in atmospheric remote sensing with infrared spectroscopy

Keyphrases

• Hessian Method 100%
• Gauss-Newton Method 100%
• State Vector 100%
• Hessian 100%
• Atmospheric Remote Sensing 100%
• Uncertainity 75%
• Eigenvector 50%
• Linear Approximation 50%
• Original State 50%
• Inverse Covariance Matrix 25%
• Gauss-Newton Algorithm 25%
• Newton's Approach 25%
• Quadratic Forms 25%
• Orthogonal Coordinates 25%
• Inter-levels Correlation 25%
• Atmospheric Trace Gases 25%
• Small Step 25%
• Coordinate System 25%
• Mixing Errors 25%
• Trace Species 25%
• Radiative Transfer 25%
• Gauss-Newton 25%
• Error Covariance Matrix 25%
• Cost Function Approximation 25%
• Vector Space 25%
• Retrieval Scheme 25%
• Flat Directions 25%
• Larger Step Size 25%
• Adaptive Algorithm 25%

Engineering

• Covariance Matrix 100%
• Gauss 100%
• Newton's Method 100%
• Step Size α 100%
• Eigenvector 66%
• Coordinate System 33%
• Error Covariance Matrix 33%
• Emission Spectra 33%
• Space Vector 33%
• Coordinate Transformation 33%

Earth and Planetary Sciences

• Hessian Matrix 100%
• Infrared Spectroscopy 100%
• Eigenvector 50%
• Coordinate Transformation 25%
• Radiative Transfer 25%
• Vector Space 25%
• Transfer Function 25%