Approach to the design and data analysis of a limb-scanning experiment

Area of Science:

• Atmospheric spectroscopy
• Remote sensing
• Geosciences

Background:

• Designing atmospheric spectroscopic measurements requires optimizing instrumental, observational, and retrieval parameters.
• Limb-scanning techniques are crucial for retrieving constituent altitude profiles.

Purpose of the Study:

• To develop and present mathematical tools for optimizing atmospheric spectroscopic measurements.
• To analyze the trade-off between vertical resolution and profile error in constituent retrieval.

Main Methods:

• Derivation of mathematical tools to study the resolution-error trade-off.
• Implementation of these tools for satellite-based measurement design.
• Simulation of retrieval techniques based on global inversion.

Main Results:

• Identification of optimal parameters for satellite measurements, balancing resolution and uncertainty.
• Successful simulation of global inversion retrieval techniques.
• Comparison of a priori uncertainty estimates with balloon-borne experiment data.

Conclusions:

• The developed mathematical framework effectively aids in designing atmospheric spectroscopic measurements.
• The tools provide a reliable method for estimating uncertainties and optimizing retrieval strategies.
• The approach is validated through applications in both satellite and balloon-borne experiments.