[Quality Optimization Method for Ambient CO(2) Inversion of High Resolution Fourier Transform Infrared Spectrum]

Area of Science:

• Atmospheric Science
• Climate Science
• Spectroscopy

Background:

• Accurate carbon dioxide (CO2) measurements are essential for understanding the global carbon cycle and predicting climate change.
• Ground-based Fourier transform infrared (FTIR) spectroscopy provides valuable data for CO2 monitoring.
• Existing retrieval methods face challenges with systematic errors and precision.

Purpose of the Study:

• To develop and validate an optimized method for retrieving CO2 products from high-resolution ground-based FTIR spectra.
• To enhance the quality and precision of column-averaged dry air mole fraction of CO2 (XCO2) measurements.
• To improve the correction of systematic errors in CO2 retrievals.

Main Methods:

• Utilized a nonlinear least squares spectral fitting algorithm for CO2 retrieval.
• Converted CO2 vertical column densities (VCDs) to XCO2 using fitted O2 VCDs for error correction.
• Implemented an empirical model to correct for virtual daily variations and introduced a spectra screening rule.

Main Results:

• The optimized method significantly reduced fitting errors by 60%.
• Achieved a two-hour-averaged precision of approximately 0.071% (0.28 ppm) for XCO2.
• The achieved precision meets the Total Carbon Column Observing Network (TCCON) threshold of <0.1%.

Conclusions:

• The proposed optimization method greatly improves the quality of ground-based XCO2 retrievals.
• Enhanced precision in CO2 measurements supports more accurate climate change trend analysis and carbon cycle research.
• The method's performance is comparable to established networks like TCCON.