研究目的
To develop and validate a fast atmospheric trace gas retrieval method (FOCAL) for hyperspectral instruments approximating multiple scattering, specifically applied to XCO2 retrievals from OCO-2, aiming to reduce computational costs while maintaining accuracy and precision in XCO2 data products.
研究成果
The FOCAL algorithm successfully reduces computational costs by orders of magnitude while producing XCO2 retrievals with accuracy and precision comparable to more computationally intensive methods. Validation against CAMS, NASA's OCO-2 product, and TCCON data shows good agreement, with systematic differences and single sounding mismatches within expected uncertainty ranges. The study highlights the potential of FOCAL for processing large datasets from current and future satellite missions.
研究不足
The study acknowledges the inherently poor throughput (11%) of the MODIS-based cloud screening used by FOCAL’s preprocessor, which results in fewer soundings compared to NASA's operational product. Additionally, the noise model and bias correction rely on assumptions that may not capture all sources of error, and the validation is limited by the availability and distribution of TCCON ground-based observations.
1:Experimental Design and Method Selection:
The study employs the FOCAL algorithm, which approximates multiple scattering effects with an analytic solution of the radiative transfer problem of an isotropic scattering layer. This method is designed to reduce computational costs significantly.
2:Sample Selection and Data Sources:
The study uses global OCO-2 L1b calibrated radiances from the year 2015 in various observation modes (glint, nadir, target, transition). Data preprocessing includes filtering for quality, cloud, and aerosol contamination.
3:List of Experimental Equipment and Materials:
The primary instrument is the OCO-2 satellite, with additional data from MODIS Aqua for cloud screening and OMI for aerosol index.
4:Experimental Procedures and Operational Workflow:
The workflow includes preprocessing (quality filtering, cloud and aerosol screening), retrieval adaptations (noise model adjustment, zero level offset correction), postprocessing (filtering, bias correction), and validation against CAMS model, NASA's OCO-2 product, and TCCON ground-based data.
5:Data Analysis Methods:
The analysis involves comparing FOCAL retrievals with other datasets (CAMS, NASA OCO-2, TCCON) to assess accuracy, precision, and biases. Statistical methods include standard deviation calculations and bias correction techniques.
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