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Python Tools for Machine Learning Bias Correction, Data Quality Filtering, and Uncertainty Analysis of OCO-2 XCO2 Retrievals
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About this technology
Overview
The package ingests v11 OCO-2 Level 2 Lite files, derives >40 M training examples (2015-2022) matched to TCCON or 100km "small-areas," and trains four Quantile-Regression-Forest models. Inference produces bias-corrected and filtered XCO2 and prediction intervals for every sounding, reducing land's bias RMSE by 20% and recovering usable data previously flagged QF=1.