A blue-band surface residual correction method for land aerosol optical depth retrieval from DQ-1 WSI

Surface reflectance prior uncertainty remains a major source of error in land aerosol optical depth (AOD) retrieval, particularly over complex surfaces and for newly launched satellite sensors lacking long-term observations for constructing stable surface priors. Here, we develop a hybrid AOD retrieval framework for the DQ-1 Wide Swath Imager (WSI) that integrates a static surface reflectance prior, machine-learning-based blue-band surface residual correction, and a physically based lookup-table (LUT) inversion. A multi-band static surface prior is first constructed from quality-controlled clear-sky observations under low-to-moderate aerosol loading. Rather than directly predicting AOD, a random forest model is used to estimate the residual between the static and reference surface terms at 0.443 µm using the static blue-band prior, top-of-atmosphere reflectance, normalized difference vegetation index (NDVI), viewing geometry, and elevation. The corrected blue-band surface term is then used in the conventional LUT retrieval, retaining the physical aerosol inversion while using machine learning only to correct surface-prior mismatch. MCD19A2 AOD is used as an external atmospheric constraint in the offline construction of LUT-derived reference surface terms and as a reference for regional spatial and hold-out-date consistency analyses, whereas AERONET observations provide independent ground-based validation. Relative to the static-prior LUT retrieval, the residual-corrected retrieval reduced the AERONET-based RMSE from 0.256 to 0.107 and the mean bias error from 0.187 to 0.059 in spring 2025 (March–May), while increasing the fraction within the expected-error envelope from 14.8 % to 55.6 %. Improvement was also observed for autumn–winter 2025 (October–December) using a season-specific static prior together with a seasonally adjusted LUT and RF model. When the spring-2025 configuration was applied to spring 2026 (March–May) without retraining or recalibration, the RMSE decreased from 0.330 to 0.153. In a held-out-scene evaluation, the blue-band surface-term MAE relative to the LUT-derived reference surface term decreased from 0.0088 to 0.0044, and hold-out-date comparisons showed regional consistency with MCD19A2. Together, these evaluations show that correcting blue-band surface-prior mismatch improves DQ-1 WSI land AOD retrieval while retaining the LUT-based physical inversion under the BTH conditions examined here.