Fusion of the Arctic Aerosol Optical Depth Based on Improved Bayesian Maximum Entropy
Abstract
The Arctic is a climate-sensitive region where Arctic Amplification is influenced by aerosol radiative forcing. Aerosol Optical Depth (AOD), quantifying aerosol extinction, is essential for assessing its effects on Arctic climate and environment. However, single-satellite AOD products exhibit large uncertainties and data gaps in the Arctic due to sensor limitations and complex surface conditions. The conventional Bayesian Maximum Entropy (BME) framework’s dependence on least-squares covariance modeling restricts its ability to model complex, nonstationary high-dimensional parameter spaces. To address these limitations, we incorporated Particle Swarm Optimization (PSO) algorithm with global search capability into the BME framework, creating a PSO-BME hybrid model that enhances both the stability and accuracy of Arctic AOD fusion. To optimize Arctic AOD fusion, we tested 24 combinations of four key parameters, using iterative fusion and sensitivity analysis to assess accuracy impacts. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied to identify the optimal parameter configuration. Results indicate that PSO-BME effectively integrates AOD data from MODIS and MISR. In overlapping regions, the fusion AOD achieves an RMSE of 0.056, an Expected Error of 76.7%, and a correlation coefficient of 0.66, while in unobserved regions, the accuracy remains acceptable. The annual coverage of the fusion AOD increases to 41.61% (compared to 14.49% of MODIS and 1.40% of MISR). Spatiotemporal analyses indicate that the fusion product exhibits a smoother spatial pattern and better captures overall variability, while its evolution suggests a dual-influence mechanism driven by Arctic meteorology and long-range transport from mid–low latitudes. Enhanced AOD coverage and accuracy materially advance Arctic climate science by providing stronger observational constraints for atmospheric research and related studies in the Arctic.
Fields of Study & Subjects
Atmospheric aerosols and clouds
Atmospheric chemistry and aerosols
Meteorological Phenomena and Simulations
Publication details
- Journal / source
- IEEE Transactions on Geoscience and Remote Sensing
- Volume
- 64
- Pages
- 1–15
- Publication date
- 1 January 2026