Scalable Bayesian Geostatistical Regression Model for Bias-Correcting Large-Scale Daily Satellite-Retrieved Aerosol Optical Depth and Chemical Transport Model Simulations.
- DOI
- 10.1016/j.atmosenv.2026.122079
- Published
- 2026 Sep 1
- Container
- Atmospheric environment (Oxford, England : 1994)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.atmosenv.2026.122079,
title = {Scalable Bayesian Geostatistical Regression Model for Bias-Correcting Large-Scale Daily Satellite-Retrieved Aerosol Optical Depth and Chemical Transport Model Simulations.},
author = {Madden WG and Liu Y and Chang HH},
year = {2026},
journal = {Atmospheric environment (Oxford, England : 1994)},
doi = {10.1016/j.atmosenv.2026.122079},
url = {https://doi.org/10.1016/j.atmosenv.2026.122079}
}RIS
TY - JOUR TI - Scalable Bayesian Geostatistical Regression Model for Bias-Correcting Large-Scale Daily Satellite-Retrieved Aerosol Optical Depth and Chemical Transport Model Simulations. AU - Madden WG AU - Liu Y AU - Chang HH PY - 2026 JO - Atmospheric environment (Oxford, England : 1994) DO - 10.1016/j.atmosenv.2026.122079 UR - https://doi.org/10.1016/j.atmosenv.2026.122079 ER -
APA
WG, M., Y, L., & HH, C. (2026). Scalable Bayesian Geostatistical Regression Model for Bias-Correcting Large-Scale Daily Satellite-Retrieved Aerosol Optical Depth and Chemical Transport Model Simulations.. Atmospheric environment (Oxford, England : 1994). https://doi.org/10.1016/j.atmosenv.2026.122079
Source records
- pubmed · retrieved 2026-11-10T15:12:17.403Z