Integrating MODIS and TROPOMI Atmospheric Products into TUV for High-Accuracy Surface UV Irradiance Modeling in the Mountainous Southwest USA
- 1Department of Chemistry and Physics, Southern Utah University, 351 W University Blvd., Cedar City, UT 84720, USA
- 2Physics Department, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, USA
Abstract
Accurate characterization of surface ultraviolet (UV) irradiance is important for many applications but remains challenging in mountainous terrain where atmospheric and surface heterogeneity introduce significant uncertainty. Radiative transfer (RT) models provide physically rigorous simulations but are limited to the precision of input parameters. This study develops and validates a multi-sensor satellite-integrated framework that combines MODIS-derived aerosol optical depth with TROPOMI-derived ozone and nitrogen dioxide within the Tropospheric Ultraviolet and Visible (TUV) radiative transfer model. The methodology is applied to three mountainous sites in the southwestern United States (El Paso, TX; Flagstaff, AZ; and Logan, UT) and evaluated under clear-sky conditions using high-resolution UV-MFRSR measurements at 332 nm and 368 nm. An uncertainty budget was constructed to attribute random and systematic error sources. The framework achieved strong agreement with observations, with R² exceeding 0.99 in most cases and RMSE generally below 3% of the observed range, outperforming typical satellite-derived UV products in complex terrain. A consistent wavelength-dependent bias was identified and attributed primarily to single-scattering albedo at 332 nm and surface albedo at 368 nm. These results demonstrate that a low-cost, reproducible, satellite-driven modeling approach can deliver high-accuracy UV irradiance estimates in data-sparse, topographically complex regions.
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BibTeX
@article{taylor2026integrating,
title = {{Integrating MODIS and TROPOMI Atmospheric Products into TUV for High-Accuracy Surface UV Irradiance Modeling in the Mountainous Southwest USA}},
author = {Nethaneel R. A. Taylor and Richard Medina-Calderon and Rosa M. Fitzgerald},
journal = {Atmosphere},
year = {2026},
month = sep,
doi = {10.3390/atmos17100945},
url = {https://doi.org/10.3390/atmos17100945},
note = {CC BY},
}
RIS
TY - JOUR
TI - Integrating MODIS and TROPOMI Atmospheric Products into TUV for High-Accuracy Surface UV Irradiance Modeling in the Mountainous Southwest USA
AU - Nethaneel R. A. Taylor
AU - Richard Medina-Calderon
AU - Rosa M. Fitzgerald
PY - 2026
DA - 2026/09/01
JO - Atmosphere
DO - 10.3390/atmos17100945
UR - https://doi.org/10.3390/atmos17100945
AB - Accurate characterization of surface ultraviolet (UV) irradiance is important for many applications but remains challenging in mountainous terrain where atmospheric and surface heterogeneity introduce significant uncertainty. Radiative transfer (RT) models provide physically rigorous simulations but are limited to the precision of input parameters. This study develops and validates a multi-sensor satellite-integrated framework that combines MODIS-derived aerosol optical depth with TROPOMI-derived ozone and nitrogen dioxide within the Tropospheric Ultraviolet and Visible (TUV) radiative transfer model. The methodology is applied to three mountainous sites in the southwestern United States (El Paso, TX; Flagstaff, AZ; and Logan, UT) and evaluated under clear-sky conditions using high-resolution UV-MFRSR measurements at 332 nm and 368 nm. An uncertainty budget was constructed to attribute random and systematic error sources. The framework achieved strong agreement with observations, with R² exceeding 0.99 in most cases and RMSE generally below 3% of the observed range, outperforming typical satellite-derived UV products in complex terrain. A consistent wavelength-dependent bias was identified and attributed primarily to single-scattering albedo at 332 nm and surface albedo at 368 nm. These results demonstrate that a low-cost, reproducible, satellite-driven modeling approach can deliver high-accuracy UV irradiance estimates in data-sparse, topographically complex regions.
SN - 2073-4433
ER -