Global Surface Ozone Concentration Dataset 1990-2017 Generated by Bayesian Maximum Entropy Data Fusion With RAMP Bias Correction

This dataset reports estimates of surface ozone concentration at fine spatial resolution for 1990 to 2017, at 0.5 degree horizontal resolution. Also reported is the variance. Estimates correspond to this paper: Becker, J. S., DeLang, M. N., K.-L. Chang, M. L. Serre, O. R. Cooper, H. Wang, M. G. Schultz, S. Schroder, X. Lu, L. Zhang, M. Deushi, B. Josse, C. A. Keller, J.-F. Lamarque, M. Lin, J. Liu, V. Marecal, S. A. Strode, K. Sudo, S. Tilmes, L. Zhang, M. Brauer, and J. J. West (2023) Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy data fusion to map global surface ozone concentration, Elementa Science of the Anthropocene, 11: 1, doi: 10.1525/elementa.2022.00025. The dataset reports estimates of surface ozone for the OSDMA8 metric (the 6-month ozone-season average of the daily maximum 8-hr concentration), estimated through a data fusion of ozone observations from the Tropospheric Ozone Assessment Report (TOAR) database, and output from multiple global atmospheric models. Estimates are created in each year by a combination of M3Fusion to create a multi-model composite, Regional Air Quality Model Performance (RAMP) regional and nonlinear bias correction, and Bayesian Maximum Entropy (BME) data fusion in space and time. The estimates here are the final results using a weighted RAMP bias correction.