Journal Article

FZJ-2021-06135

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Mapping Yearly Fine Resolution Global Surface Ozone through the Bayesian Maximum Entropy Data Fusion of Observations and Model Output for 1990–2017

DeLang, M. N. ; Becker, J. S. ; Chang, K.-L. ; Serre, M. L. ; Cooper, O. R. ; Schultz, M.FZJ* ; Schröder, S.FZJ* ; Lu, X. ; Zhang, L. ; Deushi, M. ; Josse, B. ; Keller, C. A. ; Lamarque, J.-F. ; Lin, M. ; Liu, J. ; Marécal, V. ; Strode, S. A. ; Sudo, K. ; Tilmes, S. ; Zhang, L. ; Cleland, S. E. ; Collins, E. L. ; Brauer, M. ; West, J. J. (Corresponding author)

2021
American Chemical Society Columbus, Ohio

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Please use a persistent id in citations: http://hdl.handle.net/2128/30328  doi:10.1021/acs.est.0c07742

Abstract: Estimates of ground-level ozone concentrations are necessary to determine the human health burden of ozone. To support the Global Burden of Disease Study, we produce yearly fine resolution global surface ozone estimates from 1990 to 2017 through a data fusion of observations and models. As ozone observations are sparse in many populated regions, we use a novel combination of the M3Fusion and Bayesian Maximum Entropy (BME) methods. With M3Fusion, we create a multimodel composite by bias-correcting and weighting nine global atmospheric chemistry models based on their ability to predict observations (8834 sites globally) in each region and year. BME is then used to integrate observations, such that estimates match observations at each monitoring site with the observational influence decreasing smoothly across space and time until the output matches the multimodel composite. After estimating at 0.5° resolution using BME, we add fine spatial detail from an additional model, yielding estimates at 0.1° resolution. Observed ozone is predicted more accurately (R2 = 0.81 at the test point, 0.63 at 0.1°, and 0.62 at 0.5°) than the multimodel mean (R2 = 0.28 at 0.5°). Global ozone exposure is estimated to be increasing, driven by highly populated regions of Asia and Africa, despite decreases in the United States and Russia.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)
2. Earth System Data Exploration (ESDE) (ESDE)

Appears in the scientific report 2021

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Database coverage:
; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Agriculture, Biology and Environmental Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection ; Zoological Record

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