Journal Article FZJ-2018-01627

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Tropospheric Ozone Assessment Report: Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends

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2018
BioOne Washington, DC

Elementa 6(10), 265 () [10.1525/elementa.265]

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Abstract: The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty.

Classification:

Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
  2. Troposphäre (IEK-8)
Research Program(s):
  1. 512 - Data-Intensive Science and Federated Computing (POF3-512) (POF3-512)
  2. Earth System Data Exploration (ESDE) (ESDE)

Appears in the scientific report 2018
Database coverage:
Medline ; Creative Commons Attribution CC BY (No Version) ; DOAJ ; OpenAccess ; BIOSIS Previews ; DOAJ Seal ; Thomson Reuters Master Journal List ; Zoological Record
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The record appears in these collections:
Dokumenttypen > Aufsätze > Zeitschriftenaufsätze
Institutssammlungen > ICE > ICE-3
Workflowsammlungen > Öffentliche Einträge
Institutssammlungen > JSC
IEK > IEK-8
Publikationsdatenbank
Open Access

 Datensatz erzeugt am 2018-03-05, letzte Änderung am 2024-07-12


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