Abstract

Abstract. Multi-model ensembles are frequently used to assess understanding of the response of ozone and methane lifetime to changes in emissions of ozone precursors such as NOx, VOCs (volatile organic compounds) and CO. When these ozone changes are used to calculate radiative forcing (RF) (and climate metrics such as the global warming potential (GWP) and global temperature-change potential (GTP)) there is a methodological choice, determined partly by the available computing resources, as to whether the mean ozone (and methane) concentration changes are input to the radiation code, or whether each model's ozone and methane changes are used as input, with the average RF computed from the individual model RFs. We use data from the Task Force on Hemispheric Transport of Air Pollution source–receptor global chemical transport model ensemble to assess the impact of this choice for emission changes in four regions (East Asia, Europe, North America and South Asia). We conclude that using the multi-model mean ozone and methane responses is accurate for calculating the mean RF, with differences up to 0.6% for CO, 0.7% for VOCs and 2% for NOx. Differences of up to 60% for NOx 7% for VOCs and 3% for CO are introduced into the 20 year GWP. The differences for the 20 year GTP are smaller than for the GWP for NOx, and similar for the other species. However, estimates of the standard deviation calculated from the ensemble-mean input fields (where the standard deviation at each point on the model grid is added to or subtracted from the mean field) are almost always substantially larger in RF, GWP and GTP metrics than the true standard deviation, and can be larger than the model range for short-lived ozone RF, and for the 20 and 100 year GWP and 100 year GTP. The order of averaging has most impact on the metrics for NOx, as the net values for these quantities is the residual of the sum of terms of opposing signs. For example, the standard deviation for the 20 year GWP is 2–3 times larger using the ensemble-mean fields than using the individual models to calculate the RF. The source of this effect is largely due to the construction of the input ozone fields, which overestimate the true ensemble spread. Hence, while the average of multi-model fields are normally appropriate for calculating mean RF, GWP and GTP, they are not a reliable method for calculating the uncertainty in these fields, and in general overestimate the uncertainty.

Highlights

  • One method for characterising uncertainty in the climate sciences is to perform large, multi-model ensemble studies

  • The global-mean radiative forcing (RF) for any given model is less dependent on the location of the emission for the CO case than for the VOCs or NOx case, as CO has a much longer atmospheric residence time of 3 months, which is of the same order as the hemispheric atmospheric mixing time

  • This study has investigated the derivation of RF and climate emission metrics (GWP and global temperature-change potential (GTP) at various time horizons) for emissions of short-lived climate forcing agents from multi-model assessments, using the results of the Hemispheric Transport of Air Pollutants (HTAP) ozone precursor emission experiments as an example

Read more

Summary

Introduction

One method for characterising uncertainty in the climate sciences is to perform large, multi-model ensemble studies. This approach, provided that the range of models do capture the range of climate responses to an applied perturbation, provides far more information, on the most likely climate response, and on the likelihood of a range of possible responses – i.e. the uncertainty associated with the mean response. One common example of such an application of a model ensemble is in the calculation of climate metrics and their associated uncertainty. It is desirable to be able to compute such metrics quickly and efficiently from input ensembles, but where possible without compromising on the quality of the reported values and, crucially, their associated

Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.