Show simple item record

Evaluation of the inter-annual variability of stratospheric chemical composition in chemistry-climate models using ground-based multi species time series

dc.contributor.authorPoulain, V.
dc.contributor.authorBekki, S.
dc.contributor.authorMarchand, M.
dc.contributor.authorChipperfield, M.P.
dc.contributor.authorKhodri, M.
dc.contributor.authorLefèvre, F.
dc.contributor.authorDhomse, S.
dc.contributor.authorBodeker, G.E.
dc.contributor.authorToumi, R.
dc.contributor.authorDe Maziere, M.
dc.contributor.authorPommereau, J.-P.
dc.contributor.authorPazmino, A.
dc.contributor.authorGoutail, F.
dc.contributor.authorPlummer, D.
dc.contributor.authorRozanov, E.
dc.contributor.authorMancini, E.
dc.contributor.authorAkiyoshi, H.
dc.contributor.authorLamarque, J.-F.
dc.contributor.authorAustin, J.
dc.date2016
dc.date.accessioned2016-05-09T09:34:37Z
dc.date.available2016-05-09T09:34:37Z
dc.identifier.urihttps://orfeo.belnet.be/handle/internal/3991
dc.descriptionThe variability of stratospheric chemical composition occurs on a broad spectrum of timescales, ranging from day to decades. A large part of the variability appears to be driven by external forcings such as volcanic aerosols, solar activity, halogen loading, levels of greenhouse gases (GHG), and modes of climate variability (quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO)). We estimate the contributions of different external forcings to the interannual variability of stratospheric chemical composition and evaluate how well 3-D chemistry-climate models (CCMs) can reproduce the observed response-forcing relationships. We carry out multivariate regression analyses on long time series of observed and simulated time series of several traces gases in order to estimate the contributions of individual forcings and unforced variability to their internannual variability. The observations are typically decadal time series of ground-based data from the international Network for the Detection of Atmospheric Composition Change (NDACC) and the CCM simulations are taken from the CCMVal-2 REF-B1 simulations database. The chemical species considered are column O3, HCl, NO2, and N2O. We check the consistency between observations and model simulations in terms of the forced and internal components of the total interannual variability (externally forced variability and internal variability) and identify the driving factors in the interannual variations of stratospheric chemical composition over NDACC measurement sites. Overall, there is a reasonably good agreement between regression results from models and observations regarding the externally forced interannual variability. A much larger fraction of the observed and modelled interannual variability is explained by external forcings in the tropics than in the extratropics, notably in polar regions. CCMs are able to reproduce the amplitudes of responses in chemical composition to specific external forcings. However, CCMs tend to underestimate very substantially the internal variability and hence the total interannual variability for almost all species considered. This lack of internal variability in CCMs might partly originate from the surface forcing of these CCMs by analysed SSTs. The results illustrate the potential of NDACC ground-based observations for evaluating CCMs. © 2016.
dc.languageeng
dc.titleEvaluation of the inter-annual variability of stratospheric chemical composition in chemistry-climate models using ground-based multi species time series
dc.typeArticle
dc.subject.frascatiEarth and related Environmental sciences
dc.audienceScientific
dc.subject.freeAtmospheric composition
dc.subject.freeAtmospheric pressure
dc.subject.freeClimate change
dc.subject.freeClimatology
dc.subject.freeGreenhouse gases
dc.subject.freeMultivariant analysis
dc.subject.freeRegression analysis
dc.subject.freeSolar energy
dc.subject.freeTime series
dc.subject.freeTime series analysis
dc.subject.freeUpper atmosphere
dc.subject.freeChemistry-climate models
dc.subject.freeGround-based observations
dc.subject.freeInterannual variability
dc.subject.freeInternational networks
dc.subject.freeMultivariate regression analysis
dc.subject.freeNDACC observation
dc.subject.freeQuasi-biennial oscillation
dc.subject.freeVariability
dc.subject.freeClimate models
dc.source.titleJournal of Atmospheric and Solar-Terrestrial Physics
dc.source.volume145
dc.source.page61
Orfeo.peerreviewedYes
dc.identifier.doi10.1016/j.jastp.2016.03.010
dc.identifier.scopus2-s2.0-84964515016


Files in this item

Thumbnail
Name:
Poulain(2016).pdf
Size:
6.430Mb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record