Long-term changes and variability in a transient simulation with a chemistry-climate model employing realistic forcing

Dameris, Martin; Grewe, Volker; Ponater, M.; Deckert, Rudolf; Eyring, Veronika; Mager, F.; Matthes, Sigrun; Schnadt, C.; Stenke, Andrea; Steil, B.; Brühl, Christoph; Giorgetta, Marco

doi:10.5194/acp-5-2121-2005

Cited by 116 publications

(103 citation statements)

References 87 publications

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“…Emission fluxes of CO and nitrogen oxides (NO x ) from industrial sources, traffic and biomass burning are taken from the RETRO dataset (Schultz and Rast, 2007), whereas emissions from soils and oceans follow Horowitz et al (2003). For NO x emissions from aircraft the dataset described by Dameris et al (2005) is used. NO x emissions from lightning are based on the satellite-based dataset of Turman and Edgar (1982), with a global annual NO x production of 4 Tg(N) yr −1 .…”

Section: Mezonmentioning

confidence: 99%

The SOCOL version 3.0 chemistry–climate model: description, evaluation, and implications from an advanced transport algorithm

et al. 2013

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Abstract. We present the third generation of the coupled chemistry-climate model (CCM) SOCOL (modeling tools for studies of SOlar Climate Ozone Links). The most notable modifications compared to the previous model version are (1) the dynamical core has been updated with the fifth generation of the middle-atmosphere general circulation model MA-ECHAM (European Centre/HAMburg climate model), and (2) the advection of the chemical species is now calculated by a mass-conserving and shape-preserving flux-form transport scheme instead of the previously used hybrid advection scheme. The whole chemistry code has been rewritten according to the ECHAM5 infrastructure and transferred to Fortran95. In contrast to its predecessors, SOCOLvs3 is now fully parallelized. The performance of the new SOCOL version is evaluated on the basis of transient model simulations (1975-2004) with different horizontal (T31 and T42) resolutions, following the approach of the CCMVal-1 model validation activity. The advanced advection scheme significantly reduces the artificial loss and accumulation of tracer mass in regions with strong gradients that was observed in previous model versions. Compared to its predecessors, SOCOLvs3 generally shows more realistic distributions of chemical trace species, especially of total inorganic chlorine, in terms of the mean state, but also of the annual and interannual variability. Advancements with respect to model dynamics are for example a better representation of the stratospheric mean state in spring, especially in the Southern Hemisphere, and a slowdown of the upward propagation in the tropical lower stratosphere. Despite a large number of improvements model deficiencies still remain. Examples include a too-fast vertical ascent and/or horizontal mixing in the tropical stratosphere, the cold temperature bias in the lowermost polar stratosphere, and the overestimation of polar total ozone loss during Antarctic springtime.

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Section: Mezonmentioning

confidence: 99%

The SOCOL version 3.0 chemistry–climate model: description, evaluation, and implications from an advanced transport algorithm

et al. 2013

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“…The model is an updated version of ECHAM4.L39(DLR)/CHEM (E39C) (Hein et al, 2001;Dameris et al, 2005) with the former semi-Lagrangian advection scheme replaced by the fully Lagrangian advection scheme ATTILA (Reithmeier and Sausen, 2002). In AT-TILA, the mass of the model atmosphere is divided into approximately 500 000 air parcels of equal mass which are advected three-dimensionally using the actual model wind field.…”

Section: Appendix a The E39c-a Model And Simulation Descriptionmentioning

confidence: 99%

Attribution of ozone changes to dynamical and chemical processes in CCMs and CTMs

et al. 2011

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Abstract. Chemistry-climate models (CCMs) are commonly used to simulate the past and future development of Earth's ozone layer. The fully coupled chemistry schemes calculate the chemical production and destruction of ozone interactively and ozone is transported by the simulated atmospheric flow. Due to the complexity of the processes acting on ozone it is not straightforward to disentangle the influence of individual processes on the temporal development of ozone concentrations. A method is introduced here that quantifies the influence of chemistry and transport on ozone concentration changes and that is easily implemented in CCMs and chemistry-transport models (CTMs). In this method, ozone tendencies (i.e. the time rate of change of ozone) are partitioned into a contribution from ozone production and destruction (chemistry) and a contribution from transport of ozone (dynamics). The influence of transport on ozone in a specific region is further divided into export of ozone out of that region and import of ozone from elsewhere into that region. For this purpose, a diagnostic is used that disaggregates the ozone mixing ratio field into 9 separate fields according to in which of 9 predefined regions of the atmosphere the ozone originated. With this diagnostic the ozone mass fluxes between these regions are obtained. Furthermore, this method is used here to attribute long-term changes in ozone to chemistry and transport. The relative change in ozone from one period to another that is due to changes in production or destruction rates, or due to changes in import or export of ozone, are quantified. As such, the diagnostics introduced here can be used to attribute changes in ozone on monthly, interannual and long-term time-scales to the responsible mechanisms. Results from a CCM simulation are shown here as examples, with the main focus of the paper being on introducing the method.

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“…For example, Laat et al (2001) consider the evolution of tropospheric ozone concentrations over the Indian Ocean during the spring of 1995 to evaluate the large-scale advection processes and associated tracer transport in their model. Dameris et al (2005) consider the impact of various "forcings" (including sea surface temperatures, volcanoes, and the solar cycle) on chemical composition to investigate which processes are well/poorly represented in models. Akiyoshi et al (2016) present a case study of the evolution of chemical species during the stratospheric sudden warming of winter 2010 using both a nudged model and observations to study the structure in the chemical fields.…”

Section: Introductionmentioning

confidence: 99%

The Met Office HadGEM3-ES chemistry–climate model: evaluation of stratospheric dynamics and its impact on ozone

et al. 2017

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Abstract. Free-running and nudged versions of a Met Office chemistry-climate model are evaluated and used to investigate the impact of dynamics versus transport and chemistry within the model on the simulated evolution of stratospheric ozone. Metrics of the dynamical processes relevant for simulating stratospheric ozone are calculated, and the free-running model is found to outperform the previous model version in 10 of the 14 metrics. In particular, large biases in stratospheric transport and tropical tropopause temperature, which existed in the previous model version, are substantially reduced, making the current model more suitable for the simulation of stratospheric ozone. The spatial structure of the ozone hole, the area of polar stratospheric clouds, and the increased ozone concentrations in the Northern Hemisphere winter stratosphere following sudden stratospheric warmings, were all found to be sensitive to the accuracy of the dynamics and were better simulated in the nudged model than in the free-running model. Whilst nudging can, in general, provide a useful tool for removing the influence of dynamical biases from the evolution of chemical fields, this study shows that issues can remain in the climatology of nudged models. Significant biases in stratospheric vertical velocities, age of air, water vapour, and total column ozone still exist in the Met Office nudged model. Further, these can lead to biases in the downward flux of ozone into the troposphere.

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Long-term changes and variability in a transient simulation with a chemistry-climate model employing realistic forcing

Cited by 116 publications

References 87 publications

The SOCOL version 3.0 chemistry–climate model: description, evaluation, and implications from an advanced transport algorithm

The SOCOL version 3.0 chemistry–climate model: description, evaluation, and implications from an advanced transport algorithm

Attribution of ozone changes to dynamical and chemical processes in CCMs and CTMs

The Met Office HadGEM3-ES chemistry–climate model: evaluation of stratospheric dynamics and its impact on ozone

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