Influence of different convection parameterisations in a GCM

Tost, H.; Jöckel, Patrick; Lelieveld, J.

doi:10.5194/acp-6-5475-2006

Cited by 149 publications

(142 citation statements)

References 49 publications

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“…the "E" in EMAC) have been mostly derived from the physics routines of the ECHAM5 base model (Roeckner et al, 2003, some have been further developed and include advanced or alternative parameterizations. Thus, ECHAM5 physics in EMAC is currently represented by the submodels AEROPT, CLOUDOPT, ORBIT, RAD, SURFACE (see above), GWAVE (non-orographic gravity waves; Baumgaertner et al, 2013), CONVECT (convection; Tost et al, 2006b), and CLOUD. Convective tracer transport is simulated by the submodel CVTRANS (Tost, 2006).…”

Section: Updates To the Model Infrastructurementioning

confidence: 99%

Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

et al. 2016

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Abstract. Three types of reference simulations, as recommended by the Chemistry-Climate Model Initiative (CCMI), have been performed with version 2.51 of the European Centre for Medium-Range Weather Forecasts -Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model: hindcast simulations , hindcast simulations with specified dynamics , i.e. nudged towards ERA-Interim reanalysis data, and combined hindcast and projection simulations . The manuscript summarizes the updates of the model system and details the different model set-ups used, including the on-line calculated diagnostics. Simulations have been performed with two different nudging setups, with and without interactive tropospheric aerosol, and with and without a coupled ocean model. Two different vertical resolutions have been applied. The on-line calculated sources and sinks of reactive species are quantified and a first evaluation of the simulation results from a global perspective is provided as a quality check of the data. The focus is on the intercomparison of the different model set-ups. The simulation data will become publicly available via CCMI and the Climate and Environmental Retrieval and Archive (CERA) database of the German Climate Computing Centre (DKRZ). This manuscript is intended to serve as an extensive reference for further analyses of the Earth System Chemistry integrated Modelling (ESCiMo) simulations.

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Section: Updates To the Model Infrastructurementioning

confidence: 99%

Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

et al. 2016

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“…(b ) Sensitivity to stochastic parametrization Just as simulated climate and variability are sensitive to different deterministic convective schemes (Maloney & Hartmann 2001;Tost et al 2006), one can expect corresponding sensitivity to the introduction of the stochastic parametrization schemes described in §2a. Even the early simple tests of stochastic parametrization produced substantial effects.…”

Section: Issues In Stochastic Deep Convective Parametrizationmentioning

confidence: 99%

Rethinking convective quasi-equilibrium: observational constraints for stochastic convective schemes in climate models

Neelin

Peters

Lin

et al. 2008

Phil. Trans. R. Soc. A.

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Convective quasi-equilibrium (QE) has for several decades stood as a key postulate for parametrization of the impacts of moist convection at small scales upon the large-scale flow. Departures from QE have motivated stochastic convective parametrization, which in its early stages may be viewed as a sensitivity study. Introducing plausible stochastic terms to modify the existing convective parametrizations can have substantial impact, but, as for so many aspects of convective parametrization, the results are sensitive to details of the assumed processes. We present observational results aimed at helping to constrain convection schemes, with implications for each of conventional, stochastic or 'superparametrization' schemes. The original vision of QE due to Arakawa fares well as a leading approximation, but with a number of updates. Some, like the imperfect connection between the boundary layer and the free troposphere, and the importance of free-tropospheric moisture to buoyancy, are quantitatively important but lie within the framework of ensemble-average convection slaved to the large scale. Observations of critical phenomena associated with a continuous phase transition for precipitation as a function of water vapour and temperature suggest a more substantial revision. While the system's attraction to the critical point is predicted by QE, several fundamental properties of the transition, including high precipitation variance in the critical region, need to be added to the theory. Long-range correlations imply that this variance does not reduce quickly under spatial averaging; scaling associated with this spatial averaging has potential implications for superparametrization. Long tails of the distribution of water vapour create relatively frequent excursions above criticality with associated strong precipitation events.

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“…The influence of model resolution on its ability to capture the convection through resolved or sub-grid cloud schemes is discussed by Guichard et al (2004) (see also references therein, and Tost et al, 2006). Given the model resolution used here, the subgrid convection is parameterized with a 1-D mass flux scheme (Bechtold et al, 2001).…”

Section: Model Specificationsmentioning

confidence: 99%

Medium-range mid-tropospheric transport of ozone and precursors over Africa: two numerical case studies in dry and wet seasons

et al. 2007

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Abstract.A meso-scale model was used to understand and describe the dynamical processes driving high ozone concentrations observed during both dry and monsoon season in monthly climatologies profiles over Lagos (Nigeria, 6.6 • N, 3.3 • E), obtained with the MOZAIC airborne measurements (ozone and carbon monoxide). This study focuses on ozone enhancements observed in the upper-part of the lower troposphere, around 3000 m. Two individual cases have been selected in the MOZAIC dataset as being representative of the climatological ozone enhancements, to be simulated and analyzed with on-line Lagrangian backtracking of air masses.This study points out the role of baroclinic low-level circulations present in the Inter Tropical Front (ITF) area. Two low-level thermal cells around a zonal axis and below 2000 m, in mirror symmetry to each other with respect to equator, form near 20 • E and around 5 • N and 5 • S during the (northern hemisphere) dry and wet seasons respectively. They are caused by surface gradients -the warm dry surface being located poleward of the ITF and the cooler wet surface equatorward of the ITF.A convergence line exists between the poleward low-level branch of each thermal cell and the equatorward low-level branch of the Hadley cell. Our main conclusion is to point out this line as a preferred location for fire products -among them ozone precursors -to be uplifted and injected into the lower free troposphere.The free tropospheric transport that occurs then depends on the hemisphere and season. In the NH dry season, the AEJ allows transport of ozone and precursors westward to Lagos. In the NH monsoon (wet) season, fire products are transported from the southern hemisphere to Lagos by the southeasterly trade that surmounts the monsoon layer. Additionally ozone precursors uplifted by wet convection in the ITCZ can also mix to the ones uplifted by the baroclinic cell and be advected up to Lagos by the trade flow.

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Influence of different convection parameterisations in a GCM

Cited by 149 publications

References 49 publications

Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

Rethinking convective quasi-equilibrium: observational constraints for stochastic convective schemes in climate models

Medium-range mid-tropospheric transport of ozone and precursors over Africa: two numerical case studies in dry and wet seasons

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