Uncertainties in atmospheric chemistry modelling due to convection parameterisations and subsequent scavenging

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Abstract

Moist convection in global modelling contributes significantly to the transport of energy, momentum, water and trace gases and aerosols within the troposphere. Since convective clouds are on a scale too small to be resolved in a global model their effects have to be parameterised. However, the whole process of moist convection and especially its parameterisations are associated with uncertainties. In contrast to previous studies on the impact of convection on trace gases, which had commonly neglected the convective transport for some or all compounds, we investigate this issue by examining simulations with five different convection schemes. This permits an uncertainty analysis due to the process formulation, without the inconsistencies inherent in entirely neglecting deep convection or convective tracer transport for one or more tracers. Both the simulated mass fluxes and tracer distributions are analysed. Investigating the distributions of compounds with different characteristics, e.g., lifetime, chemical reactivity, solubility and source distributions, some differences can be attributed directly to the transport of these compounds, whereas others are more related to indirect effects, such as the transport of precursors, chemical reactivity in certain regions, and sink processes. The model simulation data are compared with the average regional profiles of several measurement campaigns, and in detail with two campaigns in fall and winter 2005 in Suriname and Australia, respectively. The shorter-lived a compound is, the larger the differences and consequently the uncertainty due to the convection parameterisation are, as long as it is not completely controlled by local production that is independent of convection and its impacts (e.g. water vapour changes). Whereas for long-lived compounds like CO or O3 the mean differences between the simulations are less than 25%), differences for short-lived compounds reach up to ±100% with different convection schemes. A rating of an overall "best" performing scheme is difficult, since the optimal performance depends on the region and compound.

Figures

  • Table 1. Applied processes and respective submodels of EMAC.
  • Table 2. Convection schemes applied in the individual simulations.
  • Fig. 1. 4 months average (September–December 2005) of the zonal average updraft mass fluxes (binned into 30◦ bins) for the five simulations in g/(m2s) (a) and frequency distribution of the 4 months vertically averaged updraft mass fluxes (b).
  • Fig. 2. 4 months average (September–December 2005) of the zonal average concentration of various compounds. The vertical axis depict pressure altitude, and each bar on the horizontal axis represents an average over 30◦ latitude (90◦ S to 60◦ S, 60◦ S to 30◦ S, etc.) for all the simulations as indicated in the top row of the graphs. The first bar in each bin shows the absolute values for the respective compound in the T1 simulation (reference) using the colour bar on the left for the scale. The other four bars in each bin show the relative difference to the reference in %, using the colour scale on the right hand side of the graphs. Panel (a) depicts H2O, (b) 222Rn, (c) CO, (d) HCHO, (e) HNO3, (f) O3.
  • Table 3. 4 month average of the upper tropospheric (from the 500 hPa level to the tropopause) 222Rn burden (in g) and its fraction of the total radon burden (in %). The total burden is similar in all simulations (≈ 209 g).
  • Table 4. 4 month average of the tropospheric O3 burden (in Tg) from the surface to the tropopause.
  • Fig. 3. Taylor diagram of the comparison between aircraft data from the Emmons et al. (2000) database and the simulations using the different convection parameterisations.
  • Fig. 4. Average (over all flights) vertical profiles during the GABRIEL campaign. The black line depicts the mean observed profile, grey shaded its standard deviation. The simulations with the different convection schemes are denoted by the colours: red for T1, green for EC, blue for Ema, turquoise for ZHW and magenta for B1. The symbols depict ±σ for the model calculations with respect to time and area.

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CITATION STYLE

APA

Tost, H., Lawrence, M. G., Brühl, C., & Jöckel, P. (2010). Uncertainties in atmospheric chemistry modelling due to convection parameterisations and subsequent scavenging. Atmospheric Chemistry and Physics, 10(4), 1931–1951. https://doi.org/10.5194/acp-10-1931-2010

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