Abstract. This paper describes the global chemistry Transport Model, version 5 (TM5) which allows two-way nested zooming. The model is used for global studies which require high resolution regionally but can work on a coarser resolution globally. The zoom algorithm introduces refinement in both space and time in some predefined regions. Boundary conditions of the zoom region are provided by a coarser parent grid and the results of the zoom area are communicated back to the parent. A case study using 222Rn measurements that were taken during the MINOS campaign reveals the advantages of local zooming. As a next step, it is investigated to what extent simulated concentrations over Europe are influenced by using an additional zoom domain over North America. An artificial ozone-like tracer is introduced with a lifetime of twenty days and simplified non-linear chemistry. The concentration differences at Mace Head (Ireland) are generally smaller than 10%, much smaller than the effects of the resolution enhancement over Europe. Thus, coarsening of resolution at some distance of a sampling station seems allowed. However, it is also noted that the budgets of the tracers change considerably due to resolution dependencies of, for instance, vertical transport. Due to the two-way nested algorithm, TM5 offers a consistent tool to study the effects of grid refinement on global atmospheric chemistry issues like intercontinental transport of air pollution.

[1] The SCIAMACHY satellite instrument shows enhanced carbon monoxide (CO) columns in the Southern Hemisphere during the local Spring. Chemistry-transport model simulations using the new GFEDv2 biomass-burning emission database show a similar temporal and spatial CO distribution, indicating that the observed enhancements are mainly due to biomass burning (BB).

Abstract. The effects of three important SCIAMACHY near-infrared instrument calibration issues on the retrieved methane (CH4) and carbon monoxide (CO) total columns have been investigated: the effects of the growing ice layer on the near-infrared detectors, the effects of the orbital variation of the instrument dark signal, and the effects of the dead/bad detector pixels. Corrections for each of these instrument calibration issues have been defined. The retrieved CH4 and CO total columns including these corrections show good agreement with CO measurements from the MOPITT satellite instrument and with CH4 model calculations by the chemistry transport model TM3. Using a systematic approach, it is shown that all three instrument calibration issues have a significant effect on the retrieved CH4 and CO total columns, although the impact on the CH4 total columns is more pronounced than for CO. Results for three different wavelength ranges are compared and show good agreement. The growing ice layer and the orbital variation of the dark signal show a systematic, but time-dependent effect on the retrieved CH4 and CO total columns, whereas the dead/bad pixels show a more random effect. The importance of accurate corrections for each of these instrument calibration issues is illustrated using examples where inaccurate corrections lead to a wrong interpretation of the results.

[1] This paper presents a first quantitative and systematic analysis of one year of SCIAMACHY Carbon Monoxide (CO) total column retrievals from the IMLM algorithm (v6.3) using a chemistry-transport model simulation. The global distribution of modeled and measured CO show similar spatial patterns: a north-south gradient, low CO over mountains, and high CO over emission regions. CO column errors due to instrument noise are closely related to surface albedo and are less than 6% for monthly means at high surface albedo locations, improving to $1% for ideal circumstances: cloud-free pixels, high surface albedo, and spatial averaging (3°Â 2°). Quantitative comparison shows that measured and modeled seasonality agree very well at several locations with different types of seasonal cycles. Differences between SCIAMACHY CO and model results are less than 13% except for regions with large instrument-noise errors. Differences larger than the 2s instrument-noise error (95% confidence interval) occur in some regions with small noise errors, for example southern Africa. In this case the SCIAMACHY CO variations are different from the model biomass-burning emission seasonal cycle and more in agreement with observed fire count seasonality. The comparison with model results indicates that despite unforeseen time-dependent instrument-calibration complications, SCIAMACHY CO total column retrievals are of sufficient quality to provide useful new information on the global distribution and variation of CO. Citation: de Laat, A. T.