TM5

over the regions in Africa. However, NO2 in the following versions was overestimated. Figure 5.13 illustrates such discrepancy between the satellite data and the results of latest model version (V10) for two major events of boreal fires: in the region of Siberia in May 2003, and Alaska in June 2004.

This type of fires is typical for its smouldering combustion and low content of nitrogen which leads to low NOx/CO emission ratios. Furthermore, a rapid conversion to PAN might explain why, in the satellite observations, almost no NO2 is measured in these regions. The model simulations are much higher probably because of an incorrect parameterisation of the facts above mentioned.

Differences are also found for other types of fires in South America, in 2004, and central Africa, for both years. This is in fact quite unexpected since from V7 onwards the emission dataset was changed from a monthly based to 8 day period which should have reflected as an improvement on the simulations. However, apart from this, other modifications in the chemistry scheme and reaction rates, namely those for CO + OH, can also be a reason for an increase of NO2, when, e.g., limiting the formation of HNO3. Furthermore, NO2 from tropical fires is normally present in higher altitudes (due to pyroconvective lofting) which might not be well described in the model simulations. On the other hand, the differences found might also be related to some uncertainties in the retrieved vertical columns. In the case of fires, it is difficult to predict the vertical distribution of trace gas and particles, and how the sensitivity of the measurements would be influenced. The results presented in the previous chapters have shown that higher plumes of highly absorbing aerosol can shield the trace gas below. Thus, when this is not accounted for in the retrieval, the NO2

columns might be underestimated. Conversely, many particles mixed with the trace gas will enhance the scattering of the light.

As expected, the last two versions V9 and V10 present very similar results for the tropospheric NO2. The NO2 values in the lower atmospheric layer were not so influenced by this update because the difference between those two versions is mostly related to the stratospheric parameterisations.

Figure 5.14 Seasonality curves for 2003 of tropospheric NO2 columns measured by SCIAMACHY (open symbols) and determined by MOZART V1 (top), V7 (middle) and V10 (bottom). Monthly averages determined for the selected regions as defined in Figure 5.6.

Figure 5.15 Seasonality curves for 2004 of tropospheric NO2 columns measured by SCIAMACHY (open symbols) and determined by MOZART V9 (top) and V10 (bottom). Monthly averages determined for the selected regions as defined in Figure 5.6.

The differences found for the stratospheric product from TM5 V7 are highlighted for the second half of the year 2003 (see Figure 5.16). At high latitudes, the NO2 values from satellite are lower than the modelled ones and the opposite is observed in the tropics. The succeeding versions that provided data for the year 2004 were able to simulate slightly better the NO2 over the high latitude regions (see Figure 5.17). However, the latest version V10 overestimates the stratospheric NO2 over the South Pole region, especially in the second half of 2004. This is not surprising considering that the model is not focussed on the stratosphere, and the chemistry scheme in this layer is the same as for the troposphere. Furthermore, the concentrations in the Polar regions are dependent on many other factors related to dynamics of the polar vortex and ozone hole occurrence. Therefore, bearing this in mind, the results are quite good but also highlight the importance of correct NO2 chemistry scheme in the higher atmosphere. The seasonal trends of TM5 output for the years 2003 and 2004 (Figure 5.18) illustrate the similarity between the different model versions. The South Pole values are overestimated by V7 and V10 in the winter period (local summer) and this maximum appears to be

shifted by 1-2 months. The remaining stratospheric columns are in general good with only a remark necessary for the low seasonality observed in mid-latitudes.

Figure 5.16 Three month averages of global total NO2 columns measured by SCIAMACHY (left) and stratospheric columns determined by TM5 V7 (right) for the year 2003.

Figure 5.17 Three month averages of global total NO2 columns measured by SCIAMACHY (top) and stratospheric columns determined by TM5 V9 (middle) and V10 (bottom) for the periods of April – June (left) and July – September (right) of the year 2004 (except V9 with data only for July and August).

The evaluation of tropospheric NO2 yielded by the TM5 V7 demonstrated that the model output was too low over anthropogenic source regions, such as Europe, China or the US. This was corrected in later versions with the inclusion of a more up-to-date emission inventory for the East-Asia region, the REAS dataset. Furthermore, as illustrated in Figure 5.2, NOx and CO emissions were also corrected. Consequently, the results from V10 are more similar to the satellite measurements. Nevertheless, as it was observed for MOZART, during the winter period, the NO2

columns observed for East-Asia are still higher than the modelled values. This may be on the

account of weak seasonality implemented in the TM5 scheme, but also due to extremely low values from the emission inventories. Nevertheless, the opposite occurs for Europe in the months of January and December where the model output is slightly higher than the measurements. For the biomass burning regions, a systematic over- or underestimation of the NO2 column was not verified.

Figure 5.18 Seasonality curves for 2003 (top) and 2004 (middle and bottom) of total NO2 columns measured by SCIAMACHY (open symbols) and stratospheric columns determined by TM5 V7 (top), V9 (middle with data only for April - August 2004) and V10 (bottom). Monthly averages determined for the selected regions as defined in Figure 5.6.

Figure 5.19 Three month averages of global tropospheric NO2 columns measured by SCIAMACHY (left) and determined by TM5 V7 (right) for the year 2003.

Figure 5.20 Three month averages of global tropospheric NO2 columns measured by SCIAMACHY (top) and determined by TM5 V9 (middle) and V10 (bottom) for the periods of April – June (left) and July – September (right) of the year 2004 (except V9 with data only for July and August).

The period of July-September is a good example where both occurrences were verified. While in 2003 the simulated NO2 columns are too small over South America and central Africa, in the following year the model predicts high NO2 emissions in the Alaska region which are not detected by the satellite (see Figure 5.21). It seems that TM5 overestimates the emissions from boreal fires and underestimates those of tropical biomass burning events (except for the last months of 2004 in V10). The source of the problem could not be easily identified. It is also surprising to see that the output from V9, which erroneously used doubled emissions from biomass burning sources,

compares nicely to the satellite measurements for such events, while the TM5 V10 results for those regions are still higher than the satellite measurements. From the seasonality trends in Figure 5.22, it is also possible to observe that, for this version, while in the beginning of the year 2004 the model underestimates the NO2 columns in the North-Africa region, the opposite is registered for the month of December. The simulations of emissions from biomass burning events in the year 2004 with V10 are affected by different assumptions. In the months of January and February no GFED data was considered in the model, which might explain the underestimation of the fires in the North-Africa region. Furthermore, the definition of injection height was improved in May. This change will lead to modifications of the model output because, as explained in chapter 2, the NO2

chemistry is highly dependent on the temperature which decreases with height. While from March to May the emissions were considered in the two lowest layers of the model, for the remaining months the biomass burning emissions are injected up to 6000 m. This might explain the low values in the months of March to May and, from then onwards, higher NO2 columns than those measured by SCIAMACHY. Nevertheless, the differences in the monthly averages are quite small and the seasonality is well reproduced in these regions (see Figure 5.22). In general, for the biomass burning regions, the results are better than those produced by MOZART runs. However, because of the many factors involved in these simulations, and the several changes performed in the TM5 configuration, it is difficult to point out what exactly became an advantage in terms of model scheme and what might be the source of erroneous results.

Figure 5.21 Monthly averages of tropospheric NO2 columns measured by SCIAMACHY (left) and determined by TM5 V7 and V10 (right top and bottom, respectively) for two different case studies: Siberia fires – May 2003 (top) and, Alaska fires – June 2004 (bottom).

Figure 5.22 Seasonality curves of tropospheric NO2 columns measured by SCIAMACHY (open symbols) and determined by TM5 V7 (top) for the year 2003, and V9 (middle, with data only for April – August 2004) and V10 (bottom) for the year 2004. Monthly averages determined for the selected regions as defined in Figure 5.6