Changes in the Simulated Tropical Cyclones

Let us consider now what happens to the simulated TCs as a consequence of the greenhouse global warming. Table 4 shows the total number of TCs and TC days (upper row), the annual mean number of TCs and TC days (middle row) and their standard deviations (lower row) for the PREIND, 2CO2 and 4CO2 experiments. The method for detecting the TCs in these experiments is the same as the one used for the 20th century and discussed in Section 2.4. Also in this case we checked the sensitivity of the results to changes in the parameters used in the tracking procedure. In particular, we checked whether the results obtained from the 2CO2 and 4CO2 simulations might be affected by the choice of the vertical levels used to detect the

Table 4 Total number of TCs (left columns) and total number of TC days (right columns) found in the PREIND, 2CO2 and 4CO2 experiments. In all of the experiments a 30-year period is considered. In the upper row is the total number of TCs and TC days; in the middle row is the mean number of TCs and TC days per year; in the bottom row is the year-to-year standard deviation of the annual number of TCs and TC days. The average duration of the TCs, defined as the ratio between number of TC days and number of TCs, is 2.7 days for the PREIND, 2.8 for the 2CO2 and 2.7 for the 4CO2 experiment

Number of Tropical Cyclones Number of Tropical Cyclone Days

Table 4 Total number of TCs (left columns) and total number of TC days (right columns) found in the PREIND, 2CO2 and 4CO2 experiments. In all of the experiments a 30-year period is considered. In the upper row is the total number of TCs and TC days; in the middle row is the mean number of TCs and TC days per year; in the bottom row is the year-to-year standard deviation of the annual number of TCs and TC days. The average duration of the TCs, defined as the ratio between number of TC days and number of TCs, is 2.7 days for the PREIND, 2.8 for the 2CO2 and 2.7 for the 4CO2 experiment

Number of Tropical Cyclones Number of Tropical Cyclone Days

PREIND

2CO2

4CO2

PREIND

2CO2

4CO2

TOT

2196

1839

1229

5941

5085

3313

MEAN

73.2

61.3

41.0

198.0

169.5

110.4

STD

6.8

8.3

7.6

24.0

23.3

23.3

warm core (700, 500 and 300 hPa). The analysis indicated that the results shown in Table 4 are scarcely sensitive to small changes in the criteria we adopted.

The results illustrated in Table 4 suggest that the total number and the annual mean number of TCs and TC days appear to be substantially reduced with increased concentration of atmospheric CO2, whereas their interannual variability does not show significant changes. Also the average duration of TC (2.7 days for the PREIND and 4CO2 experiments and 2.8 days for the 2CO2 case) does not exhibit substantial variations. Our simulations, thus, indicate that increased CO2 leads to a reduction of the TC activity, both in terms of number of TCs and number of TC days. These results are consistent with previous findings (e.g., Bengtsson et al. 1996, Sugi et al. 2002, McDonald et al. 2005, Yoshimura et al. 2006), and for the first time they have been obtained using climate scenario simulations performed with a state-of-the-art fully coupled GCM.

The box plots shown in Fig. 8 represent the mean number of TCs per year for each activity area and for the three climate experiments. The reduction of the number of TCs is visible in all of the regions, though it appears to be particularly evident in the WNP and ATL areas. Interestingly, the TC activity appears to be drastically reduced also in the tropical South Atlantic (SATL).

Observational studies have hypothesized the existence of an Atlantic Multi-dicadal Oscillation (AMO; e.g., Delworth and Mann 2000), which modulating the Atlantic SST might influence the low-frequency variation of the TC activity in this region (Goldenberg et al. 2001). If the model produces an AMO-like variation of the SSTs and a consequent modulation of the Atlantic TC frequency, then the changes found in the TC number and shown in Fig. 8 could be due to a low-frequency "natural" oscillation of the storm activity. The time series of the number of TCs in the North Atlantic have been computed for 90 years of the PREIND climate simulation and the 4CO2 experiment. In the PREIND case, the series shows a pronounced decadal variation of the TC number, apparently much more pronounced than in the 4CO2 case. However, the amplitude of the oscillation is much smaller than the differences between 4CO2 and PREIND and also during the phases of lower TC activity, the number of storms in the PREIND experiment is higher

Annual TC Number x area PREIND

JJ 20

Annual TC Number x area 2C02

5 20

o fl

Annual TC Number x area 4C02

ji 20

SI AUS SP Nl WNP ENP ATL SATL

SI AUS SP Nl WNP ENP ATL SATL

SI AUS SP Nl WNP ENP ATL SATL

Fig. 8 Box plot of the annual number of TCs in the areas defined in Fig. 4 and for the tropical South-Atlantic (SATL) region. Left panel'. PREIND experiment; middle panel: 2C02 experiment; right panel: 4C02 experiment then in the 4CO2 one. Therefore, even considering the model "natural" (internal) low-frequency modulation of the TC activity, the number of TCs in the PREIND climate is systematically larger than in the 4CO2 case. This result suggests that the marked reduction of Atlantic TC number in the 4CO2 experiment is most likely ascribable to the greenhouse warming.

Generally, it is accepted that TCs tend to develop over oceanic warm waters. Specifically, climatological studies (e.g., Palmen 1948) indicate that the SST has to be warmer than about 26°C. The overall warming of the SST shown in Fig. 7, implies a poleward migration of the 26°C isotherm, therefore, one could expect to find a poleward extension of the TC activity in a warmer climate.

Figure 9 shows the zonal average of the total number of simulated TCs (left panels, dashed lines) and number of TC days (right panels, dashed lines) along with the zonal mean SST (solid lines) for the three experiments, PREIND (upper panels), 2CO2 (middle panels) and 4CO2 (lower panels). In the PREIND case the zonal mean SST threshold for TC occurrence appears to be between 25 and 26°C. The maximum number of TCs and TC days occur slightly equatorward of 20° latitude in both Hemispheres.

Increasing the atmospheric CO2 (middle and lower panels) the 26°C isotherm migrates poleward, on average, of almost 10° of latitude, but the latitudinal distribution of the number of TCs and TC days do not appear to be substantially changed. The maxima of TC occurrence, though reduced, still appears to be confined equatorward of 20° latitude, and the number of TC days tends to vanish poleward of 30° latitude. On the other hand, the zonal mean SST threshold for TC occurrence increases to about 28°C and almost 30°C for the 2CO2 and 4CO2 cases respectively. These results, in agreement with previous works (e.g., Haarsma et al. 1993, Henderson-Sellers et al. 1998) suggest that the poleward migration of warm SSTs caused by the greenhouse global warming does not imply an extension of the regions of cyclogenesis or TC activities towards the middle latitudes. Similar findings for the relationship between SSTs and convective precipitation have been indicated by Dutton et al. 2000.

In order to assess possible modifications in the strength of the simulated TCs, we have analyzed the changes in intensity of both low-level winds, minimum surface pressure and precipitation associated with the model TCs. The intensity of the TC low-level wind has been analyzed using the PDI (power dissipation index) proposed by Emanuel (2005), whereas as an index of intensity of TC precipitation we consider the rainfall averaged over a 4 by 4 grid point area around the centre of the cyclone and over the duration of the event.

When the pdf (probability density function) of the PDI for the three experiments is computed and plotted (not shown), the curves do not show significant differences. Similar results are obtained from the pdf of the lowest TC minimum surface pressure (not shown). Thus, in terms of strength of the near-surface wind, the changes in atmospheric CO2 do not appear to alterate the intensity of the simulated TCs. Simulations performed with very high resolution atmospheric models, on the other hand, showed that in a warmer climate the pdf of TC intensity shifts to higher values, with a decrease of the weaker cyclones and an increment of the most intense

PREIND

-45-40-35-30-25-20-15-10 -S 0 5 10 15 20 25 30 35 40 45

-45-40-35-30-25-20-15-10-5 0 5 10 15 20 25 30 35 40 45

■45-40-35-30-25-20-15-10-5 0 5 10 15 20 25 30 35 40 45

4C02

-45-40-35-30-25-20-15-10-5 0 5 10 15 20 25 30 35 40 45 latitude latitude

NUMBER OF TCs NUMBER OF TC DAYS

15 C

CO M

Fig. 9 Latitudinal distribution of the total number of simulated TCs (left panels), TC days (right panels) and zonal mean value of SST for the PREIND experiment (upper panels), the 2C02 case (middle panels) and the 4C02 experiment (lowerpanels). On the x-axis is the latitude. The y-axis on the left show the number of TCs and TC days and on the right the SST value. The dashed curves show the meridional distribution of the total number of TCs and TC days, with maxima centred between 15° and 20° latitude in both the Hemispheres. The solid curves show the distribution of the zonal mean SST. The two curves indicate, for each latitude, the number of TCs and the number of TC days and the corresponding values of SST ^

o ones (Knutson et al. 2004, Oouchi et al. 2006, Bengtsson et al. 2007). In particular, Bengtsson et al. (2007) have shown that the shift becomes more evident increasing the model horizontal resolution. We think that this shift does not occur in our simulations because of thes deficiencies that our model appears to have in simulating intense events. It is likely, in fact, that the model produces the most intense TCs that is capable of simulating even in the PREIND climate, at least in terms of surface wind and minimum surface pressure. Therefore, the apparent lack of impact of the global warming on the simulated PDI and surface pressure, might be actually due to the difficulties of the model in representing the TC intensity, which in turn are probably ascribable to the too coarse resolution.

Different findings are obtained when we use the precipitation field to quantify the intensity of the model TCs. Fig. 10 shows the pdf of precipitation (total, convective and non-convective) associated with a model TC for four different regions of activity and for the three experiments. In all of the cases, the maximum of pdf appears to shift to higher values of rainfall when the CO2 increases, indicating that in general in a warmer climate the TCs tend to be accompanied by more intense precipitation.

To further confirm these findings, in Fig. 11 the composite of TC precipitation are shown. The composite represents the mean rainfall rate averaged over the TC life time and over the number of TCs for the considered regions. The means have been computed for a domain centered on the core of the cyclones and extending 5° each side. The shaded patterns show the composites of TC rainfall for the PREIND case, whereas the contours are the difference between the composite 2CO2-PRE-IND (upper panels) and 4CO2-PREIND (lower panels), for the WNP region (left panels) and the ATL region (right panels). Using a boot-strap technique, the changes shown in Fig. 11 are found to be statistically significant, and suggest that the amount of TC rainfall, on average, becomes larger as a consequence of the greenhouse warming. These results are consistent with the findings of Knutson and Tuleya (2004), Bengtsson et al. (2007), Chauvin et al. (2006), for the Atlantic hurricanes, and Yoshimura et al. (2006), who used a high-resolution atmospheric only model.

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