**5. Numerical simulations**

In this section the WRF model is used to simulate the atmospheric conditions during the rainstorm on 5 December 2015. We used the WRF-NMM version 3.6.1 [3, 14, 15]. Details of the physical parameterization and model integration were given by [2].

As can be seen in **Figure 8a** and **b**, the sea level surface pressure field is well simulated by the model. There is good agreement between the position of the low pressure center associated with the cold front in the model and observations (point B in **Figure 4**). The change in the direction of low level winds due to the cold front is captured by the model (**Figures 5** and **9**). The model is able to simulate the region of divergence of mass in upper levels over the study region (**Figures 6** and **10**).

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**Figure 9.**

*UTC. Units: m s<sup>−</sup><sup>1</sup>*

*.*

**Figure 8.**

*Strong Rainfall in Mato Grosso do Sul, Brazil: Synoptic Analysis and Numerical Simulation*

*Simulated sea-level pressure on day 5 December 2015 at (a) 0600 UTC and (b) 1200 UTC.*

*Simulated low level wind at 850 hPa for day 5 December 2015 at 0600 UTC, 1200 UTC, 1800 UTC, and 2100* 

*DOI: http://dx.doi.org/10.5772/intechopen.83735*

*Strong Rainfall in Mato Grosso do Sul, Brazil: Synoptic Analysis and Numerical Simulation DOI: http://dx.doi.org/10.5772/intechopen.83735*

**Figure 8.**

*Natural Hazards - Risk, Exposure, Response, and Resilience*

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**Figure 7.**

(**Figures 6** and **10**).

**5. Numerical simulations**

*novos-estragos-em-dourados-ms.html).*

In this section the WRF model is used to simulate the atmospheric conditions during the rainstorm on 5 December 2015. We used the WRF-NMM version 3.6.1 [3, 14, 15]. Details of the physical parameterization and model integration were given by [2]. As can be seen in **Figure 8a** and **b**, the sea level surface pressure field is well simulated by the model. There is good agreement between the position of the low pressure center associated with the cold front in the model and observations (point B in **Figure 4**). The change in the direction of low level winds due to the cold front is captured by the model (**Figures 5** and **9**). The model is able to simulate the region of divergence of mass in upper levels over the study region

*Damage effects caused by the storms on 5 December 2015 in Mato do Grosso do Sul state. Source: http://g1.globo. com/mato-grosso-do-sul/noticia/2015/12/temporal-derrubou-pontes-arvores-e-comprometeu-agua-e-luz-emjardim.html; http://g1.globo.com/mato-grosso-do-sul/noticia/2015/12/chuva-e-ventania-de-56-kmh-causam-*

*Simulated sea-level pressure on day 5 December 2015 at (a) 0600 UTC and (b) 1200 UTC.*

#### **Figure 9.**

*Simulated low level wind at 850 hPa for day 5 December 2015 at 0600 UTC, 1200 UTC, 1800 UTC, and 2100 UTC. Units: m s<sup>−</sup><sup>1</sup> .*

**Figure 10.**

*Simulated divergence (×10<sup>−</sup><sup>5</sup> s<sup>−</sup><sup>1</sup> ) and high level wind at 200 hPa (m s<sup>−</sup><sup>1</sup> ) for day 5 December 2015 at 0600 UTC, 1200 UTC, 1800 UTC and 2100 UTC.*

The results presented above suggest that the present model may be an useful tool to forecast future events of severe weather. Nevertheless, many other experiments must be performed to have a better assessment of the model simulations.

## **6. Conclusions**

In this study the synoptic conditions and social impacts of the severe event on 5 December 2015 in the south of Mato Grosso do Sul State, Brazil were analyzed. The results showed that the heavy rainfall and strong winds caused floods, damage in several residences and affected the distribution of electric energy not only in the region but also in the interior of the state. The synoptic analyzes showed that the windstorm was caused by a region of wind difluence at high levels which was associated with convective clouds of large vertical development. The WRF model was used to simulate the atmospheric conditions in this severe event. The modeled values of some meteorological variables were in good agreement with the observations suggesting that the model may be used in future to forecast adverse weather conditions. This study makes part of a cooperative project between the National Institute for Space Research and the Energisa power company aimed to mitigate the

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**Author details**

provided the original work is properly cited.

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Sergio H. Franchito\*, Manoel A. Gan and Julio P. Reyes Fernandez

\*Address all correspondence to: sfranchito@hotmail.com

National Institute for Space Research, INPE, Sao Jose dos Campos, SP, Brazil

*Strong Rainfall in Mato Grosso do Sul, Brazil: Synoptic Analysis and Numerical Simulation*

ment of the resources of the energy electric sector and civil defense.

The authors declare that there is no conflict of interest.

impact of adverse weather conditions. The results obtained here may contribute to a better knowledge of the atmospheric conditions responsible for severe storms and provides subsidies for forecasting these events and thus cooperate with the manage-

This study makes part of the project "Management of the impact of climate severe events on the electric energy network" financed by the Energisa power

*DOI: http://dx.doi.org/10.5772/intechopen.83735*

**Acknowledgements**

**Conflict of interest**

company.

*Strong Rainfall in Mato Grosso do Sul, Brazil: Synoptic Analysis and Numerical Simulation DOI: http://dx.doi.org/10.5772/intechopen.83735*

impact of adverse weather conditions. The results obtained here may contribute to a better knowledge of the atmospheric conditions responsible for severe storms and provides subsidies for forecasting these events and thus cooperate with the management of the resources of the energy electric sector and civil defense.
