**1. Introduction**

The distribution and transmission of electric energy sectors are greatly affected by the climatic changes due to the global warming. Climate (and its change) is the main external agent that affects the electric energy distribution and transmission in all the world. The situation is aggravated by the increase of frequency of extreme events like tornadoes and severe storms associated to heavy rainfall, windstorms and high lightning incidence rate. Thus, studies providing useful information of the atmospheric conditions in extreme situations are essential not only for the electric energy sector but also for the national economy and people welfare. In this sense, recently the National Institute for Space Research (INPE), Brazil, and Energy Power Company developed a cooperative project aimed to mitigate the impacts of severe events. This is the first project of the Research and Development Program of the National Agency of Electric Energy (ANEEL) aimed to identify, monitoring and anticipate the occurrence of atypical severe storms that may cause climatic disasters

**Figure 1.** *Model domain of the WRF-NMM 9 km. MS in the figure indicates the location of the Mato Grosso do Sul state.*

of high impact on the electric energy distribution and socioeconomic sector. One of the project components is to identify the atmospheric conditions responsible for the severe storm events and the use of a high resolution regional numerical model to obtain the meteorological variables (for example, temperature, winds, pressure, precipitation) that describe in an adequate way the atmospheric conditions favorable for the occurrence of severe storms. The study to be presented here makes part of the above project. In this chapter the event of storms in Mato do Grosso do Sul State, Brazil that occurred on 5 December 2015 is studied.

Episodes of intense rainfall and strong winds affected the south of Mato Grosso do Sul State, (**Figure 1**) during December 2015. Events of severe weather conditions can have harmful impacts on the people life since they cause floods, damage residences, interrupt the vehicles traffic and affect the energy distribution and agricultural actives [1, 2]. This chapter has a two-fold objectives: (1) to analyze the synoptic conditions and social impacts of the rainstorm that occurred on 5 December 2015; (2) to simulate the atmospheric conditions that caused this severe event using a state-of-art regional climate model. The use of a numerical model can give useful information on the evolution of synoptic systems responsible for severe events, which will occur in future and thus can be used to forecast these events. This study is not concentrate on the evaluation of the impacts on people, i.e. it is focused on the predictive model about the meteorological aspects of the storm. The chapter is organized as it follows: Section 2 presents the Data and Methodology; An analyzes of the synoptic conditions and social impacts are shown in Sections 3 and 4, respectively; Section 5 show the numerical simulations and the conclusions are presented in the final of the chapter.

### **2. Data and methodology**

Mato do Grosso do Sul State is located in the Center-West Region of Brazil (**Figure 1**) It occupies an area of 357.125 km2 with a population of more than 2,5 million of habitants and has a tropical climate. Three vegetation types are present in the region: pasture (east), swampland (west) and tropical forest (south).

In order to analyze the synoptic systems responsible for the severe event on 5 December 2015 data of meteorological variables obtained from the global forecast system (GFS—http://nomadis.ndc.noaa/data/gfsanl) analysis are used. To identify

**19**

**Table 1.**

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

the synoptic conditions on 5 December 2015 GOES satellite images are used (http:// satellite.cptec.inpe.br/home/novoSite/index.jsp). The state-of-art numerical model used is the Weather Research and Forecasting-Nonhydrostatic Mesoscale Model (WRF-NMM) [3]. The damage effect of the rainstorm was illustrated using infor-

The Non-hydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system is a next-generation mesoscale forecast model. The NMM model was developed by the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environment Prediction (NCEP) based on the Eta model and replaces it in 2005. The model has been designed to be an efficient and flexible mesoscale modeling system for use across a broad range of weather forecast and idealized research applications, with an emphasis on horizontal grid sizes in the range of 1–10 km. although the NMM is a fully compressible, nonhydrostatic mesoscale model it has a hydrostatic option [3]. The model uses a terrain following hybrid sigmapressure vertical coordinate. A version of WRF-NMM tailored for hurricane forecasting, HWRF (hurricane weather research and forecasting), became operational in 2007. The WRF/NMM model with 9 km of horizontal resolution was introduced in 2015 in the team of models of the Center of Weather Prediction and Climate Studies (CPTEC) from INPE. The model domain cover the entire South America, with

In the simulation presented in this study, the model was integrated for a period of 84 h, starting from 1200 UTC 04 December 2015 (with spin-up of 12 h). A single domain with 9 km horizontal spatial resolution was configured. Initial and boundary conditions are derived from 6 h global analysis and forecast at 0.25° × 0.25° grids generated by the National Center for Environmental Prediction (NCEP)'s global forecast system (GFS). Analysis fields, including temperature, moisture, geopotential height and wind are interpolated to the mesoscale grid. These derived fields served as initial conditions for the present experiments. The domain is configured with vertical structure of 38 unequally spaced sigma (non-dimensional pressure) levels. The physical parameterizations used in this study are Geophysical Fluid Dynamics Laboratory (GFDL) [4, 5] for

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

mation of news agencies.

615X1392 WE/SN grid points.

Horizontal spatial resolution 9 km Simulation duration 84 h

Integration time step 15 s

*The WRF model configuration used in the simulations.*

Grid points WE/SN 615 × 1392 Center domain 58.234 W, 21.633S Horizontal grid system Arakawa E-grid Vertical co-ordinate 38 hybrid levels Radiation parameterization GFDL/GFDL

Initial and boundary conditions 0.25 × 0.25 GFS Operational Model

Map projection Rotated latitude and longitude

Surface layer parameterization Janjic similarity scheme Land surface parameterization Noah Land surface scheme Cumulus parameterization Betts-Miller-Janjic scheme PBL parameterization Mellor-Yamada-Janjic. Microphysics Ferrier scheme

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

the synoptic conditions on 5 December 2015 GOES satellite images are used (http:// satellite.cptec.inpe.br/home/novoSite/index.jsp). The state-of-art numerical model used is the Weather Research and Forecasting-Nonhydrostatic Mesoscale Model (WRF-NMM) [3]. The damage effect of the rainstorm was illustrated using information of news agencies.

The Non-hydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system is a next-generation mesoscale forecast model. The NMM model was developed by the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environment Prediction (NCEP) based on the Eta model and replaces it in 2005. The model has been designed to be an efficient and flexible mesoscale modeling system for use across a broad range of weather forecast and idealized research applications, with an emphasis on horizontal grid sizes in the range of 1–10 km. although the NMM is a fully compressible, nonhydrostatic mesoscale model it has a hydrostatic option [3]. The model uses a terrain following hybrid sigmapressure vertical coordinate. A version of WRF-NMM tailored for hurricane forecasting, HWRF (hurricane weather research and forecasting), became operational in 2007.

The WRF/NMM model with 9 km of horizontal resolution was introduced in 2015 in the team of models of the Center of Weather Prediction and Climate Studies (CPTEC) from INPE. The model domain cover the entire South America, with 615X1392 WE/SN grid points.

In the simulation presented in this study, the model was integrated for a period of 84 h, starting from 1200 UTC 04 December 2015 (with spin-up of 12 h). A single domain with 9 km horizontal spatial resolution was configured. Initial and boundary conditions are derived from 6 h global analysis and forecast at 0.25° × 0.25° grids generated by the National Center for Environmental Prediction (NCEP)'s global forecast system (GFS). Analysis fields, including temperature, moisture, geopotential height and wind are interpolated to the mesoscale grid. These derived fields served as initial conditions for the present experiments. The domain is configured with vertical structure of 38 unequally spaced sigma (non-dimensional pressure) levels. The physical parameterizations used in this study are Geophysical Fluid Dynamics Laboratory (GFDL) [4, 5] for


#### **Table 1.**

*The WRF model configuration used in the simulations.*

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

of high impact on the electric energy distribution and socioeconomic sector. One of the project components is to identify the atmospheric conditions responsible for the severe storm events and the use of a high resolution regional numerical model to obtain the meteorological variables (for example, temperature, winds, pressure, precipitation) that describe in an adequate way the atmospheric conditions favorable for the occurrence of severe storms. The study to be presented here makes part of the above project. In this chapter the event of storms in Mato do Grosso do Sul

*Model domain of the WRF-NMM 9 km. MS in the figure indicates the location of the Mato Grosso do Sul state.*

Episodes of intense rainfall and strong winds affected the south of Mato Grosso do Sul State, (**Figure 1**) during December 2015. Events of severe weather conditions can have harmful impacts on the people life since they cause floods, damage residences, interrupt the vehicles traffic and affect the energy distribution and agricultural actives [1, 2]. This chapter has a two-fold objectives: (1) to analyze the synoptic conditions and social impacts of the rainstorm that occurred on 5 December 2015; (2) to simulate the atmospheric conditions that caused this severe event using a state-of-art regional climate model. The use of a numerical model can give useful information on the evolution of synoptic systems responsible for severe events, which will occur in future and thus can be used to forecast these events. This study is not concentrate on the evaluation of the impacts on people, i.e. it is focused on the predictive model about the meteorological aspects of the storm. The chapter is organized as it follows: Section 2 presents the Data and Methodology; An analyzes of the synoptic conditions and social impacts are shown in Sections 3 and 4, respectively; Section 5 show the numerical

State, Brazil that occurred on 5 December 2015 is studied.

simulations and the conclusions are presented in the final of the chapter.

region: pasture (east), swampland (west) and tropical forest (south).

Mato do Grosso do Sul State is located in the Center-West Region of Brazil

lion of habitants and has a tropical climate. Three vegetation types are present in the

In order to analyze the synoptic systems responsible for the severe event on 5 December 2015 data of meteorological variables obtained from the global forecast system (GFS—http://nomadis.ndc.noaa/data/gfsanl) analysis are used. To identify

with a population of more than 2,5 mil-

**18**

**Figure 1.**

**2. Data and methodology**

(**Figure 1**) It occupies an area of 357.125 km2

long and short wave radiation, Noah Land surface scheme [6] for land surface, Mellor-Yamada-Janjic (MYJ) scheme [7] for planetary boundary layer, Ferrier scheme [8] for microphysics, and Janjic similarity scheme [9] for surface layer. **Table 1** shows the model configuration of the present study.

The use of the WRF model for studies of severe storms can be seen for example in [10–12].

Recently, a comparison of the results of the three operational models (WRF, Eta, BRAMS) of CPTEC was made. Tests of accuracy applied to the model results indicated that the WRF model has a better skill and computational performance (not published yet). So, in the present study a subjective (visual) method is used to analyze the WRF simulation of the storm.

The methodology used in the present study makes part of the cooperative project INPE-Energisa Company. Particularly, the use of the high resolution WRF model to predict severe storms is unique. So, the results obtained here may contribute to a better understanding of severe storms conditions and their prediction.
