Integrated system for meteorological measurements

In Brazil, the lightning cause about one hundred kills in a year and 300 to 400 people injured, besides losses of the order of approximately US$ 445 million. Only in the electric energy sector, the annual loss is estimated at US$ 270 million: a lightning can strike the transmission lines and substations, can cause interruptions in the power suply and even blackouts. Recently, problems with lightnings are increasing. One of the causes of this increase is urbanization, with formation of urban heat islands favoring the storms, and verticalization of cities, which increases lightning frequency. Nowadays the electric energy sector uses a data network lightning of high cost and complex implementation, which serves mainly the south-central Brazil (RINDAT). In average, an antenna costs US$ 80,000 and a central processing around US$ 180,000. Therewith, the advancing of implementation of more antennas for detecting lightning in Brazil suffers with high costs, without accounting for maintenance costs and data supply for the companies of electric energy sector. In addition,an integrated sensor for measuring and data transmission in real time of lightning, temperature, moisture, pressure, wind and precipitation is not available in the market . Such meteorological variables strongly impact the transmission and distribution lines and have extremely importance for the implementation of a risk management system for the electric energy sector. In this perspective, the aim of this project was to develop a national technology for mounting an integrated station with lightning, precipitation, temperature, moisture, pressure and wind sensors with low cost. This project is jointly developed by the Brazilian Agency of Meteorology (Climatempo), XMOBOTS and CTEEP (Electric Energy Transmission Company of Sao Paulo). The lightning sensors have two atmospheric electricity sensors. One is a receiving radio waves in the band of VLF (Very Low Frequency, between 3 and 30 kHz). The electrostatic field measurer (Field Mill) is a electromechanical sensor specialized for the measure of intensity of the atmospheric electrostatic field. The Field Mill consists of a set of electrodes exposed and shielded from the electric field by rotation of metal blades, so as to produce an electric current proportional to field intensity to be measured. This sensor measures the severity of storms, estimating their approach, evolution and dissipation. Equiped with a battery for electric supply, the SIMM station also can be installed in remote locations. The station has a remote processing module capable of collecting and processing the signal from the sensors, perform specific calculations within competence of meteorology and send this information for multiple servers. The data is then sent with the use of a 3G modem or satellite, in addition the station has an Ethernet port for connection via cable or modem in places provided with internet access. The meteorological data is sent for the system every minute and the data concerning the life of the station is sent every 10 minutes. A lightning forecast model based on the identification of patterns on vertical profiles of thermodynamic variables is being developped. Cases of severe events with the presence or absence of lightning which caused damage to towers of transmission lines of CTEEP are being selected and analyzed. Numerical simulations with the atmospheric model WRF (Weather Research and Forecasting Model) are made for selected cases using different parameterizations for comparison. The model was adjusted to have a time step of 30 seconds, with horizontal spacing of 15 km in the lower resolution grid (grid 1) and 5 km resolution (grid 2).The grid 1 has 150 x 150 points in horizontal and the grid 2 has 211 x 157 points. Was used 36 vertical levels. For the initial and boundary condition, was used the data from GFS/FNL (Global Forecasting System/Final Analysis), with horizontal grid spacing of 1.0 degree. Once proven predictability of parameterization of forecasting heavy rainfall, it is expected to identify similar patterns for each type (with or without lightning) in the vertical profiles of some thermodynamic variables. With the knowledge of the differences between these profiles it is intended develop a lightning forecast model.