Paper
3 May 2017 Local sensing of atmospheric electric field around Nalchik City
Aida A. Adzhieva, Vitaly A. Shapovalov, Idar Kh. Mashukov
Author Affiliations +
Abstract
In the context of rising the frequency of natural disasters and catastrophes humanity has to develop methods and tools to ensure safe living conditions. Effectiveness of preventive measures greatly depends on quality and lead time of the forecast of disastrous natural phenomena, which is based on the amount of knowledge about natural hazards, their causes, manifestations, and impact. To prevent them it is necessary to get complete and comprehensive information about the extent of spread and severity of natural processes that can act within a defined territory. For these purposes the High Mountain Geophysical Institute developed the automated workplace for mining, analysis and archiving of radar, satellite, lightning sensors information and terrestrial (automatic weather station) weather data.

The combination and aggregation of data from different sources of meteorological data provides a more informativity of the system. Satellite data shows the global cloud region in visible and infrared ranges, but have an uncertainty in terms of weather events and large time interval between the two periods of measurements, which complicates the use of this information for very short range forecasts of weather phenomena. Radar and lightning sensors data provide the detection of weather phenomena and their localization on the background of the global pattern of cloudiness in the region and have a low period measurement of atmospheric phenomena (hail, thunderstorms, showers, squalls, tornadoes).

The authors have developed the improved algorithms for recognition of dangerous weather phenomena, based on the complex analysis of incoming information using the mathematical apparatus of pattern recognition.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aida A. Adzhieva, Vitaly A. Shapovalov, and Idar Kh. Mashukov "Local sensing of atmospheric electric field around Nalchik City", Proc. SPIE 10215, Advanced Environmental, Chemical, and Biological Sensing Technologies XIV, 102150W (3 May 2017); https://doi.org/10.1117/12.2279940
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Cited by 4 scholarly publications.
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KEYWORDS
Atmospheric sensing

Earth's atmosphere

Clouds

Sensors

Atmospheric modeling

Algorithm development

Data archive systems

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