عنوان مقاله [English]
Convective storms are the most atmospheric hazards that can cause significant dangers to sectors such as agriculture, industry, aviation industry and urban and rural facilities in different parts of the world. These storms are often accompanied by thunderstorms, hails, floods or severe winds. Severe dust from some convective phenomena has also been identified as air and environmental pollutant. Therefore, studing their various aspects has provided the basis for many atmospheric studies in different parts of the world.
Accurate and timely forecasting of convective storms is still challenging in operational weather forecasting centers. Given that conventionally configured numerical models did not accurately predict this phenomenon in most cases, their nowcasting using satellite data is of great importance. Meanwhile, geostationary satellites have been recognized as a useful tool for identifying areas with potential convection.
In this paper, an attempt is made to provide an algorithm using the Meteosat8 data to identify areas prone to the convection initiation and to improve the issuance of timely warnings in a very short time. This work has been done by studying the convective events during the day and night hours of spring and summer of 1397 in Tehran province. The present algorithm is based on selecting 22 fields using the brightness temperature of infrared channels, the reflectance of visible and near-infrared channels and the differences and their 15 and 30 minute trends. The preprocessing performed on the satellite data are radiometric and geometric corrections. To do this, after calculating the radiance of individual channels from the digital counts, the brightness temperature of the infrared and reflectance of the visible and near infrared channels are calculated. Also to calculate the trend of the fields between two time steps, a spatial low-pass filter using the box-averaging method has been used.
Large-Scale atmospheric pattern analysis of the ten strongest dust convective storm events in Tehran in the last decade shows that in most of them, at least five days before the storm, a ridge of geopotential height at the 500 hPa level developed on the area. On the day of the storm, the passage of the geopotential trough and the cold front of the surface destroyed the atmospheric stability and released the energy necessary for the development of the cumulonimbus cloud and the occurrence of the storm. Finally results show that using this algorithm to nowcasting the convective initiation, the probability of detection and correct alarm rate are 62 and 79 percent, respectively.