Automatic Detection of Atmospheric Fronts using Numerical Methods on Iran and the Eastern Mediterranean (Case study: April 13-14, 2017)

Introduction
The weather fronts are  known for their large vorticity, dense, moisture, and statical Stability gradients,   and their longitudinal scale is one unit greater than their width. The width of the front is known as the baroclinical zone, in which the front lines have a very large temperature gradient, which is determined by the angle between pressure and temperature lines. Position of a front is located in warm side of the extreme temperature gradient, inside the heat transfer zone and  intensity of the front is determined by the size of the horizontal or quasi-horizontal temperature gradient.Even the numerous expert synopticians disagree with each other in the position of the fronts, their types and intensity, in the manual drawing method of the fronts. So their drawn  fronts are very different While objective front is based on numerical methods and its purpose is to avoid applying people''s tastes in their manual method. The advantages of objective front metod in comparison with subjective front method are high speed front detection, the possibility of determining front frequeny, moving, and feedback of fronts with land side effects.
So far, various methods have been developed for objective front method. They performed objective front method using numerical methods and the first and second derivatives of the temperature parameter on a regular grid points with a relatively low resolution of about 100 km. Inside the country, there has been no study about automatic and numerical front methods. On the other hand more than 90 percent of heavy rainfall in the tropics is associated with the fronts. Therefore, considering Iran''s location in the middle latitudes, it is very necessary to study and identify the fronts. So the climatological study of the manual front detectin is very time consuming, expensive and practically impossible. Therefore, in this research, the, automatic and numerical front detection have been discussed for the first time in the country.
Methodology
In this study, grid point data  from the European Center for Medium-range Weather Forecasting (ECMWF) of type (ERA - Interim) is used with gaussian grid points. In this centre, different types of data are classified into different formats and in different time intervals and different grid resolution. In order to study  of the fronts, isobaric level data with 6 hour intervals and resolution of 0.75 × 0.75 degrees with grib format is used. This grid resolution is set in a regular 61×61 matrix with a grid distance of 83 km. Different quantities can be used to select the appropriate parameter to detection of fronts such as temperature, humidity, wind direction and wind speed, vorticity, thickness and thickness changes ,and temperature is on of  the most important of them. On the other hand, detection of the exact location of the extreme temperature gradient, which is accompanied by the effects of heating on the warm convergence belt in the warm side of the front leads to warm weather, can be identified only by using the equivalent potential temperature.
Results and Discussion
The main idea for identifying frontal areas is to use a temperature parameter in two-dimensional horizontal coordinates. The line representing the front in these areas is identified using a frontal identification function. In order to identify the front, the masking conditions are applied once or several times. In other words, in this equation, the horizontal gradients of the equivalent potential temperature are used, which should not be less than the value of the K-threshold value. >K  . Several indicators are considered to identify the front. The first of them is that the front must be at a turning point in the curvature of the temperature lines which is along the temperature gradient. The second indicator is the location of the maximum values of temperature gradient,and the third criterion is the point where the second derivative of the temperature gradient is zero. Various experiments have shown that the smaller the temperature derivative of the front temperature parameter, the less error there will be (J. Jenkner, 2009). Thus, the Front Termal Parameter (TFP), invented by Renard & Clarke (1965), was used as the main method of frontal reconnaissance.
TFP =
In this equation, second derivative of the temperature parameter has been used, which has converted the temperature gradient, which is a vector quantity, to a scalar quantity.
Conclusion
Examination of the results of objective fronts showed that the detection of fronts near the ground due to the interaction between the boundary layer and the fronts is very erroneous and the fronts are practically indistinguishable. On the other hand, at higher levels, shallow fronts at numerical output are not detected. Therefore, the appropriate level for automatic identification of fronts in the study area, 700 hPa level was selected. Examining the results, it is inferred that cold and warm fronts are often found at the bottom of the ridge and above the ridge of the upper surfaces, and these fronts, during the formation stage, are often discontinuous and gradually evolve during the developmental stages. Strengthening the front will take a more integrated form. Studies have shown that cold fronts produce stronger frontogenesis than warm fronts. Also, the output of objective fronts showed that TFP is a good parameter for detecting the front in this region and with the results of previous studies such as Hewson (1998: 49), Jenkener et al. (2010: 9), they show a good match. The results of this study can be used in the discussion of climatology and forecasting of fronts and can be helpful in the discussion of flood management due to heavy rainfall on the front.