ردیابی منابع رطوبتی و تحلیل شاخص‌های ناپایداری منجر به بارش‌های سنگین شمال غرب ایران

Introduction
The study of climate hazards such as heavy precipitation is very important due to its direct impact on flooding. Due to the climate change that the world has experienced, climate hazards have increased. What is certain is that humans cannot prevent the occurrence of climate hazards, but by being aware of these events in advance, under the influence of climate forecasts, they can reduce the destructive consequences of these hazards. Also, considering the very prominent role of humans in increasing the most important climate forcing, namely greenhouse gases, especially carbon dioxide, by managing fossil fuels and increasing new energy power plants, which are known as clean energies, climate changes that cause extreme events can be reduced. Another issue is the management of heavy precipitation to control large amounts of water for use in agriculture, which seems to be able to benefit from this weather event by taking measures. Another important point regarding heavy precipitation in the northwest region of Iran is to pay attention to the construction of residential areas in places far from rivers, which are vulnerable to flooding caused by heavy precipitation. The most important cause of extreme events such as heavy precipitation is currently climate change. The main factor causing climate change and desertification is greenhouse gases. The most important type of greenhouse gas is carbon dioxide. The main reason for the increase in this gas, which has a long life and is very poorly degradable, is humans. In other words, the main cause of the increase and intensification of extreme events is human misbehavior in dealing with nature. The northwest region of Iran is prone to heavy precipitation due to its mountainous topography and location on the main path of Mediterranean cyclones. This research was conducted with the aim of identifying the moisture sources of heavy precipitation in northwest Iran and also analyzing the instability indicators related to it.
 
Materials and Methods
The study area in this study is northwest Iran, including West Azarbaijan, East Azarbaijan, Ardabil, North Kurdistan, and West Zanjan provinces. In this study, daily and hourly (3-hour) precipitation data and hourly (3-hour) wind data (speed and direction) were obtained from the Iranian Meteorological Organization (www.irimo.ir) for 23 synoptic stations located in northwest Iran during the period 1990-2019. The upper atmosphere data of the Tabriz station (the only upper atmosphere station in northwest Iran) were obtained from the University of Wyoming website (http://weather.uwyo.edu/upperair/sounding.html). The upper atmosphere data of this study were obtained from the NCEP/NCAR database (www.cdc.noaa.gov). Trial and error estimates showed that if the percentile is higher than 99 and the area covered by heavy precipitation is more than 30%, synoptic conditions will provide a good justification for heavy precipitation.
In this paper, days when at least 7 stations in the study area simultaneously had at least 20 mm of precipitation were selected. In this study, using TTI, CAPE, KI, LI, SI and SWEAT indices, the state of atmospheric instability in northwest Iran was evaluated at a representative station in the region (Tabriz) on days of heavy precipitation (43 days). Based on factor analysis in the SPSS software environment, the main factors were identified from among the 6 indicators, then using cluster analysis, the main clusters were extracted and the Skew-T diagram of the representative days of each cluster was drawn and interpreted in the RAOB software environment. To select representative stations for the northwest region of Iran, 15% (3 synoptic stations) of the stations in the study area were selected based on altitude (meters), climate (number of heavy precipitation and average heavy precipitation during the study period), and large distance from each other (based on kilometers and geographical location). Using cluster analysis in the SPSS software environment, clusters were extracted based on the effective variables (relative humidity, wind vector, precipitable water) of the mid-level atmosphere in the northwest region of Iran. Then, the representative of each cluster was determined and for each representative day of heavy precipitation event (4 days out of 43 heavy precipitation events), in each of the 3 representative stations of the study area (3 stations out of 23 synoptic stations), the path and source of moisture of heavy precipitation were traced using the backward method (72 hours before the days of heavy precipitation in northwest Iran) and using global data analyzed at the  National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) with a time step of 6 hours with a spatial resolution of 2.5 × 2.5 longitude and latitude for the levels of 850, 700 and 550 hectopascals, with the HYSPLIT web model. The wind gust diagram was drawn and interpreted using the WRPLOT software for the representative days at the representative stations of northwest Iran. The combined wind and precipitation diagram was drawn and interpreted hourly in the Excel software environment for the representative days at the representative stations of the study area.
 
Results and Discussion
According to the criteria for heavy precipitation in this study, 43 extreme precipitation events were identified in the observation period (1990-2019). Using hierarchical cluster analysis using the Ward method with Euclidean distance, 2 main clusters were extracted from the 43 extreme precipitation events. The first cluster shows heavy precipitation events with dynamic ascent in the study area, and the second cluster includes heavy precipitation events with convective ascent in the research area. Of the two clusters, the first cluster has a higher frequency and indicates the dominance of heavy precipitation with dynamic origin over heavy precipitation with thermodynamic nature in the study area during the period under study. By drawing the Skew-T diagram in the RAOB software environment for representative days of each cluster, the instability conditions on representative days indicated the intensification and stability of atmospheric instability at levels above 850 hectopascals for the representative dynamic cluster. In the representative day's Skew-T diagram, the thermodynamic instability cluster was observed up to a maximum level of 850 hectopascals. Calculations showed that, considering the instability indices and the Skew-T thermodynamic diagram, the role of the convection factor in heavy precipitation  in northwest Iran was low and the dynamic factor was the main reason for heavy precipitation. The results of the study based on the windrose diagram indicate that the prevailing winds causing heavy precipitation  events blew from the southwest and had an average speed of 3.5 m/s. The output of the HYSPLIT diagram also confirms the southwest direction of the study area for the moisture input path of extreme precipitation. Also, the results of the combined hourly wind speed and precipitation diagram showed that the maximum wind speed and maximum precipitation on heavy precipitation  days were at 12:00 GMT, equivalent to 15:30 local time, which indicates the strengthening of the effective dynamic system in the region at this hour. In other words, the cyclone located at this hour, with the convergence created, has brought maximum humidity to the region and, with its sharp ascent, has provided the cause of heavy precipitation  in northwest Iran. Based on the calculations, the average atmospheric variability of precipitable water, relative humidity, and wind speed in extreme precipitation events in northwest Iran has been 16 kg/m2, 68 percent, and 20 m/s, respectively.
 
Conclusion
Based on the research conducted in the northwest region of Iran, in the period 1990-2019 on heavy precipitation, the results showed that, considering the instability indices and the Skew-T thermodynamic diagram, the role of the convection factor in heavy precipitation was very low and the dynamic factor was the main reason for heavy precipitation. The results of the study based on the HYSPLIT model showed that the main path of moisture entry into the study area is the southwest and the main source of moisture supply for heavy precipitation is the Red Sea. The results of the study based on the windrose diagram indicate that the prevailing winds in heavy precipitation events blew from the southwest and their speed was 3.5 m/s on average. The combined hourly wind speed and precipitation diagram showed that the maximum wind speed on heavy precipitation days was at 12:00 GMT, equivalent to 15:30 local time, which indicates the strengthening of the effective dynamic system in the study area at this hour. Humans cannot eliminate weather hazards. Weather hazards are part of nature, and humans can only reduce the frequency and severity of these events. In the northwest of Iran, the best solution to deal with the risks caused by heavy precipitation  is to identify the causes of this event, such as the moisture sources that provide heavy precipitation , and to evaluate instability indicators that indicate the conditions for the formation of heavy precipitation. The next step is to inform the residents of the region, such as farmers, travelers, and others, about the occurrence of this event and warn them of the possibility of flooding. Insuring crops and residential houses, constructing residential houses in susceptible areas on high foundations with a height of 3 or 4 meters, increasing vegetation cover and planting seedlings with the aim of increasing soil permeability, dredging rivers to prevent water levels from rising due to sediment deposition, taking protective measures on river banks with the aim of reducing soil erosion in coastal areas, using mobile concrete dams during precipitation  in agricultural and residential areas with the aim of preventing possible flood damage during heavy precipitation , and avoiding unnecessary transportation due to reduced visibility, slipperiness, and flooding of urban and roadways are considered major solutions to reduce losses caused by heavy precipitation. The results of this study are in good agreement with the results of other researchers in terms of the dominance of dynamic instability in heavy rainfall, the occurrence of heavy rainfall in the spring due to convective causes, the occurrence of extreme rainfall due to the supply of moisture to the Red Sea by the Mediterranean cyclone, and the confirmation of the strengthening of cyclones causing heavy rainfall at 12:00 GMT.