Tracking Moisture Sources and Analysis of Instability Indicators leading to Heavy Rains in Northwest Iran

Extended Abstract

Introduction

Studying climatic hazards such as heavy rainfalls is very important because of its direct effect on causing floods. Due to the climate changes that the world has experienced, climate risks have increased. The northwest region of Iran is prone to heavy rains due to its mountainous topography and location in the main path of Mediterranean cyclones. This research has been carried out to identify the moisture sources of heavy rainfalls in the northwest of Iran, as well as analyze the instability indicators related to it. Naturally, humans cannot prevent the occurrence of atmospheric hazards, but by forewarning these occurrences and making climate forecasts, they can reduce the destructive results of these hazards. Also, due to the very prominent role of humans in increasing the most important climate forcing, i.e. greenhouse gases, especially carbon dioxide gas, by managing fossil fuels and increasing new energy power plants, it is possible to reduce climate changes that cause extreme events. Climatic forecasting can be used to control heavy rainfall for use in agriculture and industry.





Materials and Methods

In this research, the daily and hourly rainfall data of 23 synoptic stations located in the northwest of Iran from 1990 to 2019 were obtained from the Iranian Meteorological Organization (www.irimo.ir). The upper atmosphere data of Tabriz station (the only upper atmosphere station in northwestern Iran) was obtained from the University of Wyoming website (http://weather.uwyo.edu/upperair/sounding.html). Also, upper atmosphere data were obtained from the NCEP/NCAR database at www.cdc.noaa.gov. Using the HYSPLIT model, it was carried out at different levels of the atmosphere with the backward method for 3 days from the selected stations with a time step of 6 hours. With RAOB software, a Skew-T diagram was drawn and important instability indices such as TTI, CAPE, KI, LI, SI, and SWEAT were analyzed for heavy rainfalls. Using factor analysis by principal component analysis (PCA), the main factors were identified among the instability indicators. Then hierarchical cluster analysis was performed using Ward's method with Euclidean distance and by determining two clusters, the state of atmospheric instability was evaluated on representative days and the previous day. A windrose diagram of representative days of extreme events for selected stations was drawn to determine the direction of prevailing winds to be compared with the humidity track output of HYSPLIT software. Also, the combined graph of wind speed (meters per second) and precipitation (millimeters), was used to evaluate the maximum hours of heavy precipitation and the maximum wind speed of the study area in the days of maximum precipitation.





Results and Discussion

The calculations showed that according to the instability indices and the thermodynamic diagram of Skew-T, the role of the convection factor in the heavy rains of northwest Iran was low and the dynamic factor was the main reason for the heavy rains. The results of the study, based on the windrose diagram, indicate that the prevailing winds causing heavy rain events blew from the southwest and had an average speed of 3.5 meters per second. The output of the HYSPLIT diagram also confirms the southwest direction of the moisture entry path of extreme precipitation to the studied area. Also, the results of the combined graph of wind speed and rainfalls in an hourly manner showed that the maximum wind speed and maximum rainfalls on the days of heavy rain was 12:30 GMT (15:30 local time), which indicates the strengthening of the effective dynamic system in the region at this time. In other words, the cyclone located at this hour has been created by convergence, it has brought the maximum humidity to the region, and with its strong ascent, it has caused heavy rains in the northwest of Iran. Based on the calculations, the average atmospheric variables of precipitable water, relative humidity, and wind vector speed in extreme precipitation events in northwest Iran were 16 kg/square, 68 percent, and 20 m/s, respectively.



Conclusion

The results showed that the main source of moisture for the heavy rainfalls in northwest Iran in the period of 1990-2019 is the Red Sea and the main route of moisture entry to provide maximum precipitation in the studied area is southwest. Also, the results showed that heavy rains in the research area in the 30 years were associated with less convective instability (5%) and the role of dynamic instability was much greater (95%).