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   واکاوی چشمه‌های رطوبت و الگوهای فضایی- زمانی موثر بر بارش برف بهاره در استان چهارمحال و بختیاری  
   
نویسنده قصابی زهرا ,فتحی مائده ,نوروزی معصومه ,رضازاده پرویز
منبع جغرافيا و برنامه ريزي محيطي - 1399 - دوره : 31 - شماره : 2 - صفحه:43 -56
چکیده    تاریخچه‌ اقلیمی استان چهارمحال و بختیاری در منطقه‌ زاگرس مرکزی نشان‌دهنده‌ فراوانی بارش برف در فصل سرد است. در سال‌های اخیر گرایش بارش‌ها از برف به باران در فصول پاییز و زمستان افزایش و بارش برف در فصل زمستان در استان نسبت به میانگین بلندمدت کاهش یافته است؛ این در حالی است که گاهی شاهد بارش برف بهاری در استان هستیم.در این پژوهش شرایط دینامیکی و ترمودینامیکی برای سه بارش فرین برف در فصل بهار با استفاده از داده‌های era5 با تفکیک شبکه‌ای 0.25 درجه تحلیل می‌شود. برای بررسی اقلیمی، نابهنجاری‌های دما، بارش و ارتفاع ژئوپتانسیلی طی دوره‌ آماری 30ساله (1981-2010) محاسبه شد؛ همچنین کمیت‌های فرارفت تاوایی، شار رطوبت و آب قابل بارش برای دستیابی به منابع رطوبت موثر در ریزش برف در سطح استان بررسی شد. تحلیل نابهنجاری‌های بارش نشان می‌دهد مقدار آنها در همه‌ رویدادهای بارشی بیش از میانگین بلندمدت بوده است که با نابهنجاری دما و ارتفاع ژئوپتانسیل تراز 500 هکتوپاسکال همخوانی دارد.نتایج نشان داد رطوبت سامانه‌های مطالعه‌شده بیشتر از دریای سرخ، دریای عرب، دریای عمان و شمال اقیانوس هند تامین شده و با فرارفت تاوایی مثبت همراه بوده است. بررسی شرایط ترمودینامیکی نیز نشان داد شاخص‌های ناپایداری در ساعات پیش از آغاز بارش مساعد بوده و فعالیت همرفتی سامانه‌ها را تشدید کرده است. سرمایش همرفتی همراه با کاهش شدید دما سبب تبدیل باران به برف شده است. کاهش چشمگیر دما نسبت به میانگین بلندمدت و سردبودن ستون جوّ، بارش برف را در فصل بهار توجیه می‌کند.
کلیدواژه بارش برف بهاره، منابع رطوبت، تحلیل دینامیکی، نابهنجاری بارش، استان چهارمحال و بختیاری
آدرس پژوهشگاه هواشناسی و علوم جو, گروه پژوهشی پیش‌آگاهی مخاطرات جوی, ایران, سازمان هواشناسی کشور, ایران, اداره کل هواشناسی چهارمحال و بختیاری, ایران, سازمان هواشناسی کشور, ایران
پست الکترونیکی rezazadeh.pr@gmail.com
 
   Analysis of Moisture Sources and Spatial-Temporal Patterns Affecting Spring Snowfall in Chaharmahal and Bakhtiari Province of Iran  
   
Authors Ghassabi Zahra ,Fathi Maede ,Norouzi masoumeh ,rezazadeh parviz
Abstract    The climatic history of Chaharmahal and Bakhtiari province in the Central Zagros region shows a huge amount of snowfall in the cold season. In recent years, the tendency of precipitation from snow to rain has increased in autumns and winters and wintertime snowfall has decreased compared to the longterm average of the province, while sometimes springtime snowfall can be seen in the province. In spring, dynamic systems that stimulate atmospheric instability are still present in the region, and sometimes the combination of dynamicthermodynamic conditions causes heavy rainfalls. In the present study, the dynamic and thermodynamic conditions for three springtime snowfalls were analyzed and the effective moisture sources in springtime snowfall were obtained. MethodologyPrecipitation and temperature values in synoptic stations of Chaharmahal and Bakhtiari province in the period of 2000 to 2018 were provided by the Meteorological Organization. To select abnormal springtime precipitation, the anomaly of temperature, precipitation, and geopotential height at the level of 500hPa were analyzed. The ERA5 analysis of the data from ECMWF with a horizontal resolution of 0.25° was used to calculate moisture flux, perceptible water and vorticity advection, the monthly anomaly of precipitation, height and temperature of 500hPa, and instability indices. To analyze the causes of snowfall in spring and also to investigate the sources of moisture, the monthly anomalies of rainfall, the temperature at a height of 2 meters above the ground and height, and temperature of 500hPa level were compared to the 30year average (19812010). In a dynamic study, vorticity advection at the level of 500hPa was measured. To identify the trajectory of atmospheric moisture, moisture flux at the level of 850hPa and perceptible water were calculated. To investigate the thermodynamic conditions and atmospheric instability, SkewT diagram and atmospheric instability indices including KI, TT, PW, and CAPE were used at Shahrekord station at 00 UTC on the day of snowfall.DiscussionSnowfall is a climatic feature of Chaharmahal and Bakhtiari province that also occurs in spring, but in recent years, due to warmer weather and reduced snowfall in winter, snowfall in spring seems somewhat unexpected. Precipitation is one of the quantities whose prediction of location and intensity is associated with uncertainty. Therefore, in this study, for more accurate prediction, the moisture sources, and the dynamic and thermodynamic conditions of spring snowfall in the province were investigated. To select unusual springtime precipitation, anomalies of temperature, precipitation, and geopotential height at 500hPa were examined. As a result, snowfalls were selected in the spring of 2004, 2009, and 2016, which were different from normal compared to the longterm 30year average.Examination of the dynamic conditions of the mentioned systems showed that at the level of 500hPa with the formation of a deep trough in the eastern Mediterranean to the Red Sea, the location of the study area in the east of this trough has caused instability and upward movements. In addition, there is a positive vorticity at the level of 500hPa. Given that these conditions have occurred for all three systems, it can be concluded that the occurrence of snowfall in spring is due to a dynamic process. It is noteworthy that in April 2016, when the amount of snow was more than the other two cases, the trough formed in the area was much deeper than the other two ones, and the vorticity advection was higher. Analysis of the quantities of moisture flux and perceptible water showed that these systems supplied their moisture from the Arabian Sea, the southern Red Sea, the Sea of Oman, and the northern Indian Ocean. The sources of moisture for precipitation in the region are mainly the Arabian Sea, the Red Sea, the Sea of Oman, and the North Indian Ocean are located more than 2000 km far from the southwest of Iran.Moisture flux continues from a few days before the operation of the system with south and the southwest winds from the Arabian Sea and south of the Red Sea to the southwest of Iran. In addition, the amount of perceptible water on the day of the event increases sharply. Temperature analysis showed that the decrease in temperature on the days of the phenomenon was more severe than the previous days and compared to the climatic average, and the coldness of the entire air column illustrates snowfall in spring. Examination of climatic conditions including anomaly analysis of precipitation showed that their values in all cases were much higher than the longterm and the normal average of the region, and is consistent with prominent temperature and height anomalies at the level of 500hPa. 15 to 30 decameter drop in height and more than 1° drop in temperature were observed at this level compared to the long term. Cooling of the atmospheric column due to the process of evaporation or melting along the path and especially in the adjacent layers of the earth’s surface has an important role in precipitation in snow form. Examination of the values of instability indices in Shahrekord station also showed that these indices were prominent in the hours before the event and intensified the activity and convective cooling of the system.ConclusionThe results showed that the sources of moisture for precipitation in the region are mainly the Red Sea, Arabian Sea, Oman Sea, and the North Indian Ocean, which were associated with a positive vorticity advection. Examination of thermodynamic conditions also showed that the instability indices in the hours before the onset of precipitation were favorable and intensified the convective activity of the systems. Convection cooling along with a severe decrease in temperature has shifted rain to snow. A significant decrease in temperature compared to the longterm average and the atmospheric cold column justifies the snowfall occurrence in spring. Keywords: Springtime Snowfall, Moisture Sources, Dynamic Analysis, Precipitation Anomaly, Chaharmahal and Bakhtiyari Province. References Banacos, P. C., Schultz, D. M. (2005). The Use of Moisture Flux Convergence in Forecasting Convective Initiation: Historical and Operational Perspectives. Journal of Weather and Forecasting, 20, 351 366. Dayan, U., Nissen, K., Ulbrich, U. (2015). Atmospheric Conditions Inducing Extreme Precipitation Over the Eastern and Western Mediterranean. Natural Hazards Earth System Sciences Journal, 15, 2525 2544.  Dyer, J. L., Mote, T. L. (2006). Spatial Variability and Trends in Observed Snow Depth Over North America. Journal of Geophysical Research Letters, 33, 16503. Frei, A., Robinson, D. A. (1999). Northern Hemisphere Snow Extent: Regional variability. International Journal of Climatology, 19, 1535 1560. Gutzler, D. S. (2000). Covariability of Spring Snowpack and Summer Rainfall Across the Southwest United States. Journal of Climate, 13, 4018 4027. Holton, J. R. (2004). An Introduction to Dynamic Meteorology. Fourth Edition, San Diego, California, USA: Elsevier Academic Press. Panziera, L., Hoskins, B. (2014). Weather Developments Leading to Heavy Snow in the South Eastern Lpine Region. National Weather Science. Perry, B., Konrad, C. E. (2006). Synoptic Patterns Associated with the Record Snowfall of 1960 in the Southern Appalachians. 63rd Eastern Snow Conference, Newark, Delaware USA. Quiring, S. M., Kluver, D. B. (2009). Relationship Between Winter/Spring Snowfall and Summer Precipitation in the Northern Great Plains of North America. Journal of Hydrometeorology, 10, 1203 1217. Stander J. H., Dyson, L., Engelbrecht, C. J. (2016). A Snow Forecasting Decision Tree for Significant Snowfall Over the Interior of South Africa, South African. Journal of Science, 112. Vuille, M., Ammann, C. (1997). Regional Snowfall Patterns in the High, Arid Andes. Journal of Climate Change, 36, 413423. Zhang, Y., Li, T., Wang, B. (2004). Decadal Change of the Spring Snow Depth Over the Tibetan Plateau: The Associated Circulation and Influence on the East Asian Summer Monsoon. Journal of Climate, 17, 2780 2793.
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