Modeling Spatial Distribution of Thunderstorm Rainfalls in Mountainous Areas of the Northwest Iran

Document Type : Full length article


1 PhD in Physical Geography, University of Mohaghegh Ardabili, Ardabil, Iran

2 Professor of Physical Geography, University of Mohaghegh Ardabili, Ardabil, Iran

3 Professor of Remote Sensing, University of Tabriz, Tabriz, Iran

4 Professor of Physical Geography, University of Tehran, Tehran, Iran


Thunderstorm is one of the meteorological phenomena mainly observed in most parts of the world. It is a major threat to modern societies operating in more local-scale. This natural event, despite having advantages in most cases,  is the most severe and destructive natural disaster due to the sudden occurrence. So, this can cause severe damage to many economic activities and human casualties. Convective storms usually affect small areas relative to tropical cyclones. Moreover, destructive effects are often less than the actual value. The thunderstorms are in the most frequent mode in the warm seasons on the land surface and in the cold seasons. Many factors influencing the occurrence of thunder storms are thermodynamic and kinematic conditions of the atmosphere, topography, and surface cover, coastal configuration and atmospheric flows. In this study, daily large-scale circulation patterns are initially characterized in the northwest area of Iran through SOMs technique. Then, the potential implications of circulation patterns to explain variability and change of the Ardabil precipitation are also attempted. Therefore, studying this phenomenon and identifying synoptic patterns have great influence on the region.  
Materials and method
The observed daily extreme precipitation records more than 50 mm during the 1961–2016 was used in this study using Ardabil Meteorological Data. Additionally, the daily geopotential heights at 500 hPa isobaric level (GH500) with the spatial resolution of 2.5° latitude × 2.5° longitude based on extreme precipitation days is used for circulation types. The data were obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset to identify circulation types. The circulation patterns in Ardabil were objectively evaluated with Pettit test. Based on this method, a significant abrupt change is detected in the series of the sum of q-error and t-error. This indicates 9 distinct circulation patterns with a 3 × 36 SOM topology to describe the changes in synoptic positions in the Ardabil area. In addition, the maps were created in the Grads software.
Results and discussion
In this study, daily circulation patterns are objectively examined through the use of SOM technique and are further linked to the extreme precipitation more than 50 mm characteristics in the northern areas of Iran, Ardabil, during the period 1961–2016. The results show that the SOM method could reasonably classify the daily geopotential height field at the 500 hPa vertical level over Ardabil province. By using an objective method (the Pettit test), 9 circulation types are qualified. Most of the severe precipitation patterns in Ardebil are related to the spring months. This is the time of the occurrence of thunderstorm in Ardebil. The 500 hpa HGT patterns during spring rainfall are associated with Omega Block, Rex Block and deep wave on Caspian Sea. This atmospheric pattern at the level of 500 Hpa has a completely baroclinic and unstable atmosphere in Ardabil which produced thunderstorm. In summer patterns, Ring Of Fire Block and Cut off Block are mainly observed in the region. This type of block occurs during the summer and the conditions of high pressure system are very stable. Cut off Block is a deep craft that occur with high-altitude change. In autumn pattern, a deep wave is seen in the northern part of Iran with a cut off block. Deep Wave is supplemented by cold weather in northern latitudes. In winter pattern, there is a Rex Block which is a set of systems with a strong high stack in the vicinity of a low-altitude strong layer. Ardebil is located on the eastern side of the wave with western winds that creates barocilinc atmosphere and precipitation. In the A1 group, the highest frequency is in May with 30%, in the A2 group with 34% the highest frequency is in April and the lowest frequency is in October with 5%. In the A3 group, the frequency is 15% in February, March, April and May. Also in group B2, the frequency of April, May and August are 8%. In group B3, the highest frequency with 25% and 15% are for October and November. In the C1 group, the July-September months are more than 16%. In the C2 group, January-April is 16% and 8% and in the C3 group, May, June and September are 8%. In the spring, the highest percentage of precipitation belongs to the B3 model with 45% fluctuation and the lowest amount of precipitation belongs to the A1 pattern with 20%. The patterns of A1 and C1 (45%), B1 (35%) and C3 (20%) are summer season patterns. The C1 pattern (45%) has only some rainfall in winter. The C3 pattern has a rainfall of only 25% and 15% in spring and summer. In autumn, the patterns of A1 (28%), A2 (10%), B1 (15%) and B3 (45%) are high-end models. In winter, only the patterns of A3 (35%) and B3 (20%) can account for the rainfall events.  


Main Subjects

ایران‏پور، ف.؛ یزدان‏پناه، ح. و حنفی، ع. (1394). تجزیه و تحلیل ترمودینامیکی توفان‏های تندر در ایستگاه‏های هواشناسی همدان، مجلة جغرافیا و مخاطرات طبیعی، ش13: 116-117.
جلالی، ا. (1385). تحلیل زمانی و مکانی بارش‏های رعد و برقی منطقة شمال غرب ایران، پایان‏نامة دکتری، دانشگاه تبریز.
جلالی، ا. و جهانی، م. (1387). بررسی پراکنش مکانی بارش‏های تندری شمال غرب ایران، فصلنامة فضای جغرافیایی، ش 23: 140-145.
خالصی، ف. (1393). واکاوی زمانی توفان‏های تندری در ایران، دوفصل‏نامة آب و هواشناسی کاربردی، ش 1: 48-49.
دانشور وثوقی، ف. و دین‏پژوه، ی. (1391). بررسی روند تغییرات کیفیت آب زیرزمینی دشت اردبیل با استفاده از روش اسپیرمن، نشریة محیط‏شناسی، دورۀ 38، ش 4: 17-18.
قویدل رحیمی، ی. (1391). تحلیل سینوپتیک بارش‏های رعد و برقی 4 و 5 اردیبهشت 1389، نشریة علمی‏- پژوهشی جغرافیا، برنامه‏ریزی تبریز، ش42: 222-224.
صلاحی، ب. (1389). بررسی ویژگی‏های آماری و همدیدی توفان‏های تندری استان اردبیل، پژوهش‏های جغرافیای طبیعی، ش72: 130-132.
صلاحی، ب. و عالی‏جهان، م. (1394). استخراج و تحلیل الگوهای سینوپتیک منجر به توفان‏های تندری دشت اردبیل، پژوهش‏های جغرافیای طبیعی، دورۀ 47، ش 3: 400-402.
لشکری، ح. و آقاسی، ن. ی. (1392 ). تحلیل سینوپتیک توفان تندری تبریز در فاصلة زمانی 1996- 2005، نشریة علمی‏- پژوهشی جغرافیا و برنامه‏ریزی، ش 45: 202-206.
Bielec-Ba˛ Kowska, Z. (2003). Long-term variability of thunderstorm occurrence in Poland in the 20th century, Atmospheric Research, 67-68: 35-52.
Cassano, EN.; Lynch, AH.; Cassano, JJ. and Koslow, MR. (2006). Classification of synoptic patterns in the western Arctic associated with extreme events at barrow, Alaska, USA. Clim Res, 30: 83-97.
Dai, A. (2001). Global precipitation and thunderstorm frequencies, Part I: seasonal and interannual variations. J. Clim., 14(6): 1092-1111.
Daneshvar Vosoughi, F. and Dinpaypooh, Y. (2012). Investigating the process of underground water quality changes in Ardebil plain using Spearman method, Journal of Ecology, 38(4).
Czernecki, B., Taszarek, M., Kolendowicz, L. and Szyga-Pluta, K. (2015). "Atmospheric conditions of thunderstorms in the European part of the Arctic derived from sounding and reanalysis data". Atmospheric Research. 154. pp. 60–72.
Ghavidel Rahimi, Y. (2012). Synoptic Analysis of Thunderstorms and Thunderstorms May 4th and 5th, 2010, Geographical Research Journal, Tabriz Planning No. 42.
Hewitson, B.C. and Crane R.G. (2002). Self-organizing maps: applications to synoptic climatology, Clim Res, 22: 13-36.
Jalali, U. (2006). The temporal and spatial analysis of rainfall in the northwest Iran, PhD thesis, Tabriz University.
Johnson, N.C. and Feldstein, SB. (2010). The continuum of North Pacific Sea level pressure patterns: intra seasonal, annual, and inter decadal variability. J Clim, 23: 851-867.
Iranpour, F.; Yazdanpaq, H. and Hanafi, A. (2015) . Thermodynamic analysis of Thunder storms at Hamedan meteorological stations, Geography Magazine and natural hazards, No. 13.
Kunz, M.; Sander, J. and Kottmeier, CH. (2009). Recent trends of thunderstorm and hailstorm frequency and their relation to atmospheric characteristics in southwest Germany, International journal of climatology int. j. climatol, 29: 2283-2297.
Kohonen, T. (2001). Springer series in information sciences, In: Self-Organizing Maps, 3rd ed., Vol 30. Springer, Berlin.
Kohonen, T. (1995). Springer series in information sciences. In: Self-Organizing Maps, Vol 30. Springer, Berlin.
Kolendowicz, L. (2012). Synoptic patterns associated with thunderstorms in Poland, MeteorologischeZeitschrift, 21(2): 145-156.
Lashkari, H. and Aghasi, N. (2013). Synoptic Analysis of the Thunderbolt Tandris in Tabriz during the period 1996-2005, Journal of Geography and Planning Research, No. 45.
Pettitt, A.N. (1979). A non-parametric approach to the change pointproblem, Appl Stat, 28(2):126-135.
Rousi, E.; Anagnostopoulou, C.; Tolika, K. and Maheras, P. (2015.) Representing teleconnection patterns over Europe: a comparison of SOMand PCA methods, Atmos Res, 152: 123-137.
Rabin, R.M. and Davies-Jones, R.P. (1986). Atmospheric structure ahead of thunderstorms, Endeavour, 10(1): 20-27.
Selahi, B. and Ezzhjaran, M. (2015).  Extraction and analysis of synoptic patterns leading to Thunder storms in Ardebil plain, Natural geographic research, 47(3).
Tuomi, T.J. and Mäkelä, A. (2003). Synoptic Classification of Thunderstorms in Finland, Geophysica, 39(1-2): 3-30.
Van Delden, A. (2001). The synoptic setting of thunderstorms in Western Europe, Atmospheric Research, 56: 89-110.
Wapler, K. and James, P. (2014). Thunderstorm occurrence and characteristics in Central Europe under different synoptic conditions, Atmospheric Research, pp. 1-14.