Estimating the occurrence probability of Spring Thunderstorms using Markov chain, Case Study: Tabriz

Document Type : Research Article

Authors

1 Department of Geography, Payam Noor University, Tehran, Iran

2 Assistant Professor of Climatology, Department of Geography, Urmia University, Urmia, Iran

3 Professor of Climatology, Faculty of Geography and planning, Tabriz University, Tabriz, Iran

4 PhD Student of Climatology, Faculty of Geography and planning, Tabriz University, Tabriz, Iran

Abstract

Thunderstorms are one of the climatic phenomena that cause numerous damages in different parts of the world, due to the accompaniment with thunder, high winds, hail and heavy precipitation. In this study, the probability of thunderstorm days in Tabriz in the spring is analyzed using probabilistic rules and Markov chain model. For this purpose, the daily data related to thunderstorms (codes 95 to 99) was used for 65 years (1951-2015). At first, the daily data is classified into the normal days (code 0) and thunderstorm days (code 1). Then the frequency matrix is formed and the probability matrix is created accordingly based on maximum likelihood method. The Markov chain properties such as empirical probability and equilibrium probability, Frequency of occurrence, mean time periods and weather cycle were investigated. Finally, Occurrence Probability and return period of these spells were determined. The results show that the shortest weather cycle is in May, which has the highest frequency of thunderstorms. Conversely, the longest weather cycle is in April, which has the lowest frequency of thunderstorms. Also, in 65 years period, the one-day and two-day stormy sequences have the highest frequency. And For longer sequences, the frequency of thunderstorm days is reduced. The return period of one-day and two-day stormy spells is 1.5 and 5 days. Regression relation between the observed and estimated values of n-step periods of thunderstorm days shows that the considered accuracy and reliability for all months is more than 99%.

Keywords


References (in Persian)
Abbasnia, M., Tavoosi, T., Poorhashemi, S. (2015). Statistical Analysis and Prediction of Short-term Stormy Periods of Sabzevar by Markov Chain Model, Geographic Space, 15(50), 233-250 (In Persian).
Alizadeh, A. (2010). Principles of applied Hydrology, Imam Reza University Press, 432 pages (In Persian).
Alizadeh, A., Kamali, Gh., Mousavi, F., Mousavi Bayegi, M. (2001). Weather and Climate, Ferdowsi University of Mashhad press, Mashhad (In Persian).
Asakereh, A. (2008). Analysis of the Frequency and the Spell of Rainy Days Using Markov Chain Model for City of Tabriz, Iran, Iran-Water Resources Research, 4 (2), 46-56 (In Persian).
AshgarTousi, Sh., Alizadeh, A., Javanmard, S. (2003). Prediction of drought probability in Khorasan, Geographical Research, 70, 119-128 (In Persian).
Darand, M., Narimani, M., Shariati, J., Namdari, Sh. (2015). Temporal-Spatial Analysis of Numbering Trend of Thunderstorm Days in Iran, Geography, and Environmental Studies, 4(15), 35-48 (In Persian).
Hejazizadeh, Z., Shirkhani, A. (2005). Statistical analysis and forecasting of droughts and short-term dry and wet periods in Khorasan, Geography Research Quarterly, 37(52), (In Persian).
Jafarpour, E. (2006). Fundamentals of Climatology, Payam-e Noor University Press, 204 pages (In Persian).
Javan, K. (2017). Analysis of the Spell of Rainy Days in Lake Urmia Basin using Markov Chain Model, research in Geographical Sciences, 16 (43), 173-193 (In Persian).
Kaviani, M., Alijani, B. (1996). Fundamentals of Climatology, Samt Press (In Persian).
Khoshal Dastjerdi, J., Ghavidel Rahimi, Y., (2007). Identification of Environmental Hazards Properties in North West Iran: A Case Study of Thunderstorm Hazards in Tabriz, Human Sciences Modares, 11(53), 101-116 (In Persian).
Lashkari, H., Aghasi, N. (2013). Synoptic analysis of thunderstorms in Tabriz (1996-2005), Geography and Planning, 17(45), 203-234 (In Persian).
Moghimi, E. (2015). Hazards science (for living with better quality), University of Tehran Press, 242 pages (In Persian).
Rasouli, A. (2005). Modeling of thunderstorm rainfalls in Tabriz from the flood risk perspective, International Conference on Natural Disasters, Tabriz University, 1-119 (In Persian).
Rasouli, A., Bodaghjamali, J., Jalali, O. (2007). Temporal distribution of thunderstorm rainfalls in the northwest of IRAN, Quarterly Research Bulletin of Isfahan University (Humanities), 27(1), 156-170 (In Persian).
Rasouli, A., Javan, Kh. (2012). Analyzing of thunderstorm occurrence trends in the western part of Iran applying non-parametric statistical tests, Geographic Space, 12(38), 111-126 (In Persian).
Raziei, T., Daneshkar Arasteh, P., Akhtari, R., Saghafian, B. (2007). Investigation of Meteorological Droughts in the Sistan and Balouchestan Province, Using the Standardized Precipitation Index and Markov Chain Model, Iran-Water Resources Research, 3(1), 25-35 (In Persian).
Salahi, B. (2010). Statistical and Synoptic Analysis of Characteristics of Thunderstorms in Ardabil Province, Physical Geography Research Quarterly, 42(72), 129-141 (In Persian).
Tavoosi, T., Rigi, A. (2017). An Analysis of the Continuity of Windy Days by Using Markov Chain Model in Zahedan, Geographic Space, 17(58), 131-148 (In Persian).
 
References (in English)
Ahrens, C. D. (2012). Meteorology today: an introduction to weather, climate, and the environment. Cengage Learning.
Blunden, J., & Arndt, D. S. (2016). State of the Climate in 2015. Bulletin of the American Meteorological Society, 97(8).
Chattopadhyay, S., Acharya, N., Chattopadhyay, G., Prasad, S. K., & Mohanty, U. C. (2012). Markov chain model to study the occurrence of pre-monsoon thunderstorms over Bhubaneswar, India. Comptes Rendus Geoscience, 344(10), 473-482.
Dasgupta, S., & De, U. K. (2001). Markov chain models for pre-monsoon thunderstorm in Calcutta, India.
Gaál, L., Molnar, P., & Szolgay, J. (2014, May). Spatial analysis of intense thunderstorms in Switzerland and temporal trends in their occurrence. In EGU General Assembly Conference Abstracts (Vol. 16, p. 11136).
Kulkarni, M. K., Kandalgaonkar, S. S., Tinmaker, M. I. R., & Nath, A. (2002). Markov chain models for pre‐monsoon season thunderstorms over Pune. International journal of climatology, 22(11), 1415-1420.
Mohee, F. M., & Miller, C. (2010). Climatology of thunderstorms for North Dakota, 2002–06. Journal of Applied Meteorology and Climatology, 49(9), 1881-1890.
Moon, S. E., Ryoo, S. B., & Kwon, J. G. (1994). A Markov chain model for daily precipitation occurrence in South Korea. International journal of climatology, 14(9), 1009-1016.
Pinto, O., Pinto, I. R. C. A., & Ferro, M. A. S. (2013). A study of the long‐term variability of thunderstorm days in southeast Brazil. Journal of Geophysical Research: Atmospheres, 118(11), 5231-5246.
Sonnadara, U. (2016). Spatial and temporal variations of thunderstorm activities over Sri Lanka. Theoretical and Applied Climatology, 124(3-4), 621-628.
Wilks, D. S. (2006). Statistical methods in the atmospheric sciences (second edition). Academic Press, USA.
Volume 7, Issue 18 - Serial Number 4
December 2019
Pages 189-204
  • Receive Date: 01 June 2017
  • Revise Date: 17 April 2018
  • Accept Date: 02 June 2018
  • First Publish Date: 22 December 2018
  • Publish Date: 22 December 2018