1
Professor in Climatology, University of Sistan and Baluchestan, Zahedan, Iran
2
Ph.D in Climatology, University of Sistan and Baluchestan, Zahedan, Iran
Abstract
Background: Extreme temperature events can impose serious impacts on environment and societies. Since the outbreak of cold and frost are one of the important factors of climate in many parts of Iran, utilization of a new model for predicting the continuity of these factors is necessary. Materials and Methods: This paper uses high-order categorical non-stationary Markov chains to study the occurrence of extreme cold temperature events by transition and probabilities matrixes in Zabol, southeast of Iran. The occurrence of frost days, homogeneity, continuity and spatial duration were analyzed for 30 years (April 1982- April 2012). The multivariate regression was used to modeling and mapping the statistical characteristics of frost and Kriging interpolation method in Arc/GIS was applied for its relationship. Results: The occurrence of frost days in Zabol was in conformity with Markov model characteristic that showed the continuation of frost days depended on the weather of preceding days. Discussion and Conclusions: Heavy frost in Zabol is expected to occur in Jan and Feb. Thus, frost-free day cycle duration was more than frost cycle and occurrences of frost in short term were more than long term in the studied period.
Klemes V, Bulu A. Limited confidence in confidence limits derived by operational stochastic hydrologic models. J Hydrol. 1979; 42(2):9-22.
Ladoy Ph. Etude des probabilité s de transitions pour les types journaliers de distribution spatial de la pluie. Actes du 3`e me colloque sur l’analyse des données en géographie, Besançon, 1974: 177-202.
Mares I. A Markov chain for evaluation of Moon rainfalls (in Romanian). Studi si Cercetari de Meteorologie, Part I/139. 1976; 4: 203-219.
Subramaniam A, Sanjeeva P. Dry spell sequences in south coastal Andhra, Mausam. 1989; 40: 57-60.
Tsakiris G. Stochastic modeling of rainfall occurrences in continuous time Hydrological sciences. Journal des Sciences Hydrologiques., 1988; 33(2): 5-10.
Hess GD, Leslie LM, Guymer AE, Fraedrich K. Application of a Markov technique to the operational, short-term forecasting of rainfall. Aust Meteorol Mag. 1989; 37 (2): 83-91.
Watkins C. The Annual Period of Freezing Temperatures in England 1850-1989. Int J Climatol. 1991; 11:889-896.
McMahon TA, Srikantha R. Stochastic generation of annua, monthly and daily climate data. Hydrol Earth Syst Sc J. 2001; 5(4): 238-670.
Drton MC, Marzban PG, Schaefer JT. A Markov chain model of tornado activity. Monthly Weather Review. 2003; 131: 2941-2953.
Finley AO, Banerjee S, EK AR, Roberts RE. Bayesian multivariate process modeling for prediction of forest attributes. J Agric Biol Envir S. 2008; 13: 60.
Usman Yusuf A, Adamu L, Abdullahi M. Markov chain model and its application to annual rainfall distribution for crop production. American Journal of Theoretical and Applied Statistics. 2014; 3(2): 39-43.
Yuan W, Goncu A, OktenG. Estimating sensitivities of temperature-based weather derivatives. Applied Economic Letters J. 2015; 47(19):1942-1955.
Huang J, Wu Y, Gao T, Zhan Y, Cui W. An integrated approach based on Markov Chain and cellular automata to simulation of urban land use changes. Applied Mathematics and Information Sciences. 2015; 9 (2): 769-775.
Ramezani N, Jafari R. Droughts and wet change detection with. CA-Markov chain model (Case study: Mazandaran). Geographical Research Journal, 2012; 2: 16-18.
Hejazizadeh Z, ShirKhani A. Analysis and Predict of Statistical Drought and Short Period Dry Spells in Khorasan Region. Quarterly Geographical Research. 2005; 37(52): 2-20.
Kardavani, P. A survey on dry and wet spells in Teheran using Markov chain model and synoptic analysis. Sarzamin Quarterly Journal. 2006; 17: 11-34.
Mozaffari G, Ghaemi H. Rain Fall Condition Analysis in Dry Land Farming. Area (Case Study: East of Kermanshah). Research in Geography. 2003; 42: 103- 119.
Alijani B, Hoshiar M. Recognition of Synoptic Patterns of Severe Colds of WestNorth of Iran. Physical Geographical Research. 2007; 65: 1-16.
Lashanizand M, Gholamrezaee S. Assessment of Relationship between Climatological Variables and Discharge of Karstic Springs in order to Manage Urban Water Resources Case study: Khorramabad City. Amayesh Journal. 2012; 15: 61-64.
Feizi V, Mollashahi M, Frajzadeh M, Azizi G. Spatial and Temporal Trend Analysis of Temperature and Precipitation in Iran. Ecopersia. 2014; 2 (4): 727-742.
Khosravi M, Habibi Noukhandan M, Esmeili R. Zonation of late chilblain risk impacts on gardens (case study: Mahvalat region). Geography and Development. 2009; 6 (12): 117-144.
Hosseini A, Fallahnezhad MS, ZareMehrjardi Y, HosseiniR. Seasonal Autoregressive Models for Estimating the Probability of Frost in Rafsanjan. Journal of Nuts. 2012; 3(2):45-52.
Ghadermarzi H. Analysis and Prediction of Climatic Fluctuations in Kurdistan Province using Markov Chain Model. M.S. Thesis, Tarbiat Moallem University., Faculty of Literature and Humanities. 2005: 75-82.
Rouhi- Moghaddam E, Sargazy E, Gholamalizadeh A. Ecological Properties of Tamarix Habitats in Sistan Plain, Iran. Ecopersia, 2015; 3 (4): 1201-1211.
Ziaee AR, Kamgar-Haghighi AA, Sepaskhah AR, Ranjbar S. Development of Fars province probable minimum temperature atlas using meteorological data. Journal of Science and Technology Agriculture Research, 2006; 10(3): 13-27.
Robeson SM. Increasing growing-season length in Illinois during the 20th century. Climatic Change, 2002; 52(1): 219-238.
Liu B, Henderson M, Xu M. Spatiotemporal change in China's frost days and frost‐free season, 1955–2000. Journal of Geophysical Research: Atmospheres, 2008; 113(D12).
Meehl GA, Tebaldi C,Nychka D. Changes in frost days in simulations of twentyfirst century climate. Climate Dynamics, 2004; 23(5): 495-511.
Anandhi A, Perumal S, Gowda PH, Knapp M, Hutchinson S, Harrington J, et al. Long-term spatial and temporal trends in frost indices in Kansas, USA. Climatic Change, 2013; 120(1-2): 169-181.
Ansari H. Drought monitoring and mapping using fuzzy logic and geographic information systems, irrigation and drainage. PhD. Thesis, Tarbiat Modarres University., Faculty of Agriculture. 2005; 42-53.
Alijani B, Jafarpur Z, Ghaderi H. Precipitation Analysis and Prediction ofLarestan Region using Markov Chain. Quarterly geographical Territory. 2005; 2(7): 127-131.
Tavousi T, Derakhshi J. Statistical analysis of probability and return periods of early frost in Zahedan. Research geographical space Journal, 2011; 10(30): 89-104.
Barati G. System Relationships of Migratory High Pressures and Spring Frosts of Iran. Geographical Research Quarterly. 1999; 14 (3 and 4): 132-150.
Avissar R, Mahrer Y. Mapping frost-sensitive areas with a three-dimensional local-scale numerical model: Part I: physical and numerical aspects. Journal of applied meteorology. 1988; 27: 400-413.
Tavousi,T. and Ghobadi,A. (2017). Evaluation of Frost Days Continuity Using Markov Chain Model: Case Study of Zabol city in Iran. ECOPERSIA, 5(4), 1919-1932.
MLA
Tavousi,T. , and Ghobadi,A. . "Evaluation of Frost Days Continuity Using Markov Chain Model: Case Study of Zabol city in Iran", ECOPERSIA, 5, 4, 2017, 1919-1932.
HARVARD
Tavousi,T.,Ghobadi,A. (2017). 'Evaluation of Frost Days Continuity Using Markov Chain Model: Case Study of Zabol city in Iran', ECOPERSIA, 5(4), pp. 1919-1932.
CHICAGO
T. Tavousi and A. Ghobadi, "Evaluation of Frost Days Continuity Using Markov Chain Model: Case Study of Zabol city in Iran," ECOPERSIA, 5 4 (2017): 1919-1932,
VANCOUVER
Tavousi,T.,Ghobadi,A. Evaluation of Frost Days Continuity Using Markov Chain Model: Case Study of Zabol city in Iran. ECOPERSIA, 2017; 5(4): 1919-1932.