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:: Volume 32, Number 2 (9-2017) ::
geores 2017, 32(2): 40-51 Back to browse issues page
Examine the Balance Between the Atmosphere Changes Affecting Zab Basin Storms
Dr Nader Parvin
Assistance Professor, Department of geography Payame Noor University
Abstract:   (115 Views)
Storm as one of the natural disasters has affected different regions and caused great economic, social, political and environmental losses. In this paper, after defining storm threshold, data of level 500 HPa height for 40 days of storm during the period (1986-2011) were processed using an advanced factor analysis. And finally, based on the correlation matrix (variance-covariance) and Varmix rotation on the factors, major topography variation centers at 500 hPa that affect heavy storms at Zab River Basin were discovered and analyzed. The results show that, eight centers have been involved in occurrence of storms. Among these eight centers, four centers that have the highest anomalies (R>0.7) at 500 HPa height, are detectable. 1) Axis of Middle East - North Africa to Northern Russia. 2) African tropical areas-Indian Ocean. 3) North Asia-North Europe. 4) The Scandinavian region. Such changes would strengthen and deepen the axis of ridges in these regions at 500 hPa level, and consequently synoptic storm patterns are created. Meanwhile, changes in the first 500 HPa at the first center (Axis of Middle East - North Africa to Northern Russia), have the most influence on the development of storms in Zab River Basin.
Keywords: Storm, Factor Analysis, 500 HPa Level, Zab Lake Basin
Full-Text [PDF 1147 kb]   (78 Downloads)    
Type of Study: Research | Subject: Special
Received: 2017/09/2 | Accepted: 2017/09/2 | Published: 2017/09/2
1. Alijani, B., Rezaei, M., Jahfari, F., Pazhoh, F. (2015), Variability of geopotential height at 500 hPa and its role in January's temperature fluctuations, geographical studies drylands, 20, pp. 45-34. (in Persian).
2. .Barati, H., Haroonabadi, H., Zadehali, R. (2013), Wind speed forecasting in South Coasts of Iran، An Application of Artificial Neural Networks (ANNs) for Electricity Generation using Renewable Energy, Bull. Env. Pharmacol, Life Sci, Vol. 6, pp. 30-37.
3. Brower, M.C., M.S., Barton, L., Lledó., Jason, D. (2013), A study of wind speed variability using global reanalysis data, AWS True power, pp. 3-12.
4. Chen, X., Wang, Y., Zhao, K. (2015), Synoptic Flow Patterns and Large-Scale Characteristics Associated with Rapidly Intensifying Tropical Cyclones in the South China Sea, Monthly Weather Review, 143, pp.64-87.doi.org/10.1175/MWR-D-13-00338.1
5. Colin, M. Z. (2016), Tropical Cyclone Intensity Errors Associated with Lack of Two-Way Ocean Coupling in High-Resolution Global Simulations, Journal of Climate, 29, pp. 8589-8610.
6. Durkee, J., Degu, A.M., Hossain, F., Mahmood, R., Winchester, J., Chronis, T. (2014), Investigating the Effect of the “Land between the Lakes” on Storm Patterns, Journal of Applied Meteorology and Climatology, 53، No. 6, DOI: http،//dx.doi.org/10.1175/JAMC-D-13-088.1
7. Dynpzhoh, Y., Niyazi, F., Mofid, H. (2015), Trend analysis meteorological parameters in Tabriz, Geography and Planning, 51, pp.169-145. (in Persian).
8. Erdem, E., Shi, J., Yidong, P. (2014), Short-Term Forecasting of Wind Speed and Power - A Clustering Approach, Industrial and Systems Engineering Research Conference, pp.1-12.
9. Falah Qalhar, G.A., Shaker, F. (2015), Identify the changes in the frequency of thunderstorms in Iran, applied research Geographical Sciences, 38, pp. 118-97, (in Persian).
10. Ghaffari, D., Mostafazadeh, R. (2015), Study the origin, effects and solutions to the phenomenon of dust in Iran, protection and exploitation of natural resources, 2, pp. 107-125, (in Persian).
11. Ghasemi, A.R., Sayedi, F.S. (2015), Simulate and predict changes in wind speed using statistical data fifty years (2010-1961), GIS (sphere), 94, pp.105-95. (in Persian).
12. https//www.ipcc.ch/
13. https//www.ncdc.noaa.gov/
14. Jahanbakhsh Asl, S., Asadi, M., Akbari, E. (2016), Assess the potential wind farm using Fuzzy-AHP in GIS (Case Study, the North East of the country), Geography and Planning, 56, pp. 301-277, (in Persian).
15. Karimi, M., Azizi, G., Shamsipour, A., Rezaei Mehdi Abadi, L. (2016), Dynamic simulation impact on the thickness and depth of the Alborz mountain range on the southern coast of the Caspian Sea Breeze, applied research Geographical Sciences, 41, pp. 152-135. (in Persian).
16. Karimyan, B., Landi, A., Hojjati, S., Ahadyan, J. (2016), Determine the physical, chemical and mineralogical dust Ahvaz, Iran Soil and Water Research, 1, pp.173-159, (in Persian).
17. Kermani, M., Taherian, E., Izanloo, M. (2016), Analyzed satellite images of dust storms and dust in Iran to investigate internal and external to recognize the sources and methods of their control, health outcomes, 1, pp. 51-39. (in Persian).
18. Lashkary, H., Agassi, N. (2013), Synoptic analysis thunderstorms Tabriz are Zmany2005-1996, Geography and Planning, 45, pp. 234-203. (in Persian).
19. Masumpoor Samakoosh, J., Fajavand, A. (2015), Statistical analysis - Thermodynamics thunderstorms Iran, geography and regional development, 25, pp.248-227. (in Persian).
20. Mekis, E., Lucie, A., Vincent, M., Shephard, W., Zhang, X. (2015), Observed Trends in Severe Weather Conditions Based on Humidex, Wind Chill, and Heavy Rainfall Events in Canada for 1953–2012, Atmosphere-Ocean, 53, pp. 383-397.
21. Mirzakhani, A. (1999), analysis of flood risk and its harmful effects on Iran, insurance, 13, pp. 15-8, (in Persian).
22. Muis, S., Verlaan, M., Winsemius, H.C., Aerts, J.C.J., Ward, P.J. (2016), A global reanalysis of storm surges and extreme sea levels, Nature Communications, 7, pp. 1-12.
23. Mullens, E.D., Leslie, L.M., J. Lamb, P.J. (2016), Synoptic Pattern Analysis and Climatology of Ice and Snowstorms in the Southern Great Plains, 1993–2011, Weather and Forecasting, DOI: http،//dx.doi.org/10.1175/WAF-D-15-0172.1
24. Nakajo, S., Mori, N., Yasuda, T., Mase, H. (2014), Global Stochastic Tropical Cyclone Model Based on Principal Component Analysis and Cluster Analysis, DOI: http،//dx.doi.org/10.1175/JAMC-D-13-08.1.
25. Needham, H.F., Keim, B.D., Sathiaraj, D. (2015), A review of tropical cyclone-generated storm surges، Global data sources, observations, and impacts, Rev, Geophys. 53, pp. 545–591.
26. Parvin, N. (2013), Classification and analysis Synoptic patterns of the most sever wet year Urmia Lake Basin during 1977-2012, International Research Journal of Applied and Basic Sciences, 10, pp. 3058-3062.
27. Rezaei Banafsheh, M., Javan, K., Zainal, B. (2011), Assess changes in wind speed in the North West of Iran, Geography, 13, pp. 36-27. (in Persian).
28. Saligheh, M. (2015), Climate change and climatic hazards in Tehran, spatial analysis of environmental hazards, 3, pp. 32-15. (in Persian).
29. Shen, S. (2003), Global warming science and policy، progress 2002-2003, Proceeding of 14th Global warming International conference and expo (24-30 may, Boston. USA), pp. 7-18.
30. Tuovinen, J.P., Rauhala, J., Schultz, D.M. (2015), Significant-Hail-Producing Storms in Finland, Convective-Storm Environment and Mode, Weather and Forecasting, 30, pp. 1064-1076.
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DOI: 10.18869/acadpub.geores.32.2.40

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Parvin N. Examine the Balance Between the Atmosphere Changes Affecting Zab Basin Storms. geores. 2017; 32 (2) :40-51
URL: http://georesearch.ir/article-1-214-en.html
Volume 32, Number 2 (9-2017) Back to browse issues page
فصلنامه تحقیقات جغرافیایی Geographical Researches Quarterly Journal
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