Classification of Air Masses in Urmiah by Cluster Analysis and Quality Control Inter Group’s Variance Indices

Document Type : Research Paper

Authors

Climatology, Faculty of Natural Resources, University of Kurdistan

Abstract

     In order to dong this study, daily data of 34 meteorological variables during 1/1/1961 to 30/6/2013 from Urmiah synoptic station has been used. Cluster Analysis with Ward method applied on the Euclidean distance. The numbers of clusters determined by quality control inter group’s variance Indices. The results show that clustering air mass to seven groups is the optimum. The second air mass is the most rainiest air mass which its rainy occurrence probability equal to 65.7% and the amount of precipitation per day equal to 6.6 mm. The fourth air mass is the hottest and drier air mass which has observed in the one third of year’s day. The fourth air mass with the occurrence index of 0.89 and with persistency of 9 days is the most stable air mass. While the third air mass with the occurrence index of 0.43 and with persistency of 1.7 days is the most unstable air mass. The third air mass with sequantality of 21.1% is the most agreeable air mass which occurs after the second air mass subsequently. Daily variety of air mass index get highest value during winter season (69%) while it gets to zero in some days of July and August which indicates a certain air mass (the fourth).

Keywords


1-    علیجانی، ب. 1381. شناسایی تیپ­های هوایی باران آور تهران براساس محاسبه چرخندگی. مجله تحقیقات جغرافیایی،شماره (63): 132-114.
 
2-    فتاحی، ا. و ز. حجازی­زاده. 1384. طبقه بندی همدیدی فضایی توده های هوا در حوضه­های جنوب­غربی ایران، مجله جغرافیا و توسعه، شماره (6):
156-135.
3-    مسعودیان، س.ا. 1391. شناسایی گونه­های هوای اصفهان، مجله تحقیقات جغرافیایی، شماره(27): 86-65.
 
4-    Alpert, P., Osetinsky, I., Ziv,  B. and H. Shafir.  2004.  Semi-objective classification for daily synoptic systems: Application to the eastern Mediterranean climate change. International Journal of Climatology, 24: 1001–1011.
 
5-    Coleman, J.S.M. and J.C. Rogers. 2007. A synoptic climatology of the central United States and associations with Pacific teleconnection pattern frequency, Journal of Climate, 20: 3485–3497.
 
6-    Dunn, J.C. 1974. Well separated clusters and optimal fuzzy partitions, Journal of Cybernetics, 4: 95-104.
 
7-    Hewitson, B.C. and R.G.  Crane. 2002. Self organizing maps: applications to synoptic climatology. Climate Research, 22: 13–26.
 
8-    Hubert, L. and J. Schultz. 1976. Quadratic assignment as a general data-analysis strategy. British Journal of Mathematical and Statistical Psychology, 29: 190-241.
 
9-    Huth, R. Beck, Ch., Philipp, A., Demuzere, M., Ustrnul, Z., Cahynova, M., Kysely, J and E. Tveito. 2008. Classification of atmospheric circulation patterns: Recent advances and application, Trends and direction in climate research. Annals of the New York Academy of Sciences, 1146: 105-152.
 
10- Jiang, N. 2011. A new objective procedure for classifying New Zealand synoptic weather types during 1958–2008. International Journal of Climatology, 31: 863-879.
 
11- Kalkstein,  L.S., Nichols, M.C., Barthel, C.D., and J.S. Greene. 1996. A new spatial synoptic classification: application to air-mass analysis.  International Journal of Climatology, 16: 983–1004.
 
12- Kassomenos PA, Gryparis A. and K. Katsouyanni. 2007. On the association between daily mortality and air mass types in Athens, Greece during winter and summer. International Journal of Biometerology, 51: 315–322.
 
13- Key, J. and R.G. Crane. 986. A comparison of synoptic classification schemes based on objective procedures.  Journal of Climate,  6: 375–388.
 
14- Kidson,  J.W. 1994. An automated procedure for the identification of synoptic types applied to the New Zealand region. International Journal of Climatology,  14: 711–721.
 
15- Kostopoulou , E. and P.D. Jones. 2007. Comprehensive analysis of the climate variability in the eastern Mediterranean, Part II: relationships between atmospheric circulation patterns and surface climatic elements.  International Journal of Climatology,  27: 1351–1371.
 
16- Lamb,  H.H. 1950. Types and spells of weather around the year in the British Isles: annual trends, seasonal structure of the year Singularities. Quarterly Journal of Royal Meteorological Society, 76:  393–429.
 
17- Maheras,  P. 1989.  Delimitation of the summer dry period in Greece according to the frequency of weather-types. Theoritical and Applied Climatology, 39: 171–176.
 
18- Maheras, P. 1988. The synoptic weather types and objective delimitation on the winter period in Greece. Weather, 43: 40–45.
 
19- Michailidou, C., Maheras, P., Arseni-Papadimititriou, A., Kolyva-Machera, F. and  A. Anagnostopoulou. 2008. A study of weather types at Athens and Thessaloniki and their relationship to circulation types for the cold-wet period, part I: two-step cluster analysis. Theoritical and Applied Climatology, 97: 179-94.
 
20-  Schwartz, M.D.  and B. R Skeeter. 1994. Linking air mass analysis to daily and monthly mid-tropospheric flow patterns, International Journal of Climatology, 14: 439–464.
 
21- Xie, X.L. and G. Beni. 1991. A validity measure for fuzzy clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(4): 841-846.
 
22- Yarnal, B. 1993. Synoptic climatology in environmental analysis. Belhaven Press, London, UK, 195 pp.
 
23- Yarnal, B., Comrie,  A.C., Frakes,  B. and D.P.  Brown. 2001.  Developments and prospects in synoptic climatology. International Journal of Climatology, 21: 1923–1950.
Volume 40, Issue 2
September 2017
Pages 183-198
  • Receive Date: 25 April 2015
  • Revise Date: 25 September 2017
  • Accept Date: 01 May 2016
  • Publish Date: 23 August 2017