شناسایی کانون‌های فعالیت تاوایی نسبی تراز 500 هکتوپاسکال مؤثر بر بارندگی در ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس سازمان هواشناسی کشور

2 استاد ،دانشگاه خوارزمی تهران، تهران، ایران

3 دانشیار، عضو هیات علمی پژوهشگاه هواشناسی و علوم جو

چکیده

به منظور واکاوی همبستگی بین بارندگی بخش­های مختلف ایران با پراکنش زمانی و مکانی کانون­های فعالیت تاوایی نسبی، مقادیر ماهانه تاوایی نسبی در بازه زمانی 2017-1981 با استفاده از باد مداری و نصف­النهاری پایگاه داده­های بازتحلیل NCEP-DOE در تراز فشاری 500 هکتوپاسکال در محدوده مکانی 10تا70 درجه شرقی و 10تا70 درجه شمالی محاسبه شد. داده­های بارندگی ماهانه کشور نیز در همان بازه زمانی از 97 ایستگاه سینوپتیک کشور دریافت شدند. آن­گاه با استفاده از روش تحلیل مؤلفه­­های اصلی، کانون­های فعالیت تاوایی نسبی در منطقه مورد مطالعه و کانون­های بارشی کشور شناسایی شدند. سپس تحلیل همبستگی کانونیکال بر روی نمره عاملی این کانون­ها اجرا شد و با شناسایی سه ترکیب خطی مختلف، محدوده­های فضایی فعالیت تاوایی نسبی مؤثر بر بارندگی بخش­های مختلف کشور شناسایی شدند. در ترکیب خطی اول تغییرات تاوایی نسبی تراز 500 هکتوپاسکال در محدوده خاورمیانه و مدیترانه شرقی با بارندگی شرق کشور، به میزان 0.7 همبستگی مثبت دارد و در صورتی که مقادیر تاوایی نسبی در محدوده یاد شده مثبت باشد، بارندگی در شرق کشور افزایش می­یابد. در ترکیب دوم تغییرات تاوایی نسبی تراز یاد شده در محدوده شرق اروپا با بارندگی سواحل جنوبی دریای خزر به میزان 0.65 همبستگی منفی دارد. بدین­معنی که هر چه تمایل مقادیر تاوایی نسبی روی شرق اروپا به سمت مقادیر منفی­تر باشد، بارندگی در حاشیه جنوب غربی دریای خزر بیش­تر می­شود. در ترکیب سوم نیز تغییرات تاوایی نسبی روی منطقه چرخندزایی ترکیه و قبرس نیز با بارندگی شمال غربی ایران به میزان 0.5 همبستگی مثبت داشته و تاوایی مثبت در آن محدوده منجر به افزایش بارندگی در شمال غربی کشور می­شود. این سه ترکیب خطی در مجموع 82.5 درصد از پراش مشترک بین تاوایی نسبی و بارندگی را توضیح می­دهند.

کلیدواژه‌ها


عنوان مقاله [English]

Identification of the 500 hPa relative vorticity Centers of action affecting Iran rainfall

نویسندگان [English]

  • Azita Amiri 1
  • Bohlol Alijani 2
  • Ebrahim Fattahi 3
1 IRIMO expert
2 Prof., Kharazmi University, Theran, Iran
3 Associate Prof. ASMERC
چکیده [English]

Introduction:
Investigating the components of general atmospheric circulation is important to discover the rules governing the country's rainfall. The relative vorticity as a key variable of synoptic motions is one of the best components in this regard. Relative vorticity is a measure of the intensity and direction of spin in a circular movement which is performed by a unit volume of air around the vertical axis perpendicular to the plane over which this rotation occurs. This research is looking for the relationship between spatiotemporal variations of relative vorticity and precipitation in Iran to improve forecasting skills.
In this study the connection between the 500 hPa relative vorticity field and precipitation over Iran is investigated using canonical correlation analysis (CCA). Using of CCA statistical method is usual in climatological studies but it has not yet entered into the Iran climatological studies.
Data and Methods:
Two main data sets were used in this study; the time series of 500 hPa monthly relative vorticity fields and monthly precipitation for 97 Iran stations during the rainy season (November to February). The study area extends from latitude of 10 to 70 degrees north and a longitude of 10 to 70 degrees east over a region affecting Iran's precipitation.
Relative vorticity monthly values (1981-2017) using the U and V component wind values obtained from NCEP-DOE reanalysis databases at grid points spaced by 2.5° at the pressure level of 500 hPa was calculated. NCEP-DOE Reanalysis II that is an improved version of the NCEP-NCAR Reanalysis I model that fixed errors and updated parameterizations of physical processes.
The monthly precipitation data (1981-2017) were received from 97 synoptic stations of Iran and were used after standardization. To achieve the purpose of this study, at first the activity centers of vorticity and precipitation were identified by applying S mode principle component analysis (PCA). Then canonical correlation analysis (CCA) was performed on factor scores of these centers. The 30 years base period (1981-2010) was selected to applying CCA method while the years 2010 to 2017 were used as evidence.
This multivariate statistical method was originally developed by Hotelling in 1936 from an interdependence model and first applied in climatology during the 1980s by Barnett and Preisendorfer and also by Nicholls in 1987.
Canonical correlation analysis is a multivariate statistical technique for analyzing internal relations between a set of multiple independent variables (predictors) and a set of multiple dependent variables (predictants).
This method is often used in atmospheric sciences to identify predictors within the datasets. Relationships between variables are highlighted through CCA.
Results and Discussions:
The application of PCA led to 6 factors for the precipitation over Iran and 18 factors for the 500 hPa relative vorticity, accounting for 72% and 80% of the total variance respectively. The first meaningful factor of Iran precipitation is located in northwest of Iran. Second factor is extended from east to south and the fifth factor is in the Caspian Sea southern coasts.
PCA factor scores time series of the each two sets were used for the subsequent CCA.
CCA yielded three physically reasonable relevant pairs of patterns that describe the simultaneous responses of the precipitation field to the relative vorticity changes accounting for 82.5% of the common variance of both fields.
The first CCA pair exhibits a correlation between the precipitation over east of Iran and the 500 hPa relative vorticity changes in the eastern Mediterranean and the Middle East. The second CCA pair reveals a negative correlation between the precipitation over the Caspian Sea southwest coasts and the relative vorticity activities, centered over Eastern Europe. The third CCA pair shows a correlation between the rain of northwest Iran and the relative vorticity activities over Turkey, Cyprus, and the Black sea.
Conclusion:
The influence of the relative vorticity centers of activity in different regions of the Middle East, eastern Mediterranean, and Europe that appear in the form of the positive or negative relative vorticity on the Iran precipitation anomalies was investigated.
In this case, three linear combinations were found by the canonical correlation analysis technique.
According to the first pattern,  negative vorticity centered over the eastern Mediterranean and the Middle East is associated with below normal precipitation over the east and southern regions of Iran. In fact, the negative vorticity region in the eastern Mediterranean and the Middle East indicates the location of the ridge and the east of Iran locates in front of this ridge that is the area of descending movements that result in weather stability in this part of Iran.
The second pattern reveals that however the relative vorticities will go up to the negative values in Eastern Europe; the rainfall will be higher on the southwest margin of the Caspian Sea. In the winter when Eastern Europe is located in ascending region of western winds (ridge), the Caspian Sea would be located in descending region of mid-level (trough) which will increase weather instability and increase precipitation in the southern coast.
The third pattern says that as far as the relative vorticity tends to positive values in the Cyprus and Turkish cyclogenesis areas, the rainfall will be higher in the northwest of Iran. That’s because the extension of western winds in this area in winter could bring Mediterranean humidity to the northwest and west of Iran with no mountainous barrier.
Therefore, these results can be used to increase rainfall forecasting skills in different parts of the country. The results of this study confirm the results of the study of Rezaei et al. (2012 and 2013).

کلیدواژه‌ها [English]

  • Relative vorticity
  • Canonical Correlation Analysis
  • Rainfal
  • Iran
  1.  

    1. Ahmed, N.H. and S.M. Deni. 2013. Homogeneity test on daily rainfall series for Malaysia. MATEMATIKA. 29(1c). pp. 141-150.
    2. Ahmed, M. El Kenawi, McCabe, M.F., Stenchikov, G.L. and J. Raj. 2014. Multi-decadal classification of synoptic weather types, observed trends and links to rainfall characteristics over Saudi Arabia. DOI: 10.3389/fenvs.2014.00037, Frontiers in environmental science, Original Research Article. vol. 2(37). pp. 1-15.
    3. Ahrens, C.D. 2011. Meteorology today: An introduction to weather, climate and environment. Translated by Babaee, M. 1391. M. R., Aeej press. Edition 8. ISBN: 978-964-970-310-7. 718 pages.
    4. Alijani, B. 2002. Variation of 500hPa flow patterns over Iran and surrounding areas and their relationship with climate of Iran. Theor.Appl.Climatol. vol. 71. pp. 41-44.
    5. Alijani, B. 2012. Synoptic climatology. samt press, ISBN: 978-964-459-609-4. 257 pages. (In Persian)
    6. Alijani, B. 2013. Climate of Iran. Payam Nour University, ISBN: 978-964-455-621-0. 221 pages. (In Persian)
    7. Al-Khalidi, J., Dima, M., Vaideanu, P. and S. Stefan. 2017. North Atlantic and Indian Ocean links with Iraq climate. DOI: 10.3390/atmos8120235, Atmosphere. Vol. 8(12). pp. 235-245.
    8. Amiri, A. 2017. The Relationship between Spatiotemporal Distribution of Relative Vorticity and Climate of Iran. PhD Thesis in Climatology, Khurazmi University, Advisor: Dr. Alijani, B. 160 pages. (In Persian)
    9. Asakereh, H., Ghaemi, H. and A. Beyranvand. 2015. on the seasonal variability trend of sub tropical jet stream in Iran climatic area in recent decades. J. Research of Natural Geograph. Vol. 47(1). pp. 57-72. (In Persian)
    10. Barnett, T. and R. Preisendorfer. 1987. Origins and levels of monthly and seasonal forecasts skill for the United States surface air temperatures determined by canonical correlation analysis. DOI: 10.1175/1520-0493(1987)115, Monthly Weather Review. Vol. 115. pp. 1825-1850.
    11. Barnston, A.G. and T.M. Smith. 1996. Specification and prediction of global surface temperature and precipitation from global SST using CCA. Int. J. Climatol. Vol. 9. pp. 2660-2697.
    12. Bartzokas, A., Lolis, C.J. and Metaxas, D.A., 2003. The 850 hPa relative vorticity centers of action for winter precipitation in the Greek area. DOI: 10.1002/joc.909, Int. J. Climatol. Vol. 23, pp. 813-828.
    13. Casado, M.J., Pastor, M.A. and F.J. Doblas-Reyes. 2009. Euro-Atlantic circulation types and modes of variability in winter. Theoretical and Applied Climatology. vol. 96. pp. 17-29.
    14. Campins, J., Genoves, A., Picornell, M. A., and A. Jansa. 2011. Climatology of Mediterranean cyclones using the ERA-40 dataset. DOI: 10.1002/joc.2183, Int. J. Climatol. Vol. 31. pp. 1596-1614.
    15. DuNkelon, A. and J. Jacobeit. 2003. Circulation dynamics of Mediterranean precipitation variability 1948-98. DOI: 10.1002/joc.973, Int. J. Climatol. Vol. 23. pp. 1843-1866.
    16. Fatemi, , Omidvar, K., Hatami, K. and M. Narangifard. 2015. Using Principle Component Analysis in identifying synoptic patterns of wet periods in central Iran. DOI: 10.4172/2157-7617.1000309, J. Earth Sci Clim Chang., Vol. 6(9). pp. 1-8.
    17. Fekadu, K. 2015. Ethiopian seasonal rainfall variability and prediction using Canonical Correlation Analysis (CCA). DOI: 10.11648/j.earth.20150403.14, Earth Sciences. Vol. 4(3). pp. 112-119.
    18. Flocas, H.A., Maheras, P., Karacostas, T.S., Patrikas, I. and C. Anagnistopoulou. 2001. A 40-year climatological study of relative vorticity distribution over the Mediterranean. DOI: 10.1002/joc.705, Int. J. Climatol. Vol. 21. pp. 1759-1778.
    19. Flocas, H.A., Simmonds, I., Kouroutzoglou, J., Keay, K., Hatzaki, M., Bricolas, V. and D. Asimakopoulos. 2010. on cyclonic tracks over the eastern Mediterranean. DOI: 10.1175/2010JCLI3426.1, Int. J. Climatol. Vol. 23(19). pp. 5243-5257.
    20. Holton, J.R. and Hakim, G.J. 2012. An introduction to dynamic meteorology. ISBN: 9780123848673, Elsevier, Academic press, Fifth edition, 552 pages.
    21. Hoskins, B. J. and K. I. Hodges. 2002. New perspectives on the Northern Hemisphere Winter Storm Tracks. DOI: 10.1175/1520-0469(2002)059, J. Atmos. Sci. Vol. 59 pp.1041-1061.
    22. Hotelling, H. 1936. Relations between two sets of variates. DOI: 10.2307/2333955, Biometrika. Vol. 28. pp. 321-377.
    23. 2013. Climate change 2013: The physical science basis. Contribution of working group 1 to the fifth assessment report of the Intergovernmental Panel on Climate Change [Stoker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press. Cambridge, United Kingdom and New York, NY, USA. 1535 pages.
    24. Jolliffe I.T. and J. Cadima. 2016. Principal Component Analysis: a review and recent developments. Doi: 10.1098/rsta.2015.0202, Philos Trans a Math Phys Eng Sci. vol. 374. pp. 1-16.
    25. Kalnay, E. and 21Co-authors. 1996. The NCEP-NCAR 40-year reanalysis project. DOI: 10.1175/1520-0477(1996)077, American Meteorological Society. Vol. 77(3). pp. 437-471.
    26. Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, J., Fiorino, H.M. and G.L. Potter. 2002. NCEP-DOE AMIP-II Reanalysis (R2). DOI: 10.1175/BAMS-83-11-1631, American Meteorological Society. Vol. 83(11). pp. 1631-43.
    27. Kaviani, M., Masoudian, S.M. and B. Najafpour. 2007. The relationship between circulation patterns of 500 hPa and precipitation over Mond basin. J. Humanities Researches, Vol. 3. pp. 1-12. (In Persian)
    28. Kistler, R. and 12Co-authors. 2001. The NCEP-NCAR 50-year reanalysis: Monthly means cd-rom and documentation. DOI: 10.1175/1520-0477(2001)082, American Meteorological Society. Vol. 82(2). pp. 247-268.
    29. Lefevre, R. J. and J. W. Gammon. 1995. An objective climatology of mobile troughs in the Northern Hemisphere. DOI: 10.1034/j.1600-0870.1995.00110.x, Tellus. Vol. 47(5). pp. 638-655.
    30. Lolis, C. J., Metaxas, D. A. and A. Bartzokas. 2008. on the intra-annual variability of atmospheric circulation in the Mediterranean region. DOI: 10.1002/joc.1634, Int. J. Climatol. Vol 28. pp. 1339-55.
    31. Marosz, M. 2009. Seasonal variability in the response of the airflow characteristics to the changes in the macro-scale westerly flow intensity over Europe, 1971-2000. DOI:10.1002/joc.1708, Int. J. Climatol. Vol. 29. pp. 481-500.
    32. Nicholls, N. 1987. The use of canonical correlation to study teleconnections. DOI: 10.1175/1520-0493(1987)115, Monthly Weather Review. Vol. 115(2). pp. 393-399.
    33. Omidvar, K., Fatemi, M., Narangifard, M. and K. Hatami. 2016. A study of the circulation patterns affecting drought and wet years in central Iran. DOI: 10.1155/2016/1843659, Advances in Meteorology. Vol. 2016. pp. 1-14.
    34. Perron, M. and P. Sura. 2013. Climatology of non Gaussian atmospheric statistics. DOI: 10.1175/JCLI-D-11-00504.1, American Meteorological Society. Vol. 26. pp. 1063-1083.
    35. Rahimzadeh, F. and M. Nassaji Zavareh. 2014. Effects of adjustment for non climatic discontinuities on determination of temperature trends and variability over Iran. DOI: 10.1002/joc.3823, Int. J. Climatol. vol. 34(6). pp. 2079-2096.
    36. Rahimzadeh, F., Asgari, A. and E. Fattahi. 2009. Variability of extreme temperature and precipitation in Iran during recent decades. DOI: 10.1002/joc.1739, Int. J. Climatol. Vol 29(3). pp. 329-343.
    37. Raziei, T., Mofidi, A., Santos, JA. And I. Bordi. 2012. Spatial patterns and regimes of daily precipitation in Iran in relation to large scale atmospheric circulation. DOI: 10.1002/joc.2347, Int. J. Climatol. Vol. 32. pp. 1226-1237.
    38. Raziei T, Bordi I, Santos J.A, A. Mofidi. 2013. Atmospheric circulation types and winter daily precipitation in Iran. Doi: 10.1002/joc.3596, Int. J. Climatol. Vol. 33(9). pp. 2232-2246.
    39. Raziei T. 2017. Identification of precipitation regimes of Iran using multivariate methods. Doi: 10.22059/JESPHYS.2017.60290, J. Earth and Space Physics. Vol. 43(3). pp. 673-695.
    40. Rousta, I., Soltani, M., Zhou, W. and H. N. C. Hoffman. 2016. Analysis of extreme precipitation events over central plateau of Iran. DOI: 10.4236/ajcc.2016.53024, American Journal of Climate Change. Vol. 5. pp. 297-313.
    41. Sinclair, M. R. 1994. Objective cyclone climatology of the southern hemisphere. DOI: 10.1175/1520-0493, Monthly Weather Review. Vol. 122(10). pp. 2239-2256.
    42. Vicente-Serrano, S.M. and 7 Co-authors. 2011. The 2010 extreme winter north hemisphere atmospheric variability in Iberian precipitation: anomalies, driving mechanisms and future projections. Doi: 10.3354/cr00977, Clim. Res. Vol. 46. pp. 51-65.
    43. Von Storch, H. and Zwiers, F.W., 2004. Statistical analysis in Climate research. ISBN: 0-511-03753-8, Cambridge University Press, first published 1999, 496 pages.
    44. Wilks, D.S. 2011. Statistical methods in the atmospheric sciences. ISBN: 978-0-12-385022-5, Elsevier Inc., Academic Press. Vol. 100. Third edition. 704 pages.
    45. Xoplacki, E., Gonzalez-Rouco, J.F., Luterbacher, J. and H. Wanner. 2003. Mediterranean summer air temperature variability and its connection to the large-scale atmospheric circulation and SSTs. DOI: 10.1007/s00382-003-0304-x, Climate Dynamics. Vol. 20(7). pp. 723-739.
    46. Xoplacki, E., Gonzalez-Rouco, J. F., Luterbacher, J. and H. Wanner. 2004. Wet season Mediterranean precipitation variability: influence of large scale dynamics and trends. DOI: 10.1007/s00382-004-0422-0, Climate Dynamics, Vol. 23. pp. 63-78.