بررسی روند تغییرات سرعت باد در ایران مرکزی با استفاده از داده های بازتحلیل شده ECMWF

نوع مقاله : مقاله کامل

نویسندگان

1 دانشجوی دکتری آب‏ وهواشناسی سینوپتیک، دانشگاه شهید بهشتی، دانشکدة علوم زمین، تهران، ایران

2 دانشیار آب‏ وهواشناسی دانشگاه شهید بهشتی، دانشکدة علوم زمین، تهران، ایران

چکیده

باد یکی از پارامترهای مهم اقلیم است و به‏عنوان یک شاخص مناسب می‏تواند برای تغییرات اقلیمی و الگوهای مرتبط با جریان هوا به‏کار برده شود. هدف از این تحقیق بررسی روند تغییرات بلندمدت سرعت باد در ایران مرکزی است. به این منظور، از داده‏های سرعت باد پایگاه بازتحلیل‏شدة ECMWF نسخة ERA-Interim با تفکیک مکانی 75/0×75/0 درجة قوسی و داده‏های هفت ایستگاه سینوپتیک طی دورة آماری ۱۹۸۰-2017 استفاده شد. برای درستی‏سنجی داده‏های پایگاه ECMWF از روش‏های R2، MBE، و RMSE و برای محاسبة روند از آزمون ناپارامتریک من- کندال (M-K) استفاده شد. نتایج نشان داد پایگاه ECMWF از دقت مناسبی برای برآورد سرعت باد برخوردار است؛ به‏طوری‏که مقدار R2در ایستگاه‏های مورد مطالعه بین 72/0 تا 95/0 متغیر است. متوسط سرعت باد در ایران مرکزی m/s19/3 محاسبه شد. کمینة سرعت باد در ماه ژانویه با 01/2 و بیشینة سرعت باد با m/s 95/3 در ماه ژلای محاسبه شد. به‏ترتیب بیشترین شدت روند افزایشی و کاهشی سرعت روند سرعت باد در ماه‏های مارس (نمرة Z، 91/4) و دسامبر (نمرة Z، 73/2-) محاسبه شد که در سطح آماری 01/0 معنی‏دار است. همچنین، بیشینة پهنه‏های روند افزایشی و کاهشی سرعت باد به‏ترتیب در ماه‏های فوریه و ژانویه به‏دست آمده است.

کلیدواژه‌ها


عنوان مقاله [English]

Investigation of wind speed trend changes in central Iran using ECMWF Reanalysis data

نویسندگان [English]

  • asghar molaei 1
  • Hassan Lashkari 2
1 PhD student in Meteorology, Shahid Beheshti University, Faculty of Earth Sciences, Tehran, Iran
2 Shahid Beheshti University (SBU)
چکیده [English]

Investigation of wind speed trend changes in central Iran using ECMWF Reanalysis data

Extended Abstract

Introduction
Among climate variables, wind has a skewing role due to its high spatio-temporal variability and its role in other parameters such as air temperature. It is important to study wind changes in different ways so as wind speed decreases its energy and consequently increases urban pollution. Reducing the wind speed also reduces heat transfer, viscosity between the earth's surface and the atmosphere, and ultimately increases the temperature. Decreasing wind speeds at night, especially in winter nights, cause the Earth to radiate inversion. Increasing wind speeds will also result in high winds, tornadoes and damage to affected areas. Also, wind speed is one of the important components in combinatorial equations to estimate evapotranspiration and any trends in wind speed will also affect the water requirement of plants.
As discussed, wind is a very important climatic parameter, but its study in particular is changing its course with limitations such as inaccessibility of homogeneous time series and long term data with inadequate stations. Station data, on the other hand, can also be affected by discontinuities associated with changes in measuring equipment, station location, or different measurement methods. To overcome these limitations, the re-analyzed global meteorological dataset, available for a long period, is useful for meteorological studies. In recent years, these databases have also been used for various wind energy applications.
The purpose of this study was to evaluate wind speed changes and trends in central Iran and since most of the area is arid and insufficient stations, ECMWF database data were used. The results of this study can be useful for studies on climate change, agriculture and renewable energies.

Research Methodology
The study area is Central Iran. Central Iran is said to be bounded on the north by the Alborz Mountains, on the west and south by the Zagros Mountains, and on the east by the dispersed Khorasan Mountains. Much of central Iran has warm and dry climates that are milder and humid in the highlands. In this study, four provinces of central Iran were selected and evaluated for wind changes.
Two groups of data were used in this study. 1- Wind speed data from Synoptic stations and 2- Wind speed data from ECMWF ERA-Interim version with spatial resolution of 0.75 × 0.75 °. Kolmogorov-Smirnov (K – S) test confirmed the normality of the data and the missing data were reconstructed using linear interpolation method. Synoptic station data were also used to validate the ERA-Interim ECMWF database data. Coefficient of determination (R2), Mean bias error (MBE) and root-mean-square error (RMSE) of open data analysis of ECMWF database ERA-Interim were used for wind speed trend in central Iran with nonparametric Mann-Kendall test. Was evaluated.

Results and discussion
Minimum wind clock speeds are only less than 2 meters in November (1.98) and December (1.96). In other months this fluctuates between 2.01 and 2.59 meters. The maximum wind speeds were also between 3.43 and 5.90 meters, respectively, from November to July, respectively. During the warmer months of June (Jun, July and August) the maximum wind speed is more than 5 meters. The average wind speed is also presented in this table, based on the results of the long-term minimum wind speed in central Iran with a mean of 2.83 meters in January and its maximum with a value of 3.95 meters in July. On this basis, it can be said that during the cold period of the year in central Iran, the wind speed is slower, as the hot months of the year ahead, the wind speed will increase. The average annual wind speed was 3.19 meters. Among the seasons and months studied, winter showed the highest intensity of the trend of increasing wind speed (Z-score of 4.916 Mann-Kendall test), which is significant at 99% level. The focus of the maximum wind speed increase trend is in Semnan province, and as we move from January to March, the intensity of the trend increases. The highest percentage of incremental trend zones is in February, with 92.20% of central Iran showing an increasing trend of wind speed this month. June with 80.52% of the upward trend zones after March accounted for most of the areas with upward wind speeds in the spring. In contrast to the upward trend zones that peaked in January but the maximum upward trend intensities in April reached the Mann-Kendall Z test score of 4.031, which was statistically significant at 99%.

Conclusion
The results showed that the ECMWF database is well suited for wind clock evaluation. The Shahroud, Yazd and Kerman stations showed maximum coefficient of determination (R2) and minimum error. Yazd and Kerman also showed less deviation from synoptic stations. Minimum wind speeds in November and December and maximum wind speeds were calculated in July and June. The mean wind speed was calculated based on the ECMWF results of 19.1 m / s. The average wind speed in central Iran is directly related to the air temperature and season. Generally, during the cold season of the year the wind speed from south to north and during the warm season from north to south of central Iran is increased due to the location of arid regions such as Dasht-e Kavir in the north and Dasht-e Lut in the south of the study area. The trend of the wind clock in central Iran has shown that the maximum intensity of the trend of increasing wind speed is in the winter of March (Mann-Kendall Z test score of 4.916) which is significant at 99% level. Also, the maximum decreasing trend with the Z-score of Man-Kendall test is -2.73 in December. The upward trend of wind speeds in more than 50 percent of central Iran in 10 months of the year, while only in October and February, is the decline observed in more than 50 percent of the study area. Since the most important factor in reducing or increasing wind speed is pressure gradient changes, wind speed variations can be a sign of climate change.

Keywords: Wind speed, ECMWF base, Mann-Kendall nonparametric test, Central Iran.

کلیدواژه‌ها [English]

  • wind speed
  • ECMWF base
  • Mann-Kendall nonparametric test
  • Central Iran
آب‌خرابات، ش.؛ کریمی، م.؛ فتح‏نیا، ا. و شام بیاتی، م.ح. (1396). بررسی نقش باد 120 روزۀ سیستان در وزش دمایی شرق و جنوب ‏شرق ایران، پژوهش‏های جغرافیای طبیعی، 49(۳):477-489.
حمیدیان‏پور، م.؛ مفیدی، ع. و سلیقه، م. (1395). تحلیل ماهیت و ساختار باد سیستان، مجلة ژئوفیزیک ایران، 10(۲): 83-109.
رحیم‏زاده، ف.؛ پدرام، م.؛ صداقت‏کردار، ع. و کمالی، غ. (1388). برآورد انرژی باد در ایستگاه‏های همدیدی استان اصفهان، مجلة جغرافیا و برنامه ریزی محیطی، 35(3): 155-172.
رضایی بنفشه، م.؛ خدیجه، ج. و زینالی، ب. (1390). بررسی روند تغییرات سرعت باد در شمال غرب ایران، جغرافیای طبیعی، 4(۱۳):27-36.
رضیئی، ط. و ستوده، ف. (1396). بررسی دقت مرکز اروپایی پیش‏بینی‏های میان‏مدت جوی (ECMWF) در پیش‏بینی بارش مناطق گوناگون اقلیمی ایران، فیزیک زمین و فضا، 43(۱): 133-147.
علیزاده چوبری، ا. و نجفی، م. س. (1396). روند تغییرات دمای هوا و بارش در مناطق مختلف ایران، فیزیک زمین و فضا، 43(3): 569-584.
قاسمی، ا. و سیدی، ف. (1394). شبیه‏سازی تغییرات و پیش‏بینی سرعت باد در ایران با استفاده از داده‏های آماری پنجاه‏ساله (۱۹۶۱-2010)، فصل‏نامة علمی- پژوهشی اطلاعات جغرافیایی «سپهر»، 24(۹۴): 95-105.
قهرمان، ن. و قره‏خانی، ا. (1389). بررسی روند تغییرات زمانی سرعت باد در گسترة اقلیمی ایران، مجلة آبیاری و زهکشی، ایران، 1(4): 31-43.
مفیدی، ع.؛ حمیدیان‏پور، م.؛ سلیقه، م. و علیجانی، ب. (1392). تعیین زمان آغاز، خاتمه، و طول مدت وزش باد سیستان با بهره‏گیری از روش‏های تخمین نقطة تغییر، جغرافیا و مخاطرات محیطی، 2(8): 65-86.
میرعباسی نجف‏آبادی، ر. و دین‏پژوه، ی. (1394). بررسی روند تغییرات سرعت باد در ایستگاه‏های منتخب ایران، نشریة جغرافیا و برنامه‏ریزی، 19(52): 277-301.
Abkharabat, S.; Karimi, M.; Fathnia, A. and Shambaiati, M. (2017). The Role of Sistan 120 Days Wind in Thermal Advection of East and Southeast Iran. Physical Geography Research Quarterly, 49(3): 477-489. (In Persian).
Alizadeh-Choobari, O. and Najafi, M. (2017). Trends and changes in air temperature and precipitation over different regions of Iran. Journal of the Earth and Space Physics, 43(3): 569-584. (In Persian).
Buishand, T. A. (1982). Some methods for testing the homogeneity of rainfall records, Journal of hydrology, 58(1-2): 11-27.
Cannon, D. J.; Brayshaw, D. J.; Methven, J.; Coker, P. J. and Lenaghan, D. (2015). Using reanalysis data to quantify extreme wind power generation statistics: A 33 year case study in Great Britain. Renewable Energy, 75: 767-778.
Dee, D. P.; Uppala, S. M.; Simmons, A. J.; Berrisford, P.; Poli, P.; Kobayashi, S. ... and Bechtold, P. (2011). The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the royal meteorological society, 137(656): 553-597.
Fant, C.; Gunturu, B. and Schlosser, A. (2016). Characterizing wind power resource reliability in southern Africa. Applied energy, 161: 565-573.
Hamidian Pour, M.; Mofidi, A. and Salighe, M. (2016). Analysis of the nature and structure of Sistan wind. Iranian Journal of Geophysics, 10(2): 83-109. (In Persian).
Hande, L. B.; Siems, S. T. and Manton, M. J. (2012). Observed trends in wind speed over the Southern Ocean. Geophysical Research Letters, 39(11).
Hero, n. And Qarakhani, A. (2010). Investigating the trend of temporal changes in wind speed in the climatic range of Iran, Journal of Irrigation and Drainage, Iran, 1 (4): 31-43. (In Persian).
Kendall, M. (1975). Multivariate analysis, Charles Griffin.
Mann, H. B. (1945) .Nonparametric tests against trend. Econometrical: Journal of the Econometric Society, 245-259.
Marcos, R.; González-Reviriego, N.; Torralba, V.; Soret, A. and Doblas-Reyes, F. J. (2019). Characterization of the near surface wind speed distribution at global scale: ERA-Interim reanalysis and ECMWF seasonal forecasting system 4. Climate Dynamics, 52(5-6): 3307-3319.
Meurers, B. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656): 553-597.
Mir Abbasi Najafabadi, R. and theologian, Y. (2015). Investigating the trend of wind speed changes in selected stations of Iran, Journal of Geography and Planning, 19(52): 277-301. (In Persian).
Polinder, H.; Ferreira, J. A.; Jensen, B. B.; Abrahamsen, A. B.; Atallah, K. and McMahon, R. A. (2013). Trends in wind turbine generator systems. IEEE Journal of emerging and selected topics in power electronics, 1(3): 174-185.
Pryor, S. C.; Barthelmie, R. J.; Young, D. T.; Takle, E. S.; Arritt, R. W.; Flory, D. ...and Roads, J. (2009). Wind speed trends over the contiguous United States. Journal of Geophysical Research: Atmospheres, 114(D14).
Qasemi, A. and Sidi, F. (2019). Simulation of changes and wind speed forecasting in Iran using fifty-year statistical data (1961-2010), Sepehr Geographical Information Quarterly, 24(94): 95-105. (In Persian).
Rahimzadeh, F.; Pedram, M.; Sedaghatkar, P. and Kamali, Gh. (2009). Estimation of wind energy in synoptic stations of Isfahan province, Journal of Geography and Environmental Planning, 35 (3): 155-172. (In Persian).
Raziei, T. and Sotoudeh, F. (2017). Investigation of the accuracy of the European Center for Medium Range Weather Forecast (ECMWF) in forecasting observed precipitation in different climates of Iran. Journal of the Earth and Space Physics, 43(1): 133-147. (In Persian).
Rezaei Banafsheh, M.; Khadijeh, J. and Zeinali, B. (2011). Investigation of the trend of wind speed changes in northwestern Iran, Natural Geography, 4(13): 27-36. (In Persian).
Rose, S. and Apt, J. (2015). What can reanalysis data tell us about wind power?.Renewable Energy, 83: 963-969.
Saeidabadi, R.; Najafi, M. S.; Roshan, G.; Fitchett, J. M. and Abkharabat, S. (2016). Modelling spatial, altitudinal and temporal variability of annual precipitation in mountainous regions: The case of the Middle Zagros, Iran. Asia-Pacific Journal of Atmospheric Sciences, 52(5): 437-449.
Solomon, S.; Qin, D.; Manning, M.; Averyt, K.; Marquis, M. and Tignor, M. M. (Eds.). (2007). Climate change 2007-the physical science basis: Working group I contribution to the fourth assessment report of the IPCC (Vol. 4). Cambridge university press.
Torralba, V.; Doblas-Reyes, F. J. and Gonzalez-Reviriego, N. (2017). Uncertainty in recent near-surface wind speed trends: a global reanalysis intercomparison. Environmental Research Letters, 12(11): 114019.
Useful, A.; Hamidianpour, M.; Saligheh, M. and Alijani, B. (2013). Determining the time of beginning, end, and duration of Sistan wind using the methods of estimating the point of change, Geography and environmental hazards, 2(8): 65-86. (In Persian).
Vautard, R.; Cattiaux, J.; Yiou, P.; Thépaut, J. N. and Ciais, P. (2010). Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nature geoscience, 3(11): 756.
Vitart, F. (2004). Monthly forecasting at ECMWF. Monthly Weather Review, 132(12): 2761-2779.
Williams, P. D.; Alexander, M. J.; Barnes, E. A.; Butler, A. H.; Davies, H. C.; Garfinkel, C. I. ... and Maue, R. N. (2017). A census of atmospheric variability from seconds to decades. Geophysical Research Letters, 44(21): 11-201.