پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شماره‌ها | 6,532 |
| تعداد مقالات | 70,504 |
| تعداد مشاهده مقاله | 124,124,278 |
| تعداد دریافت فایل اصل مقاله | 97,232,722 |
ارزیابی دقت خروجی مدل‌های منطقه‌ای آب و هوا در ایران | ||
| پژوهش های جغرافیای طبیعی | ||
| مقاله 11، دوره 50، شماره 1، فروردین 1397، صفحه 161-176 اصل مقاله (1.52 M) | ||
| نوع مقاله: مقاله کامل | ||
| شناسه دیجیتال (DOI): 10.22059/jphgr.2018.237966.1007088 | ||
| نویسندگان | ||
| اصغر کامیار1؛ حجت الله یزدان پناه2؛ سعید موحدی* 3 | ||
| 1دانشجوی دکتری آب‌وهواشناسی، دانشکدة علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان | ||
| 2دانشیار اقلیم شناسی، دانشکدة علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان | ||
| 3دانشیار اقلیم شناسی، دانشکدة علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان | ||
| چکیده | ||
| بررسی تغییرات منطقه‌ای آب و هوا به منظور سازگاری و ارائة خط مشیهای تعدیلی در سطح ملی یکی از موضوعات مهم در مطالعۀ تغییر اقلیم است. هدف از این پژوهش بررسی دقت خروجی مدل‌های منطقه‌ای آب و هوا در پروژة ریزمقیاس‌نمایی هماهنگ منطقه‌ای (CORDEX) در ایران است. بدین منظور، خروجیهای بارش و دمای کمینه و بیشینه برای سه RCM در دو محدودۀ CORDEX شامل شمال افریقا- خاورمیانه (MNA) با قدرت تفکیک 25 و 50 کیلومتر و جنوب آسیا (WAS) با قدرت تفکیک 50 کیلومتر از پایگاه دادة ESGF و دادههای ایستگاههای همدیدی به عنوان دادة مشاهداتی جهت ارزیابی خروجی مدلها از سازمان هواشناسی کشور طی دورۀ زمانی 1990ـ2005 دریافت شد. سپس، نزدیک‌ترین ایستگاه به یاختة متناظرش شناسایی شد و با روشهای میانگین خطا، همبستگی پیرسن، و RMSE مقایسه شد. نتایج این پژوهش نشان داد که به‌طورکلی مدل‌های موجود در پروژة CORDEX برای بارش همبستگی زیادی با دادههای مشاهداتی نداشتند؛ ولی مقدار خطا و RMSE در مدل RCA4-MNA0.22 کمتر از سایر مدلها بود. همچنین، در ارتباط با دمای بیشینه و کمینه به‌ترتیب مدل‌های HadRM3P و RegCM4.1 در محدودۀ جنوب آسیا برآورد نسبتاً درستی داشتند و در بیشتر نواحی کشور همبستگی بالا و خطایی کمتر از یک درجة سلسیوس را با دادههای مشاهداتی نشان دادند. | ||
| کلیدواژه‌ها | ||
| ایران؛ ریزمقیاس‌نمایی؛ مدل منطقه‌ای آب و هوا؛ CORDEX | ||
| عنوان مقاله [English] | ||
| Accuracy Evaluation of the Outputs of Regional Climate Models in Iran | ||
| نویسندگان [English] | ||
| Asghar Kamyar1؛ Hojjat Yazdanpanah2؛ Saeed Movahedi3 | ||
| 1PhD Student in Climatology, Department of Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Iran | ||
| 2Associate Professor of Climatology, Faculty of Geographical Sciences and Planning, University of Isfahan, Iran | ||
| 3Associate Professor of Climatology, Faculty of Geographical Sciences and Planning, University of Isfahan, Iran | ||
| چکیده [English] | ||
| Introduction All studies in the field of assessment of climate change impacts needs climate data with different spatial and temporal scales. The lack of temperature and precipitation data with high spatial resolution is a major limitation to analysis of future climate change. In addition, the output of the models has the error that needs to be corrected; otherwise, they will make a significant bias for assessing the effects of climate change. Therefore, identifying the best regional climate model for downscale the global climate models is essential to better understanding of climate conditions in the local and regional scale. In the last few years, use of various regional climate models for producing a multi-member set of the downscaled data in the CMIP5 project by World Climate Research Program (WCRP) in action with Coordinated Regional climate Downscaling Experiment (CORDEX) was established as an input to the researches about the impacts of climate change and adaptation ways. The main objective of this research is accuracy evaluation of different model outputs of the CORDEX project with different domain and resolution in Iran. Materials and Methods In the CORDEX project, there are two domains that covering Iran. These two domains are North Africa-Middle East (CORDEX-MNA) and South Asia (CORDEX-WAS). To do this research, daily output of precipitation, maximum and minimum temperatures in the period of 1990-2005 for three regional climate models with a special resolution of 0.22° and 0.44° are performed by three international meteorology institutes, available at ESGF web site (Table 1). Daily observation data recorded in 304 synoptic stations in Iran for the three variables were collected from Iran Meteorology Organization and transferred to a matrix with 3044×5844 dimensions. Then, several scripts were written in the MATLAB software to extract the model data in Iran and compare model output and observational data with two conditions. The first condition is in the output model resolution of 0.44° (spatiotemporal matrix with dimensions of 5844×740), the observation station should have a distance of less than 25 km, and the next condition is in the resolution of 0.22 ° (spatiotemporal matrix with dimensions of 5844×3218) should have a distance of less than 12 km. The difference between observation values and its corresponding estimated values were investigated with statistical method such as Mean Error (ME), Pearson Correlation Coefficient, Root Mean Square Error (RMSE) and Standard Deviation (SD). We also used Box-Whisker plots and Taylor Diagram to find the best regional climate model. Results and Discussion The precipitation accuracy of regional climate models output presented by different meteorological institutes (Table 1) was evaluated by observational data in two domains, CORDEX-MENA and CORDEX-WAS, in Iran (Fig. 4). The calculation of the outputs mean error of different models showed that none of the models have a suitable estimation of precipitation values in research domain. The HadRM3P model shows the lowest RMSE relative to observational data for the maximum temperature across Iran except the central parts. However, for the minimum temperature RegCM4.1 model shows the lowest difference with comparison with observation data in most parts of the research domain. For annual precipitation using the Box-Whisker plot, we can compare the correlation coefficients between the observed data and the corresponding cells in the northern and southern parts of Iran. According to the results, none of the models have an accurate estimate of precipitation in Iran (Fig. 8a). This plot for different models showed that the outputs of the HadRM3P and RegCM4.1 models have more than 0.8 correlation coefficien for maximum and minimum temperatures in most cells, respectively, (Fig. 8b and c). Conclusion The correlation of rainfall data shows that most models in the central and mountainous regions of Iran do not have high correlation coefficient with observational data. Spatial distribution of correlation between maximum temperature model outputs and observational data in Iran shows that the two HadRM3P and RCA4-WAS0.44 models have a strong correlation coefficient. The results also show that changes in the correlation coefficient in the HadRM3P model are low in both the northern and the southern parts of Iran. The RegCM4.1 model had the stronger correlation in the northern half in comparison with the southern parts of Iran. Also, the mean difference of estimated model output with observation data of this variable in the whole of Iran is less than 1°C and this model is the most appropriate model among the available models for minimum temperature in Iran. | ||
| کلیدواژه‌ها [English] | ||
| downscaling, CORDEX, Regional Climate Model (RCM), Iran | ||
| مراجع | ||
|
عزیزی، ق.؛ صفرراد، ط.؛ فرجی، ح. و محمدی، ح. (1395). ارزیابی و مقایسة دادههای بازکاوی‌شدة بارش جهت استفاده در ایران، پژوهشهای جغرافیای طبیعی، 48(1): 33ـ49. Ahmed, K.F.; Wang, G.; Silander, J.; Wilson, A.M.; Allen, J.M.; Horton, R. and Anyah, R. (2013). Statistical downscaling and bias correction of climate model outputs for climate change impact assessment in the U.S. northeast, Global and Planetary Change, 100: 320-332. Almazroui, M.; Islam, M.N.; Al-Khalaf, A.K. and Saeed, F. (2016). Best convective parameterization scheme within RegCM4 to downscale CMIP5 multi-model data for the CORDEX-MENA/Arab domain, Theoretical and Applied Climatology, 124(3): 807-823. doi:10.1007/s00704-015-1463-5 Almazroui, M. (2013). Simulation of present and future climate of Saudi Arabia using a regional climate model (PRECIS), Int J. Climatol, 33: 2247-2259. doi:10.1002/joc.3721. Azizi, Gh.; Safarrad, T.; Faraji, H.A. and Mohamadi, H. (2016). Evaluate and Comparison Reanalyzed Data for Using in Iran, Journal of Physical Geography Quarterly, 48(1): 33-49. (In Persian). Casanueva, A.; Kotlarski, S.; Herrera, S.; Fernández, J.; Gutiérrez, J.M.; Boberg, F. and Vautard, R. (2016). Daily precipitation statistics in a EURO-CORDEX RCM ensemble: added value of raw and bias-corrected high-resolution simulations, Climate Dynamics, 47(3): 719-737. doi:10.1007/s00382-015-2865-x. Dosio, A. (2016). Projections of climate change indices of temperature and precipitation from an ensemble of bias-adjusted high-resolution EURO-CORDEX regional climate models, Journal of Geophysical Research: Atmospheres, 121(10): 5488-5511.doi:10.1002/2015JD024411. Dosio, A.; Panitz, H.-J.; Schubert-Frisius, M. and Lüthi, D. (2015). Dynamical downscaling of CMIP5 global circulation models over CORDEX-Africa with COSMO-CLM: evaluation over the present climate and analysis of the added value, Climate Dynamics, 44(9): 2637-2661. doi:10.1007/s00382-014-2262-x. Emmanouil, F.; Philippe, D.; Marco, B.; Jean-Christophe, C.; Guy, D.; Efrat, M.; … and Roberta, T. (2012). Assessment of gridded observations used for climate model validation in the Mediterranean region:theHyMeX and MED-CORDEX framework, Environmental Research Letters, 7(2): 024017. Giorgi, F. and Mearns, L.O. (1991). Approaches to the simulation of regional climate change: a review, Reviews of Geophysics, 29(2): 191-216, http://dx.doi.org/10.1029/ 90RG02636. Giorgi F. and Hewitson, B. (2001). Regional climate information-evaluation and projections. In: Houghton J.T., Ding Y., Griggs D.J., Noguer M., van der Linden P.J., Xioaosu D. (eds) Climate change 2001: the scientific basis, contribution of working group I to the third assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge. Giorgi, F.; Jones, C. and Asrar, G. (2009). Addressing climate information needs at the regional level: the CORDEX framework, World Meteorol Organ (WMO) Bull, 58: 175-183. Isotta, F.A.; Frei, C.; Weilguni, V.; Per_cec Tadi,_C.M.; Lass_egues, P.; Rudolf, B.; Pavan, V.; Cacciamani, C.; Antolini, G.; Ratto, S.M.; Munari, M.; Micheletti, S.; Bonati, V.; Lussana, C.; Ronchi, C.; Panettieri, E.; Marigo, G. and Verta_cnik, G. (2013). The climate of daily precipitation in the Alps: development and analysis of a high-resolution grid dataset from pan-Alpine rain-gauge data, International Journal of Climatology, DOI 10.1002/joc.3794. Islam, M.N. (2009). Rainfall and temperature scenario for Bangladesh, Open Atmos Sci J., 3: 93-103. Ji, Zhenming and Kang, Sh. (2015). Evaluation of extreme climate events using a regional climate model for China, International Journal of Climatology, 35: 888-902. Jones, R.G.; Noguer, M. and Hassell, D.C. (2004). Generating high-resolution climate change scenarios using PRECIS, Met Office Hadley Centre, Exeter, UK. Haylock, M.R.; Hofstra, N.; Klein Tank, A.M.G.; Klok, E.J.; Jones, P.D. and New, M. (2008). A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006, J. Geophys. Res., 113, D20119, doi:10.1029/2008JD010201. Kidson, J.W. and Thompson, C.S. (1998). A comparison of statistical and model-based downscaling techniques for estimating local climate variations, Journal of Climate, 11: 735-753. Murphy, J. (1999). An evaluation of statistical and dynamical techniques for downscaling local climate, Journal of Climate, 12(8): 2256-2284. Pal, J.S.; Giorgi, F.; Bi, X. and Elguindi, N. (2007). The ICTP RegCM3 and RegCNET: regional climate modeling for the developing world, Bull Am Meteorol Soc, 88(9): 1395-1409. Raju, P.V.S.; Bhatla, R.; Almazroui, M. and Assiri, M. (2015). Performance of convection schemes on the simulation of summer monsoon features over the South Asia CORDEX domain using RegCM-4.3, International Journal of Climatology, 35(15): 4695-4706. doi:10.1002/joc.4317. Shongwe, M.E.; Lennard, C.; Liebmann, B.; Kalognomou, E.-A.; Ntsangwane, L. and Pinto, I. (2015). An evaluation of CORDEX regional climate models in simulating precipitation over Southern Africa, Atmospheric Science Letters, 16(3): 199-207. doi:10.1002/asl2.538. Taylor, K.E. (2001). Summarizing multiple aspects of model performance in a single diagram, Journal of Geophysical Research: Atmospheres, 106(D7), 7183-7192. doi: 10.1029/2000JD900719 XueJie, G.; Shi, Ying; ZhangDong, F.; Giorgi, F. (2012). Climate change in China in the 21st century as simulated by a high resolution regional climate model, Chin Sci Bull, 57(10). Zhou, W.; Tang J.; Wang, X.; Wang, S.; Niu, X.; Wang, Y. (2016). Evaluation of regional climate simulations over the CORDEX-EA-II domain using the COSMO-CLM model, Asia-Pacific Journal of Atmospheric Sciences, Volume 52, Number 2, Page 107.
| ||
|
آمار تعداد مشاهده مقاله: 1,034 تعداد دریافت فایل اصل مقاله: 721 |
||