Projections of Variation in precipitation extream values in Sabzevar by LARS-WG downscaling model during 2011-2030 to 2046-2065
Subject Areas : ClimatologySeyedMohammad askarizadeh 1 , GolamAli mozaffari 2 , Ahmad mazidy 3
1 - Ph.D Climatology, Meteorology Directorate General of Khorasan Razavi
2 - Associate Professor of Climate change yazd university , Yazd, Iran
3 - Associate Professor of Climate change yazd university , Yazd, Iran
Keywords: Sabzevar, extreme events, Downscaling, Atmospheric-Ocean General Circulation Model,
Abstract :
facing mankind ( Ipcc,2008 ). Infact one of the important aspects of climate change is understanding its behavior To have an outlook on future projections of climate extremes part Changes in extreme climate events has significant effects which caused a it to become as the most important challenges icularly precipitation, the outputs derived from three coupled general circulation models (HadCM3, CNCM3, NCCCSM) contributing to the Fourth Assessment Report of the IPCCAR4, under A1B emission scenarios have been downscaled by LARS-WG during three period 2011-2030, 2046-2065 for Sabzevar, station. The extremes are described by seven indices based on precipitation including (PRCPTOT,R10mm, R20mm,R95p,R99p,RX1day,RX5day,SDII) Results show that averages of Rx5day and SDII during The period of 2011-2030 will be probably increase under A2 sceranario . Inddition , alarge fraction of total annual precipitation is progected to occure in The form of heavy and showery events in 95th and 99th percentile . Regarding to The resultso incroases of 95th and 99th indices means That The frequency of flash floode and its intencity will be increased during 2011-2030 . Howerer , the intencity of precipitation and SDII will be probably to decreabse during2046-2064.
1. اشرف ، ب. موسوی بایگی ، م. کمالی ، غ و داوری ، ک.(1390) . پیش بینی نیاز آبی چغندر قند در دوره 2030 -2011 با استفاده از داده های اقلیمی شبیه سازی شده توسط مدل زیر مقیاس کننده LARS-WG (مطالعه موردی استان خراسان رضوی ) مجله آب و خاک . جلد 25 . شماره 5 . صص 1196-1184 مشهد .
2. بابائیـان،ا. ونجفی نیک،ز.(1384) "ارزیــابی تغییر اقلیم استـان خراسان رضوی در دوره 2039 – 2010 با استفاده از ریزمقیاس نمایی خروجی مدل GCM"، گزارش پروژه پژوهشکده اقلیم شناسی و سازمان هواشناسی کشور.
3.بابائیـان،ا و کوهی، م. ( 1391) ارزیابی شاخص های اقلیم کشاورزی تحت سناریوهای تغییر اقلیم در ایستگاههای منتخب خراسان رضوی ، نشریه آب و خاک ( علوم و صنایع کشاورزی) ج 26، ش 4، مهر- ابان؛ 967-953.
4.براتی ، غ وجهادی طرقی ، م.( 1378) " تعیین روند تغییرات دما و بارش شهر مشهد طی دوره آماری 1994-1951" فصلنامه تحقیقات جغرافیا شماره 55-54.
5.خزانه داری، ل.کوهی، م . زابل عباسی، ف. قندهاری، ش و ملبوسی، ش.( 1389) بررسی روند خشکسالی در ایران طی 30 سال آینده 2039-2010 ، چهارمین کنفرانس منطقها ی تغییر اقلیم
6.رحیم زاده، ف . عسکری، ا. فتاحی، ا. محمدیان، ن.و تقی پور، ا .(1388) "روند نمایه های فرین اقلیمی دما در ایران طی دوره 2003-1951"، فصلنامه تحقیقات جغرافیایی، شماره 93، صص 15717-15742.
7.عسکری،ا.رحیم زاده، ف. محمدیان، ن.و فتاحی، ا .(1386) "تحلیل روند نمایه های بارش های فرین در ایران"، تحقیقات منابع آب ایران، سال سوم، شماره 3، 56-42.
8..عساکره، ح. (1389) "تحلیل تغییرات بارش های فرین شهرزنجان"، پژوهش های اقلیم شناسی، سال اول، شماره اول و دوم، صص 100-89.
9. کردجزی، م. باقری، س. بابائیان، ا و عبدالرجبار، م. ( 1390) تحلیل خشکسالی هواشناسی استان گلستان در دوره 2030-2010 میلادی با استفاده از سناریوهای مختلف مدل گردش عمومی جو HADCM3 ، چهارمین کنفرانس مدیریت منابع آب.
10.گل محمدی، م و مساح بوانی، ع. (1390) "بررسی تغییرات شدت و دوره بازگشت خشکسالی حوضه قره سو در دوره های آتی تحت تاثیر تغییر اقلیم". نشریه آب و خاک (علوم و صنایع کشاورزی)، 25 (2): 315 تا 326.
11.مساح بوانی، ع و سادات آشفته، پ. (1386) "بررسی اهمیت موضوع تغییر اقلیم در جهان و تاثیر آن بر سیستمهای مختلف". کارگاه فنی اثرات تغییر اقلیم بر منابع آب، 24 بهمن ماه 1386. تهران.
span>
'Business as usual' climate change scenario. Climate Change Journal62, 217-232
27- Rusticucci, M., and Renom, M. 2008. Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay. Int. J. Clim. 28: 1083-1095.
28- Roy K., Rahman M., and KumanU. 2009. Future climate change and moisture stress: Impact on crop agriculture in south-western Bangladesh. Climate Change and Development Perspective. 1(1):1-8.
29-Todisco F and Vergni L, 2008. Climatic changes in central Italy and their potential effects on corn water consumption. Agric For Meteorol 148: 1–11.
_||_12. Bonsal, B. R., X. Zhang, L. A. Vincent, and W. D. Hogg, (2001), Characteristics of daily and extremetemperature over Canada,” Journal of Climate, 14, pp. 1959-1976.
13. DeaGaetano, A.T., (1996), “Recent trends in Maximum and Minimum temperature threshold exceedencesin Northern United States,” Journal of Climate, 9, pp. 1646-1657.
14. Intergovernmental Panel on Climate Change (2010), Meeting Report, IPCC Expert Meeting on Assessing and Combining Multi Model Climate Projections, National Center for Atmospheric Research, Boulder, Colorado. USA.
15. Intergovernmental Panel on Climate Change IPCC Technical Paper VI - June 2008. Bates, B.C., Z.W. Kundzewicz, S. Wu and J.P. Palutikof, Eds. IPCC Secretariat, Geneva, 210 pp. Available from IPCC ...
16.Jiang, Z,·Song, J, Li,·L, Chen, W, Wang, Z., Wang, J (2012),“Extreme Climate Events In China: IPCC-AR4 Model Evaluation And Projection,”Climatic Change, 11(1-2), Pp.385-401
17. Plummer, N. Salinger MJ, Nicholls N.Suppiah R. Hennessy Kj Leighton RM, Trewin BC, page CM,Lough JM, (1999), “Changes in climate extremes over the Australian region and New Zeland during thetwentieth century,” Climate Change 42:183-202.
18.Rodrigues Da Silva, V. P. 2004. On Climate Variability In Northeast Of Brazil, J. Arid Envir, 58: 575-596.
19.Semenov, M )2008),“Simulation Of Extreme Weather Events By A Stochastic Weather Generator,”Climate Research, 35, 203–212.
20.Semenov, M. A., Stratonovitch, P (2010), “Use of Multi-model Ensembles from Global Climate Models for Assessment of Climate Change Impacts,” CLIMATE RESEARCH, 4, pp. 1–14.
21. Semenov , M.A.,and Barrow , E.M.,1997 . Use of a stochastic weather generator in the development of climate change scenarios . Climatic Change 35,397-414.
22. Sillmann, J (2005), “Extreme Events in Climate Model Data,” IPCC Workshop, International Max Plank Research School on Earth System Modeling.
23.Turkesh,M. Sumer,M.U And Demir,S.(2002);"Re- Evaluation Of Trends And Changes In Mein, Maximum And Minimum Temperatures Of Turkey For The Period 1929-1999", International Journal Of Climatology,22
24.Wehner, M. F (2011), “Extremes from Climate Models Overview of AR4 and USGCRP reports Plans for AR5, Summer Colloquia: Statistical Assessment of Extreme Weather Phenomena under Climate Change (RAL/MMM/IMAGe), Advanced Study Program,” National Center for Atmospheric Research (NCAR).
25.World Meteorological Organization (2011), Weather extremes in a changing climate: hindsight on foresinght,” ISBN:978-92-63-11075-6.
26.Wang, X. L., Feng, Y. 2010. RHtestsV3 User Manual, Climate Research Division, Atmospheric Science and Technology Directorate, Science and Technology Branch, Environment Canada, Toronto, Ontario, Canada, Published onlin at http://cccma.seos.uvic.ca/ ETCCDMI/ software.shtml, January 2010,Visited in June 2010.
27. Zhai Pm. Sun A, Ren F Liu X, gao B. Zhang Q., (1999), “Changes of climate extremes in China,” ClimateChange 42: 203-218e
28.Zongxing, L, He, Y, Wang, P, Theakstone, W.H, An, W, Wang, X., Lu, A, Zhang, W, Cao, W (2011), “Changes Of Daily Climate Extremes In Southwestern China During1961–2008,”Global And Planetary Change, 80-81, Pp. 255–272.
29.Zhang, W., Cao, W (2011), “Changes of daily climate extremes in southwestern China during1961–2008,”Global and Planetary Change, 80-81, pp. 255–272.
t:normal;direction:ltr;unicode-bidi:embed'>27- Rusticucci, M., and Renom, M. 2008. Variability and trends in indices of quality-controlled daily temperature extremes inUruguay. Int. J. Clim. 28: 1083-1095.
28- Roy K., Rahman M., and KumanU. 2009. Future climate change and moisture stress: Impact on crop agriculture in south-western Bangladesh. Climate Change and Development Perspective. 1(1):1-8.
29-Todisco F and Vergni L, 2008. Climatic changes in central Italy and their potential effects on corn water consumption. Agric For Meteorol 148: 1–11.