جابه جاییِ مناطقِ اقلیمی کوپن-گایگردر فلاتِ بلوچستانِ پاکستان و چالش هایِ بالقوه آن بر ایران
محورهای موضوعی : اقلیم شناسیمحمدیوسف احمدپور 1 , تقی طاوسی 2 , حمید نظری پور 3
1 - دانشجوی کارشناسی ارشد گروه جغرافیای طبیعی، دانشگاه سیستان و بلوچستان، زاهدان، ایران
2 - استاد گروه جغرافیای طبیعی، دانشگاه سیستان و بلوچستان، زاهدان، ایران.
3 - استادیار گروه جغرافیای طبیعی، دانشگاه سیستان و بلوچستان، زاهدان، ایران.
کلید واژه: امنیت, تغییر اقلیم, دامنه تغییرات, مهاجران اقلیمی, سیستم طبقه بندی اقلیم,
چکیده مقاله :
سیستم های طبقه بندی اقلیم، ابزارهای مهم برای درک مشخصه های اقلیم یک منطقه می باشند. هدف اصلی این طبقه بندی ها، تعیین انواع مُدهای اقلیم و یافتن شباهت ها و تمایز وتغییرپذیری در الگوهای اقلیم می باشد.مناطق اقلیمی در معرض تهدیدات ناشی از گرمایش جهانی و تغییرات اقلیم قرار دارند. این بررسی، با هدف ارزیابی جابه جایی احتمالی مرزهای اقلیم در فلات بلوچستان پاکستان و اثرات بالقوه آن بر ایران بر پایه روش بهبود یافته کوپن-گایگر انجام گرفته است.داده های مقیاس ماهانه بارش و دما در دوره 2017-1900 از پایگاه داده دانشگاه دلاور اساس این پژوهش را شکل می دهند. نتایج طبقه بندی، بیانگر حاکمیت اقلیم های بیابانی گرم و سرددر منطقه مورد مطالعه می باشد.گستره اقلیم بیابانی گرم، مناطق جنوبی و غربی می باشد. در حالی که، اقلیم بیابانی سرد، در مناطق شمالی و غربی نمود دارد. در دهه های اخیر، دامنه اقلیم بیابانی سرد به طور محسوس کاهش داشته و از حدود 65-55 به حدود 55-50 درصد رسیده است. در مقابل، دامنه اقلیم بیابانی گرمدر پاسخ به این شرایط، افزایش و از حدود 45-35 به حدود 50-45 درصد رسیده است. بنابراین، دامنه اقلیم بیابانی گرم در دهه های اخیر با روند افزایشی سبب محدود شدن اقلیم بیابانی سرد گردیده و پیش بینی می شود این شرایط در آینده نیز تداوم داشته باشد. این شرایط سبب کاهش کیفیت محیط و منابع به ویژه در سرزمین های همجوار با ایران گردیده و می تواند چالش های مهم از قبیل مهاجرت های اقلیمی ، امنیت مرز و سلامت در برداشته باشد.نتایج این بررسی می تواند سهم قابل توجهی در اتخاذ سیاست های آینده نگرانه برای رویارویی با اثرات و چالش های تغییراقلیم منطقه موردمطالعه بر روی مناطق مرزی ایران ایفا کند.
Climate classification systems(CCSs) are important tools for understanding the specific characteristics of a region's climate. The main purpose of these classifications is to determine the climate types and to find their similarities, differences and variability. Climate zones are threatened by global warming and climate change. The purpose of this study is to evaluate the possible shifts of climate zones over the Balochistan plateau of Pakistan and its potential challenges to Iran based on the improved Koppen-Geiger CCSs. The data includes average monthly precipitation and temperature of the Delaware university dataset for the 1990-2017 periods. The results show the main climate with two subgroups in the study area. These climates include a hot desert climate(BWh) and a cold desert climate(BWk). The hot desert climate is dominated in southern and western and the cold desert climate in northern and western regions.In recent decades, the increasing range of hot desert climate limited the cold desert climate. The range of the cold desert climate has declined sharply, reaching from about 55-65 to about 50-55 percent. In contrast, the range of hot desert climate increased in response to these conditions, reaching from about 35-45 to about 45-50 percent.Therefore, it is expected that the zones of the hot desert climate will increase rapidly in the future. These conditions will add to environmental quality and resource depletion problems especially in border areas with Iran and can pose important challenges such as climate migration, border security, and health. The results of this research can play a significant role in adopting forward-looking policies to address the impacts and challenges of climate change on the border regions of Iran.
1- رضیئی، طیب.،(1396): چشم‌اندازی از مناطق اقلیمی ایران به روش کوپن-گایگر در سده بیست و یکم. مجله ژئوفیزیک ایران،1(11)، صص 100-84.
2- رضیئی، طیب.، (1396): منطقه بندی اقلیمی ایران به روش کوپن-گایگر و بررسی جابه‌جایی مناطق اقلیمی کشور در سدۀبیستم، فیزیک زمین و فضا، 2(43)، صص 439-419.
3-Adnan, S., Ullah, K., Gao, S., Khosa, A. H., &Wang, Z. (2017):Shifting Of Agro‐Climatic Zones, Their Drought Vulnerability, And Precipitation And Temperature Trends In Pakistan. International Journal Of Climatology, 37, Pp. 529-543.
4-Alvares, C. A., Stape, J. L., Sentelhas, P. C., De Moraes, G., Leonardo, J., &Sparovek, G. (2013):Köppen's Climate Classification Map For Brazil. Meteorologischezeitschrift, 22(6), Pp. 711-728
5-Baker, B., Diaz, H., Hargrove, W., &Hoffman, F. (2010):Use Of The Köppen–Trewartha Climate Classification To Evaluate Climatic Refugia In Statistically Derived Ecoregions For The People’s Republic Of China. Climatic Change, 98(1-2), 113.
6-Beck, C., Grieser, J., Kottek, M., Rubel, F., &Rudolf, B. (2005):Characterizing Global Climate Change By Means Of Köppen Climate Classification. Klimastatusbericht, 51, Pp. 139-149.
7-Chan, D., Wu, Q., Jiang, G., &Dai, X. (2016):Projected Shifts In Köppen Climate Zones Over China And Their Temporal Evolution In CMIP5 Multi-Model Simulations. Advances In Atmospheric Sciences, 33(3), Pp. 283-293.
8-Chen, D., &Chen, H. W. (2013):Using The Köppen Classification To Quantify Climate Variation And Change: An Example For 1901–2010. Environmental Development, 6, Pp. 69-79.
9-De Castro, M., Gallardo, C., Jylha, K., &Tuomenvirta, H. (2007):The Use Of A Climate-Type Classification For Assessing Climate Change Effects In Europe From An Ensemble Of Nine Regional Climate Models. Climatic Change, 81(1), Pp. 329-341.
10-De Souza Rolim, G., & De O. Aparecido, L. E. (2016):Camargo, Köppen And Thornthwaite Climate Classification Systems In Defining Climatical Regions Of The State Of São Paulo, Brazil. International Journal Of Climatology, 36(2), Pp. 636-643.
11-Eckstein, D., Künzel, V., Schäfer, L., &Winges, M. (2019):Global Climate Risk Index 2020. Bonn: Germanwatch.
12-Fraedrich, K., Gerstengarbe, F. W., &Werner, P. C. (2001):Climate Shifts During The Last Century. Climatic Change, 50(4), Pp. 405-417.
13-Gallardo, C., Gil, V., Hagel, E., Tejeda, C., & De Castro, M. (2013):Assessment Of Climate Change In Europe From An Ensemble Of Regional Climate Models By The Use Of Köppen–Trewartha Classification. International Journal Of Climatology, 33(9), Pp. 2157-2166.
14-Guetter, P. J., &Kutzbach, J. E. (1990):A Modified Köppen Classification Applied To Model Simulations Of Glacial And Interglacial Climates. Climatic Change, 16(2), Pp. 193-215.
15- Kleidon, A., Fraedrich, K., &Heimann, M. (2000):A Green Planet Versus A Desert World: Estimating The Maximum Effect Of Vegetation On The Land Surface Climate. Climatic Change, 44(4), Pp. 471-493.
16-Kim, H. J., Wang, B., Ding, Q., &Chung, I. U. (2008):Changes In Arid Climate Over North China Detected By The Koppen Climate Classification. Journal Of The Meteorological Society Of Japan. Ser. II, 86(6), Pp. 981-990.
17-Kottek, M., Grieser, J., Beck, C., Rudolf, B., &Rubel, F. (2006):World Map Of The Köppen-Geiger Climate Classification Updated. Meteorologischezeitschrift, 15(3), 259-263.
18-Larson, P. R., &Lohrengel, C. F. (2014):An Addendum To “A New Tool For Climatic Analysis Using Köppen Climate Classification”. Journal Of Geography, 113(1), Pp. 35-38.
19-Lohmann, U., Sausen, R., Bengtsson, L., Cubasch, U., Perlwitz, J., &Roeckner, E. (1993):The Köppen Climate Classification As A Diagnostic Tool For General Circulation Models. Climate Research, 3, Pp. 177-193.
20-Peel, M. C., Finlayson, B. L., & Mcmahon, T. A. (2007):Updated World Map Of The Köppen-Geiger Climate Classification. Hydrology And Earth System Sciences Discussions, 4(2), Pp. 439-473.
21-Petersen, J.F., D. SACK, R.E. GABLER, (2012): Physical Geography. Brooks/Cole Cengage Learning, Belmont, Pp. 646.
22-Rohli, R.V., A.J. VEGA, (2012): Climatology. 2nd Ed. – Jones &Bartlett Learning, Udbury, Pp. 425.
23-Sattari, M. T., Rezazadeh-Joudi, A., &Kusiak, A. (2017):Assessment Of Different Methods For Estimation Of Missing Data In Precipitation Studies. Hydrology Research, 48(4), Pp. 1032-1044.
24-Shamshad, K. M. (1988):The Meteorology Of Pakistan: Climate And Weather Of Pakistan. Royal Book Company.
25-Stern, H., De Hoedt, G., &Ernst, J. (2000):Objective Classification Of Australian Climates. Australian Meteorological Magazine, 49(2), Pp. 87-96.
26-Tularam, G. A., &Ilahee, M. (2010):Time Series Analysis Of Rainfall And Temperature Interactions In Coastal Catchments. Journal Of Mathematics And Statistics, 6(3), Pp. 372-380.
27-Wang, M., &Overland, J. E. (2004):Detecting Arctic Climate Change Using Köppen Climate Classification. Climatic Change, 67(1), Pp. 43-62.
28-Ying, S., Xue-Jie, G., &Jia, W. (2012):Projected Changes In Köppen Climate Types In The 21st Century Over China. Atmospheric And Oceanic Science Letters, 5(6), Pp. 495-498.
29-Young, K. C. (1992):A Three-Way Model For Interpolating For Monthly Precipitation Values. Monthly Weather Review, 120(11), Pp. 2561-2569.
30-Yan, X., &Su, X. (2009):Linear Regression Analysis: Theory And Computing. World Scientific, London, Vol. 1–2.
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1- رضیئی، طیب.،(1396): چشم‌اندازی از مناطق اقلیمی ایران به روش کوپن-گایگر در سده بیست و یکم. مجله ژئوفیزیک ایران،1(11)، صص 100-84.
2- رضیئی، طیب.، (1396): منطقه بندی اقلیمی ایران به روش کوپن-گایگر و بررسی جابه‌جایی مناطق اقلیمی کشور در سدۀبیستم، فیزیک زمین و فضا، 2(43)، صص 439-419.
3-Adnan, S., Ullah, K., Gao, S., Khosa, A. H., &Wang, Z. (2017):Shifting Of Agro‐Climatic Zones, Their Drought Vulnerability, And Precipitation And Temperature Trends In Pakistan. International Journal Of Climatology, 37, Pp. 529-543.
4-Alvares, C. A., Stape, J. L., Sentelhas, P. C., De Moraes, G., Leonardo, J., &Sparovek, G. (2013):Köppen's Climate Classification Map For Brazil. Meteorologischezeitschrift, 22(6), Pp. 711-728
5-Baker, B., Diaz, H., Hargrove, W., &Hoffman, F. (2010):Use Of The Köppen–Trewartha Climate Classification To Evaluate Climatic Refugia In Statistically Derived Ecoregions For The People’s Republic Of China. Climatic Change, 98(1-2), 113.
6-Beck, C., Grieser, J., Kottek, M., Rubel, F., &Rudolf, B. (2005):Characterizing Global Climate Change By Means Of Köppen Climate Classification. Klimastatusbericht, 51, Pp. 139-149.
7-Chan, D., Wu, Q., Jiang, G., &Dai, X. (2016):Projected Shifts In Köppen Climate Zones Over China And Their Temporal Evolution In CMIP5 Multi-Model Simulations. Advances In Atmospheric Sciences, 33(3), Pp. 283-293.
8-Chen, D., &Chen, H. W. (2013):Using The Köppen Classification To Quantify Climate Variation And Change: An Example For 1901–2010. Environmental Development, 6, Pp. 69-79.
9-De Castro, M., Gallardo, C., Jylha, K., &Tuomenvirta, H. (2007):The Use Of A Climate-Type Classification For Assessing Climate Change Effects In Europe From An Ensemble Of Nine Regional Climate Models. Climatic Change, 81(1), Pp. 329-341.
10-De Souza Rolim, G., & De O. Aparecido, L. E. (2016):Camargo, Köppen And Thornthwaite Climate Classification Systems In Defining Climatical Regions Of The State Of São Paulo, Brazil. International Journal Of Climatology, 36(2), Pp. 636-643.
11-Eckstein, D., Künzel, V., Schäfer, L., &Winges, M. (2019):Global Climate Risk Index 2020. Bonn: Germanwatch.
12-Fraedrich, K., Gerstengarbe, F. W., &Werner, P. C. (2001):Climate Shifts During The Last Century. Climatic Change, 50(4), Pp. 405-417.
13-Gallardo, C., Gil, V., Hagel, E., Tejeda, C., & De Castro, M. (2013):Assessment Of Climate Change In Europe From An Ensemble Of Regional Climate Models By The Use Of Köppen–Trewartha Classification. International Journal Of Climatology, 33(9), Pp. 2157-2166.
14-Guetter, P. J., &Kutzbach, J. E. (1990):A Modified Köppen Classification Applied To Model Simulations Of Glacial And Interglacial Climates. Climatic Change, 16(2), Pp. 193-215.
15- Kleidon, A., Fraedrich, K., &Heimann, M. (2000):A Green Planet Versus A Desert World: Estimating The Maximum Effect Of Vegetation On The Land Surface Climate. Climatic Change, 44(4), Pp. 471-493.
16-Kim, H. J., Wang, B., Ding, Q., &Chung, I. U. (2008):Changes In Arid Climate Over North China Detected By The Koppen Climate Classification. Journal Of The Meteorological Society Of Japan. Ser. II, 86(6), Pp. 981-990.
17-Kottek, M., Grieser, J., Beck, C., Rudolf, B., &Rubel, F. (2006):World Map Of The Köppen-Geiger Climate Classification Updated. Meteorologischezeitschrift, 15(3), 259-263.
18-Larson, P. R., &Lohrengel, C. F. (2014):An Addendum To “A New Tool For Climatic Analysis Using Köppen Climate Classification”. Journal Of Geography, 113(1), Pp. 35-38.
19-Lohmann, U., Sausen, R., Bengtsson, L., Cubasch, U., Perlwitz, J., &Roeckner, E. (1993):The Köppen Climate Classification As A Diagnostic Tool For General Circulation Models. Climate Research, 3, Pp. 177-193.
20-Peel, M. C., Finlayson, B. L., & Mcmahon, T. A. (2007):Updated World Map Of The Köppen-Geiger Climate Classification. Hydrology And Earth System Sciences Discussions, 4(2), Pp. 439-473.
21-Petersen, J.F., D. SACK, R.E. GABLER, (2012): Physical Geography. Brooks/Cole Cengage Learning, Belmont, Pp. 646.
22-Rohli, R.V., A.J. VEGA, (2012): Climatology. 2nd Ed. – Jones &Bartlett Learning, Udbury, Pp. 425.
23-Sattari, M. T., Rezazadeh-Joudi, A., &Kusiak, A. (2017):Assessment Of Different Methods For Estimation Of Missing Data In Precipitation Studies. Hydrology Research, 48(4), Pp. 1032-1044.
24-Shamshad, K. M. (1988):The Meteorology Of Pakistan: Climate And Weather Of Pakistan. Royal Book Company.
25-Stern, H., De Hoedt, G., &Ernst, J. (2000):Objective Classification Of Australian Climates. Australian Meteorological Magazine, 49(2), Pp. 87-96.
26-Tularam, G. A., &Ilahee, M. (2010):Time Series Analysis Of Rainfall And Temperature Interactions In Coastal Catchments. Journal Of Mathematics And Statistics, 6(3), Pp. 372-380.
27-Wang, M., &Overland, J. E. (2004):Detecting Arctic Climate Change Using Köppen Climate Classification. Climatic Change, 67(1), Pp. 43-62.
28-Ying, S., Xue-Jie, G., &Jia, W. (2012):Projected Changes In Köppen Climate Types In The 21st Century Over China. Atmospheric And Oceanic Science Letters, 5(6), Pp. 495-498.
29-Young, K. C. (1992):A Three-Way Model For Interpolating For Monthly Precipitation Values. Monthly Weather Review, 120(11), Pp. 2561-2569.
30-Yan, X., &Su, X. (2009):Linear Regression Analysis: Theory And Computing. World Scientific, London, Vol. 1–2.