مقایسه‌ی مدل‌های ریزمقیاس‌نمایی LARS-WG و SDSM در پیش‌بینی تغییرات دما و بارش تحت سناریوهایRCP

نویسندگان

1 دانشگاه کاشان

2 مرکز تحقیقات آموزش کشاورزی و منابع طبیعی اراک

چکیده

روش‌های مختلفی برای تبدیل داده‌های بزرگ‌مقیاس به داده‌های اقلیمی منطقه‌‌ای گسترش یافته‌اند که در کم‌تر مطالعه‌ای نتایج این روش‌ها از لحاظ آماری مورد مقایسه قرار گرفته است. هدف از این مطالعه‌، مقایسه‌ی نتایج مدل‌های SDSM و LARS-WG در ریزمقیاس‌نمایی داده‌های خروجی مدل‌های گردش عمومی CANE-SM2 و HADGEM2-ES تحت سناریوهایRCP2.6 ، RCP4.5 وRCP8.5 است. جهت انجام این مطالعه‌، دمای حداقل، دمای حداکثر و بارش در دوره‌ی پایه (2005-1980) ایستگاه سینوپتیک اراک مورداستفاده قرار گرفت و نتایج حاصل از پیش‌بینی‌های دو مدلSDSM و LARS-WG برای سه دوره‌ی 2040-2021، 2060-2041 و 2080-2061 مقایسه شد. به‌ منظور ارزیابی عملکرد مدل‌ها شاخص‌های RMSE، R2، MAE و NSE استفاده شد. بر اساس نتایج شاخص‌های ارزیابی، هر دو مدل کارآیی مناسبی در شبیه‌سازی متغیرهای اقلیمی دارد. نتایج ریزمقیاس‌نمایی دو مدل نشان داد که به‌طورکلی در هر سه سناریو و هر سه دوره‌ از ماه ژانویه تا ژوئن مقادیر پیش‌بینی دمای حداقل و دمای حداکثر نسبت به دوره‌ی پایه افزایش می‌یابد و مدل LARS-WG در مقایسه با مدل SDSM مقدار دمای حداقل و حداکثر را نسبت به دوره‌ی پایه بیش‌تر برآورد نموده است. تغییرات بارش پیش‌بینی‌شده به ‌وسیله‌ی دو مدل SDSM و LARS-WG دارای روند مشخصی نبوده است. بررسی درصد تغییرات داده‌های دما و بارش نشان داد که خروجی مدل SDSM تغییرات بیش‌تری را در بارش و خروجی مدل LARS-WG تغییرات بیش‌تری را در دمای حداقل و دمای حداکثر نسبت به دوره‌ی پایه نشان می‌دهد. بر اساس نتایج این مطالعه‌ نمی‌توان برتری دقیقی برای هر یک از مدل‌های موردمطالعه‌ بیان کرد، ولی به‌طورکلی می‌توان گفت که نتایج پیش‌بینی دو مدل در اکثر موارد از نظر آماری اختلاف معنی‌دار (01/0P<) دارند.

کلیدواژه‌ها

عنوان مقاله [English]

Comparison of LARS-WG and SDSM Downscaling Models for Prediction Temperature and Precipitation Changes under RCP Scenarios

نویسندگان [English]

  • zohreh zoheyri 1
  • reza ghazavi 1
  • ebrahim omidvar 1
  • aliakbar Davudi_rad 2
چکیده [English]

Various methods developed to convert large-scale data to regional climatic data. In few studies , the results of these methods have been statistically compared. The main purpose of this study was to compare SDSM and LARS-WG models for Downscaling output data of CANE-SM2 and HADGEM2-ES general circulation models under RCP2.6, RCP4.5 and RCP8.5 scenarios. For this study, precipitation, minimum and maximum temperature of Arak synoptic station were used as the base period (1980-2005). The results of the predictions of the SDSM and LARS-WG models were compared for three periods (2021-2040, 2041-2060 and 2061-2080). The RMSE, R2, MAE and NSE criteria were used to evaluate the performance of SDSM and LARS-WG models. Based on the results of the evaluation criteria, both models have an acceptable resuts in simulation of climate variables. Downscaling results of both models showed that minimum and maximum temperatures should increased compare to baseline in all scenarios and periods from January to June, but LARS-WG model had a over estimation compared to the SDSM model. Changes in predicted precipitation by SDSM and LARS-WG models did not have a clear trend. According to the results, the SDSM model shows more changes in precipitation, wherase, the LARS-WG model shows more changes in minimum and maximum temperature compared to the base period. Based on the results of this study, it is not possible to determine the exact superiority of each of the models, But SDSM model had a better prediction for precipitation and maximum temperature, while, LARS model had better results for maximum and minimum temperature.in general it can be said that the prediction results of both models are statistically significant (P<0.01) in most cases.

کلیدواژه‌ها [English]

  • climate change
  • general circulation models
  • Downscaling
  • Global warming
  • Arak

مراجع

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