تحلیل فضایی مخاطرات محیطی

تحلیل فضایی مخاطرات محیطی

مطالعه مقایسه‌ای روش‌های نگاشت چندک برای تصحیح اریبی داده‌های بارش بازتحلیل ERA5

نویسندگان
کاوه باپیرزاده
حسام سیدکابلی
لیلا نجفی
دانشگاه صنعتی چندی شاپور دزفول
چکیده
این تحقیق به ارزیابی توانایی روش‌های مختلف نگاشت چندک (QM) به عنوان یک تکنیک تصحیح اریبی داده‌های بارش بازتحلیل ERA5 می‌پردازد. نوع اقلیم و موقعیت جغرافیایی می‌توانند عملکرد روش تصحیح اریبی را به دلیل تفاوت در خصوصیات بارش تحت تأثیر قرار دهند. به این منظور داده‌های بارش بازتحلیل ERA5 برای سال‌های 2019-1989 به صورت روزانه برای 10 ایستگاه سینوپتیک منتخب در اقلیم‌هایی با ویژگی‌های توپوگرافیک گوناگون از سایت مرکز پیش‌بینی میان مدت جوی اروپا (ECMWF) دریافت شد. تصحیح اریبی این داده‌ها با استفاده از 5 روش نگاشت چندک بر پایه داده‌های مشاهداتی در محیط نرم‌افزار R انجام گرفت. ارزیابی دوبخشی و دیاگرام تیلور برای مقایسه عملکرد روش‌های مختلف به کار گرفته شد. نتایج نشان داد که عملکرد روش نگاشت چندک به توابع عملکرد، مجموعه پارامتر‌ها و شرایط اقلیمی بستگی دارد. به طورکلی روش‌های ناپارامتریک نگاشت چندک عملکرد مناسب‌تری نسبت به روش‌های پارامتریک دارند به گونه‌ای که بهترین عملکرد مربوط به روش QUANT و RQUANT است، در این بین روش DIST ضعیف‌ترین عملکرد را دارد.
کلیدواژه‌ها
نگاشت چندک
تصحیح اریبی
ERA5
ECMWF

عنوان مقاله English

A comparative study of quantitative mapping methods for bias correction of ERA5 reanalysis precipitation data

نویسندگان English

Kaveh Bapirzadeh
Hesam SeyedKaboli
Leila Najafi
Jundi-Shapur University of Technology-Dezful
چکیده English

A comparative study of quantitative mapping methods for bias correction of ERA5 reanalysis precipitation data



Kaveh Bapirzadeh1, Hesam Seyed kaboli*2, Leila Najafi3

1 MSc student, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.

*2 Associate Professor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran. Corresponding Author: Email: hkaboli@jsu.ac.ir

3 Instructor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.

Abstract

This study evaluates the ability of different quantitative mapping (QM) methods as a bias correction technique for ERA5 reanalysis precipitation data. Climate type and geographical location can affect the performance of the bias correction method due to differences in precipitation characteristics. For this purpose, ERA5 reanalysis precipitation data for the years 1989-2019 for 10 selected synoptic stations in climates with different topographic characteristics were received daily from the European Centre for Medium-Range Weather Forecasts (ECMWF) website. Bias correction of these data was performed using 5 quantitative mapping methods based on observational data in R software environment. Two-part evaluation and Taylor diagram were used to compare the performance of different methods. The results showed that the performance of the quantification mapping method depends on the performance functions, set of parameters and climatic conditions. In general, non-parametric methods of multiple mapping have better performance than parametric methods, so that the best performance is related to QUANT and RQUANT methods, among which DIST method has the weakest performance.



Keywords: Quantitative mapping, Bias correction, ERA5, ECMWF

کلیدواژه‌ها English

Quantitative mapping
Bias correction
ERA5
ECMWF
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