تعیین مقیاس زمانی مناسب پیش‎بینی‎ های کوتاه و میان‎ مدت مدلهای عددی هواشناسی جهانی در بخشهای مختلف ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته رشته مهندسی منابع آب، گروه مهندسی آب دانشگاه بین المللی امام خمینی، قزوین

2 عضو هیئت علمی گروه مهندسی آب دانشگاه بین المللی امام خمینی قزوین

3 دانشیار گروه مهندسی آب، دانشگاه بین المللی امام خمینی، قزوین

چکیده

مدل‎های پیش‎بینی بارش نقش اساسی در عملکرد هر چه بهتر سامانه‌های پیش‎بینی هواشناسی و سیلاب ایفا می‌کنند. در مطالعه حاضر، عملکرد پیش‎بینی‎های پنج مدل عددی هواشناسی موجود در پایگاه TIGGE به منظور بررسی دقت پیش‎بینی‎ها طی گام زمانی‎های 1 تا 10 روزه در اقلیم‌های مختلف کشور ایران (در محل 38 ایستگاه سینوپتیک) طی بازه زمانی 2014 تا 2018 مورد ارزیابی و اصلاح اریبی قرار گرفتند. بررسی شاخص‎های آماری و جدولی حاکی از کاهش دقت پیش‎بینی‎ها با افزایش گام زمانی می‌باشد. طبق نتایج بدست آمده عمده مدلهای هواشناسی به ویژه دو مدل ECMWF و UKMO حداکثر تا افق زمانی 3 روزه از همبستگی مناسبی با داده‌های زمینی برخوردار بوده و در عین حال نیز دارای خطای کمتری (در تخمین مقدار بارش و پیش‌بینی روزهای بارانی) می‌باشند. با اصلاح اریبی داده‌های خام پیش‌بینی عملکرد مدلهای عددی آب و هوا به طور قابل توجهی افزایش یافت، به طوری که در گام زمانی 10 روزه در مدلهای ECMWF، JMA و KMA به ترتیب بیش از 70، 65 و 73 درصد از مقدار شاخص RMSE کاهش یافت. پس از اصلاح داده‌های بارش، عملکرد عمده مدلهای عددی به غیر از JMA حتی تا گام زمانی 7 روزه نیز در اکثر اقلیمهای کشور منجربه نتایج قابل قبولی گردید. مدل JMA در اقلیم‌های مرطوب که شامل مناطق غربی و شمالی کشور است، به دلیل ساختار مدل آشفتگی موجود در این مدل دارای اریبی زیادی بوده و نتایج غیرقابل اعتمادی ارائه نموده است.

کلیدواژه‌ها


عنوان مقاله [English]

Determining the Appropriate Temporal Resolution of Short and mid-terms of Global Precipitation Forecasting Systems over Iran

نویسندگان [English]

  • Setareh Amini 1
  • Asghar Azizian 2
  • Peyman Arasteh 3
1 MSc of water resources engineering, Water engineering Department, IKIU University, Qazvin,
2 Assistant Professor in Water Engineering Dept./ Imam Khomeini International University
3 Assistance Professor, Water Engineering Department, IKIU University, Qazvin
چکیده [English]

Precipitation forecasting models play important role in the performance of flood and meteorological warning systems. In this research, the efficiency of five numerical weather prediction (NWP) models, which exist in the TIGGE database, are assessed to determine the best temporal resolution of forecasted datasets at distinct climate regions of Iran, during 2014-2018. Findings show that by increasing the lead time the accuracy of all forecasts decreases significantly. Moreover, most of the NWP models, especially the ECMWF and UKMO perform well, based on correlation coefficient (CC) and RMSE metrics, up to lead time of 3 days. Also, results indicate that by removing biases from the raw forecast datasets, the performance of all NWP models in different lead times increases considerably. After bias correction, the RMSE values of ECMWF, JMA, and KMA models in the lead time of 10 days reduces about 70, 65, and 73%, respectively, and, except for JMA, all NWP models perform well in most climate regions. The JMA model in humid climate zones (north and west parts of Iran) has a high level of bias and leads to unreliable forecasts.

کلیدواژه‌ها [English]

  • prediction
  • Flood warning
  • Rainfall
  • Remote-Sensing
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