مقایسه پوشش برف بین برونداد یک مدل پیش بینی عددی و داده های سنجده MODIS در ایران

نوع مقاله: مقاله پژوهشی

نویسندگان

1 پژوهشکده هواشناسی-سازمان هواشناسی کشور

2 هیات علمی پژوهشکده هواشناسیی

3 کارشناس پژوهشکده هواشناسی

چکیده

هدف این مطالعه، امکان‌سنجی استفاده از برونداد پوشش برف مدل پیش‌بینی عددیWRF با هدف بهبود پیش‌بینی‌های مرتبط با ذوب برف می‌باشد. با توجه به تعداد محدود ایستگاه های دیدبانی برف سنجی در مناطق کوهستانی کشور، داده های ماهواره ای به عنوان اطلاعات دیدبانی و سنجش برف با پوشش گسترده مکانی، میتواند مورد استفاده قرار گیرد. در این مطالعه شاخص نرمال شده تمایز برف با استفاده از داده های سنجنده MODIS استخراج و با برونداد مدل پیش‌بینی عددی WRF در یک مطالعه موردی مقایسه و خروجی مدل با استفاده از جدول احتمالاتی ارزیابی می‌شود. منطقه مورد مطالعه محدوده گچسر تا کندوان استان البرز مورخ 28 تا 30 ژانویه 2017 با بارش برف سنگین می‌باشد. تحلیل همدیدی معرف شیو فشاری قوی همراه با هوای سرد در لایه میانی جو است. برهم‌نهی داده پوشش برف ماهواره و خروجی مدل در یک شبکه منظم 78×90 نقطه‌ای با تفکیک 5 کیلومتر، معرف ضریب همبستگی خطی 7/0 در سطح معنی داری95% برای سه روز می‌باشد. میانگین احتمال آشکارسازی برف 87% و میانگین احتمال آشکار سازی نادرست مدل حدود 20% برآورد شده است. شاخص آزمون مهارت هیدک کیفیت اجرای مدل را حدود 70% در روزهای بدون ابر برآورد می‌کند. به‌نظر می‌رسد به علت ابرناکی، هم خوانی داده‌های ماهواره با برونداد مدل کاهش یافته باشد. به گونه‌ای که در روز 28 ژانویه (هوای نیمه ابری)، صحت پیش‌بینی‌ها به 57% کاهش می‌یابد که ممکن است ناشی از دیدبانی نادرست ماهواره یا پیش‌بینی نادرست باشد. به علت عدم وجود ایستگاه زمینی نمی‌توان به درستی در این خصوص اظهار نظر نمود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Comparison of snow cover resulting from satellite and a numerical prediction model in Iran

نویسندگان [English]

  • Mahdi rahnama 2
  • amir hossein nikfal 3
2 faculty member of ASMERC
3 Expet f ASMERC
چکیده [English]

The prediction of snow cover is fundamental in terms of the snow melting role for runoff prediction. The purpose of this study is the feasibility of using snow cover output of the WRF model with the aim of predicting snow melting. Since there are a few snow monitoring stations in the mountainous areas of Iran, satellite data are suitable widespread observation data. Accordingly, the extraction of snow cover data using MODIS sensor was addressed. Afterwards, it was compared to the snow cover of the WRF model outputs for a case study. Finally, the results were assessed using the contingency table. The studied area is located on Chalous Road, during January 28 to January 30, 2017 with heavy snowfall. Synoptic analysis indicates a strong pressure gradient in surface level associated with cold air in upper layers. Overlapping of satellite snow cover data with model output shows the linear correlation coefficient 0f 0.7 at a significant level of 0.01 in a 90 × 78 points network, 5 km resolution. The probability of detecting snow on 3 day average is 87% and the Probability of false detection is about 20%. Heidke Skill Score is about 0.7 for clear sky days (January 29th and January 30th.) which is the best result. In January 28th. The Heidke Skill Score is reduced to 57%. It may be the result of inaccurate satellite observation due to cloudiness sky or inaccurate forecasting. Since there is no ground station in the selected area, one cannot properly comment on this.

کلیدواژه‌ها [English]

  • WRF numerical weather prediction
  • normalized snow cover index
  • probabilistic table and remote sensing data
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