کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
6388032 1627746 2016 13 صفحه PDF سفارش دهید دانلود رایگان
عنوان انگلیسی مقاله ISI
On the ability of statistical wind-wave models to capture the variability and long-term trends of the North Atlantic winter wave climate
ترجمه فارسی عنوان
در توانایی مدل های موج باد آماری برای تطبیق تنوع و روندهای بلندمدت آب و هوای زمستانی اقیانوس اطلس شمالی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
چکیده انگلیسی
A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean Modelling - Volume 103, July 2016, Pages 177-189
نویسندگان
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