کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4532093 1325093 2013 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-model ensemble forecasting and glider path planning in the Mid-Atlantic Bight
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات زمین شناسی
پیش نمایش صفحه اول مقاله
Multi-model ensemble forecasting and glider path planning in the Mid-Atlantic Bight
چکیده انگلیسی

During the first two weeks of November 2009, a field experiment was conducted in the Mid-Atlantic Bight region to demonstrate a coastal ocean observatory that can collect observations from heterogeneous platforms and forecast fields from four different ocean models, provide multi-model ensemble forecasts based on either an equal weighting (EQ) or objective weighting (OBJ) method, and use model forecasts in a path planning system to relocate autonomous gliders. This experiment is a prototype for the command and control component of cyberinfrastructure of the Ocean Observatories Initiative funded by the National Science Foundation. The four individual models use different forcing fields, boundary conditions and data assimilation techniques, and have resolutions varying from 2 km to 15 km. Our results indicate that for sea surface temperature and surface currents, the OBJ ensemble outperforms the four individual models, while the EQ ensemble can also provide an effective way to improve individual model forecasts. In terms of glider path planning, the OBJ ensemble has a performance similar to the best individual model, which has the finest horizontal resolution. This field experiment demonstrates the first-ever use of ensemble current forecasts to guide glider path planning in the context of real-time data collection and ocean model forecasting.


► A coastal ocean observatory field experiment was conducted in November 2009.
► Two ensemble forecasting techniques were tested in the field experiment.
► The performance of current forecasts was accessed in terms of glider path planning.
► The objective weighting method tends to improve individual model forecasts.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Continental Shelf Research - Volume 63, Supplement, 15 July 2013, Pages S223–S234
نویسندگان
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