Mitigation of model bias influences on wave data assimilation with multiple assimilation systems using WaveWatch III v5.16 and SWAN v41.20

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Wave data assimilation using non-stationary kriging

We present a fast sequential assimilation technique for conditioning wave simulations using buoy data. It is based on non-stationary kriging that uses a separable space-time variogram. This variogram is estimated from the history of simulations, as a collection of maps of variances of increments between the logarithms of simulated and observed wave heights. The method finally provides a set of ...

متن کامل

هم‌جوشی داده‌های موج در خلیج فارس با مدل طیفی ویوواچ3

The major problems in modeling of different oceanographic and meteorological parameters are limitations in numerical methods and human incomplete knowledge in physical processes involved. As a result, significant differences between the results of these models and in situ observations of these parameters might exist. One of the powerful solutions for decreasing the forecast errors in the models...

متن کامل

Ensemble smoother with multiple data assimilation

In the last decade, ensemble-based methods have been widely investigated and applied for data assimilation of flow problems associated with atmospheric physics and petroleum reservoir history matching. This paper focuses entirely on the reservoir history-matching problem. Among the ensemble-based methods, the ensemble Kalman filter (EnKF) is the most popular for history-matching applications. H...

متن کامل

Sequential data assimilation with multiple models

Data assimilation is an essential tool for predicting the behavior of real physical systems given approximate simulation models and limited observations. For many complex systems, there may exist several models, each with different properties and predictive capabilities. It is desirable to incorporate multiple models into the assimilation procedure in order to obtain a more accurate prediction ...

متن کامل

Reconstructing neural dynamics using data assimilation with multiple models

Assimilation of data with models of physical processes is a critical component of modern scientific analysis. In recent years, nonlinear versions of Kalman filtering have been developed, in addition to methods that estimate model parameters in parallel with the system state. We propose a substantial extension of these tools to deal with the specific case of unmodeled variables, when training da...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Geoscientific Model Development

سال: 2020

ISSN: 1991-9603

DOI: 10.5194/gmd-13-1035-2020