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Victor Shutyaev, Vladimir Zalesny, Valeriy Agoshkov, Eugene Parmuzin and Natalia Zakharova
The use of Four-Dimensional variational (4D-Var) data assimilation technology in the context of sea dynamics problems, with a sensitivity analysis of model results to observation errors, is presented. The technology is applied to a numerical model of oce...
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Jhon Edinson Hinestroza-Ramirez, Juan Ernesto Soto Barbosa, Andrés Yarce Botero, Danilo Andrés Suárez Higuita, Santiago Lopez-Restrepo, Lisseth Milena Cruz Ruiz, Valeria Sólorzano Araque, Andres Céspedes, Sara Lorduy Hernandez, Richard Caceres, Giovanni Jiménez-Sánchez and Olga Lucia Quintero
This manuscript introduces an exploratory case study of the SIMFAC?s (Sistema de Información Meteorológica de la Fuerza Aérea Colombiana) operational implementation of the Weather Research and Forecasting (WRF) model with a 3DVAR (three-dimensional varia...
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Yinghao Qin, Qinglong Yu, Liying Wan, Yang Liu, Huier Mo, Yi Wang, Sujing Meng, Xiangyu Wu, Dandan Sui and Jiping Xie
In this study, a global-ocean-data-assimilation system based on the three-dimensional variational (3DVAR) scheme is built for operational oceanography. The available observations include satellite altimetry; the satellite-measured sea-surface temperature...
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Abubakar Haruna, Pierre-André Garambois, Hélène Roux, Pierre Javelle and Maxime Jay-Allemand
We compare three hydrological models of different complexities, GR4H (lumped, continuous), SMASH (distributed, continuous), and MARINE (distributed, event-based), for Mediterranean flash flood modeling. The objective was to understand how differently the...
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Jose M. Gonzalez-Ondina, Lewis Sampson and Georgy I. Shapiro
Data assimilation methods are an invaluable tool for operational ocean models. These methods are often based on a variational approach and require the knowledge of the spatial covariances of the background errors (differences between the numerical model ...
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Vladimir Zalesny, Valeriy Agoshkov, Victor Shutyaev, Eugene Parmuzin and Natalia Zakharova
The technology is presented for modeling and prediction of marine hydrophysical fields based on the 4D variational data assimilation technique developed at the Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS). The technol...
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Lei Shi, Liujuan Tang and Edward Myers
This paper presents an incremental variational method to assimilate the observed tidal harmonic constants using a frequency domain linearized shallow water equation. A cost function was constructed with tidal boundary conditions and tidal forcing as its ...
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Jiaying Zhang, Liao-Fan Lin and Rafael L. Bras
Precipitation estimates from numerical weather prediction (NWP) models are uncertain. The uncertainties can be reduced by integrating precipitation observations into NWP models. This study assimilates Version 04 Integrated Multi-satellite Retrievals for ...
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Valery Agoshkov, Natalia Lezina and Tatiana Sheloput
One of the modern fields in mathematical modelling of water areas is developing hybrid coastal ocean models based on domain decomposition. In coastal ocean modelling a problem to be solved is setting open boundary conditions. One of the methods dealing w...
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Mingyang Zhang, Lifeng Zhang and Bin Zhang
A four-dimensional ensemble variational assimilation system for FY-3A satellite data is constructed using the Proper Orthogonal Decomposition (POD)-based ensemble four-dimensional variational (4DVar) assimilation method (referred to as POD-4DEnVar Satell...
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