scholarly journals High-resolution data assimilation of cardiac mechanics applied to a dyssynchronous ventricle

2017 ◽  
Vol 33 (11) ◽  
pp. e2863 ◽  
Author(s):  
Gabriel Balaban ◽  
Henrik Finsberg ◽  
Hans Henrik  Odland ◽  
Marie E. Rognes ◽  
Stian Ross ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Cardiac Mechanics ◽  
High Resolution Data ◽  
Resolution Data

scholarly journals Recent Progress of the NHM-4DVAR towards a Super-High Resolution Data Assimilation

SOLA ◽  
2014 ◽  
Vol 10 (0) ◽  
pp. 145-149 ◽  
Author(s):  
Takuya Kawabata ◽  
Kosuke Ito ◽  
Kazuo Saito
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Recent Progress ◽  
High Resolution Data ◽  
Resolution Data

scholarly journals Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model

2018 ◽  
Vol 24 ◽  
pp. 85-90 ◽  
Author(s):  
Henrik Finsberg ◽  
Gabriel Balaban ◽  
Stian Ross ◽  
Trine F. Håland ◽  
Hans Henrik Odland ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Mechanical Model ◽  
Cardiac Contraction ◽  
High Resolution Data ◽  
Resolution Data

scholarly journals Improving Short-Term Storm Predictions by Assimilating both Radar Radial-Wind and Reflectivity Observations

2008 ◽  
Vol 23 (3) ◽  
pp. 373-391 ◽  
Author(s):  
Qingyun Zhao ◽  
John Cook ◽  
Qin Xu ◽  
Paul R. Harasti
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Radar Data ◽  
Naval Research ◽  
Short Term ◽  
High Resolution Data ◽  
Reflectivity Data ◽  
The Impact ◽  
Data Assimilation System ◽  
Resolution Data

Abstract A high-resolution data assimilation system is under development at the Naval Research Laboratory (NRL). The objective of this development is to assimilate high-resolution data, especially those from Doppler radars, into the U.S. Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System to improve the model’s capability and accuracy in short-term (0–6 h) prediction of hazardous weather for nowcasting. A variational approach is used in this system to assimilate the radar observations into the model. The system is upgraded in this study with new capabilities to assimilate not only the radar radial-wind data but also reflectivity data. Two storm cases are selected to test the upgraded system and to study the impact of radar data assimilation on model forecasts. Results from the data assimilation experiments show significant improvements in storm prediction especially when both radar radial-wind and reflectivity observations are assimilated and the analysis incremental fields are adequately constrained by the model’s dynamics and properly adjusted to satisfy the model’s thermodynamical balance.

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