Imperial College London
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DrRossellaArcucci

Faculty of Engineering, Department of Earth Science & Engineering

Senior Lecturer in Data Science and Machine Learning
 
 
 
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Contact

 

r.arcucci Website

 
 
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Location

 

Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Arcucci:2017:10.1063/1.4992721,
author = {Arcucci, R and Celestino, S and Toumi, R and Laccetti, G},
doi = {10.1063/1.4992721},
publisher = {AIP Publishing},
title = {Toward the S3DVAR data assimilation software for the Caspian Sea},
url = {http://dx.doi.org/10.1063/1.4992721},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Data Assimilation (DA) is an uncertainty quantification technique used to incorporate observed data into a prediction model in order to improve numerical forecasted results. The forecasting model used for producing oceanographic prediction into the Caspian Sea is the Regional Ocean Modeling System (ROMS). Here we propose the computational issues we are facing in a DA software we are developing (we named S3DVAR) which implements a Scalable Three Dimensional Variational Data Assimilation model for assimilating sea surface temperature (SST) values collected into the Caspian Sea with observations provided by the Group of High resolution sea surface temperature (GHRSST). We present the algorithmic strategies we employ and the numerical issues on data collected in two of the months which present the most significant variability in water temperature: August and March.
AU  - Arcucci,R
AU  - Celestino,S
AU  - Toumi,R
AU  - Laccetti,G
DO  - 10.1063/1.4992721
PB  - AIP Publishing
PY  - 2017///
SN  - 1551-7616
TI  - Toward the S3DVAR data assimilation software for the Caspian Sea
UR  - http://dx.doi.org/10.1063/1.4992721
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000410159800531&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/53979
ER  -
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