Standard

Improved ocean analysis for the Indian Ocean. / Rahaman, Hasibur; Venugopal, T.; Penny, Stephen G. и др.

в: Journal of Operational Oceanography, Том 12, № 1, 02.01.2019, стр. 16-33.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

Harvard

Rahaman, H, Venugopal, T, Penny, SG, Behringer, DW, Ravichandran, M, Raju, JVS, Srinivasu, U & Sengupta, D 2019, 'Improved ocean analysis for the Indian Ocean', Journal of Operational Oceanography, Том. 12, № 1, стр. 16-33. https://doi.org/10.1080/1755876X.2018.1547261

APA

Rahaman, H., Venugopal, T., Penny, S. G., Behringer, D. W., Ravichandran, M., Raju, J. V. S., Srinivasu, U., & Sengupta, D. (2019). Improved ocean analysis for the Indian Ocean. Journal of Operational Oceanography, 12(1), 16-33. https://doi.org/10.1080/1755876X.2018.1547261

Vancouver

Rahaman H, Venugopal T, Penny SG, Behringer DW, Ravichandran M, Raju JVS и др. Improved ocean analysis for the Indian Ocean. Journal of Operational Oceanography. 2019 янв. 2;12(1):16-33. doi: 10.1080/1755876X.2018.1547261

Author

Rahaman, Hasibur ; Venugopal, T. ; Penny, Stephen G. и др. / Improved ocean analysis for the Indian Ocean. в: Journal of Operational Oceanography. 2019 ; Том 12, № 1. стр. 16-33.

BibTeX

@article{28fd4512fe9a477a97cf474f94db609c,
title = "Improved ocean analysis for the Indian Ocean",
abstract = "The National Centers for Environmental Prediction (NCEP) and the Indian National Centre for Ocean Information Services (INCOIS) produce global ocean analyses based on the Global Ocean Data Assimilation System (GODAS). This system uses a state of the art ocean general circulation model named moduler ocean model (MOM) and the 3D-Variational (3DVar) data assimilation technique. In this study we have evaluated the INCOIS-GODAS operational analysis products with an upgrade of the physical model from MOM4p0d to MOM4p1. Two experiments were performed with same atmospheric forcing fields:(i) using MOM4p0d (GODAS_p0), and (ii) using MOM4p1 (GODAS_p1). Observed temperature and salinity profiles were assimilated in both experiments. Validation with independent observations show improvement of sea surface temperature(SST), sea surface salinity (SSS) and surface currents in the new analysis GODAS_p1 as compared to the old analysis GODAS_p0.",
keywords = "Global Ocean Data Assimilation System (GODAS), Indian Ocean, Ocean Analysis, SUMMER MONSOON RAINFALL, IMPROVED COUPLED MODEL, INTRASEASONAL VARIABILITY, ERROR QUANTIFICATION, MINI-WARM POOL, MIXED-LAYER, ENSO PREDICTION, SEA-SURFACE SALINITY, DATA ASSIMILATION SYSTEM, INDONESIAN THROUGHFLOW",
author = "Hasibur Rahaman and T. Venugopal and Penny, {Stephen G.} and Behringer, {David W.} and M. Ravichandran and Raju, {J. V.S.} and U. Srinivasu and Debasis Sengupta",
note = "Publisher Copyright: {\textcopyright} 2018, {\textcopyright} 2018 Institute of Marine Engineering, Science & Technology.",
year = "2019",
month = jan,
day = "2",
doi = "10.1080/1755876X.2018.1547261",
language = "English",
volume = "12",
pages = "16--33",
journal = "Journal of Operational Oceanography",
issn = "1755-876X",
publisher = "Taylor and Francis Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Improved ocean analysis for the Indian Ocean

AU - Rahaman, Hasibur

AU - Venugopal, T.

AU - Penny, Stephen G.

AU - Behringer, David W.

AU - Ravichandran, M.

AU - Raju, J. V.S.

AU - Srinivasu, U.

AU - Sengupta, Debasis

N1 - Publisher Copyright: © 2018, © 2018 Institute of Marine Engineering, Science & Technology.

PY - 2019/1/2

Y1 - 2019/1/2

N2 - The National Centers for Environmental Prediction (NCEP) and the Indian National Centre for Ocean Information Services (INCOIS) produce global ocean analyses based on the Global Ocean Data Assimilation System (GODAS). This system uses a state of the art ocean general circulation model named moduler ocean model (MOM) and the 3D-Variational (3DVar) data assimilation technique. In this study we have evaluated the INCOIS-GODAS operational analysis products with an upgrade of the physical model from MOM4p0d to MOM4p1. Two experiments were performed with same atmospheric forcing fields:(i) using MOM4p0d (GODAS_p0), and (ii) using MOM4p1 (GODAS_p1). Observed temperature and salinity profiles were assimilated in both experiments. Validation with independent observations show improvement of sea surface temperature(SST), sea surface salinity (SSS) and surface currents in the new analysis GODAS_p1 as compared to the old analysis GODAS_p0.

AB - The National Centers for Environmental Prediction (NCEP) and the Indian National Centre for Ocean Information Services (INCOIS) produce global ocean analyses based on the Global Ocean Data Assimilation System (GODAS). This system uses a state of the art ocean general circulation model named moduler ocean model (MOM) and the 3D-Variational (3DVar) data assimilation technique. In this study we have evaluated the INCOIS-GODAS operational analysis products with an upgrade of the physical model from MOM4p0d to MOM4p1. Two experiments were performed with same atmospheric forcing fields:(i) using MOM4p0d (GODAS_p0), and (ii) using MOM4p1 (GODAS_p1). Observed temperature and salinity profiles were assimilated in both experiments. Validation with independent observations show improvement of sea surface temperature(SST), sea surface salinity (SSS) and surface currents in the new analysis GODAS_p1 as compared to the old analysis GODAS_p0.

KW - Global Ocean Data Assimilation System (GODAS)

KW - Indian Ocean

KW - Ocean Analysis

KW - SUMMER MONSOON RAINFALL

KW - IMPROVED COUPLED MODEL

KW - INTRASEASONAL VARIABILITY

KW - ERROR QUANTIFICATION

KW - MINI-WARM POOL

KW - MIXED-LAYER

KW - ENSO PREDICTION

KW - SEA-SURFACE SALINITY

KW - DATA ASSIMILATION SYSTEM

KW - INDONESIAN THROUGHFLOW

UR - http://www.scopus.com/inward/record.url?scp=85057612256&partnerID=8YFLogxK

U2 - 10.1080/1755876X.2018.1547261

DO - 10.1080/1755876X.2018.1547261

M3 - Article

AN - SCOPUS:85057612256

VL - 12

SP - 16

EP - 33

JO - Journal of Operational Oceanography

JF - Journal of Operational Oceanography

SN - 1755-876X

IS - 1

ER -

ID: 17687772