TY - JOUR
T1 - Variability of the sea surface salinity (SSS) in the western tropical Pacific
T2 - On the ability of an OGCM to simulate the SSS, and on the sampling of an operating merchant ship SSS network
AU - Ioualalen, Mansour
AU - Wakata, Yoshinobu
AU - Kawahara, Yoshikazu
AU - Gouriou, Yves
AU - Varillon, David
N1 - Funding Information:
The authors acknowledge with thanks colleagues from IRD/Nouméa for their efforts in monitoring the IRD/ Nouméa TSG-XBT network, M. McPhaden, P. Freitag and M. McCarty, PMEL, for use of TAO buoy data and kindly providing us with Seacat and TSG SSS data obtained with R/Vs TAO suppliers, the National Geophysical Data Center (NGDC) for the model bathymetry and the National Centers for Environmental Prediction (NCEP) for the reanalysis. Thanks are due to C. Okesha for computational help. This work was supported by the Regional P011 convention between the South Pacific Regional Environment Program (SPREP) and IRD (former ORSTOM) via the Caisse Française de Développement. The authors would like to acknowledge with thanks the support of the French Embassy in Tokyo, in particular through the help
Copyright:
Copyright 2004 Elsevier Science B.V., Amsterdam. All rights reserved.
PY - 2003/2
Y1 - 2003/2
N2 - The sea surface salinity (SSS) derived from a network developed at Institut de Recherche pour le Développement (IRD/Nouméa has been analyzed during the period 1995-1998 in the tropical western Pacific. The measurements were made with thermosalinographs installed on merchant ships selected for their regularity and routes. The western tropical Pacific was sampled mainly along three regular routes across the equator leading to an average of a one month frequency. We analyze here how such a network can be efficient in monitoring the SSS at time scales longer than one month. For this purpose we have used results derived from the Princeton Ocean Model (POM) which is forced by the surface flux of National Centers for Environmental Prediction (NCEP) reanalysis data. The interannual variability of the simulated SSS exhibits very similar features to (sub-sampled) observations despite its being weakly damped to a climatology in order to avoid biases. Even smaller time scale phenomena can be simulated, like the erosion/reconstruction of the region composed of low density waters lying within the Pacific warm pool. The agreement between the observational data and the simulations indicate that the network sampling is sufficient to monitor the SSS variability of the western tropical Pacific from three-month to interannual time scales.
AB - The sea surface salinity (SSS) derived from a network developed at Institut de Recherche pour le Développement (IRD/Nouméa has been analyzed during the period 1995-1998 in the tropical western Pacific. The measurements were made with thermosalinographs installed on merchant ships selected for their regularity and routes. The western tropical Pacific was sampled mainly along three regular routes across the equator leading to an average of a one month frequency. We analyze here how such a network can be efficient in monitoring the SSS at time scales longer than one month. For this purpose we have used results derived from the Princeton Ocean Model (POM) which is forced by the surface flux of National Centers for Environmental Prediction (NCEP) reanalysis data. The interannual variability of the simulated SSS exhibits very similar features to (sub-sampled) observations despite its being weakly damped to a climatology in order to avoid biases. Even smaller time scale phenomena can be simulated, like the erosion/reconstruction of the region composed of low density waters lying within the Pacific warm pool. The agreement between the observational data and the simulations indicate that the network sampling is sufficient to monitor the SSS variability of the western tropical Pacific from three-month to interannual time scales.
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U2 - 10.1023/A:1022876708829
DO - 10.1023/A:1022876708829
M3 - Article
AN - SCOPUS:0038105991
SN - 0916-8370
VL - 59
SP - 105
EP - 111
JO - Journal of Oceanography
JF - Journal of Oceanography
IS - 1
ER -