FN Archimer Export Format
PT J
TI A large-scale view of oceanic variability from 2007 to 2015 in the global high resolution monitoring and forecasting system at Mercator Océan
BT 
AF GASPARIN, Florent
   GREINER, Eric
   LELLOUCHE, Jean-Michel
   LEGALLOUDEC, Olivier
   GARRIC, Gilles
   DRILLET, Yann
   BOURDALLE-BADIE, Romain
   LE TRAON, Pierre-Yves
   REMY, Elisabeth
   DREVILLON, Marie
AS 1:1;2:2;3:1;4:1;5:1;6:1;7:1;8:1,3;9:1;10:1;
FF 1:;2:;3:;4:;5:;6:;7:;8:PDG-ODE;9:;10:;
C1 Mercator Ocean Int, 10 Rue Hermes, F-31520 Ramonville St Agne, France.
   CLS, 11 Rue Hermes, F-31520 Ramonville St Agne, France.
   Ifremer, F-29280 Plouzane, France.
C2 MERCATOR OCEAN, FRANCE
   CLS, FRANCE
   IFREMER, FRANCE
SI BREST
SE PDG-ODE
IN WOS Ifremer jusqu'en 2018
   copubli-france
IF 2.539
TC 29
UR https://archimer.ifremer.fr/doc/00448/55956/57550.pdf
LA English
DT Article
DE ;Global ocean monitoring and forecasting system;Climate variability;System evaluation/qualification;Global ocean observing system
AB The global high resolution monitoring and forecasting system PSY4 at Mercator Océan, initialized in October 2006, has achieved 11 years of global ocean state estimation. Based on the NEMO global 1/12° configuration, PSY4 includes data assimilation of satellite and multi-instrument in situ observations. In parallel to this monitoring system, a twin-free simulation (with no assimilation) has been performed for the period 2007-2015. In this study, monthly-averaged fields of both ocean state estimates are compared with observation products for the period 2007-2015, to examine the consistency of PSY4 fields with related observations for representing large-scale variability and to provide a baseline that is mainly focused on in situ comparisons for validation/qualification of on-going system developments. Observations play a major role in correctly positioning the main energetic structures, both in space and time. In addition, data assimilation appears to overcome the other deficiencies of models by reducing SST bias in upwelling regions and by increasing the thermocline gradient in the tropics. Generally, the amplitude of the total-resolved variability in both PSY4 estimates is consistent with observation data sets. Annual cycle and longer-term variability in temperature, salinity and sea surface height are significantly improved with data assimilation, but some progress is still needed to better represent the amplitude of changes of ocean heat and freshwater contents on long timescales. Finally, the PSY4 system’s ability to capture the large scale variability is further investigated by using as a case study the northward pathways of El Niño anomalies in the tropical North Pacific in 2014 and 2015 in order to illustrate how such systems can be used to answer relevant scientific questions. 
PY 2018
PD NOV
SO Journal Of Marine Systems
SN 0924-7963
PU Elsevier Science Bv
VL 187
UT 000445313300019
BP 260
EP 276
DI 10.1016/j.jmarsys.2018.06.015
ID 55956
ER

EF