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1. Introduction Oceanic salinity plays an important role in the climate system due to its significant influence on oceanic stratification and barrier layers ( Sprintall and Tomczak 1992 ; Thompson et al. 2006 ; Balaguru et al. 2016 ) and ocean circulation ( Gordon et al. 2003 ; Feng et al. 2015 ; Hu and Sprintall 2016 , 2017a , b ), and has a close link to the global hydrological cycle ( Durack and Wijffels 2010 ; Durack et al. 2012 ). Investigation of ocean salinity variability and
1. Introduction Oceanic salinity plays an important role in the climate system due to its significant influence on oceanic stratification and barrier layers ( Sprintall and Tomczak 1992 ; Thompson et al. 2006 ; Balaguru et al. 2016 ) and ocean circulation ( Gordon et al. 2003 ; Feng et al. 2015 ; Hu and Sprintall 2016 , 2017a , b ), and has a close link to the global hydrological cycle ( Durack and Wijffels 2010 ; Durack et al. 2012 ). Investigation of ocean salinity variability and
Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis winds, surface heat fluxes ( Kalnay et al. 1996 ), and relaxation to the climatological salinity of the World Ocean Atlas 1998 ( Boyer et al. 1998a , b , c ). In the existing publications, the OFES model simulation has been widely used and validated with observational data and is shown to simulate the western tropical Pacific Ocean circulation well (e.g., Zhang et al. 2014 , 2020 ; Chen et al. 2016 ; Ren et al. 2018 ). The
Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis winds, surface heat fluxes ( Kalnay et al. 1996 ), and relaxation to the climatological salinity of the World Ocean Atlas 1998 ( Boyer et al. 1998a , b , c ). In the existing publications, the OFES model simulation has been widely used and validated with observational data and is shown to simulate the western tropical Pacific Ocean circulation well (e.g., Zhang et al. 2014 , 2020 ; Chen et al. 2016 ; Ren et al. 2018 ). The
measurements. A miniature version of the Bailong buoy system from the FIO ( Cole et al. 2011 ) was used in the program (SB1), which has a surface meteorological package to measure the surface air temperature, humidity, pressure, winds, and shortwave and longwave radiation at a 10-min interval, and a subsurface (within the upper 500 m) oceanographic package to measure upper-ocean temperature, salinity, pressure, oxygen, and current speed and direction at a 30-min interval. The details of the instrumentation
measurements. A miniature version of the Bailong buoy system from the FIO ( Cole et al. 2011 ) was used in the program (SB1), which has a surface meteorological package to measure the surface air temperature, humidity, pressure, winds, and shortwave and longwave radiation at a 10-min interval, and a subsurface (within the upper 500 m) oceanographic package to measure upper-ocean temperature, salinity, pressure, oxygen, and current speed and direction at a 30-min interval. The details of the instrumentation
Oceanography, include salinity and temperature profiles on a 1° longitude × 1°latitude horizontal grid and in 58 vertical levels from 2.5 to 1975 m ( Roemmich and Gilson 2009 ). Absolute geostrophic currents (AGCs) were calculated using the P-vector method ( Chu 1995 ) based on the gridded Argo profiles. The P-vector method assumes conservation of potential density and potential vorticity and is equivalent to the β -spiral method under the Boussinesq and geostrophic approximation ( Yuan et al. 2014 ). The
Oceanography, include salinity and temperature profiles on a 1° longitude × 1°latitude horizontal grid and in 58 vertical levels from 2.5 to 1975 m ( Roemmich and Gilson 2009 ). Absolute geostrophic currents (AGCs) were calculated using the P-vector method ( Chu 1995 ) based on the gridded Argo profiles. The P-vector method assumes conservation of potential density and potential vorticity and is equivalent to the β -spiral method under the Boussinesq and geostrophic approximation ( Yuan et al. 2014 ). The
-GCM variations” ( DeMott et al. 2015 ). Thus, similar studies as ours with diverse models should be encouraged, which would not only assess the model dependency of our conclusions, but, more important, explore the influence of other factors on estimates of MJO predictability. Acknowledgments We thank NOAA’s Climate Program Office for their support through the Modeling, Analysis, Predictions, and Projections (MAPP). Author Zhu is partially supported by the NASA Ocean Salinity Science Team Grant NNX17AK09G. We
-GCM variations” ( DeMott et al. 2015 ). Thus, similar studies as ours with diverse models should be encouraged, which would not only assess the model dependency of our conclusions, but, more important, explore the influence of other factors on estimates of MJO predictability. Acknowledgments We thank NOAA’s Climate Program Office for their support through the Modeling, Analysis, Predictions, and Projections (MAPP). Author Zhu is partially supported by the NASA Ocean Salinity Science Team Grant NNX17AK09G. We
this analysis. Acknowledgments We thank NOAA’s Climate Program Office for their support. Author J. Zhu is partially supported by the NASA Ocean Salinity Science Team Grant NNX17AK09G. REFERENCES Ge , X. , W. Wang , A. Kumar , and Y. Zhang , 2017 : Importance of the vertical resolution in simulating SST diurnal and intraseasonal variability in an oceanic general circulation model . J. Climate , 30 , 3963 – 3978 , https://doi.org/10.1175/JCLI-D-16-0689.1 . 10.1175/JCLI-D-16
this analysis. Acknowledgments We thank NOAA’s Climate Program Office for their support. Author J. Zhu is partially supported by the NASA Ocean Salinity Science Team Grant NNX17AK09G. REFERENCES Ge , X. , W. Wang , A. Kumar , and Y. Zhang , 2017 : Importance of the vertical resolution in simulating SST diurnal and intraseasonal variability in an oceanic general circulation model . J. Climate , 30 , 3963 – 3978 , https://doi.org/10.1175/JCLI-D-16-0689.1 . 10.1175/JCLI-D-16
