The hydrodynamics of marginal seas exhibit internal variability unprovoked by external forcing. So far, the role of tides in reducing this “noise” has not been studied. We investigate the effect of tides on internal variability in the... more
The hydrodynamics of marginal seas exhibit internal variability unprovoked by external forcing. So far, the role of tides in reducing this “noise” has not been studied. We investigate the effect of tides on internal variability in the Bohai and Yellow Sea. To do so, we conducted three ensembles of numerical experiments using the Finite-Volume Coastal Ocean Model (FVCOM) with tidal forcing, with “half tidal” forcing, and without tidal forcing, while everything else was unchanged, and determined the intensity of the signal-to-noise ratio (hereinafter referred to as the S/N ratio), with the “signal” represented by the variance of the coherent variations of the different simulations subject to the same atmospheric variability and the noise represented by the intraensemble variance. The S/N ratio is determined for barotropic velocity, surface temperature, and surface salinity. The first result is that in all three ensembles, noise emerges but with different intensities. In the ensemble with tidal forcing, unprovoked variability emerges mostly at smaller scales. When the tides are weakened or turned off, the S/N ratios are reduced, more so in the Yellow Sea than in the Bohai. The increase in the S/N ratio is largest for large scales and for barotropic velocity. The reduction in tidal forcing results in an approximately 30% increase in S/N ratios in the Bohai at large scales. Thus, the absence of tidal forcing favours the emergence of unprovoked variability at large and medium scales but not at small scales, likely because of an increase in covariations related to the forced tidal variability.
La insularidad de Japón ha sido, a lo largo de su historia, el factor que más ha afectado al desarrollo tecnológico y cultural en el archipiélago. Si bien lo tradicional ha sido estudiar estas innovaciones desde un punto de vista... more
La insularidad de Japón ha sido, a lo largo de su historia, el factor que más ha afectado al desarrollo tecnológico y cultural en el archipiélago. Si bien lo tradicional ha sido estudiar estas innovaciones desde un punto de vista exclusivamente insular y sin integrarlas en la red de comunicaciones que conformaban islas y continente, con un estudio más profundo, se llega a la conclusión de que el archipiélago nipón no estaba en modo alguno aislado, sino que se integraba en una extensa red de comunicaciones centrada en el Mar Amarillo, con China como principal foco integrador y exportador de tecnologías y cultura. El estudio de estas relaciones es de capital importancia para comprender los cambios socio-económicos que tuvieron lugar durante la Protohistoria japonesa, y que terminarían conformando una serie de factores que favorecerían la deriva de una sociedad de jefaturas a un proto-estado imperial.
Reanalysis data sets have been widely used in regional climate dynamical downscaling studies. In this study, we test the use of various reanalysis data sets in constraining dynamical downscaling by assessing the skill of the... more
Reanalysis data sets have been widely used in regional climate dynamical downscaling studies. In this study, we test the use of various reanalysis data sets in constraining dynamical downscaling by assessing the skill of the reconstruction of the coastal winds of the Yellow Sea using the COSMO model in CLimate Mode (CCLM) with 7-km resolution. Four reanalysis forcing data sets are used as lateral boundary conditions and as internal large-scale constraints (spectral nudging): the NCEP/NCAR reanalysis data set (NCEP1) downscaled to an intermediate domain with 55-km resolution (CCLM_55km), the ERA-interim reanalysis data set (ERAint), the NCEP climate forecast system reanalysis data set (CFSR) and the Japanese 55-year reanalysis data set (JRA55).
Several statistical analysis methods are employed to assess the modeled winds through comparison with observed offshore wind data from 2006, and it is found that the downscaled simulations yield good-quality wind speed products. However, they all tend to overestimate observed low wind speeds and to underestimate observed high wind speeds. Furthermore, the quality of the modeled wind direction is strongly associated with the wind speed intensities, exhibiting much better reproduction of wind direction at strong wind speeds than at light wind speeds.
The downscaling simulations driven by ERAint, JRA55 and CFSR are consistent with each other in the reproduction of local wind speed and direction; the simulations driven by ERAint and JRA55 are slightly better for strong winds, and those driven by CFSR are better for light winds. All three simulations generate local wind estimates that are superior to those of the simulation driven by CCLM_55km. This superiority reflects the better quality of the CFSR, ERAint and JRA55 reanalyses with regard to assimilated local observations compared with the CCLM_55km hindcast, which exploits only upper-air large-scale NCEP1 wind fields.
