Analysis and modeling of the seasonal South China Sea temperature cycle using remote sensing |
| |
| Authors: | Daniel J Twigt Erik D De Goede Ernst J O Schrama Herman Gerritsen |
| |
| Institution: | (1) WL|Delft Hydraulics, P.O.Box 177, 2600 MH Delft, The Netherlands;(2) Delft University of Technology, Kluyverweg 1, 2629 HS Delft, The Netherlands |
| |
| Abstract: | The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale.
It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated
tidal mixing and exchange. This is motivated by the possibility to significantly increase the model’s computational efficiency
when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate
transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal
time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature
cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed
using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly
mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological
forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature
(SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed
against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good
agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply
a SST nudging method at the free water surface. This considerably improves the model’s vertical temperature representation
in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal
temperature cycle for the deep SCS basin can be represented to a good degree. For shallow regions, the absence of tidal mixing
and exchange has a clear impact on the model’s temperature representation. This effect on the large-scale temperature cycle
can be compensated to a good degree by SST nudging for diagnostic applications. |
| |
| Keywords: | South China Sea Baroclinic temperature model Reduced depth modeling Altimeter data Radiometer data Temperature nudging |
| 本文献已被 SpringerLink 等数据库收录！ |
|
