Impacts of precipitation in the upper ocean in the western Pacific warm pool during TOGA‐COARE

Abstract

An ocean mixed‐layer model with a modified Kraus‐Turner parameterization scheme is used to investigate the impacts of precipitation in the upper ocean in the western Pacific warm pool during Tropical Ocean Global Atmosphere‐Coupled Ocean Atmosphere Response Experiment (TOGA‐COARE). Heat and salt budgets calculated in the upper ocean indicate local balance between surface forcing and the ocean response. Thus the mixed‐layer model captures the dominant processes governing heat and salt variability. The model responses are analyzed and compared with the observed upper ocean in three distinctive layers determined by Monin‐Obukhov length scales. In the top layer (the top 5 m), about 90% of the surface buoyancy flux is absorbed, and strong diurnal and intraseasonal variations are excited. The second layer, 5–20 m, contains intraseasonal variability that is characterized by nearly neutral stratification during strong westerly wind events, strong thermal stratification during clear‐sky days, and strong saline stratification during heavy precipitation. The dominant effect of precipitation is to generate a stable stratification and to form a barrier layer. The third layer, 20–50 m, has intraseasonal variations due to mixing during westerly wind events. Heavy precipitation amplifies mixed‐layer temperature fluctuations by a cycle of strong surface cooling and entrainment warming through the following processes. Heavy precipitation causes a shallower mixed layer and a larger cooling rate. Surface temperature drops rapidly, and the upper ocean becomes thermally unstable. The salinity maintains a weak density stability, which causes strong entrainment warming. Surface freshwater flux is the key factor controlling saline structure when advection is excluded. However, experiments without the entrainment process show a significant bias toward a lower salinity, indicating that the entrainment process must be properly treated in the model to prevent a biased trend.