Air-Sea Heat Flux Variability in the Southeast Indian Ocean and Its Relation With Ningaloo Nino

Previous studies suggest that both air-sea heat flux anomalies and heat advection caused by an anomalous Leeuwin Current play an important role in modulating the sea surface temperature (SST) variability associated with the Ningaloo Nino. However, the estimates of surface heat fluxes vary substantially with the datasets, and the uncertainties largely depend on the time scale and locations. This study investigates air-sea flux variability associated with the Ningaloo Nino using multiple datasets of surface fluxes. The climatological net surface heat flux off the west coast of Australia from six major air-sea flux products shows large uncertainties, which exceeds 80 W m(-2), especially in the austral summer when the Ningaloo Nino develops. These uncertainties stem mainly from those in shortwave radiation and latent heat flux. The use of different bulk flux algorithms and uncertainties of bulk atmospheric variables (wind speed and air specific humidity) are mostly responsible for the difference in latent heat flux climatology between the datasets. The composite evolution of air-sea heat fluxes over the life cycle of Ningaloo Nino indicates that the anomalous latent heat flux is dominant for the net surface heat flux variations, and that the uncertainties in latent heat flux anomaly largely depend on the phase of the Ningaloo Nino. During the recovery period of Ningaloo Nino, large negative latent heat flux anomalies (cooling the ocean) are evident in all datasets and thus significantly contribute to the SST cooling. Because the recovery of winds occurs earlier than SST, high SST and strong winds favor large evaporative cooling during the recovery phase. In contrast, the role of latent heat flux during the developing phase is not clear, because the sign of the anomalies depends on the datasets in this period. The use of high-resolution SST data, which can adequately represent SST variations produced by the anomalous Leeuwin Current, could largely reduce the errors in latent heat flux anomalies during the onset and peak phases.