Annual, Seasonal, and Interannual Variability of Air–Sea Heat Fluxes in the Indian Ocean

Abstract

This study investigated the accuracy and physical representation of air-sea surface heat flux estimates for the Indian Ocean on annual, seasonal, and interannual time scales. Six heat flux products were analyzed, including the newly developed latent and sensible heat fluxes from the Objectively Analyzed Air-Sea Heat Fluxes (OAFlux) project and net shortwave and longwave radiation results from the International Satellite Cloud Climatology Project (ISCCP), the heat flux analysis from the Southampton Oceanography Centre (SOC), the National Centers for Environmental Prediction reanalysis 1 (NCEP1) and reanalysis-2 (NCEP2) datasets, and the European Centre for Medium-Range Weather Forecasts operational (ECMWF-OP) and 40-yr Re-Analysis (ERA-40) products.This paper presents the analysis of the six products in depicting the mean, the seasonal cycle, and the interannual variability of the net heat flux into the ocean. Two time series of in situ flux measurements, one taken from a 1-yr Arabian Sea Experiment field program and the other from a 1-month Joint Air-Sea Monsoon Interaction Experiment (JASMINE) field program in the Bay of Bengal were used to evaluate the statistical properties of the flux products over the measurement periods. The consistency between the six products on seasonal and interannual time scales was investigated using a standard deviation analysis and a physically based correlation analysis.The study has three findings. First of all, large differences exist in the mean value of the six heat flux products. Part of the differences may be attributable to the bias in the numerical weather prediction (NWP) models that underestimates the net heat flux into the Indian Ocean. Along the JASMINE ship tracks, the four NWP modeled mean fluxes all have a sign opposite to the observations, with NCEP1 being underestimated by 53 W m Ϫ2 (the least biased) and ECMWF-OP by 108 W m Ϫ2 (the most biased). At the Arabian Sea buoy site, the NWP mean fluxes also have an underestimation bias, with the smallest bias of 26 W m Ϫ2 (ERA-40) and the largest bias of 69 W m Ϫ2 (NCEP1). On the other hand, the OAFluxϩISCCP has the best comparison at both measurement sites. Second, the bias effect changes with the time scale. Despite the fact that the mean is biased significantly, there is no major bias in the seasonal cycle of all the products except for ECMWF-OP. The latter does not have a fixed mean due to the frequent updates of the model platform. Finally, among the four products (OAFluxϩISCCP, ERA-40, NCEP1, and NCEP2) that can be used for studying interannual variability, OAFluxϩISCCP and ERA-40 Q net have good consistency as judged from both statistical and physical measures. NCEP1 shows broad agreement with the two products, with varying details. By comparison, NCEP2 is the least representative of the Q net variabilities over the basin scale.

RAMA: The Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction*

“…The SST trend has been linked to drought in the African Sahel (Giannini et al 2003) and in the northern hemisphere midlatitudes (Hoerling and Kumar 2003). the early 1980s over the Indian Ocean (Yu and Weller 2007), suggesting that changes in surface fluxes are a response to, rather than the cause of, this SST trend. It is likely, therefore, that ocean dynamics play a role in producing the observed SST trend, although the precise mechanisms remain uncertain (Alory et al 2007).…”

“…However, surface heat and moisture flux climatologies are poorly known in the Indian Ocean (Yu and McCreary 2004;Yaremchuk 2006;Yu et al 2007) and in several regions, annual means in net surface heat flux from presently available climatologies typically differ by 30-40 W m~2 (Fig. 5).…”

“…For example, surface heat fluxes were calculated from data at three of the RAMA mooring sites for comparison with numerical weather prediction (NWP) model flux products, the International Satellite Cloud Climatology Project (ISCCP) radiation product (Zhang et al 2004) and an objectively analyzed (OA) turbulent heat flux product (OA flux; Yu and Weller 2007). Results (Fig.…”

Contrasting Development and Decay Processes of Indian Ocean Dipoles in the 2000s

“…Because the buoy meteorological observations had non-negligible missing values, we used satellite-based and reanalysis airsea flux datasets after validations. We used turbulent heat fluxes obtained from the Objectively Analyzed air-sea heat Fluxes (OAFlux; Yu and Weller 2007). Longwave radiation was taken from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis products (Kalnay et al 1996).…”

Teleconnection between Australian winter temperature and Indian summer monsoon rainfall

“…Monthly mean evaporation rate, specific humidity at 2m and SST over the ocean at 1 • × 1 • resolution are taken from the Objectively Analyzed Air-Sea Fluxes dataset (OAFlux) of Woods Hole Oceanographic Institution (Yu et al, 2007, download source listed under OAFlux (2012 in the Bibliography). Since only wind magnitudes but not wind vectorial components are available in OAFlux, NNRP 10 m-wind is used instead.…”