Estimates of Ocean–Atmosphere Heat Fluxes in the Tropical Atlantic from Different Bulk Parameterization Schemes Used Operationally in Brazil

The ocean–atmosphere turbulent heat exchange plays a critical role in the energy and moisture budgets of the Tropical Atlantic Ocean (TAO) and in weather and climate forecasts. However, its estimation strongly depends on the choice of bulk parameterization, as direct in situ measurements are sparse. This study evaluates sensible (Hs) and latent (Hl) heat fluxes derived from three bulk parameterization schemes used operationally in models at the Brazilian Center for Weather Forecast and Climate Studies (CPTEC) of the National Institute for Space Research (INPE), Brazil: the Brazilian Atmospheric Model (BAM), the Modular Ocean Model version 6 (MOM6), and the Weather Research and Forecasting (WRF) model. Using daily in situ observations from seven Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) buoys across the TAO during 1997–2023, we computed monthly mean fluxes and compared them against the Coupled Ocean–atmosphere Response Experiment (COARE) algorithm version 3.0b (COARE 3.0b) reference. COARE version 3.6 (COARE 3.6) and European Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis 5th generation (ERA5) data were included as additional benchmarks. All offline schemes were forced with identical buoy data, isolating differences in internal physical assumptions. Hl is approximately one order of magnitude larger than Hs across all sites, and inter-scheme differences are substantially larger for Hl (±50 W∙m⁻²) than for Hs (±5 W∙m⁻²). All schemes reproduce the seasonal cycle linked to the Intertropical Convergence Zone (ITCZ) migration and trade-wind variability, with correlations generally exceeding 0.8 (p < 0.001) for most buoys. However, systematic magnitude biases remain. The Coordinated Ocean Research Experiments (CORE) bulk formulation implemented in MOM6 (MOM6-CORE) shows high temporal correlation (often r ≈ 1.0) but a persistent negative bias for both Hs and Hl (e.g., B1 Hl bias = −24.0 W∙m⁻²), indicating weaker turbulent exchange relative to COARE 3.0b. BAM overestimates Hs (by 1–3 W∙m⁻²) and underestimates Hl at most northern and southern sites, while the parametrization of the Yonsei University (YSU) implemented in the WRF model (WRF-YSU) amplifies Hs variability intermittently, particularly at the equator (B4). As expected, COARE 3.6 remains the closest to the reference (differences < 1 W∙m⁻² for Hs and <7 W∙m⁻² for Hl; r ≈ 0.99). ERA5 captures temporal variability well (r ≈ 0.7–0.9) but systematically overestimates Hl (positive bias up to +47.6 W∙m⁻² at B7), implying stronger evaporative cooling. Buoy-specific regimes modulate skill. The choice of bulk formulation thus remains a first-order source of uncertainty in turbulent heat flux estimates over the TAO, with direct implications for mixed-layer heat budgets, SST evolution, and coupled ocean–atmosphere variability. MOM6-CORE provides the most consistent performance relative to the COARE reference and emerges as the most robust option for operational applications at CPTEC/INPE. The findings also provide guidance for improving the representation of ocean–atmosphere turbulent exchanges in MONAN (Model for Ocean-Land-Atmosphere Prediction), the new Brazilian Earth System Model under development for weather and climate prediction.