The performance of 20 models participating in the atmospheric model intercomparison project (AMIP) is evaluated concerning surface latent (Q_LH) and sensible (Q_SH) heat flux over the tropical oceans (30°S–30°N). Biases were calculated by comparing model fluxes to observations from moored buoys and the objectively analyzed air–sea fluxes (OAFlux) database. All 20 AMIP models overestimate Q_LH with an ensemble mean bias of 20 W m⁻², and 18 of the 20 models overestimate Q_SH with an ensemble mean bias of 5 W m⁻² when compared to OAFlux, implying a systematic positive bias over the tropical oceans. A comparison with buoy observations also showed similar biases. To obtain insights into the causes behind model bias, we quantified the contribution from near-surface winds, specific humidity, and temperatures. It is found that near-surface humidity contributes more to the bias in Q_LH than wind speed, while air temperature contributes more to bias in Q_SH than wind speed. On the other hand, the root mean squared error (RMSE) in Q_LH has contributions from both near-surface humidity and wind. The contribution from humidity to the mean bias in Q_LH is 13 W m⁻², with RMSE of 15 W m⁻², suggesting a systematic overestimation of sea-air humidity difference in models. The model ensemble, in general, simulates Q_LH and Q_SH better than individual models. Models with higher horizontal and vertical resolutions perform better than coarse resolution models.

对20个参与大气模型比对项目（AMIP）的模型的性能进行了评估，涉及热带海洋（30°S–30°N）上的表面潜热（Q _LH）和显热（Q _SH）。通过将模型通量与系泊浮标的观测值和客观分析的海气通量（OAFlux）数据库进行比较，可以计算偏差。所有20个AMIP模型都以集合平均偏差为20 W m ^-2高估了Q _LH，而20个模型中的18个模型以集合平均偏差为5 W m ^-2高估了Q _SH与OAFlux相比，意味着对热带海洋有系统的积极偏见。与浮标观测值的比较也显示出类似的偏差。为了深入了解模型偏差背后的原因，我们量化了近地表风，比湿和温度的影响。发现近地表湿度比风速对Q _LH的影响更大，而气温比风速对Q _SHH的影响更大。另一方面，Q _LH中的均方根误差（RMSE）来自近地表湿度和风。湿度对Q _LH中平均偏差的贡献为13 W m ^-2，RMSE为15 W m ^-2，这表明系统地高估了模型中的海洋空气湿度差。通常，模型集成比单个模型更好地模拟Q _LH和Q _SH。水平和垂直分辨率较高的模型比粗分辨率模型的性能更好。