摘要
Changes of the net ocean surface heat flux（Q_（net）） into the tropical Indian Ocean（TIO） may be an indicator of the climate changes in the Asia and Indian–Pacific Ocean regions with the steadily warming trend in the TIO since the 1950 s. Using two observational ocean surface flux products,this letter evaluates the historical simulations of Q_（net） over the TIO during 1984–2005 in two versions of FGOALS, from CMIP5. The results show that both models present a basin-wide underestimation of net surface heat flux, possibly resulting from the positive latent heat flux biases extending over almost the entire TIO basin. Both models share an Indian Ocean dipole-like bias in the net surface heat flux, consistent with precipitation, SST, and subsurface ocean temperature biases, which can be traced to errors in the South Asian summer monsoon. Area-averaged annual time series analyses of the surface heat budget imply that the FGOALS-s2 bias lies more in radiative imbalance, illustrating the need to improve cloud simulation; while the FGOALS-g2 bias presents ocean surface turbulence flux as the key process, requiring improvement in the simulation of oceanic processes. Neither FGOALS-g2 nor FGOALS-s2 can capture the decreasing tendency of Q_（net） well. All observed and simulated datasets imply surface latent heat flux as the primary contributing component, indicating the simulation biases of models may derive mainly from the biases in simulating latent heat flux. A small latent heat flux increase in models can be considered to be slowed by relaxed wind, increased stability, and surface relative humidity.
热带印度洋海表热收支平衡极大地影响着周边的气候变化,对此的精确模拟是提高海气耦合模式模拟区域气候能力的重要一方面。本文使用不同数据来源的格点资料集OAFlux和NOCS-V2的海表通量产品,评估了FGOALS-g2和FGOALS-s2两个模式对热带印度洋海表热收支平衡的模拟结果。发现模拟净热通量存在海盆尺度的低估,来源于潜热通量的高估。相对而言FGOALS-s2模拟的辐射通量误差更大。模式无法模拟出净热通量的减少趋势,主因在于对潜热通量趋势模拟能力不足。
基金
supported by the National Basic Research Program of China[grant number 2012CB417403]
State Key Laboratory of Tropical Oceanography,South China Institute of Oceanology,Chinese Academy of Sciences[project number LTO1502]
