陆地表面温度的远程影响及其对海洋表面温度模式的启示
Remote Influences of Land Surface Temperature and their Implications for Sea Surface Temperature Patterns
AI总结：
研究通过耦合海洋-陆地-大气模型，探讨陆地表面温度变化对热带太平洋均态的影响，发现南美地区升温强化了热带太平洋经向温差，产生类似拉尼娜状态，而其他地区如马六甲海峡或青藏高原则无显著影响。
摘要：
海洋表面温度（SST）的空间模式在塑造气候系统中起核心作用，但陆地表面温度（LST）的影响仍不明确。利用先进的耦合海洋-陆地-大气模型，研究通过LST nudging和理想化的时间依赖性阶梯升温模拟，检验模型对区域LST扰动的响应。发现南美地区LST升温强化了热带太平洋经向SST梯度，产生更接近拉尼娜的均态。增强的LST增加了对流加热的经向对比，激发了站态罗斯贝波响应，强化了东太平洋沿岸风和海岸上升流。这提供了区域陆地升温改变赤道太平洋均态的动力学路径。类似响应在北美和中非地区也出现，伴随太平洋或大西洋的冷却。相比之下，马六甲海峡或青藏高原的升温未引起显著SST模式变化。历史模拟中，向观测LST nudging显示出热带东南太平洋的冷却，暗示LST不确定性可能在历史时期导致模型模拟的SST偏差。
英文摘要：
The spatial pattern of sea surface temperature (SST) plays a central role in shaping the climate system, yet the influence of land surface temperature (LST) on large-scale SST patterns remains understudied. Using a state-of-the-art coupled climate model, we investigate the climate response to regional abrupt LST warming and time-dependent ramped-warming. We find that regional LST warming can substantially alter the mean-state SST pattern, with the response depending strongly on the location of land warming. In particular, warming over South America strengthens the zonal SST gradient across the tropical Pacific, producing a more La Niña-like mean state. Enhanced land warming increases the zonal contrast in diabatic heating, which excites stationary Rossby wave responses that strengthen alongshore winds and coastal upwelling in the eastern tropical Pacific, providing a dynamical pathway linking regional land warming to changes in the equatorial Pacific mean state. Similar remote SST responses occur for warming over North America, which is accompanied by cooling in the North Pacific, and over Central Africa, which is accompanied by cooling in the tropical Atlantic. In contrast, warming over the Maritime Continent and Tibetan Plateau produces little systematic change in large-scale SST patterns. These results demonstrate that regional LST changes can exert a substantial and geographically dependent influence on remote ocean temperatures. They further suggest that biases in both the mean state and warming trends of LST may contribute to biases in simulated SST patterns in historical simulations, highlighting the importance of accurately representing LST in climate models.
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