古气候数值模拟:进展评述

数值模拟是古气候研究的一个重要内容。过去30年来,古气候数值模拟研究在相当程度上深化了我们对古气候变化机制的理解。在轨道尺度上,数值模拟证明了冰后期气候系统变化主要是对地球轨道参数变化的响应,同时揭示了温室气体、植被、海洋、冰盖等反馈因子的重要性。针对短尺度气候变化,数值模拟揭示出大洋传送带对北大西洋淡水注入的敏感性。在构造尺度上,数值模拟揭示了气候系统对于高原抬升、海道开合、大陆漂移导致的古地理变化、大气CO2浓度变化和太阳常数变化等的响应,揭示了气候系统突变对驱动因子阈值的敏感性。目前,古气候模拟研究中还存在分辨率不高、模拟结果与记录不完全吻合、模拟的边界条件不清楚等诸多问题。今后古气候模拟研究的改进有赖于模式的改进和计算机运算速度的提高,也有赖于对变化机制的更深理解和对边界条件更精确的重建。

Numerical modeling in paleoclimate study: Progress and problems

Numerical modeling is one of the most powerful tools in resolving various issues associated with paleoclimate research. In the last decades, a wide spectrum of numerical modeling experiments has provided important insights into the mechanisms of driving climate changes on different timescales. On the orbital timescale, modeling experiments have demonstrated the first-order importance of variations in latitudinal and seasonal distribution of insolation in forcing glacial-interglacial climate changes and recognized most of the significant feedback processes involved in glacial cycles, such as greenhouse gases, vegetation cover, oceanographic conditions, and polar ice sheets. Modeling results also suggest that freshwater input into the northern North Atlantic could be a potential trigger for the abrupt, millennial-scale climate changes during the last glacial period, by revealing the high sensitivity of the thermohaline circulation in it. On the tectonic timescale, numerical experiments have been successful in assessing the sensitivity of the global climate system to paleogeographie changes resulting from tectonic-plate movement, plateau uplift, and opening or closure of oceanic gateway and of atmospheric CO2 concentration changes, likely associated mainly with biogeoehemical weathering of silicate rocks. These modeling results are also useful in recognizing some of the threshold values of the climate system in response to the tectonic-scale forcing. The endeavor of the paleoelimatie modeling community is currently focused mainly on developing finer-grid models, increasing the degree of consistency between modeling results, paleoelimate records, and reconstructing boundary conditions that are more reliable. Obviously, further progress of paleoelimatie modeling depends not only on developing more powerful numerical models and computers, but also on deepening the understanding of climate change processes as well.