东亚夏季风变化机理的模拟和未来变化的预估:成绩和问题、机遇和挑战

东亚夏季风对于我国东部气候具有重要影响,呈现出多种时间尺度的变化特征。在理解东亚夏季风过去和当前的变化机理、预测和预估其未来变化等方面,气候系统模式发挥着不可替代的作用。但是当前的气候模式在东亚夏季风的模拟上尚存在诸多不足,这使得其模拟结果存在不确定性,既制约了我们对过去和当前季风变化机理的准确理解,又降低了未来预测预估结果的可信度。关于造成季风模拟偏差的原因,既涉及模式本身的性能问题,又与模拟系统的构建、强迫资料的误差、乃至我们当前对季风变化规律自身的认知水平有关。本文以时间尺度为序,从气候态、日变化、年际变率、年代际变率、长期气候变化和未来预估等季风学界关注的热点问题角度,本着总结成绩、归纳问题、寻找机遇、面对挑战的目的,从七个方面系统总结了当前气候模式的水平,归纳了其主要偏差特征,讨论了影响模式性能的可能因素。内容涉及模式分辨率和地形效应、对流和云辐射效应的作用、与季风相关的热带海气相互作用关键过程、内部变率（太平洋年代际振荡）、自然变率（太阳辐照度变化和火山气溶胶强迫）和人为辐射强迫（人为温室气体和气溶胶排放）对季风变化的不同影响、热力和动力过程及气候敏感度对季风环流（副高）和降水预估不确定性的影响等。最后从优化参数、实现场地观测和过程模拟的协同、发展高分辨和对流解析模式等角度,讨论了提升东亚夏季风模拟能力的技术途径。

A Review of East Asian Summer Monsoon Simulation and Projection: Achievements and Problems, Opportunities and Challenges

The East Asian Summer Monsoon (EASM), which has profound societal and economic impacts in China, has exhibited multiple time-scale variabilities. Climate models play an irreplaceable role in understanding the past changes and predicting/projecting the future changes in the EASM. However, current state of the climate models still shows evident biases in the simulation of EASM. This kind of model deficiency has limited our understanding of the mechanisms responsible for the EASM variability based on numerical model experiments and reduced the reliability of long-term climate change projection. This paper provides a synthesis review on our progresses in climate modeling study with a focus on the EASM. The achievements made in the last 5 years are summarized along with an extension to earlier studies in case of needing. The observational metrics used to gauge model performances include the climatology, diurnal cycle, interannual variability, interdecadal variability, and long-term climate change and climate projection. The following processes that are crucial to a successful modeling of monsoon mean state, variability and changes are reviewed, which include the effects of model resolution and model topography, climate effects of moist convection and cloud-radiation, monsoon-related tropical air-sea interactions, impacts of internal variability modes such as the Pacific Decadal Oscillation on the inter-decadal variability of EASM, the role of natural external forcing including solar radiation and volcanic aerosols, the contribution of anthropogenic forcing (including emissions of greenhouse gases and aerosols). In addition, the thermodynamic and dynamic processes associated with climate sensitivity that are responsible for the uncertainties in climate change projections are also discussed. Both the strengths and weakness of the current state of the art climate models are documented. Instead of simply summarizing the models'' performance, the review is done along with a discussion on our understanding of the strengths and weaknesses from the perspective of dynamical/physical processes. In the final part, we provide a list of potential ways to improve the models'' performance, which includes the optimization of model parameters, improvement of model physics by coordinating model studies and field campaigns, and development of high-resolution and convection-permitting models.