青藏高原感热气泵影响亚洲夏季风的机制

本文回顾了二十年来关于青藏高原感热驱动气泵(TP-SHAP)及其影响亚洲夏季风的研究进展,并从能量(θ)、位涡—加热(PV–Q)、和角动量守恒(AMC)的不同角度阐述其影响机制。指出高原斜坡上的表面感热加热改变了移向高原的大气质块的能量从而出现垂直抽吸的重要性。强调了高原加热产生的位涡强迫在近地层制造了强度大范围广的、环绕高原的气旋式环流,把丰沛的水汽从海洋输运到大陆,为季风对流降水提供充足的水汽条件。证明高原加热还通过改变其上空的温、压场的结构从而制造出高原上空近对流层顶的绝对涡度和位涡的最小值,在角动量平衡约束下,在亚洲季风区激发出与Hadley环流反向的季风经圈环流,从而为季风发生发展提供了大范围上升运动的背景。文中还对近年来有关青藏高原影响亚洲夏季风机制的讨论进行概述,并展望了未来的研究方向。     

LASG/IAP 大气环流谱模式对陆面过程的敏感性试验

将中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室最近发展的高分辨率全球大气环流谱模式SAMIL-R42L26, 分别与两个陆面模式--NCAR通用陆面模式CLM和简化的简单生物圈模式SSiB进行耦合.在比较了两个陆面过程模式, 指出CLM改进方面的基础上, 通过分析两个陆气耦合模式所模拟的陆气通量交换结果, 指出新版本的陆气耦合模式(SAMIL-R42L26与CLM耦合)对表面感热、温度、降水率、潜热通量和海平面气压场的模拟能力大大提高, 尤其对于夏季表面感热通量场, 使亚洲北部和东南部、格陵兰岛以及北美洲大部分地区的数值从100 W/m2 降低到接近60 W/m2, 与NCEP再分析资料一致.新版本的陆气耦合模式模拟陆地表面能量收支趋于平衡, 为下一步发展海-陆-气-冰耦合气候系统模式提供保障.采用CLM陆面模式, SAMIL-R42L26能较好地模拟亚洲季风区地表感热和潜热的季节演变趋势, 而采用SSiB陆面模式的结果, 则存在较大误差.文中的结果表明, 不同的陆面模式所模拟的大气下垫面(包括洋面)通量发生的变化, 通过陆气耦合过程产生的影响不仅仅是局地性的, 而且是全球范围的.     

基于LASG/IAP大气环流谱模式的气候系统模式

文章扼要介绍了基于LASG/IAP大气环流谱模式(SAMIL)的气候系统模式的新版本FGOALS-s的发展和结构。出于发展一个在东亚季风模拟方面有一定优势的气候系统模式之目的,FGOALS-s的大气模式分量SAMIL采用了较高的水平分辨率R42,这相当于2.8125°(经度)×1.66°(纬度),高于三角截断T42的分辨率。对FGOALS-s在模拟大气、陆面、海洋和海冰的气候平均态,以及主要的年际变率信号方面的能力进行了检验。分析表明,FGOALS-s成功地控制了气候漂移趋势,能够较为真实地模拟大气、海洋和陆面的气候平均态,特别是受益于大气模式的较高分辨率,由中国西南向东北延伸的夏季风雨带的分布,在模式中得到较为真实的再现,表明该模式在东亚夏季风的模拟上具有较强能力。耦合模式能够成功再现El Ni~no事件的非规则周期变化,但是其年际变化的振幅较之观测要弱。赤道中西太平洋年际变率的强度较之赤道中东太平洋要强。在中高纬度,模式模拟的北大西洋涛动模态,在空间分布上与观测接近。FGOALS-s模式存在的主要问题,是模拟的热带海温偏冷、而中纬度海温则偏暖,原因是模式模拟的云量分布存在偏差,它直接影响到海表的净热通量收支。模式模拟的北大西洋高纬度地区的海温明显偏冷,令该地区的年平均海冰分布的范围明显偏大;然而受南极周边海温偏高影响,南极洲周围的海冰范围则偏少。FGOALS-s的未来工作重点,宜放在大气模式的云过程、海洋模式的经向能量输送过程、以及海洋与大气的淡水通量耦合方案的改进方面。     

The Flexible Global Ocean-Atmosphere-Land system model, Spectral Version 2: FGOALS-s2

The Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2) was used to simulate realistic climates and to study anthropogenic influences on climate change. Specifically, the FGOALS-s2 was integrated with Coupled Model Intercomparison Project Phase 5 (CMIP5) to conduct coordinated experiments that will provide valuable scientific information to climate research communities. The performances of FGOALS-s2 were assessed in simulating major climate phenomena, and documented both the strengths and weaknesses of the model. The results indicate that FGOALS-s2 successfully overcomes climate drift, and realistically models global and regional climate characteristics, including SST, precipitation, and atmospheric circulation. In particular, the model accurately captures annual and semi-annual SST cycles in the equatorial Pacific Ocean, and the main characteristic features of the Asian summer monsoon, which include a low-level southwestern jet and five monsoon rainfall centers. The simulated climate variability was further examined in terms of teleconnections, leading modes of global SST (namely, ENSO), Pacific Decadal Oscillations (PDO), and changes in 19th–20th century climate. The analysis demonstrates that FGOALS-s2 realistically simulates extra-tropical teleconnection patterns of large-scale climate, and irregular ENSO periods. The model gives fairly reasonable reconstructions of spatial patterns of PDO and global monsoon changes in the 20th century. However, because the indirect effects of aerosols are not included in the model, the simulated global temperature change during the period 1850–2005 is greater than the observed warming, by 0.6°C. Some other shortcomings of the model are also noted.     

Seasonal evolution of subtropical anticyclones in the climate system model FGOALS-s2

The simulation characteristics of the seasonal evolution of subtropical anticyclones in the Northern Hemisphere are documented for the Flexible Global Ocean-Atmosphere-Land Systemmodel, Spectral Version 2 (FGOALS-s2), developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, the Institute of Atmospheric Physics. An understanding of the seasonal evolution of the subtropical anticyclones is also addressed. Compared with the global analysis established by the European Centre for Medium-Range Forecasts, the ERA-40 global reanalysis data, the general features of subtropical anticyclones and their evolution are simulated well in both winter and summer, while in spring a pronounced bias in the generation of the South Asia Anticyclone(SAA) exists. Its main deviation in geopotential height from the reanalysis is consistent with the bias of temperature in the troposphere. It is found that condensation heating (CO) plays a dominant role in the seasonal development of the SAA and the subtropical anticyclone over the western Pacific (SAWP) in the middle troposphere. The CO biases in the model account for the biases in the establishment of the SAA in spring and the weaker strength of the SAA and the SAWP from spring to summer. CO is persistently overestimated in the central-east tropical Pacific from winter to summer, while it is underestimated over the area from the South China Sea to the western Pacific from spring to summer. Such biases generate an illusive anticyclonic gyre in the upper troposphere above the middle Pacific and delay the generation of the SAA over South Asia in April. In midsummer, the simulated SAA is located farther north than in the ERA-40 data owing to excessively strong surface sensible heating (SE) to the north of the Tibetan Plateau. Whereas, the two surface subtropical anticyclones in the eastern oceans during spring to summer are controlled mainly by the surface SE over the two continents in the Northern Hemisphere, which are simulated reasonably well, albeit with their centers shifted westwards owing to the weaker longwave radiation cooling in the simulation associated with much weaker local stratiform cloud. Further improvements in the related parameterization of physical processes are therefore identified.     

冬季北太平洋海表面热通量异常和海气相互作用的耦合模式模拟

基于中国科学院大气物理研究所大气科学与地球流体力学数值模拟国家重点实验室(LASG/IAP)开发的耦合气候系统模式FGOALS_s1.0控制试验的积分结果,分析了冬季北太平洋海表面湍流热通量(潜热和感热通量之和)异常及其对海表面温度(SST)异常的影响,并通过分析海温倾向方程,比较了各因子对SST变率的相对贡献.结果表...     

大气环流模式SAMIL模拟的夏季全球加热场和东亚夏季风

各国科学家一直致力于从理论和数值模拟上对季风系统进行全面地研究。本文根据“热力适应”理论, 从分析中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室的最新版本大气环流谱模式(SAMIL2.4.7) 对全球非绝热加热场的模拟性能出发, 分析并解释了SAMIL对东亚夏季风 (EASM) 子系统的模拟情况。通过与再分析资料Reanalysis-2 ( NCEP/DOE AMIP-II Reanalysis ) 对比分析发现, SAMIL能很好地模拟出夏半球副热带地区加热场的四叶型分布 (LOSECOD), 但模拟的各加热场在强度上存在一定的偏差, 主要表现在感热加热在大陆上普遍偏高, 而潜热加热在印度半岛两侧、西太平洋地区(尤其在南北纬10°) 偏高, 赤道带、中南半岛、中国南海等地区偏弱。而对EASM子系统的分析发现, SAMIL能很好地模拟南亚高压; 较好地模拟西太平洋副热带高压的主体, 但西太平洋 (30°N附近) 潜热偏强使得模拟的副高强度偏强、 西伸脊点过于偏西; 模式也能较好地抓住夏季西风急流的两个中心, 但中纬度潜热、 感热的模拟偏弱造成急流两中心风速均小于Reanalysis-2资料 10 m/s左右。进一步的讨论可知, 造成感热和潜热偏差的主要原因是模式中云参数化方案和积云对流参数化方案的不足, 改进模式中相关的物理参数化方案将是SAMIL后续发展的首要工作。     

2022年汛期气候趋势预测与展望

中国是自然灾害频发的国家,气象灾害造成的损失占自然灾害造成损失的70%。2020年夏季出现超长梅雨期,长江和淮河发生洪水;2021年夏季,华北雨季开始早,结束晚,期间发生了“21·7”河南地区特大暴雨事件。这些气象灾害都对人民生命财产造成严重损失。因此,有必要提前对气候异常进行预测,以提高国家的防灾减灾能力。2022年3月,中国科学院大气物理研究所开展汛期（6～8月）的全国汛期气候趋势预测会商会。通过综合大气所各个数值模式和统计模型的结果,在未来4～6个月全球短期气候仍处在La Ni?a事件恢复到ENSO正常状态的背景下,预计2022年汛期（6～8月）,东北东部和中部、华北大部分地区、黄河中下游、东南沿海、西北地区中部、西藏大部分地区、西南地区东部和云南大部分地区降水正常略偏多,其中环渤海湾地区降水偏多2～5成,可能发生局地洪涝灾害。全国其他大部分地区降水正常略偏少,其中长江下游地区和新疆北部降水偏少2～5成。预计今年登陆台风数正常略偏多。由于未来ENSO的趋势演变具有一定的不确定性以及夏季降水受到中高纬大气环流季节内变化的影响,因此,此次汛期预测结果具有一定的不确定性。我们将根据2022年春末、夏初大气环流和海洋等因子的实际演变趋势,做进一步补充订正预测。     

FGOALS高分辨率气候模式系统模式研制与应用综述

当今气候系统模式发展的重要趋势之一,是通过提高模式的空间分辨率,改进对气候系统中多尺度相互作用过程和极端事件的模拟能力。过去5年里,中国科学院大气物理研究所发展并完善了25 km分辨率大气环流分量模式FAMIL2.2、1/10°分辨率海洋环流分量模式LICOM3.0,并以此为基础建立了高分辨率气候系统模式FGOALS-f3-H。利用上述高分辨率模式,开展了大量的数值模拟试验和预报/预测研究,其中包括国际耦合模式比较计划第六阶段（CMIP6）的高分辨率模式比较子计划（HighResMIP）,建立了海洋环流预测系统（LFS）等。初步评估分析表明,相对于低分辨率模式,高分辨率模式对气候平均态和气候变率的模拟能力均有明显改进。其中高分辨率大气环流模式可以更好地模拟台风、极端降水事件,高分辨率海洋模式可以更好地模拟海洋中尺度涡旋和西边界流,而高分辨率耦合模式则可以更好重现中尺度海气相互作用过程、热带不稳定波动（TIW）等事件。     

Experimental Dynamical Forecast of an MJO Event Observed during TOGA-COARE Period

With a hybrid atmosphere-ocean coupled model we carried out an experimental forecast of a well documented Madden-Julian Oscillation (MJO) event that was observed during the period of Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE). The observed event, originated in the western Indian Ocean around 6 January 1993, moved eastward with a phase speed of about 6.2 m s-1 and reached the dateline around February 1. The hybrid coupled model reasonably forecasts the MJO initiation in the western Indian Ocean, but the predicted MJO event propagates too slow (~ 4.4 m s-1). Results from previous observational studies using unprecedented humidity profiles obtained by NASA Aqua/AIRS satellite suggested that two potential physical processes may be responsible for this model caveat. After improving the cumulus parameterization scheme based on the observations, the model is able to forecast the same event one month ahead. Further sensitivity experiment confirms that the speed-up of model MJO propagation is primarily due to the improved convective scheme. Further, air-sea coupling plays an important role in maintaining the intensity of the predicted MJO. The results here suggest that MJO prediction skill is sensitive to model cumulus parameterization and air-sea coupling. Citation: Fu, X., B. Wang, Q. Bao, et al., 2008: Experimental dynamical forecast of an MJO event observed during TOGA-COARE period, Atmos. Oceanic Sci. Lett., 1, 24-28