古气候模拟

古气候模式与现代气候模式控制因子不完全相同,有的因子在现代气候模拟中可以不考虑,但是在古气候模拟中则是必不可少的,例如轨道参数、大气中温室气体的浓度、大陆冰盖、大洋热盐环流等。而且,随着模拟的时间尺度不同,这些因子的作用也不同。评价古气候模拟,可以从3处着眼:气候变化的方向、幅度和速度。但是,长期以来古气候模拟仅仅涉及到前两个问题,也就是研究气候对外强迫的平衡响应。集其大成者是古气候模式比较计划(Paleaoclimate Modelling Intercomparison Project,     

与当前全球增暖有关的古气候学问题

根据最新研究成果，对从古气候学角度展望未来全球气候变化问题的可能性和方法进行了讨论和总结。过去温室气体含量、温度、降水、海平面和突然气候变化等古资料记录及其分析加深了我们对于气候系统物理过程的理解，古气候类比方法以及古资料在气候模式校准中的应用也显示了古气候学对于未来气候预测的潜在意义。     

古气候学——过去是未来的钥匙

科学家们用他们建立的理论来诠释古气候数据记录、理解现代气候,并预测未来几年到几十年的气候变化。为了检验气候理论,来自NASA戈达德空间科学研究所（GISS）和其他地方的科学家正在建立强有力的数学模型,用来模拟地球和大气条件的变化是如何影响气候的。     

第四次国际古气候模拟比较计划（PMIP4）概况与评述

古气候模拟比较计划（PMIP）是古气候数值模拟领域一项重大的国际合作研究计划,其主旨是为古气候模拟和模拟结果评估提供一个协调机制,理解过去气候变化的物理机制和气候反馈的重要作用,为未来气候预估提供科学依据。同时,通过对比分析验证模式的模拟性能,探索其不确定性,促进耦合气候系统模式的发展。PMIP目前进行到第四阶段（PMIP4)。PMIP4进一步加强了与第六次国际耦合模式比较计划（CMIP6）的协作,选取了5组共同关注的PMIP4-CMIP6古气候模拟试验（中全新世、末次盛冰期、过去千年、末次间冰期和上新世暖期),考察气候系统对不同气候背景的综合响应。除此以外,PMIP4还设计了众多敏感性试验研究不同外强迫因子的影响。PMIP4模拟试验不仅为古气候研究提供大量的模拟数据,还将服务于CMIP6及其他众多模式比较计划。     

CMIP6地球工程模式比较计划（GeoMIP）概况与评述

太阳辐射管理地球工程是应对气候变化的备用措施。地球工程模式比较计划（GeoMIP）是第六次国际耦合模式比较计划（CMIP6）的重要组成部分。GeoMIP设计了一系列理想化地球工程试验,包括直接减少太阳辐射强度、向平流层注入硫酸盐气溶胶、向海表上空云层注入气溶胶凝结核、增加海水反照率等。在GeoMIP的统一模拟框架下开展地球工程模拟试验,进一步揭示了不同地球工程措施对全球气候的影响和作用机理,从而帮助我们更好地认知气候系统对地球工程的响应过程。更多的中国气候模式参加GeoMIP将提升我国在地球工程研究和国际气候谈判中的国际影响力和话语权。     

一个以全露点温度为湿度变量的低谱湿模式

(一)1.研究古气候和气候变迁问题的一个有力的途径是实施数值试验。目前,在数值模拟试验中,广泛地使用了大气环流模式(GCM)。对气候平均场和短期气候变化的模拟取得了引人注目的结果。这些显示了 GCM 广泛应用的前景。2.无论是谱展开,还是差分方法,基本方程组都被转化为一个强迫耗散的自治的或非自治的非线性系统。古气候和气候变迁的问题,是气候学的课题。当我们用数值模拟的途径去     

我国的古气候研究

古气候学这一多学科综合性研究领域,近十余年来获得了长足进展,这是因为许多原因使得古气候研究日益受到重视,一些新技术、新方法的应用,也促进了这一发展。古气候研究的主要内容是:调查古气候变化的证据,还原或重建古气候,给出气候要素序列和气候变化模型;探讨气候变化机制和原因。我国的研究偏重在前面两项。古气候包括史前气候(又称地质时期气候)和历史气候两部份,二者的时间界限并无定论。我国大致以仰韶文化期(公元前3,000年)作为历史气候的开端。一、回顾我国的古气候研究可追溯到本世纪二十年代,     

古气候的启示

回顾了近20～30年古气候的研究进展,包括下列问题:雪球和热力极大期、冰期-间冰期旋回、古季风、D/O循环和H事件、全新世季风、全新世气候突变、气候变化与古文明、近2000年的气候。研究表明,第四纪前的气候变化中CO_2起着重要的作用,但是在冰期-间冰期旋回中CO_2变化落后于温度变化。这说明虽然影响机制不同,但是温室气体和气候间有着密切的相互作用这一点则是可以肯定的。地球目前处于间冰期,面临着冰期来临的威胁。人类活动造成的气候变暖有可能推迟下一次冰期的到来。21世纪全球变暖仍将继续,人们可能做的、也是必须要做的,是尽可能地降低变暖的速率,以及可能达到的变暖峰值。     

国外有关近两千年气候变化的研究进展

该文综述了20世纪90年代以来，国外在利用历史文献档案、冰芯、树木年轮研究最近2000年以来气候变化的主要进展。分地域陈述了各位学者提取古气候信息的方法、重建的各种古气候代用资料序列以及关于特征气候时期和年－百年尺度气候变化方面的新认识。     

气溶胶对中国天气、气候和环境影响综述

空气污染、天气和气候与大众生活息息相关,全球变化与可持续发展更是全人类面临的共同挑战。空气污染与气候变化对发展中国家带来的挑战更为显著。中国作为人口最多、发展飞速的国家,面临这两方面的挑战尤为严峻。因此,深入了解空气污染与气候变化的成因和发展机制,摸清两者相互关系对提高人们的生活质量和科学发展方针政策的制定具有指导意义。随着全球变化研究的深入,气溶胶与温室气体作为影响地球气候的两个最重要的人类排放物,在气候变化科学中起着至关重要的作用,气溶胶研究也成为地球科学发展最快的一个分支学科。中国天气、气候的变化特征,如高温增多、寒潮变少、风速减小、大气变稳、小雨减少、大雨增多、雷暴增强、季风减弱等,与空气污染都存在不同程度的联系。本文主要综述气溶胶对我国天气、气候的影响以及与气象因素相关的空气污染问题,侧重于气溶胶与极端天气事件之间包括影响程度和影响机理在内的错综复杂的关系。研究方法涉及星、地、空综合观测资料分析和模式模拟等。观测资料包括长时间历史观测资料、短时段强化观测实验资料、全球卫星资料等。     

欧洲地区不同温室气体背景下土地利用/覆盖变化的气候效应

通过温室气体排放和土地利用/覆盖变化,人类活动对气候变化产生显著影响。为了探究在不同温室气体浓度（Greenhouse gas concentration,GHG）背景下,相同的土地利用/覆盖变化（Land Use and Land Cover Change,LULCC）对于欧洲区域气候的影响差异,采用CESM（Community Earth System Model）耦合模式进行了模拟研究。研究发现,在1850年温室气体浓度背景下,土地利用/覆盖变化导致欧洲中东部地区降水显著增加,而在2000年温室气体浓度背景下,土地利用/覆盖变化导致欧洲中东部地区降水减少。温室气体增加后,LULCC导致该地区对流层低层大气环流由辐合变为辐散,气温以及大气水汽含量降低,这些变化能较大程度的改变LULCC对区域降水的净影响力。     

新昌硅化木揭示的早白垩世东南沿海地区古气候特征分析

根据浙江省新昌硅化木的分布与特点，应用硅化木记录的可知性和植物学的类比原理，通过该地区硅化木、其他植物化石和岩性组合等综合分析，初步探讨了早白垩世新昌盆地南洋杉型木的生态环境，以此研究该时期东南沿海地区的古气候主要特征。研究表明：该地区早白垩世古气候的主要特点是温暖、湿润及有时存在相对干旱的季节，同时呈现由温湿逐渐转变为干旱炎热的气候变化趋势；新昌硅化木中有明显的树木年轮，表明这种古气候可能存在一定的季节变化。     

An annotated bibliography on the greenhouse effect and climate change

The literature on climate change from an enhanced greenhouse effect is large and growing rapidly. The problems considered are increasingly inter-disciplinary. For these reasons many workers will find useful pointers to the literature in the fields interacting with, but outside of, their own. We present here an annotated bibliography on issues relating to changes in the concentrations of Earth's greenhouse gases. The areas covered include theory and numerical modelling of climate change; cycles involving carbon dioxide and other radiatively important trace gases; observations of climate change and the problems associated with those observations; paleoclimatology as it relates to previous changes in the greenhouse gases; the impacts on and interactions with managed and natural ecosystems from climate change; policy issues related to climate change and to the limitation of climate change; history of the study of the greenhouse effect; and some other causes of climate change. Selection of papers has been made to facilitate rapid introduction to most of the important issues and findings in an area. Over 600 articles, reports, and books are discussed.     

A framework for regional modeling of past climates

Summary The methods of reconstructing ancient climate information from the rock record are summarized, and the climate forcing factors that have been active at global and regional scales through Earth history are reviewed. In this context, the challenges and approaches to modeling past climates by using a regional climate model are discussed. A significant challenge to such modeling efforts arises if the time period of interest occurred prior to the past ∼3–5 million years, at which point land–sea distributions and topography markedly different from present must be specified at the spatial resolution required by regional climate models. Creating these boundary conditions requires a high degree of geologic knowledge, and also depends greatly upon the global climate model driving conditions. Despite this and other challenges, regional climate models represent an important and unique tool for paleoclimate investigations. Application of regional climate models to paleoclimate studies may provide another way to assess the overall performance of regional climate models.     

Contributions of solar and greenhouse gases forcing during the present warm period

Due to the dramatic increase in the global mean surface temperature (GMST) during the twentieth century, the climate science community has endeavored to determine which mechanisms are responsible for global warming. By analyzing a millennium simulation (the period of 1000–1990 ad) of a global climate model and global climate proxy network dataset, we estimate the contribution of solar and greenhouse gas forcings on the increase in GMST during the present warm period (1891–1990 ad). Linear regression analysis reveals that both solar and greenhouse gas forcing considerably explain the increase in global mean temperature during the present warm period, respectively, in the global climate model. Using the global climate proxy network dataset, on the other hand, statistical approach suggests that the contribution of greenhouse gas forcing is slightly larger than that of solar forcing to the increase in global mean temperature during the present warm period. Overall, our result indicates that the solar forcing as well as the anthropogenic greenhouse gas forcing plays an important role to increase the global mean temperature during the present warm period.     

A mental picture of the greenhouse effect

The popular picture of the greenhouse effect emphasises the radiation transfer but fails to explain the observed climate change. An old conceptual model for the greenhouse effect is revisited and presented as a useful resource in climate change communication. It is validated against state-of-the-art data, and nontraditional diagnostics show a physically consistent picture. The earth’s climate is constrained by well-known and elementary physical principles, such as energy balance, flow, and conservation. Greenhouse gases affect the atmospheric optical depth for infrared radiation, and increased opacity implies higher altitude from which earth’s equivalent bulk heat loss takes place. Such an increase is seen in the reanalyses, and the outgoing long-wave radiation has become more diffuse over time, consistent with an increased influence of greenhouse gases on the vertical energy flow from the surface to the top of the atmosphere. The reanalyses further imply increases in the overturning in the troposphere, consistent with a constant and continuous vertical energy flow. The increased overturning can explain a slowdown in the global warming, and the association between these aspects can be interpreted as an entanglement between the greenhouse effect and the hydrological cycle, where reduced energy transfer associated with increased opacity is compensated by tropospheric overturning activity.     

Climate modification by future ice sheet changes and consequences for ice sheet mass balance

The future evolution of global ice sheets under anthropogenic greenhouse forcing and its impact on the climate system, including the regional climate of the ice sheets, are investigated with a comprehensive earth system model consisting of a coupled Atmosphere–Ocean General Circulation Model, a dynamic vegetation model and an ice sheet model. The simulated control climate is realistic enough to permit a direct coupling of the atmosphere and ice sheet components, avoiding the use of anomaly coupling, which represents a strong improvement with respect to previous modelling studies. Glacier ablation is calculated with an energy-balance scheme, a more physical approach than the commonly used degree-day method. Modifications of glacier mask, topographic height and freshwater fluxes by the ice sheets influence the atmosphere and ocean via dynamical and thermodynamical processes. Several simulations under idealized scenarios of greenhouse forcing have been performed, where the atmospheric carbon dioxide stabilizes at two and four times pre-industrial levels. The evolution of the climate system and the ice sheets in the simulations with interactive ice sheets is compared with the simulations with passively coupled ice sheets. For a four-times CO₂ scenario forcing, a faster decay rate of the Greenland ice sheet is found in the non-interactive case, where melting rates are higher. This is caused by overestimation of the increase in near-surface temperature that follows the reduction in topographic height. In areas close to retreating margins, melting rates are stronger in the interactive case, due to changes in local albedo. Our results call for careful consideration of the feedbacks operating between ice sheets and climate after substantial decay of the ice sheets.     

Paleoclimate modeling in China: A review

This paper provides a review of paleoclimate modeling activities in China. Rather than attempt to cover all topics, we have chosen a few climatic intervals and events judged to be particularly informative to the international community. In historical climate simulations, changes in solar radiation and volcanic activity explain most parts of reconstructions over the last millennium prior to the industrial era, while atmospheric greenhouse gas concentrations play the most important role in the20 th century warming over China. There is a considerable model–data mismatch in the annual and boreal winter temperature change over China during the mid-Holocene [6000 years before present(ka BP)], while coupled models with an interactive ocean generally perform better than atmospheric models. For the Last Glacial Maximum(21 ka BP), climate models successfully reproduce the surface cooling trend over China but fail to reproduce its magnitude, with a better performance for coupled models. At that time, reconstructed vegetation and western Pacific sea surface temperatures could have significantly affected the East Asian climate, and environmental conditions on the Qinghai–Tibetan Plateau were most likely very different to the present day. During the late Marine Isotope Stage 3(30–40 ka BP), orbital forcing and Northern Hemisphere glaciation, as well as vegetation change in China, were likely responsible for East Asian climate change. On the tectonic scale,the Qinghai–Tibetan Plateau uplift, the Tethys Sea retreat, and the South China Sea expansion played important roles in the formation of the East Asian monsoon-dominant environment pattern during the late Cenozoic.     

Identification of linear relationships from noisy data using errors-in-variables models??relevance for reconstruction of past climate from tree-ring and other proxy information

Reliable paleoclimate reconstructions are needed to assess if the recent climatic changes are unusual compared to pre-industrial climate variability. Here, we focus on one important problem in climate reconstructions: Transfer functions relating proxies (predictors) and target climatic quantities (predictands) can be seriously biased when predictand and predictor noise is not adequately accounted for, resulting in biased amplitudes of reconstructed climatic time series. We argue for errors-in-variables models (EVM) for unbiased identification of linear structural relationships between noisy proxies and target climatic quantities by (1) introducing underlying statistical concepts and (2) demonstrating the potential biases of using the EVM approach, the most commonly used direct ordinary least squares (OLS) regression, inverse OLS regression, or the reduced major axis method (??variance matching??) with a simulation example of artificial noise-disturbed sinusoidal time series. We then develop an alternative strategy for paleoclimate reconstruction from tree-ring and other proxy data, explicitly accounting for the identified problem.