地表温度对太阳常数变化响应的数值试验研究

通过改变太阳常数，利用NCAR气候系统模式CSM1．4就地表温度对强外辐射强迫变化的响应及性质进行了研究。结果表明：虽然局地的增温幅度变化很大，但各试验的全球增温分布特征非常相似，并从一定程度上反映了全球增暖典型试验中的增温分布特点，即陆地比海洋增暖幅度更强，高纬度地区比低纬度地区增暖幅度更强，这一特点在太阳常数增加较大的试验中表现尤为明显。气候系统响应的性质在太阳常数分别增加2，5％、10％和15％与增加25％之间其响应方式有所改变，即气候系统对较小太阳常数变化的响应是线性的，而对较大太阳常数变化的响应则很可能是非线性的。     

亚洲夏季风对强外辐射强迫变化的响应

该文通过改变太阳常数,利用NCAR气候系统模式CSM1.4研究了亚洲夏季风对强外辐射强迫变化的响应。结果表明:随太阳常数增加,局地增温幅度变化很大,中高纬地区比低纬地区增暖幅度强,这在太阳常数增加较大的试验中表现尤为明显;随太阳常数增大越大,大气温度升高越高,对流层有强烈增温,对流层高层更为显著;随太阳常数增大,亚洲夏季风系统的响应越强,太平洋副热带高压和南亚高压强度增强明显,并且太阳常数增加越大,高压强度越强,但形式有所不同,500 hPa太阳常数增加2.5%高压强度随纬度增高增强幅度变小,太阳常数增加10%和25%高压强度随纬度增高增强幅度变大。100 hPa太阳常数增加2.5%和10%高压强度随纬度增高增强幅度变小,太阳常数增加25%高压强度随纬度增高增强幅度变大。     

亚洲冬季风对强外辐射强迫变化的响应

本文采用NCAR气候系统模式CSM1.4研究了冬季风对强外辐射强迫变化的响应,其中外辐射强迫直接由太阳常数的变化而引入。结果表明：随太阳常数的增加,局地的增温幅度变化很大,中高纬地区比低纬地区增暖幅度强,这在太阳常数增加较大的试验中表现更为明显;随太阳常数增大越大,大气温度升高越高,对流层有强烈增温,对流层高层尤为显著,平流层中上层有降温现象;随太阳常数增大,亚洲冬季风系统的响应越强,系统强度增强明显,但形式不同,500hPa随纬度增高增强幅度变大,100hPa随纬度增高增强幅度变小。     

亚洲冬季风对强外辐射强迫变化的响应

本文采用NCAR气候系统模式CSM 1.4研究了冬季风对强外辐射强迫变化的响应,其中外辐射强迫直接由太阳常数的变化而引入。结果表明:随太阳常数的增加,局地的增温幅度变化很大,中高纬地区比低纬地区增暖幅度强,这在太阳常数增加较大的试验中表现更为明显;随太阳常数增大越大,大气温度升高越高,对流层有强烈增温,对流层高层尤为显著,平流层中上层有降温现象;随太阳常数增大,亚洲冬季风系统的响应越强,系统强度增强明显,但形式不同,500 hPa随纬度增高增强幅度变大,100 hPa随纬度增高增强幅度变小。      

对流层增暖热带放大现象：基于FGOALS-g3的模拟研究

热带地区的湿绝热过程会放大地表的增暖幅度,在约200 hPa高度上产生增暖峰值,该现象被称为“热带对流层放大”。热带对流层放大是气候变化的显著特征之一,是检验气候模式性能的重要指标。本文基于RSS4.0卫星数据和ERA5.1再分析资料,系统分析了FGOALS-g3模式对气温变化特别是热带对流层放大的模拟能力,并通过新旧版本模式（FGOALS-g3与FGOALS-g2）的比较指出了新版本模式模拟技巧的提升;通过比较FGOALS-g3历史模拟试验与GAMIL3单独大气模式AMIP试验结果,研究了海气耦合过程对模拟结果的影响。结果表明,FGOALS-g3能够合理再现观测中的全球对流层显著增温趋势,但模拟的增温趋势偏强,这与气候系统内部变率以及两代气候系统模式所使用的历史气候外强迫差异有关。其对于观测中热带平均增温廓线以及热带对流层放大的空间分布均表现出良好的模拟性能,模拟的热带对流层放大现象的量值大小存在正偏差,与模拟的对流层低层温度变化偏强有关。FGOALS-g3较FGOALS-g2在性能上有一定提升,主要表现为增加了对于火山气溶胶强迫的响应,并在热带对流层放大的空间分布及平均气温趋势廓线...     

太阳常数的微小变化在气候变化中的作用

将复杂的气候系统抽象为含有云辐射动态反馈过程的高度非线性气候模型,利用分岔理论,分析了该模型的平衡态及其稳定性。计算结果表明,云反照率反馈、地表反照率反馈和水汽反馈是气候系统呈现多平衡态结构的主要因素,是气候变化复杂性根源,而云放射率反馈对系统结构的影响,只有在强烈的水汽放射率反馈条件下才表现明显。较强的地表反照率反馈和水汽放射率反馈,均可在太阳常数仅有微小变化时就能导致全球气候突变。     

气候系统对CO2强迫和太阳辐射强迫在不同时间尺度的响应

使用HadCM3L气候模式,针对突然增加的4倍CO₂浓度和增加4%的太阳辐射强迫进行一系列理想化模拟试验,分析并比较了CO₂强迫和太阳辐射强迫对气候系统的影响机制和异同。模拟结果表明,突然增加的4倍CO₂浓度和增加4%的太阳辐射造成的长期全球表面平均温度变化基本相同,但二者造成降水的变化差异很大。气候系统对CO₂和太阳辐射的响应可以分为快响应和慢响应两个部分,而降水的差异主要体现在大约1个月时间尺度内的快响应阶段,在这一时间段,陆地区域CO₂的气孔效应减少了植被的蒸腾作用,导致降水受到抑制;海洋区域CO₂的辐射效应会首先导致大气长波吸收增强,而海洋的比热较大,所以海表温度变化落后于低层大气,低层大气的垂直稳定度增加,海表向上蒸发受到抑制。此外,比较不同时间尺度上CO₂对气候系统的影响,可以发现在1个月的短时间尺度上,对陆地而言,CO₂的气孔效应对气候系统的影响占主导地位,但在数年以上更长的时间尺度上,CO₂的辐射效应是导致地气系统温度升高的主要原因。     

NCAR科学家发现全球增暖导致2005年飓风加倍

NCAR的Kevin Trenberth和Dennis Shea的最新研究表明，2005年热带北大西洋海域的增暖是飓风增加的主要原因，其热量的一半来自全球增暖，自然循环只是次要原因。该研究发表在2007年6月27日的Geophysical Research Letters杂志上。     

气候系统及模式中反馈机制研究 I.概念和方法

气候系统中存在着各种各样的气候反馈机制,而气候模式对这些反馈机制描述的差异,正是造成不同模式对同一直接辐射强迫（如二氧化碳加倍）的响应不同的主要原因。因此,只有正确描述气候系统中的各种反馈作用,气候模式才可能用来对未来的气候变化进行预测。为此,本文首先介绍了气候系统及模式反馈机制分析研究时所常用的一些概念,如气候敏感性参数、云辐射强迫等,随后概述了气候模式反馈机制比较分析时常用的各种方法,并指出了这些方法各自的优缺点。而详细的有关气候系统及模式中反馈作用及其机制的分析则在文章的第ＩＩ部分给出。     

气候系统及模式中反馈机制研究 Ⅰ.研究和方法

气候系统中存在着各种各样的气候反馈机制,而气候模式对这些反馈机制描述的差异,正是造成不同模式对同一直接辐射强迫（如二氧化碳加倍）的响应不同的主要原因。因此,只有正确描述气候系统中的各种反馈作用,气候模式才可能用来对未来的气候变化进行预测。为此,本文首先介绍了气候系统及模式反馈机制分析研究时所常用的一些概念,如气候敏感性参数、云辐射强迫等,随后概述了气候模式反馈机制比较分析时常用的各种方法,并指出了这些方法各自的优缺点。而详细的有关气候系统及模式中反馈作用及其机制的分析则在文章的第II部分给出。     

Climate sensitivity and climate change under strong forcing

A version of the National Centre for Atmospheric Research (NCAR) coupled climate model is integrated under current climate conditions and in a series of experiments with climate forcings ranging from modest to very strong. The purpose of the experiments is to investigate the nature and behaviour of the climate feedback/sensitivity of the model, its evolution with time and climate state, the robustness of model parameterizations as forcing levels increase, and the possibility of a “runaway” warming under strong forcing. The model is integrated for 50 years, or to failure, after increasing the solar constant by 2.5, 10, 15, 25, 35, and 45% of its control value. The model successfully completes 50 years of integration for the 2.5, 10, 15, and 25% solar constant increases but fails for increases of 35% and 45%. The effective global climate sensitivity evolves with time and analysis indicates that a new equilibrium will be obtained for the 2.5, 10, and 15% cases but that runaway warming is underway for the 25% increase in solar constant. Feedback processes are analysed both locally and globally in terms of longwave and shortwave, clear-sky/surface, and cloud forcing components. Feedbacks in the system must be negative overall and of sufficient strength to balance the positive forcing if the system is to attain a new equilibrium. Longwave negative feedback processes strengthen in a reasonably linear fashion as temperature increases but shortwave feedback processes do not. In particular, solar cloud feedback becomes less negative and, for the 25% forcing case, eventually becomes positive, resulting in temperatures that “run away”. The conditions under which a runaway climate warming might occur have previously been investigated using simpler models. For sufficiently strong forcing, the greenhouse effect of increasing water vapour in a warmer atmosphere is expected to overwhelm the negative feedback of the longwave cooling to space as temperature increases. This is not, however, the reason for the climate instability experienced in the GCM. Instead, the model experiences a “cloud feedback” warming whereby the decrease in cloudiness that occurs when temperature increases beyond a critical value results in an increased absorption of solar radiation by the system, leading to the runaway warming.     

On the numerical integration of a randomly forced system: variation and feedback estimation

Simulated climate variables in a simple energy balance model subject to linearly increasing external forcing (due to increasing greenhouse gas emissions) and random internal forcings have been studied for more accurate climate prediction. The numerical method for such a system requires careful treatment of random forcings. Mathematical analyses show that the effect of random forcings should be diminished in the numerical integration method by the reciprocal of the root of the integration time step $ \left( {1/\sqrt {{\Delta t}} } \right) $ , which we call an attenuator. Our simulations consistently show that the attenuator desirably reduces variances of simulated climate variables and eliminates overestimation of the variances. However, the attenuator tends to bias the estimates of the climate feedback parameter obtained from a simple regression analysis of simulated variables toward unrealistically low values. This is because the reduced random forcings amplify the negative effect of a warming trend due to greenhouse emissions (when added to random forcing) on feedback estimation. Without the attenuator, the estimated feedback is much more accurate. The bias induced from the attenuator was largely resolved for the feedback estimation by the methodology of Lindzen and Choi (Asia-Pacific J Atmos Sci 47(4):377–390, 2011), which minimizes the negative effect of the warming trends by isolating short (few months) segments of increasing and decreasing temperature changes.     

Responses of Mean and Extreme Precipitation to Different Climate Forcing Under Radiative-Convective Equilibrium

Understanding the responses of mean and extreme precipitation to climate change is of great importance.Previous studies have mainly focused on the responses to prescribed sea surface warming or warming due to increases of CO2.This study uses a cloud-resolving model under the idealization of radiative-convective equilibrium to examine the responses of mean and extreme precipitation to a variety of climate forcings,including changes in prescribed sea surface temperature,CO2,solar insolation,surface albedo,stratospheric volcanic aerosols,and several tropospheric aerosols.The different responses of mean precipitation are understood by examining the changes in the surface energy budget.It is found that the cancellation between shortwave scattering and longwave radiation leads to a small dependence of the mean precipitation response on forcings.The responses of extreme precipitation are decomposed into three components(thermodynamic,dynamic,and precipitation efficiency).The thermodynamic components for all climate forcings are similar.The dynamic components and the precipitation-efficiency components,which have large spreads among the cases,are negatively correlated,leading to a small dependence of the extreme precipitation response on the forcings.     

The impact of natural and anthropogenic forcings on climate and hydrology since 1550

A climate simulation of an ocean/atmosphere general circulation model driven with natural forcings alone (constant “pre-industrial” land-cover and well-mixed greenhouse gases, changing orbital, solar and volcanic forcing) has been carried out from 1492 to 2000. Another simulation driven with natural and anthropogenic forcings (changes in greenhouse gases, ozone, the direct and first indirect effect of anthropogenic sulphate aerosol and land-cover) from 1750 to 2000 has also been carried out. These simulations suggest that since 1550, in the absence of anthropogenic forcings, climate would have warmed by about 0.1 K. Simulated response is not in equilibrium with the external forcings suggesting that both climate sensitivity and the rate at which the ocean takes up heat determine the magnitude of the response to forcings since 1550. In the simulation with natural forcings climate sensitivity is similar to other simulations of HadCM3 driven with CO₂ alone. Climate sensitivity increases when anthropogenic forcings are included. The natural forcing used in our experiment increases decadal–centennial time-scale and large spatial scale climate variability, relative to internal variability, as diagnosed from a control simulation. Mean conditions in the natural simulation are cooler than in our control simulation reflecting the reduction in forcing. However, over certain regions there is significant warming, relative to control, due to an increase in forest cover. Comparing the simulation driven by anthropogenic and natural forcings with the natural-only simulation suggests that anthropogenic forcings have had a significant impact on, particularly tropical, climate since the early nineteenth century. Thus the entire instrumental temperature record may be “contaminated” by anthropogenic influences. Both the hydrological cycle and cryosphere are also affected by anthropogenic forcings. Changes in tree-cover appear to be responsible for some of the local and hydrological changes as well as an increase in northern hemisphere spring snow cover.

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The role of atmospheric teleconnection in the subtropical thermal forcing on the equatorial pacific

The equatorial response to subtropical Pacific forcing was studied in a coupled climate model.The forcings in the western,central and eastern subtropical Pacific all caused a significant response in the equatorial thermocline,with comparable magnitudes.This work highlights the key role of air-sea coupling in the subtropical impact on the equatorial thermocline,instead of only the role of the ＂oceanic tunnel＂.The suggested mechanism is that the cyclonic （anticyclonic） circulation in the atmosphere caused by the subtropical surface warming （cooling） can generate an anomalous upwelling （downwelling） in the interior region.At the same time,an anomalous downwelling （upwelling） occurs at the equatorward flank of the forcing,which produces anomalous thermocline warming （cooling）,propagating equatorward and resulting in warming （cooling） in the equatorial thermocline.This is an indirect process that is much faster than the ＂oceanic tunnel＂ mechanism in the subtropical impact on the equator.     

气候系统模式FGOALS_gl模拟的20世纪气温变化

分析了中国科学院大气物理研究所大气科学和地球流体力学国家重点实验室(LASG/IAP)发展的快速耦合气候系统模式FGOALS_gl对近100年气温变化的模拟,讨论了20世纪气温变化的机理。结果表明,在自然因素和人为因素的共同强迫作用下,FGOALS_gl能够合理再现20世纪全球平均和纬向平均地表气温随时间的演变。利用太阳辐照度等自然强迫、温室气体和气溶胶等人为强迫因子来驱动耦合模式,能够模拟出过去100年全球平均气温的增温趋势和年代际变化。耦合模式可以较好地模拟出20世纪全球气温变化趋势的空间分布。对区域气温变化模拟效果的分析表明,除北大西洋外,FGOALS_gl对其他地区具有较高的模拟技巧,表明外强迫是造成多数地区气温变化的主要原因。FGOALS_gl的主要缺陷在于模拟的变暖强度偏弱,大气模式自身的偏差以及耦合模式对温室气体响应的敏感度偏低是造成上述缺陷的主要原因。总体而言,FGOALS_gl对20世纪气温变化的模拟效果较为理想,特别是在全球、半球和大陆尺度上,该模式对过去100年气温变化的模拟较为合理。     

Twenty-first century Arctic climate change in the CCSM3 IPCC scenario simulations

Arctic climate change in the Twenty-first century is simulated by the Community Climate System Model version 3.0 (CCSM3). The simulations from three emission scenarios (A2, A1B and B1) are analyzed using eight (A1B and B1) or five (A2) ensemble members. The model simulates a reasonable present-day climate and historical climate trend. The model projects a decline of sea-ice extent in the range of 1.4–3.9% per decade and 4.8–22.2% per decade in winter and summer, respectively, corresponding to the range of forcings that span the scenarios. At the end of the Twenty-first century, the winter and summer Arctic mean surface air temperature increases in a range of 4–14°C (B1 and A2) and 0.7–5°C (B1 and A2) relative to the end of the Twentieth century. The Arctic becomes ice-free during summer at the end of the Twenty-first century in the A2 scenario. Similar to the observations, the Arctic Oscillation (AO) is the dominant factor in explaining the variability of the atmosphere and sea ice in the 1870–1999 historical runs. The AO shifts to the positive phase in response to greenhouse gas forcings in the Twenty-first century. But the simulated trends in both Arctic mean sea-level pressure and the AO index are smaller than what has been observed. The Twenty-first century Arctic warming mainly results from the radiative forcing of greenhouse gases. The 1st empirical orthogonal function (explains 72.2–51.7% of the total variance) of the wintertime surface air temperature during 1870–2099 is characterized by a strong warming trend and a “polar amplification”-type of spatial pattern. The AO, which plays a secondary role, contributes to less than 10% of the total variance in both surface temperature and sea-ice concentration.     

The CLIVAR C20C project: selected twentieth century climate events

We use a simple methodology to test whether a set of atmospheric climate models with prescribed radiative forcings and ocean surface conditions can reproduce twentieth century climate variability. Globally, rapid land surface warming since the 1970s is reproduced by some models but others warm too slowly. In the tropics, air-sea coupling allows models to reproduce the Southern Oscillation but its strength varies between models. We find a strong relationship between the Southern Oscillation in global temperature and the rate of global warming, which could in principle be used to identify models with realistic climate sensitivity. This relationship and a weak response to ENSO suggests weak sensitivity to changes in sea surface temperature in some of the models used here. In the tropics, most models reproduce part of the observed Sahel drought. In the extratropics, models do not reproduce the observed increase in the North Atlantic Oscillation in response to forcings, through internal variability, or as a combination of both.     

Fast versus slow response in climate change: implications for the global hydrological cycle

Recent studies have shown that changes in global mean precipitation are larger for solar forcing than for CO₂ forcing of similar magnitude. In this paper, we use an atmospheric general circulation model to show that the differences originate from differing fast responses of the climate system. We estimate the adjusted radiative forcing and fast response using Hansen’s “fixed-SST forcing” method. Total climate system response is calculated using mixed layer simulations using the same model. Our analysis shows that the fast response is almost 40% of the total response for few key variables like precipitation and evaporation. We further demonstrate that the hydrologic sensitivity, defined as the change in global mean precipitation per unit warming, is the same for the two forcings when the fast responses are excluded from the definition of hydrologic sensitivity, suggesting that the slow response (feedback) of the hydrological cycle is independent of the forcing mechanism. Based on our results, we recommend that the fast and slow response be compared separately in multi-model intercomparisons to discover and understand robust responses in hydrologic cycle. The significance of this study to geoengineering is discussed.