基于耦合线的高隔离度三频分支线耦合器

本文提出了一种应用于无线功率传输系统中的新型三频分支线耦合器.通过在传统分支线耦合器的基础上加载1/4波长短路耦合线来实现3个频段的通带.每个通带之间均保持高的隔离度,且通过改变加载耦合线的奇偶模阻抗值,耦合器通带的中心频率可以在较宽频带范围内调节.对一个工作在0.69/1.0/1.4 GHz的平面三频耦合器模型进行了设计与加工,测试结果与理论期望值吻合较好.     

数值预报模式动力框架发展的若干问题综述

作者就大气数值模式动力框架发展的几个问题做了回顾和展望.关于模式地形的处理,讨论了"地形追随"(terrain-following)坐标和"台阶地形"(step-mountain)η坐标的优点、问题和对策.关于物理量守恒格式的构造,回顾了从"瞬时"守恒到隐式、显示和半隐式完全(包括时间离散)守恒格式的发展和近况,介绍了加速非线性全隐式问题迭代收敛的途径.还讨论了半拉格朗日守恒格式的构造问题.最后,对目前广泛使用的全球谱模式,讨论了其长处、局限和发展前景,并简单介绍了谱元方法.     

区域海气耦合模式FROALS的发展及其应用

区域海气耦合模式是研究局地海气相互作用过程影响气候变率的重要平台,也是对全球气候模式进行"动力降尺度"的重要工具.本文介绍了LASG(State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics)/IAP(Institute of Atmospheric Physics)发展的区域海气耦合模式FROALS(Flexible Regional Ocean-Atmosphere-Land System model),并总结了过去五年围绕该区域海气耦合模式开展的研究工 作.FROALS的特点之一是有两个完全不同的大气模式分量和海洋模式分量选项,可以适应不同的模拟研究需 求.针对区域海气耦合模式在西北太平洋地区的模拟偏差,通过分步骤考察不同大气模式分量和不同海洋模式分量对模式模拟性能的影响,指出大气模式是导致区域海气耦合偏差的主要分量.通过改进对流触发的相对湿度阈值标准,有效地改善了此前区域海气耦合模式在亚洲季风区普遍出现的"模拟海温冷偏差".改进的FROALS对西北太平洋地区的大气和海洋环境有较好的模拟能力,合理地再现了西北太平洋地区表层洋流气候态和年际变率.较之非耦合模式,考虑区域海气耦合过程后,改进了东亚和南亚地区的降水和热带气旋潜势年际变率的模拟.最后,针对东亚—西北太平洋地区,利用FROALS对IAP/LASG全球气候模式模拟和预估的结果进行了动力降尺 度,得到了东亚区域50 km高分辨率区域气候变化信息.分析显示,FROALS模拟得到的东亚区域气候较之全球气候模式和非耦合区域气候模式结果具有明显的"增值",显示出区域海气耦合模式在该区域良好的应用前景.     

日本气象工作考察印象（3）

6日本气象厅的气侯业务日本气象厅对气候工作十分重视。1990年6月成立了气候资料中心,主要任务是控集全球气候资料和温室气体等资料,进行综合鳖理分析,定期向政府、大学、科研所以及世界气象组织提供.为加强和扩大气候资料捏集工作,成立了厄尔尼诺监测中心、温暖化变化中心,并高度注意对o:的监测.”气候研究工作由气象研究所气候研究部承担。在气候研究方面,目前主要开展了以下几个方面的工作:6.l利用数值模式进行气候和长期预报的研究,建立l～6个月长期预报动力数值预报模式,巳在业务上应用.6.2异常天气、气候变化机制的研究.对中、高纬大…     

T213L31全球模式的云和对流参数化方案改进试验

针对中国业务中期数值预报模式T213对中雨最级以上的降水预报空报比较明显的问题,文中对此模式预报的降水进行了诊断分析.发现T213模式预报的总降水分布主要是由可分辨尺度降水决定的,且在降水偏多最明显的地区,可分辨尺度的降水即超过或达到了观测的总降水,表明降水空报的主要原因在于可分辨尺度降水偏多.可分辨尺度降水偏多的可能原因有:土壤湿度初始化、云变量的初始化和直接产生降水的云与对流参数化方案存在一定的缺陷.鉴于前两者是目前国际上的难点,文中针对第3个方面的可能原因进行了分析和相应的改进.包括在对流方案之前增加一次云方案的调用;对流参数化办案的闭合由"动力型"改为对流有效化能调整闭合;更复杂的对流触发机制;改进冰沉降和降水通量计算.改进的主要目的是使对流参数化方案更活跃,从而减少格点尺度对流的发生.采用改进的方案,进行了敏感性试验和2005年夏季的连续滚动同化预报试验,并与中国区域400个标准站的降水观测和GPCP的全球降水观测进行了比较.结果表明,改进的方案无论是对中国区域还是全球夏季平均的降水分布预报都好于业务,但四川省和赤道东太平洋降水偏多的问题依然存在.中国区域的降水统计检验还表明,除小雨外,其他量级在大部分时效七降水的Ts评分增加,预报偏差降低.     

用QuikSCAT资料分析"黄蜂"登陆前后近地层风场的分布特征

利用QuikSCAT资料对"黄蜂"近地层风场分布的演变特征进行了诊断分析.并采用了离散余弦转换(DCT)对其方差的波谱结构进行了讨论.结果表明台风近地层风场分布具有明显的不对称性,其方差大部分产生于波数1和2的气流中,并且与波的方向有关.当台风沿纬向西移时,有两个纬向排列的波谱中心,主要是纬向波数2和经向波数1的气流;而当台风沿径向北上时,有两个经向排列的波谱中心,主要是纬向波数1和经向波数2的气流.波数1的气流对切向风的方差做主要贡献,波数2的气流对径向风的方差做主要贡献.不对称性分布的特征随大尺度环境场和台风自转气旋环流的改变而改变.当台风靠近大陆时台风大风出现的在台风前进方向前沿,类似于陈联寿等分析的第二类台风大风模式,在左前方是西北偏北大风,在右前方是东南大风.     

垂直-倾斜对流一体化参数化方案的实现及数值试验

在Kuo-Anthes垂直对流参数化方案和Nordeng倾斜对流参数化方案基础上,提出了垂直-倾斜对流一体化参数化方案,并引入MM5模式中.利用该方案对2008年1月28-29日发生在中国南方的一次暴雪过程和2005年"海棠"台风过程进行了数值模拟,模拟结果表明,此次暴雪过程在垂直方向主要表现对流稳定状态,但在对流层低层始终存在条件件对称不稳定层,并且当条件性对称不稳定区向高层发展时,伴随着强上升运动作为触发机制,引发条件性对称不稳定能量的释放,产生更多的对流降水,使模拟的总降水量与实况更加一致.条件性对称不稳定的发展加强与降雪强度、辐合辐散和上升运动变化一致,条件性对称不稳定是造成暴雪发展加强的主要机制之一.通过对"海棠"台风72 h的模拟表明,条件性对称不稳定主要发生在台风的低层,且其水平分布呈螺旋状结构.条件性对称不稳定效应对台风路径影响较小,但对台风强度影响较大,在模式中考虑垂直-倾斜对流一体化参数化方案后,与仅考虑垂直积云对流参数化方案相比,72 h模拟的平均台风中心最低气压降低了3 hPa,最大达8 hPa.在模式中考虑条件性对称不稳定的影响,可使模式台风中上层的暖心结构更加明显,上升运动和对流性降水增强,对流释放的更多凝结潜热使台风得到进一步加强.     

IAP-AGCM对QBO模拟的动量收支分析

平流程准两年振荡(QBO)是赤道平流层(～100-1 hPa)变率的主要模态,可对中高纬地区的环流产生重要影响,但目前利用通用大气环流模式(GCM)对其进行准确模拟仍然是一个挑战.本文利用IAP大气环流模式(IAP-AGCM)的中高层大气模式版本(IAP-AGCML69)对QBO进行模拟,并对其动量收支情况进行分析.研究发现,QBO主要是由对流活动引起的重力波强迫(参数化)引起的,但该动量强迫被平流层赤道上升流所引起的平流过程显著削弱.模式可分辨尺度的波动强迫对赤道上空的QBO的总纬向风倾向有正贡献,在上平流层,其量值大小与参数化的重力波强迫相当.以上结果提供了QBO形成机制以及模式模拟差异可能原因的认识.     

IAP-AGCM对QBO模拟的动量收支分析（英文）

平流层准两年振荡(QBO)是赤道平流层(～100-1 hPa)变率的主要模态,可对中高纬地区的环流产生重要影响,但目前利用通用大气环流模式(GCM)对其进行准确模拟仍然是一个挑战.本文利用IAP大气环流模式(IAP-AGCM)的中高层大气模式版本(IAP-AGCML69)对QBO进行模拟,并对其动量收支情况进行分析.研究发现,QBO主要是由对流活动引起的重力波强迫(参数化)引起的,但该动量强迫被平流层赤道上升流所引起的平流过程显著削弱.模式可分辨尺度的波动强迫对赤道上空的QBO的总纬向风倾向有正贡献,在上平流层,其量值大小与参数化的重力波强迫相当.以上结果提供了对QBO形成机制以及模式模拟差异可能原因的认识.     

中国稻田甲烷产生和排放研究 Ⅱ.模式研究和减排措施

主要介绍了近 2 0年来稻田甲烷排放的模式研究和排放量的估算以及减少稻田甲烷排放的措施。数值模式是估算稻田甲烷排放量的一条有效途径 ,模式的研究现在正处于发展阶段。介绍了几个主要的模型 ,既有物理过程模型也有经验模型。年排放量的估算范围为 6 79～ 4 1 4Tg ,随着技术的发展和大量实验的进行估算值的精度正得到不断的提高。减排措施是减少稻田甲烷排放的必要手段 ,但是目前的减排技术均处于研究阶段 ,应用还不成熟     

海气耦合环流模式及耦合技术的研究

介绍了近年来国内外海气耦合环流模式的研究、发展趋势,对不同模式的耦合技术及其人预报试验进行了综合分析,从ＥＮＳＯ预测与耦合环流模式的组成分类、模式的气候漂移及其处理技术（耦合方案）的特点,模式的季节、年际、年代际预报能力等方面评述了当前海气耦合环流模式的研究进展和影响耦合模式预报能力的有关问题,指出目前发展海气耦合模式的观难点所在,并就我国现状提出了进行针对性研究的具体想法。     

Flux correction: tests with a simple ocean-atmosphere model

 Flux correction schemes are used in order to suppress the drift of coupled ocean atmosphere models. This technique is tested for a simple box model of the climate system. Two “perfect” models of the ocean and the atmosphere are available. These are coupled to form an ocean-atmosphere model representing the true climate system. This climate system is simulated by a climate model which is also constructed by coupling those two perfect models. This time, however, both models are run first separately as models of the atmosphere and the ocean. In that case, “observations” from the climate system are prescribed at the ocean surface in the uncoupled models. It is assumed that these observations are imperfect. A drift results, when these models are coupled to form an ocean-atmosphere stimulation model. A flux adjustment scheme is implemented to remove this drift. It is argued that the merits and shortcomings of the flux correction technique can be assessed more clearly this way than by coupling imperfect models as is done normally. Sensitivity tests are performed where either radiation parameters are changed or a salt anomaly is implanted. Model parameters are chosen such that the ocean has a thermally direct circulation in the unperturbed climate state. It is found that the flux correction technique is performing satisfactorily as long as the imposed perturbations are small enough so that the ocean circulation does not change its sense. If, however, the model climate is close to the transition to an indirect circulation, then the flux correction technique is unreliable. The predictions of the coupled model with flux correction may deviate substantially from the response of the climate system in that case. Received: 4 December 1995/Accepted: 15 October 1996     

A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments

Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach.     

Modelling European winter wind storm losses in current and future climate

Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (?22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.     

Development of global coupled ocean-atmosphere general circulation models

It has long been believed that a climate model capable of realistically simulating many features of global climate, variability, and climate change must interactively represent the major components of the dynamically coupled climate system, particularly the atmosphere, ocean, and cryosphere. This effort traditionally has been constrained by computing power, our understanding of the observed system, and climate modeling capability. With the advent of supercomputers, improved understanding of global climate processes, and computationally efficient general circulation climate models, we have witnessed a rapid increase in the simulation of global climate by coupling together various representations of atmosphere, ocean, and sea ice. Beginning in the late 1960s and continuing through the early 1980s, general circulation models (GCMs) of the atmosphere, ocean, and sea ice were coupled and run asynchronously to produce credible simulations of the global climate. Systematic errors in these component models later led some modeling groups to use flux correction or flux adjustment, whereby either one or several of the variables at the air-sea interface are adjusted to bring the simulations in closer agreement with observations. Further advances in computing power and climate modeling techniques in the past few years have allowed global coupled ocean-atmosphere GCMs to be run synchronously (i.e., atmosphere and ocean communicate at least once each model day). Computing constraints, combined with the need for multidecadal climate integrations, still only allow relatively coarse-grid ocean GCMs to be coupled to correspondingly coarse-grid atmospheric models (on the order of 500 km × 500 km). However, results from this current generation of global, coupled GCMs have revealed interesting characteristics associated with ocean dynamics and global climate in experiments with gradual increases of carbon dioxide. Another somewhat surprising aspect of the global-coupled GCM simulations is the appearance of some features associated with the El Niño-Southern Oscillation. Along with concurrent efforts with other types of limited-domain, dynamical coupled models, this has led to the realization that inherent unstable coupled modes exist in the climate system that are the unique product of the interactive coupling of the atmosphere and the ocean. All of these efforts are leading to the next generation of coupled ocean-atmosphere GCMs. These models will run on even faster and larger-memory computers and will have higher-resolution atmosphere and ocean components, more accurate sea-ice formulations, improved cloud-radiation schemes, and increasingly realistic land-surface processes.This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. DümenilThe National Center for Atmospheric Research is sponsored by the National Science Foundation     

大气环流模式（SAMIL）海气耦合前后性能的比较

基于耦合器框架，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大气环流谱模式 （SAMIL）最近成功地实现了与海洋、海冰等气候分量模式的耦合，形成了“非通量调整”的海－陆－气－冰直接耦合的气候模式系统（FGOALS-s）。在耦合系统中，由于海温、海冰等的分布由预报模式驱动，大气与海洋、海冰之间引入了相互作用过程，这样大气环流的模拟特征与耦合前会有不同。为分析耦合系统的性能，作者对耦合前后的模拟结果进行了分析比较，重点是大气模拟特征的差异。结果表明，耦合前、后大气环流的基本特征相似，都能成功地模拟出主要的环流系统分布及季节变化，但是由于海温和海冰的模拟存在系统性的偏差，使得耦合后的大气环流受到明显影响。例如耦合后热带海温偏冷，南大洋、北太平洋和北大西洋等中纬度地区的海温偏高，导致海温等值线向高纬海域的伸展较弱，海温经向梯度减小。耦合后海冰在北极区域范围偏大，在南极周边地区则偏小。海温、海冰分布模拟的偏差影响到中、高纬低层大气的温度。热带海温偏低，使得赤道地区降水偏弱，凝结潜热减少，热带对流层中高层温度比耦合前要低，大气温度的经向梯度减小。经向温度梯度的改变，直接影响到对平均经圈环流及西风急流强度的模拟。尽管耦合系统中海温、海冰的模拟存在偏差，但在亚洲季风区，耦合后季风环流及降水等的分布都比耦合前单独大气模式的结果合理，表明通过海[CD*2]气相互作用可减少耦合前季风区的模拟误差，改善季风模拟效果。比较发现，海温、海冰模拟的偏差，除与海洋模式中经向热输送偏弱、海冰模式中海冰处理等有关外，也与大气模式中总云量模拟偏低有关。大气模式本身的误差，特别是云、辐射过程带来的误差，对耦合结果具有极为重要的影响。完全耦合后，这些误差通过与海洋、海冰的反馈作用而放大。因此，对于FGOALS-s而言，要提高耦合系统的整体性能，除改进各气候分量模式的模拟性能外，需要重点改进大气模式中的云、辐射过程。     

区域海气耦合模式模拟中国夏季降水能力分析

基于OASIS3(Ocean Atmosphere Sea Ice Soil version 3)耦合器,耦合区域气候模式RegCM3(Regional Climate Model version 3)和海洋模式HYCOM(Hybrid Coordinate Ocean Model),建立一个区域海气耦合模式,并通过嵌套方法处理海洋模式的侧边界问题。运用该耦合模式对1982～2001年包括中国在内的东亚地区气候进行连续模拟,重点分析其对中国夏季(6～8月)降水的模拟性能。结果表明:耦合模式基本可以模拟出中国夏季降水的空间分布特征,模拟的降水量值和年际变化在靠近海洋的沿海区域比参照试验有一定程度的改善;能够再现观测夏季降水经验正交函数第一模态(EOF1)的空间分布特征,与观测EOF1的时间相关性也比参照试验有较大提高;前6个模态的组合分析也表明耦合模式对长江中下游、山东半岛、海南岛等区域夏季降水的较大时间尺度气候分量的模拟改善更显著。     

Dependence of Indian monsoon rainfall on moisture fluxes across the Arabian Sea and the impact of coupled model sea surface temperature biases

The Arabian Sea is an important moisture source for Indian monsoon rainfall. The skill of climate models in simulating the monsoon and its variability varies widely, while Arabian Sea cold sea surface temperature (SST) biases are common in coupled models and may therefore influence the monsoon and its sensitivity to climate change. We examine the relationship between monsoon rainfall, moisture fluxes and Arabian Sea SST in observations and climate model simulations. Observational analysis shows strong monsoons depend on moisture fluxes across the Arabian Sea, however detecting consistent signals with contemporaneous summer SST anomalies is complicated in the observed system by air/sea coupling and large-scale induced variability such as the El Ni?o-Southern Oscillation feeding back onto the monsoon through development of the Somali Jet. Comparison of HadGEM3 coupled and atmosphere-only configurations suggests coupled model cold SST biases significantly reduce monsoon rainfall. Idealised atmosphere-only experiments show that the weakened monsoon can be mainly attributed to systematic Arabian Sea cold SST biases during summer and their impact on the monsoon-moisture relationship. The impact of large cold SST biases on atmospheric moisture content over the Arabian Sea, and also the subsequent reduced latent heat release over India, dominates over any enhancement in the land-sea temperature gradient and results in changes to the mean state. We hypothesize that a cold base state will result in underestimation of the impact of larger projected Arabian Sea SST changes in future climate, suggesting that Arabian Sea biases should be a clear target for model development.     

可计算一般均衡框架下的气候变化经济影响综合评估

气候变化是21世纪人类面临的重大挑战之一,并对自然系统和社会经济系统造成了各种负面影响。对气候变化的影响进行经济评估是气候变化研究中的重要问题。而可计算一般均衡框架下的综合评估模型（CGE_IAMs）是评估气候变化经济影响的有效手段之一,文中对气候变化影响经济评估的主要CGE_IAMs进行了文献调研,并对这些模型进行了比较分析。研究表明不同模型在温室气体排放、气候参数的处理方式以及气候影响的引入机制等方面有着较大区别,因而各模型对气候变化影响的经济评估结果也有一定的差异。此外,当前CGE_IAMs在评估气候变化经济影响时存在支撑数据未及时更新、方法不细致以及评估不全面等问题。未来该领域的相关研究应该更加关注于模型与支撑数据的精细化和开源化,此外还应加强CGE_IAMs中经济模块与复杂气候模式的耦合。