硫酸盐直接辐射强迫的在线与固定转化率模拟方法的对比研究

以2000年1、4、7、10月为例，利用区域气候模式，比较了模拟硫酸盐气溶胶分布和直接辐射强迫的在线模拟方法与固定SO2到硫酸盐转化率方法，并与全球模式的结果进行了对比检验。结果表明：在线模拟得到的主要结果与全球平均结果符合得很好，但固定转化率方法存在明显偏差；两种方法硫酸盐柱含量的差异在-4-12mg／m^2范围内，占在线模拟柱含量的42％以上，7月份差异最显著，1月份差异最小；大气顶辐射强迫差异在-1.8-0．4W／m^2之间，此差别占在线辐射强迫的26％以上；采用36．7％的固定转化率对冬季过大、夏季偏小，只有春秋季的江南部分地区适合。由于固定转化率方法不能反映温度、辐射、水汽、云水等气象要素的季节性变化对硫酸盐生成率的影响，因而对硫酸盐含量和分布的季节变化模拟存在偏差，这是导致上述差异的重要原因。     

2006年中国地区大气气溶胶浓度分布特征的模拟研究

结合2006年最新的气溶胶排放源资料,以NCEP/NCAR再分析资料为气象场,驱动大气化学传输模式MATCH（Model of Atmospheric Transport and Chemistry）,模拟了2006年中国地区硫酸盐、黑碳和沙尘气溶胶的质量浓度分布及其季节变化。模拟的气溶胶光学厚度（AOD）结果与CSHNET观测网数据比较分析后发现,基于21个观测站的61组月平均数据与相应模拟结果的相关系数为0.63。模拟结果表明：2006年中国地区硫酸盐气溶胶高值区主要分布在中国的四川盆地、华北及长江流域等工业较发达地区,而且具有明显的季节变化,四川盆地及长江以南地区,硫酸盐气溶胶1月份浓度高于7月份,长江以北的大部分地区,7月份浓度高于1月份;黑碳气溶胶主要分布在黄河、长江中下游地区及华南等地区,1月份浓度高于7月份;沙尘气溶胶主要分布在内蒙古中部沙漠地区,4月份浓度最高,7月份次之,其他月份较少。     

月和季节尺度区域气候模拟的对比分析

利用区域气候模式RegCM3分别进行了东亚夏季月尺度和季节尺度区域气候模拟试验,并将两种时间尺度试验的逐月模拟结果进行了对比分析。结果表明,不同初始场和不同时间尺度模拟降水量存在一定的不确定性,但模拟的降水分布格局和模拟时间尺度关系不大,其模拟结果主要取决于模式对区域内大气降水过程的描述能力。两种时间尺度模拟的月平均环流形势几乎一致,随着模拟时间延长,两种时间尺度模拟的月平均环流、温度和湿度之间的差别在模式内部区域有所增加。但两者没有出现本质差别,且两者之间的偏差不会随模拟时间尺度的延长而无限制增长,只在一定范围内波动。两种时间尺度模拟对7月份淮河流域降水集中期暴雨和高低空急流刻画差别不大,但两者对8月份东北降水集中期模拟差别稍明显一些,其差别主要表现在对低空急流的模拟上。     

区域气候模式REMO对东亚季风季节变化的模拟研究

将欧洲区域气候模式REMO首次应用于东亚区域,利用该模式对1980年和1990年东亚季风季节变化进行了模拟研究,并将模拟结果与NCEP再分析资料进行比较,以检验该模式对东亚季风的模拟能力.研究表明,区域气候模式REMO能够较好地模拟出东亚地区高、低空的大气环流特征,模拟的高度场、流场和温度场与NCEP再分析资料场都比较一致.模拟结果显示了东亚季风的月变化和季节转换特征.模拟的降水场与GPCC降水资料的对比结果表明,REMO能较为成功地模拟出东亚地区降水的空间分布,并能较好地反映降水的季节变化及主要降水趋势,夏季降水模拟偏大,整个区域平均的降水量偏差约为18%左右.     

非对流云的观测事实及其对大气环流模式设计的意义

通过非对流云的气候资料分析和个例分析表明：(1)非对流云有季节变化,也随海陆分布的不同而变化,还与大气三圈环流及季风等密切相关。由于它们的相关性,在大气环流模式(GCM)中对非对流云的模拟必须与提高模式其他部分的模拟能力相辅相成。(2)产生于中高纬度大范围上升气流的非对流云,由赤道辐合带积云对流所致的高空赤道地区的卷云与卷层云和形成于副热带冷海水上空的层云与层积云是新一代大气环模式显式预报的3类主要非对流云。这3类非对流云均是大尺度的,GCM的网格能显示分辨,但在垂直方向如何提高GCM的分辨率问题仍是一个有待研究的问题。(3)在GCM中如何模拟冷海水上空的层云和赤道ITCZ所对应的大范围卷云和卷层云是十分困难和必要的。(4)通过对东亚及西太平洋区域非对流云系的个例分析,可以认为在新一代大气环流模式中,应显式预报行星大槽及赤道辐合带所对应的非对流云系。在模拟这些非对流云系时,应考虑它们的生消过程、平流过程与辐射过程。由于一段时间内大气环流模式尚难以分辨锋面与α中尺度的气旋,因此有必要在GCM中参数化这些系统,或采用更小的网格距。至于对非对流云所对应的降水参数化问题的研究,需要进一步的观测为基础。     

P-σ坐标系区域气候模式与GCM的嵌套试验

将P-σ坐标系区域气候模式与大气环流模式（GCM）单向嵌套，对我国1998年夏季长江流域严重洪涝进行模拟试验，并与GCM的模拟结果进行了比较。试验表明，嵌套的区域气候模式对降水场的模拟结果较GCM的结果有明显的改进，这是由于P-σ坐标系区域气候模式能够更真实地描述地形的动力和热力作用，因而能更准确地模拟青藏高原及其邻近地区的气压系统，在一定程度上弥补了低分辨率的GCM模拟在高原地区的不足，文中指出，与GCM嵌套的区域气候模式比GCM能够更有效地模拟区域气候的变化，尤其是对区域气候性特征比较明显的地区。     

P-σ区域气候模式对东亚副热带西风急流的数值模拟

为评估P-σ九层区域气候模式模拟对流层上层东亚副热带西风急流季节变化的能力,比较模式模拟的东亚副热带西风急流季节变化与NCEP/NCAR再分析资料之间的差异及其与对流层中上层大气南北温度差异的关系。结果表明,模式模拟东亚副热带西风急流的能力在洋面上空强于大陆上空,模拟低纬度急流的能力好于高纬度。模拟的东亚副热带西风急流垂直结构、水平结构和季节变化等的主要特征与NCEP/NCAR再分析资料基本一致,但模拟的急流强度全年偏弱。分析急流与对流层中上层经向温度梯度的季节变化发现,急流出现的位置总是对应着经向温度梯度较大区域,急流中心有随气温南北差异大值中心移动的趋势,急流中心与最大温差中心相对应,表明急流中心的位置变化是对气温南北差异季节变化的响应。与再分析资料相比,模拟的经向温度梯度比再分析资料偏小约2K/10纬距,与此相对应的模拟的急流中心风速偏小约10 m.s-1。由于大气温度变化与非绝热加热有关,进一步分析发现,模式模拟的夏季副热带急流偏差与东亚地区的地面感热及潜热等非绝热加热的模拟偏差具有密切的关系。     

论区域气候模式与全球模式嵌套时边界区的选择

做了3个试验,第一个试验只用大气环流模式(GCM),主要考察GCM的性能并确定其误差的区域分布.后两个为对比试验,一个试验中,将区域气候模式(RCM)(NjU-RCM)的侧边界放在全球模式(L9R15)中我们感兴趣的区域,未考虑侧边界区GCM的误差大小,另一个试验中,RCM的侧边界位置根据GCM预报误差的空间分布选取,使其落在GCM预报误差较小的区域.3个试验都对1998年5、6、7月份中国区域的降水过程进行了模拟和比较.结果表明:单独使用GCM的效果最差;当用GCM-RCM嵌套模式对区域气候进行预测时,GCM侧边界值的误差对RCM的模拟结果有显著的影响,嵌套侧边界若选择在GCM系统性误差较小的地区,模拟或预测效果会有明显的改进.     

季节尺度区域气候模拟适应调整时间选取问题的数值试验

文中利用区域气候模式RegCM3,以1998年夏季中国异常气候事件为例,对季节尺度区域气候模拟适应调整时间的选取问题进行了数值研究。共做了11个试验,每个试验的适应调整时间最短为10 d,最长为6个月,以检验适应调整时间长短对夏季中国异常气候事件模拟结果的影响。结果表明:对于大气变量而言,模式通常在经过4—8 d的适应调整时间后,就进入"气候模态"运行,此后模拟误差主要是由于模式对区域内大气过程描述能力不足造成的,对适应调整时间选取不再敏感,这进一步证实了区域气候模拟是一个边值问题的观点。各气候区平均降水量模拟结果受适应调整时间影响也不大,但不同的适应调整时间对降水分布格局模拟将产生一定影响,降水分布模拟结果随适应调整时间的不同存在一定的不确定性,这种不确定性通常出现在强降水发生区域。总之,对于季节尺度降水模拟,适应调整时间大于2个月效果更好。对降水分布格局模拟误差和东亚夏季风系统进退过程之间关系的进一步分析发现,模式对受夏季风系统影响比较大的区域模拟的降水相关系数变化性也比较大,因此,发展合适的积云对流参数化方案以提高受夏季风系统直接影响区域强降水过程的描述能力是改进区域气候模式对中国区域夏季气候模拟效果的有效途径。     

西北太平洋台风季节预报的数值模拟

利用中尺度气象模式WRF（weather research and forecasting）对2006年7月1日-9月30日的西北太平洋夏季台风进行了动力季节预报试验。结果表明：1）在对3个月以内的台风作动力季节预报试验时,WRF模式模拟的台风总个数与实况接近,模式模拟的总登陆台风数与实况相比偏小。从各月模拟情况看,台风总数与登陆数的模拟均与实况有差距。WRF模式对台风强度的模拟总体偏弱。2）WRF在模拟2006年7q月台风以及平均高度场、水平风垂直切变时,7月与实况接近,随时间增长,与实况的差别明显增大．WRF模式具有一定的台风动力季节预报能力,但其预报时限有待探讨。     

Winter season stratospheric circulation in the SAMIL/LASG general circulation model

In this paper, we examine the performance of the 26-level version of the SAMIL/LASG GCM (R42/L26) in simulating the seasonal cycle and perpetual winter mean stratospheric circulation as well as its variability by comparing them with the NCEP/NCAR reanalysis. The results show that the model is capable of reproducing many key features of the climatology and seasonal variation of the stratospheric circulation despite that the model’s mean polar vortex is stronger and more zonally symmetric compared to the obse...     

A Coupled General Circulation Model for the Tropical Pacific Ocean and Global Atmosphere

On the basis of Zeng’s theoretical design, a coupled general circulation model (CGCM) is developed with its characteristics different from other CGCMs such as the unified vertical coordinates and subtraction of the standard stratification for both atmosphere and ocean, available energy consideration, and so on. The oceanic component is a free surface tropical Pacific Ocean GCM between 30oN and 30oS with horizontal grid spacing of 1o in latitude and 2o in longitude, and with 14 vertical layers. The atmospheric component it a global GCM with low-resolution of 4o in latitude and 5o in longitude, and two layers or equal man in the vertical between the surface and 200 hPa. The atmospheric GCM includes comprehensive physical processes. The coupled model is subjected to seasonally-varying cycle. Several coupling experiments, ranging from straight forward coupling without flux correction to one with flux correction, and to so-called predictor-corrector monthly coupling (PCMC), are conducted to show the existence and final controlling of the climate drift in the coupled system. After removing the climate drift with the PCMC scheme, the coupled model is integrated for more than twenty years. The results show reasonable simulations of the annual mean and its seasonal cycle of the atmospheric and oceanic circulation. The model also produces the coherent interannual variations of the climate system, manifesting the observed El Ni?o / Southern Oscillation (ENSO).     

The WAMME regional model intercomparison study

Results from five regional climate models (RCMs) participating in the West African Monsoon Modeling and Evaluation (WAMME) initiative are analyzed. The RCMs were driven by boundary conditions from National Center for Environmental Prediction reanalysis II data sets and observed sea-surface temperatures (SST) over four May–October seasons, (2000 and 2003–2005). In addition, the simulations were repeated with two of the RCMs, except that lateral boundary conditions were derived from a continuous global climate model (GCM) simulation forced with observed SST data. RCM and GCM simulations of precipitation, surface air temperature and circulation are compared to each other and to observational evidence. Results demonstrate a range of RCM skill in representing the mean summer climate and the timing of monsoon onset. Four of the five models generate positive precipitation biases and all simulate negative surface air temperature biases over broad areas. RCM spatial patterns of June–September mean precipitation over the Sahel achieve spatial correlations with observational analyses of about 0.90, but within two areas south of 10°N the correlations average only about 0.44. The mean spatial correlation coefficient between RCM and observed surface air temperature over West Africa is 0.88. RCMs show a range of skill in simulating seasonal mean zonal wind and meridional moisture advection and two RCMs overestimate moisture convergence over West Africa. The 0.5° computing grid enables three RCMs to detect local minima related to high topography in seasonal mean meridional moisture advection. Sensitivity to lateral boundary conditions differs between the two RCMs for which this was assessed. The benefits of dynamic downscaling the GCM seasonal climate prediction are analyzed and discussed.     

Modeling the Tropical Pacific Ocean Using a Regional Coupled Climate Model

A high-resolution tropical Pacific general circulation model (GCM) coupled to a global atmospheric GCM is described in this paper. The atmosphere component is the 5°×4°global general circulation model of the Institute of Atmospheric Physics (IAP) with 9 levels in the vertical direction. The ocean component with a horizontal resolution of 0.5°, is based on a low-resolution model (2°×1°in longitude-latitude).Simulations of the ocean component are first compared with its previous version. Results show that the enhanced ocean horizontal resolution allows an improved ocean state to be simulated; this involves (1) an apparent decrease in errors in the tropical Pacific cold tongue region, which exists in many ocean models,(2) more realistic large-scale flows, and (3) an improved ability to simulate the interannual variability and a reduced root mean square error (RMSE) in a long time integration. In coupling these component models, a monthly "linear-regression" method is employed to correct the model's exchanged flux between the sea and the atmosphere. A 100-year integration conducted with the coupled GCM (CGCM) shows the effectiveness of such a method in reducing climate drift. Results from years 70 to 100 are described.The model produces a reasonably realistic annual cycle of equatorial SST. The large SSTA is confined to the eastern equatorial Pacific with little propagation. Irregular warm and cold events alternate with a broad spectrum of periods between 24 and 50 months, which is very realistic. But the simulated variability is weaker than the observed and is also asymmetric in the sense of the amplitude of the warm and cold events.     

Compilation method for 1 km grid data of monthly mean air temperature for quantitative assessments of climate change impacts

A new method is proposed to compile 1 km grid data of monthly mean air temperature by dynamically downscaling general circulation model (GCM) data with a regional climate model (RCM). The downscaling method used is a technique referred to as the pseudoglobal warming method to reduce GCM bias. For the grid data, RCM data were corrected with data from an existing meteorological network. The correction model for the RCM bias was developed by stepwise multiple regression analysis using the difference in the monthly mean air temperatures between the observation and RCM output as a dependent variable and the geographical factors as independent variables. Our method corrected the RCM bias from 1.69°C to 0.58°C for the month of August in the 1990s (1990–1999).     

Performance of the OPA/ARPEGE-T21 global ocean-atmosphere coupled model

 The climatology of the OPA/ARPEGE-T21 coupled general circulation model (GCM) is presented. The atmosphere GCM has a T21 spectral truncation and the ocean GCM has a 2^°×1.5^° average resolution. A 50-year climatic simulation is performed using the OASIS coupler, without flux correction techniques. The mean state and seasonal cycle for the last 10 years of the experiment are described and compared to the corresponding uncoupled experiments and to climatology when available. The model reasonably simulates most of the basic features of the observed climate. Energy budgets and transports in the coupled system, of importance for climate studies, are assessed and prove to be within available estimates. After an adjustment phase of a few years, the model stabilizes around a mean state where the tropics are warm and resemble a permanent ENSO, the Southern Ocean warms and almost no sea-ice is left in the Southern Hemisphere. The atmospheric circulation becomes more zonal and symmetric with respect to the equator. Once those systematic errors are established, the model shows little secular drift, the small remaining trends being mainly associated to horizontal physics in the ocean GCM. The stability of the model is shown to be related to qualities already present in the uncoupled GCMs used, namely a balanced radiation budget at the top-of-the-atmosphere and a tight ocean thermocline. Received: 1 February 1996 / Accepted: 1 August 1996     

CoPIVEP: a theory-based analysis of coupled processes and interannual variability in the Equatorial Pacific in four coupled GCMs

 The interannual variability over the tropical Pacific and a possible link with the mean state or the seasonal cycle is examined in four coupled ocean-atmosphere general circulation models (GCM). Each model is composed of a high-resolution ocean GCM of either the tropical Pacific or near-global oceans coupled to a moderate-resolution atmospheric GCM, without using flux correction. The oceanic subsurface is considered to describe the mean state or the seasonal cycle through the analytical formulations of some potential coupled processes. These coupled processes characterise the zonal gradient of sea surface temperature (hereafter SST), the oceanic vertical gradient of temperature and the equatorial upwelling. The simulated SST patterns of the mean state and the interannual signals are generally too narrow. The grid of the oceanic model could control the structure of the SST interannual signals while the behaviour of the atmospheric model could be important in the link between the oceanic surface and the subsurface. The first SST EOFs are different between the coupled models, however, the second SST EOFs are quite similar and could correspond to the return to the normal state while that of the observations (COADS) could favour the initial anomaly. All the models seem to simulate a similar equatorial wave-like dynamics to return to the normal state. The more the basic state is unstable from the coupled processes point of view, the more the interannual signal are high. It seems that the basic state could control the intensity of the interannual variability. Two models, which have a significant seasonal variation of the interannual variance, also have a significant seasonal variation of the instability with a few months lag. The potential seasonal phase locking of the interannual fluctuations need to be examined in more models to confirm its existence in current tropical GCMs. Received: 30 July 1999 / Accepted: 25 April 2000     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

Annual and seasonal climate and climatic changes in the Canadian prairies simulated by the CCC GCM

Abstract

As part of a study on the effects of climatic variability and change on the sustainability of agriculture in Alberto, the modelling performance of the second‐generation Canadian Climate Centre GCM (general circulation model) is examined. For the region in general, the simulation of 1 × CO₂ mean temperature is generally better than that for mean precipitation, and summer is the season best modelled for each variable. At the scale of individual grid squares, DJF (December, January, February) (temperature) and JJA (June, July, August) (precipitation) are the seasons best modelled. The GCM‐simulated increases in mean annual temperature resulting from a doubling of CO₂ are of the order of 5 to 6°C in the Prairie region, with much of this increase resulting from substantial warming in the winter and spring. Increases in mean annual precipitation are of the order of 50 to 150 mm (changes of +5 to +15%), with the greatest changes again occurring in winter and spring. As far as the limited GCM run durations allow, temperature and precipitation variance generally show no significant changes from a 1 × CO₂ to a 2 × CO₂ climate. Increased precipitation in winter and spring does not result in greater snow accumulations owing to the magnitude of warming; and significant decreases in soil moisture content occur in summer and fall. The resulting effects on the growing season and moisture regime have the potential to affect agricultural practices in the area.     

A comparison of the climatology of a tropospherestratosphere-mesosphere model with observations

Mean fields from a perpetual January simulation of a GCM extending from the surface to 0.01 hPa (near 80 km) are compared to observations. The zonal mean temperature and wind fields correspond quite well with reality; the low stratosphere, especially in the polar night, is too cold, but warmer than in the original version of the model, with an upper boundary at 25 hPa. Mean fields at standard levels show that the major features of the troposphere are represented by the model, but rather over emphasised; the stratospheric winter polar vortex is too strong, too cold, and too barotropic; it resembles an `undisturbed' January rather than the climatology. Differences in the stationary eddy activity between the extended and orginal versions of the model are noted, and used to explain some differences between the two simulations.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 für Meteorology. Guest Editor for these papers is Dr. L. Dümenil