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1.
Andreas Sterl Richard Bintanja Laurent Brodeau Emily Gleeson Torben Koenigk Torben Schmith Tido Semmler Camiel Severijns Klaus Wyser Shuting Yang 《Climate Dynamics》2012,39(11):2631-2657
EC-Earth is a newly developed global climate system model. Its core components are the Integrated Forecast System (IFS) of the European Centre for Medium Range Weather Forecasts (ECMWF) as the atmosphere component and the Nucleus for European Modelling of the Ocean (NEMO) developed by Institute Pierre Simon Laplace (IPSL) as the ocean component. Both components are used with a horizontal resolution of roughly one degree. In this paper we describe the performance of NEMO in the coupled system by comparing model output with ocean observations. We concentrate on the surface ocean and mass transports. It appears that in general the model has a cold and fresh bias, but a much too warm Southern Ocean. While sea ice concentration and extent have realistic values, the ice tends to be too thick along the Siberian coast. Transports through important straits have realistic values, but generally are at the lower end of the range of observational estimates. Exceptions are very narrow straits (Gibraltar, Bering) which are too wide due to the limited resolution. Consequently the modelled transports through them are too high. The strength of the Atlantic meridional overturning circulation is also at the lower end of observational estimates. The interannual variability of key variables and correlations between them are realistic in size and pattern. This is especially true for the variability of surface temperature in the tropical Pacific (El Ni?o). Overall the ocean component of EC-Earth performs well and helps making EC-Earth a reliable climate model. 相似文献
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3.
June-Yi Lee Bin Wang I.-S. Kang J. Shukla A. Kumar J.-S. Kug J. K. E. Schemm J.-J. Luo T. Yamagata X. Fu O. Alves B. Stern T. Rosati C.-K. Park 《Climate Dynamics》2010,35(2-3):267-283
Given observed initial conditions, how well do coupled atmosphere–ocean models predict precipitation climatology with 1-month lead forecast? And how do the models’ biases in climatology in turn affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981–2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models’ ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian–Australian monsoon system over four major sub-domains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated. 相似文献
4.
This paper shows demonstrable improvement in the global seasonal climate predictability of boreal summer (at zero lead) and fall (at one season lead) seasonal mean precipitation and surface temperature from a two-tiered seasonal hindcast forced with forecasted SST relative to two other contemporary operational coupled ocean–atmosphere climate models. The results from an extensive set of seasonal hindcasts are analyzed to come to this conclusion. This improvement is attributed to: (1) The multi-model bias corrected SST used to force the atmospheric model. (2) The global atmospheric model which is run at a relatively high resolution of 50 km grid resolution compared to the two other coupled ocean–atmosphere models. (3) The physics of the atmospheric model, especially that related to the convective parameterization scheme. The results of the seasonal hindcast are analyzed for both deterministic and probabilistic skill. The probabilistic skill analysis shows that significant forecast skill can be harvested from these seasonal hindcasts relative to the deterministic skill analysis. The paper concludes that the coupled ocean–atmosphere seasonal hindcasts have reached a reasonable fidelity to exploit their SST anomaly forecasts to force such relatively higher resolution two tier prediction experiments to glean further boreal summer and fall seasonal prediction skill. 相似文献
5.
Torben Koenigk Christof K?nig Beatty Mihaela Caian Ralf D?scher Klaus Wyser 《Climate Dynamics》2012,38(11-12):2389-2408
Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2?m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations. 相似文献
6.
经过近60年的发展,我国短期气候预测技术和方法也有了长足进步。近年来,一些新的预报技术和机理认识不断应用于短期气候预测业务。ARGO海洋观测资料的使用大大提高了业务模式的预测技巧,新一代气候预测模式系统已经投入准业务化运行,研发了多种模式降尺度释用技术,多模式气候预测产品解释应用集成系统(MODES)和动力-统计结合的季节预测系统(FODAS)逐渐应用于业务中,大气季节内振荡(MJO)逐步在延伸期预报中得到应用。近年来,对全球海洋、北极海冰、欧亚积雪、南半球环流系统对东亚季风影响的新认识也不断引入到短期气候预测业务中。这些新技术和新认识的应用极大提高了我国短期气候预测的业务能力。 相似文献
7.
Torben Koenigk Laurent Brodeau Rune Grand Graversen Johannes Karlsson Gunilla Svensson Michael Tjernström Ulrika Willén Klaus Wyser 《Climate Dynamics》2013,40(11-12):2719-2743
The Arctic climate change is analyzed in an ensemble of future projection simulations performed with the global coupled climate model EC-Earth2.3. EC-Earth simulates the twentieth century Arctic climate relatively well but the Arctic is about 2 K too cold and the sea ice thickness and extent are overestimated. In the twenty-first century, the results show a continuation and strengthening of the Arctic trends observed over the recent decades, which leads to a dramatically changed Arctic climate, especially in the high emission scenario RCP8.5. The annually averaged Arctic mean near-surface temperature increases by 12 K in RCP8.5, with largest warming in the Barents Sea region. The warming is most pronounced in winter and autumn and in the lower atmosphere. The Arctic winter temperature inversion is reduced in all scenarios and disappears in RCP8.5. The Arctic becomes ice free in September in all RCP8.5 simulations after a rapid reduction event without recovery around year 2060. Taking into account the overestimation of ice in the twentieth century, our model results indicate a likely ice-free Arctic in September around 2040. Sea ice reductions are most pronounced in the Barents Sea in all RCPs, which lead to the most dramatic changes in this region. Here, surface heat fluxes are strongly enhanced and the cloudiness is substantially decreased. The meridional heat flux into the Arctic is reduced in the atmosphere but increases in the ocean. This oceanic increase is dominated by an enhanced heat flux into the Barents Sea, which strongly contributes to the large sea ice reduction and surface-air warming in this region. Increased precipitation and river runoff lead to more freshwater input into the Arctic Ocean. However, most of the additional freshwater is stored in the Arctic Ocean while the total Arctic freshwater export only slightly increases. 相似文献
8.
H. Goelzer P. Huybrechts M. F. Loutre H. Goosse T. Fichefet A. Mouchet 《Climate Dynamics》2011,37(5-6):1005-1018
We use the Earth system model of intermediate complexity LOVECLIM to show the effect of coupling interactive ice sheets on the climate sensitivity of the model on a millennial time scale. We compare the response to a 2×CO2 warming scenario between fully coupled model versions including interactive Greenland and Antarctic ice sheet models and model versions with fixed ice sheets. For this purpose an ensemble of different parameter sets have been defined for LOVECLIM, covering a wide range of the model??s sensitivity to greenhouse warming, while still simulating the present-day climate and the climate evolution over the last millennium within observational uncertainties. Additional freshwater fluxes from the melting ice sheets have a mitigating effect on the model??s temperature response, leading to generally lower climate sensitivities of the fully coupled model versions. The mitigation is effectuated by changes in heat exchange within the ocean and at the sea?Cair interface, driven by freshening of the surface ocean and amplified by sea?Cice-related feedbacks. The strength of the effect depends on the response of the ice sheets to the warming and on the model??s climate sensitivity itself. The effect is relatively strong in model versions with higher climate sensitivity due to the relatively large polar amplification of LOVECLIM. With the ensemble approach in this study we cover a wide range of possible model responses. 相似文献
9.
Of great importance for guiding numerical weather and climate predictions, understanding predictability of the atmosphere in the ocean − atmosphere coupled system is the first and critical step to understand predictability of the Earth system. However, previous predictability studies based on prefect model assumption usually depend on a certain model. Here we apply the predictability study with the Nonlinear Local Lyapunov Exponent and Attractor Radius to the products of multiple re-analyses and forecast models in several operational centers to realize general predictability of the atmosphere in the Earth system. We first investigated the predictability characteristics of the atmosphere in NCEP, ECMWF and UKMO coupled systems and some of their uncoupled counterparts and other uncoupled systems. Although the ECMWF Integrated Forecast System shows higher skills in geopotential height over the tropics, there is no certain model providing the most precise forecast for all variables on all levels and the multi-model ensemble not always outperforms a single model. Improved low-frequency signals from the air − sea and stratosphere − troposphere interactions that extend predictability of the atmosphere in coupled system suggests the significance of air − sea coupling and stratosphere simulation in practical forecast development, although uncertainties exist in the model representation for physical processes in air − sea interactions and upper troposphere. These inspire further exploration on predictability of ocean and stratosphere as well as sea − ice and land processes to advance our understanding of interactions of Earth system components, thus enhancing weather − climate prediction skills.
相似文献10.
Both observational and numerical studies demonstrate the sensitivity of the atmosphere to variations in the extent and mass of snow cover. There is therefore a need for simple but realistic snow parameterizations in forecast and climate models. A new snow hydrology scheme has recently been developed at Météo-France for use in the ARPEGE climate model and has been successfully tested against local field measurements in stand-alone experiments. This study describes the global validation of the parameterization in a 3-year integration for the present-day climate within the T42L30 version of ARPEGE. Results are compared with those from a control simulation and with available observed climatologies, in order to assess the impact of the new snow parameterization on the simulated surface climate. The seasonal cycle of the Northern Hemisphere snow cover is clearly improved when using the new scheme. The snow pack is still slightly overestimated in winter, but its poleward retreat is better reproduced during the melting season. As a consequence, the modified GCM performs well in simulating the springtime continental heating, which may play a strong role in the simulation of the Asian summer monsoon. 相似文献
11.
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。 相似文献
12.
区域气候模拟研究及其应用进展 总被引：10，自引：3，他引：7
区域气候模拟研究在过去十几年里取得了显著的进步。经过广泛的发展和不断的检验,区域气候模式现在已经成为气候研究和业务预报的重要工具。目前已经发表了很多令人鼓舞的结果,其中包括过去极端气候事件的模拟,当前气候发展演变和未来气候变化的预测,特别是对月和季节尺度气候的模拟与预测。通过对高分辨率和动力连续的区域气候模式结果的分析,人们对于周-季节时间尺度的各种物理过程,包括陆面和水文过程、边界层、云和降水、云-辐射相互作用的认识也在不断的深入。然而,区域气候是多尺度扰动(如中尺度、天气尺度、行星尺度扰动)和多圈层系统(如大气圈、生物圈、水圈、冰雪圈、陆面)相互作用的结果,同时物理过程本身具有不确定性,人们对一些复杂的物理过程,特别是土壤湿度作用以及云-气候反馈过程也缺乏深刻的理解,因此该领域的研究还面临着很多挑战。作者重点总结并评述了区域气候模式对现在和未来区域气候模拟、极端天气和气候事件模拟、物理过程研究、短期气候预测几方面应用的研究进展,最后讨论了区域气候模式发展在上述各方面,特别是周-次季节时间尺度区域天气和气候的模拟与预测所面临的挑战和应用前景。 相似文献
13.
Gerald A. Meehl 《Climate Dynamics》1990,5(1):19-33
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 相似文献
14.
Inherent sea ice predictability in the rapidly changing Arctic environment of the Community Climate System Model, version 3 总被引：2，自引：1，他引：1
Seasonal predictions of Arctic sea ice have typically been based on statistical regression models or on results from ensemble ice model forecasts driven by historical atmospheric forcing. However, in the rapidly changing Arctic environment, the predictability characteristics of summer ice cover could undergo important transformations. Here global coupled climate model simulations are used to assess the inherent predictability of Arctic sea ice conditions on seasonal to interannual timescales within the Community Climate System Model, version 3. The role of preconditioning of the ice cover versus intrinsic variations in determining sea ice conditions is examined using ensemble experiments initialized in January with identical ice?Cocean?Cterrestrial conditions. Assessing the divergence among the ensemble members reveals that sea ice area exhibits potential predictability during the first summer and for winter conditions after a year. The ice area exhibits little potential predictability during the spring transition season. Comparing experiments initialized with different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher potential predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1?year. In all regimes, ice thickness has high potential predictability for at least 2?years. 相似文献
15.
R. Bintanja 《Theoretical and Applied Climatology》1997,56(1-2):1-24
Summary In this paper a simple climate model is presented which is used to perform some sensitivity experiments. The atmospheric part is represented by a vertically and zonally averaged layer in which the surface air temperature, radiative fluxes at the surface and at the top of the atmosphere, the turbulent fluxes between atmosphere and surface and the snow cover are calculated. This atmospheric layer is coupled to a two-dimensional advection-diffusion ocean model in which the zonal overturning pattern is prescribed. The ocean model evaluates the temperature distribution, the amount of sea-ice and the meridional and vertical heat fluxes. The present-day climate simulated by the model compares reasonably well with observations of the seasonal and latitudinal distribution of temperature, radiation, surface alebdo, sea-ice and snow cover and meridional energy fluxes. Then, the sensitivity of the model-simulated present-day climate to perturbations in the incident solar radiation at the top of the atmosphere is investigated. The temperature response displays large latitudinal and seasonal variations, which is in qualitative agreement with results obtained with other climate models. It is found that the seasonal variation of sea-ice cover (and hence, the effective oceanic heat capacity) is one of the most important elements determining seasonal variations in climate sensitivity. Differences in sensitivity between the seasonal and annual mean version of the model are discussed. Finally, the equilibrium response to perturbations in some selected model variables is presented; these variables include meridional diffusion coefficients, drag coefficient, sea-ice thickness, atmospheric CO2-concentration and cloud optical thickness.With 13 Figures 相似文献
16.
The characteristics of the El-Nino Southern Oscillation (ENSO) simulated in free integrations using two versions of the Seoul National University (SNU) ocean–atmosphere coupled global climate model (CGCM) are examined. A revised version of the SNU CGCM is developed by incorporating a reduced air–sea coupling interval (from 1?day to 2?h), a parameterization for cumulus momentum transport, a minimum entrainment rate threshold for convective plumes, and a shortened auto-conversion time scale of cloud water to raindrops. With the revised physical processes, lower tropospheric zonal wind anomalies associated with the ENSO-related sea surface temperature anomalies (SSTA) are represented with more realism than those in the original version. From too weak, the standard deviation of SST over the eastern Pacific becomes too strong in the revised version due to the enhanced air–sea coupling strength and intraseasonal variability associated with ENSO. From the oceanic side, the stronger stratification and the shallower-than-observed thermocline over the eastern Pacific also contribute to the excessive ENSO. The impacts of the revised physical processes on the seasonal predictability are investigated in two sets of the hindcast experiment performed using the two versions of CGCMs. The prediction skill measured by anomaly correlation coefficients of monthly-mean SSTA shows that the new version has a higher skill over the tropical Pacific regions compared to the old version. The better atmospheric responses to the ENSO-related SSTA in the revised version lead to the basin-wide SSTA maintained and developed in a manner that is closer to observations. The symptom of an excessively strong ENSO of the new version in the free integration is not prominent in the hindcast experiment because the thermocline depth over the eastern Pacific is maintained as initialized over the arc of time of the hindcast (7?months). 相似文献
17.
An extensive set of boreal summer seasonal hindcasts from a two tier system is compared with corresponding seasonal hindcasts from two other coupled ocean–atmosphere models for their seasonal prediction skill (for precipitation and surface temperature) of the Asian summer monsoon. The unique aspect of the two-tier system is that it is at relatively high resolution and the SST forcing is uniquely bias corrected from the multi-model averaged forecasted SST from the two coupled ocean–atmosphere models. Our analysis reveals: (a) The two-tier forecast system has seasonal prediction skill for precipitation that is comparable (over the Southeast Asian monsoon) or even higher (over the South Asian monsoon) than the coupled ocean–atmosphere. For seasonal anomalies of the surface temperature the results are more comparable across models, with all of them showing higher skill than that for precipitation. (b) Despite the improvement from the uncoupled AGCM all models in this study display a deterministic skill for seasonal precipitation anomalies over the Asian summer monsoon region to be weak. But there is useful probabilistic skill for tercile anomalies of precipitation and surface temperature that could be harvested from both the coupled and the uncoupled climate models. (c) Seasonal predictability of the South Asian summer monsoon (rainfall and temperature) does seem to stem from the remote ENSO forcing especially over the Indian monsoon region and the relatively weaker seasonal predictability in the Southeast Asian summer monsoon could be related to the comparatively weaker teleconnection with ENSO. The uncoupled AGCM with the bias corrected SST is able to leverage this teleconnection for improved seasonal prediction skill of the South Asian monsoon relative to the coupled models which display large systematic errors of the tropical SST’s. 相似文献
18.
Intermediate models of the coupled tropical atmosphere?Cocean system have been used to illuminate the physics of interannual climate phenomenon such as El Ni?o Southern Oscillation (ENSO) in the tropical Pacific and to explore how the tropics might respond to a forcing such as changing insolation (Milankovitch) or atmospheric carbon dioxide. Importantly, most of the intermediate models are constructed as anomaly models: models that evolve on a prescribed climatological mean state, which is typically prescribed and done so on a rather ad hoc basis. Here we show how the observed climatological mean state fields [ocean currents and upwelling, sea surface temperature (SST) and atmospheric surface winds] can be incorporated into a linearized intermediate model of the tropical coupled atmosphere?Cocean system: called Linear Ocean?CAtmosphere Model (LOAM), it is a linearized version of the Zebiak and Cane model. With realistic, seasonally varying mean state fields, we find that the essential physics of the ENSO mode is very similar to that in the original model and to that in the observations and that the observed mean fields support an ENSO mode that is stable to perturbations. Thus, our results provide further evidence that ENSO is generated and maintained by stochastic (uncoupled) perturbations. The method that we have outlined can be used to assimilate any set of ocean and atmosphere climatological data into the linearized atmosphere?Cocean model. In a companion paper, we apply this same method to incorporate mean field output from two global climate models into the linearised model. We use the latter to diagnose the physics of the leading coupled mode (ENSO) that is supported by the climate models, and to illuminate why the structure and variance in the ENSO mode changes in the models when they are forced by early Holocene and Last Glacial Maximum boundary conditions. 相似文献
19.
Martina Weiss Bart van den Hurk Reindert Haarsma Wilco Hazeleger 《Climate Dynamics》2012,39(11):2733-2746
Climate models often use a simplified and static representation of vegetation characteristics to determine fluxes of energy, momentum and water vapour between surface and lower atmosphere. In order to analyse the impact of short term variability in vegetation phenology, we use remotely-sensed leaf area index and albedo products to examine the role of vegetation in the coupled land–atmosphere system. Perfect model experiments are carried out to determine the impact of realistic temporal variability of vegetation on potential predictability of evaporation and temperature, as well as model skill of EC-Earth simulations. The length of the simulation period is hereby limited by the availability of satellite products to 2000–2010. While a realistic representation of vegetation positively influences the simulation of evaporation and its potential predictability, a positive impact on 2?m temperature is of smaller magnitude, regionally confined and more pronounced in climatically extreme years. 相似文献
20.
热带大气季节内振荡 (Madden-Julian oscillation,MJO) 是次季节-季节时间尺度气候变率的支配模态。它不仅对低纬度地区天气气候产生重要影响,还能够通过经向传播和激发大气遥相关波列对中高纬度地区产生影响,是延伸期尺度最重要的可预报性来源。因此,MJO预报是次季节-季节气候预测中极为重要的部分,近年来受到国际学术界广泛关注。该文回顾了MJO预报发展历史,概述了当前国际上主要科研业务机构的MJO预报发展现状。目前基于统计方法和气候模式的MJO预报研究取得了较大进展,特别是多个耦合气候模式和一种基于时空投影方法的统计模型均能够显著提升MJO预报技巧 (有效预报可达20 d以上)。该文还介绍了中国气象局国家气候中心在MJO预报技术发展和业务系统研制方面的新进展,当前基于第2代大气环流模式的MJO业务预报填补了国内空白,技巧为16~17 d,而耦合气候模式试验的技巧已达到约20 d。总体来看,利用耦合模式预报MJO是未来发展的主要方向,其中,面向MJO的模式初始化和集合预报新方法研究将是关注重点。 相似文献