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1.
不同海温强迫的月动力延伸集合预报试验 总被引：1，自引：0，他引：1
利用全球谱模式T106L19和增长模繁殖法（BGM）建立了月动力延伸集合预报系统,基于气候海表面温度（SST）和预测海表面温度,设计了三组集合预报试验,一组为气候SST作为模式下边界条件的集合预报试验（CSST试验）,另一组为预测SST作为模式的下边界条件的集合预报试验（FSST试验）,第三组为前两组试验的集合预报结果之和（AVE30试验）,对两种海温强迫分别进行了48个月的试验,并对预报结果进行了检验和分析。结果表明：相对于单一的控制预报,不管是CSST试验还是FSST试验,利用BGM方法制作的初值集合预报能显著提高月平均环流的预报技巧,集合预报对PNA区域的预报技巧改进显著,特别是预测SST强迫有正的贡献;同时考虑初值和边值不确定性影响的集合预报试验（AVE30试验）,其全球预报技巧不仅高于控制预报,也分别高于FSST试验和CSST试验,这说明要提高月延伸预报技巧,必须同时考虑初值和边值的影响;大气对SST强迫的响应在模式积分10天开始显著,SST对第二旬和第三旬的作用直接影响月平均环流的预报效果,而SST对第二旬和第三旬预报的影响不仅与SST本身变化有关,还与初值有关,不同的初值其作用不同;集合预报对我国夏季月平均温度分布具有较强预报能力,采用预报海温强迫的预报结果,总体上优于气候海温强迫的结果。 相似文献
2.
Hervé Douville 《Climate Dynamics》2005,24(4):373-391
While time-slice simulations with atmospheric general circulation models (GCMs) have been used for many years to regionalize climate projections and/or assess their uncertainties, there is still no consensus about the method used to prescribe sea surface temperature (SST) in such experiments. In the present study, the response of the Indian summer monsoon to increasing amounts of greenhouse gases and sulfate aerosols is compared between a reference climate scenario and three sets of time-slice experiments, consisting of parallel integrations for present-day and future climates. Different monthly mean SST boundary conditions have been tested in the present-day integrations: raw climatological SST derived from the reference scenario, observed climatological SST, and observed SST with interannual variability. For future climate, the SST forcing has been obtained by superimposing climatological monthly mean SST anomalies derived from the reference scenario onto the present-day SST boundary conditions. None of these sets of time-slice experiments is able to capture accurately the response of the Indian summer monsoon simulated in the transient scenario. This finding suggests that the ocean–atmosphere coupling is a fundamental feature of the climate system. Neglecting the SST feedback and variability at the intraseasonal to interannual time scales has a significant impact on the projected monsoon response to global warming. Adding interannual variability in the prescribed SST boundary conditions does not mitigate the problem, but can on the contrary reinforce the discrepancies between the forced and coupled experiments. The monsoon response is also shown to depend on the simulated control climate, and can therefore be sensitive to the use of observed rather than model-derived SSTs to drive the present-day atmospheric simulation, as well as to any approximation in the prescribed radiative forcing. While such results do not challenge the use of time-slice experiments for assessing uncertainties and understanding mechanisms in transient scenarios, they emphasize the need for high-resolution coupled atmosphere-ocean GCMs for dynamical downscaling, or at least for high-resolution atmospheric GCMs coupled with a slab or a regional ocean model. 相似文献
3.
Both seasonal potential predictability and the impact of SST in the Pacific on the forecast skill over China are investigated by using a 9-level global atmospheric general circulation model developed at the Institute of Atmospheric Physics under the Chinese Academy of Sciences (IAP9L-AGCM). For each year during 1970 to 1999, the ensemble consists of seven integrations started from consecutive observational daily atmospheric fields and forced by observational monthly SST. For boreal winter, spring and summer,the variance ratios of the SST-forced variability to the total variability and the differences in the spatial correlation coefficients of seasonal mean fields in special years versus normal years are computed respectively. It follows that there are slightly inter-seasonal differences in the model potential predictability in the Tropics. At northern middle and high latitudes, prediction skill is generally low in spring and relatively high either in summer for surface air temperature and middle and upper tropospheric geopotential height or in winter for wind and precipitation. In general, prediction skill rises notably in western China, especially in northwestern China, when SST anomalies (SSTA) in the Nino-3 region are significant. Moreover,particular attention should be paid to the SSTA in the North Pacific (NP) if one aims to predict summer climate over the eastern part of China, i.e., northeastern China, North China and southeastern China. 相似文献
4.
The relative influence of soil moisture and SST in climate predictability explored within ensembles of AMIP type experiments 总被引：4，自引：1，他引：4
Three ensembles of AMIP-type simulations using the Arpege-climat coupled land–atmosphere model have been designed to assess the relative influence of SST and soil moisture (SM) on climate variability and predictability. The study takes advantage of the GSWP2 land surface reanalysis covering the 1986–1995 period. The GSWP2 forcings have been used to derive a global SM climatology that is fully consistent with the model used in this study. One ensemble of ten simulations has been forced by climatological SST and the simulated SM is relaxed toward the GSWP2 reanalysis. Another ensemble has been forced by observed SST and SM is evolving freely. The last ensemble combines the observed SST forcing and the relaxation toward GSWP2. Two complementary aspects of the predictability have been explored, the potential predictability (analysis of variance) and the effective predictability (skill score). An analysis of variance has revealed the effects of the SST and SM boundary forcings on the variability and potential predictability of near-surface temperature, precipitation and surface evaporation. While in the tropics SST anomalies clearly maintain a potentially predictable variability throughout the annual cycle, in the mid-latitudes the SST forced variability is only dominant in winter and SM plays a leading role in summer. In a similar fashion, the annual cycle of the hindcast skill (evaluated as the anomalous correlation coefficient of the three ensemble means with respect to the “observations”) indicates that the SST forcing is the dominant contributor over the tropical continents and in the winter mid-latitudes but that SM is supporting a significant part of the skill in the summer mid-latitudes. Focusing on boreal summer, we have then investigated different aspects of the SM and SST contribution to climate variations in terms of spatial distribution and time-evolution. Our experiments suggest that SM is potentially an additional source of climate predictability. A realistic initialization of SM and a proper representation of the land–atmosphere feedbacks seem necessary to improve state-of-the-art dynamical seasonal predictions, but will be actually efficient only in the areas where SM anomalies are themselves predictable at the monthly to seasonal timescale (since remote effects of SM are probably much more limited than SST teleconnections). 相似文献
5.
Most estimates of the skill of atmospheric general circulation models (AGCMs) for forecasting seasonal climate anomalies have been based on simulations with actual observed sea surface temperatures (SSTs) as lower boundary forcing. Similarly estimates of the climatological response characteristics of AGCMs used for seasonal-to-interannual climate prediction generally rest on historical simulations using "perfect" SST forecasts. This work examines the errors and biases introduced into the seasonal precipitation response of an AGCM forced with persisted SST anomalies, which are generally considered to constitute a good prediction of SST in the first three-month season. The added uncertainty introduced by the persisted SST anomalies weakens, and in some cases nullifies, the skill of atmospheric predictions that is possible given perfect SST forcing. The use of persisted SST anomalies also leads to changes in local signal-to-noise characteristics. Thus, it is argued that seasonal-to-interannual forecasts using AGCMs should be interpreted relative to historical runs that were subject to the same strategy of boundary forcing used in the current forecast in order to properly account for errors and biases introduced by the particular SST prediction strategy. Two case studies are examined to illustrate how the sensitivity of the climate response to predicted SSTs may be used as a diagnostic to suggest improvements to the predicted SSTs. 相似文献
6.
Li Shi Harry H. Hendon Oscar Alves Matthew C. Wheeler David Anderson Guomin Wang 《Climate Dynamics》2011,37(1-2):313-324
The importance of initializing atmospheric intra-seasonal (stochastic) variations for prediction of the onset of the 1997/1998 El Ni?o is examined using the Australian Bureau of Meteorology coupled seasonal forecast model. A suite of 9-month forecasts was initialized on the 1st December 1996. Observed ocean initial conditions were used together with five different atmospheric initial conditions that sample a range of possible initial states of intra-seasonal (stochastic) variability, especially the Madden-Julian Oscillation (MJO), which is considered the primary stochastic variability of relevance to El Ni?o evolution. The atmospheric initial states were generated from a suite of atmosphere-only integrations forced by observed sea surface temperatures (SST). To the extent that low frequency variability of the tropical atmosphere is forced by slow variations in SST, these atmospheric states should all represent realistic low frequency atmospheric variability that was present in December 1996. However, to the extent that intra-seasonal variability is not constrained by SST, they should capture a range of intra-seasonal states, especially variations in the activity, phase and amplitude of the MJO. For each of these five states, a 20-member ensemble of coupled model forecasts was generated by the addition of small random perturbations to the SST field at the initial time. The ensemble mean from all five sets of forecasts resulted in El Ni?o but three of the sets produced substantially greater warming by months 4?C5 in the NINO3.4 region compared to the other two. The warmer group stemmed from stronger intra-seasonal westerly wind anomalies associated with the MJO that propagated eastward into the central Pacific during the first 1?C2?months of the forecast. These were largely absent in the colder group; the weakest of the colder group developed strong easterly wind anomalies, relative to the grand ensemble mean, that propagated into the central Pacific early in the forecast, thereby generating significantly weaker downwelling Kelvin waves in comparison to the warmer group. The strong reduction in downwelling Kelvin waves in the weakest case acted to limit the warming in the eastern Pacific, resulting in a ??Modoki?? type El Ni?o that is more focused in the central Pacific. Our results suggest that the intra-seasonal stochastic component of the atmospheric initial condition has an important and potentially predictable impact on the forecasts of the initial warming and flavour of the 1997/1998 El Ni?o. However, to the extent that atmospheric intra-seasonal variability is not predictable beyond a month or two, these results imply a limit to the accuracy with which the strength and perhaps the spatial distribution of an El Ni?o can ultimately be predicted. These results do not preclude a predictable role of the MJO and other intra-seasonal stochastic variability at longer lead times if some aspects of the stochastic variability are preconditioned by the evolving state of El Ni?o or other low frequency boundary forcing. 相似文献
7.
In the recent decade, operational seasonal prediction systems based on initialized coupled models have been developed. An analysis of how the predictability of seasonal means in the initialized coupled predictions evolves with lead-time is presented. Because of the short lead-time, such an analysis for the temporal behavior of seasonal predictability involves a mix of both the predictability of the first and the second kind. The analysis focuses on the lead-time dependence of ensemble mean variance, and the forecast spread. Further, the analysis is for a fixed target season of December?CJanuary?CFebruary, and is for sea surface temperature, rainfall, and 200-mb height. The analysis is based on a large set of hindcasts from an initialized coupled seasonal prediction system. Various aspects of predictability of the first and the second kind are highlighted for variables with long (for example, SST), and fast (for example, atmospheric) adjustment time scale. An additional focus of the analysis is how the predictability in the initialized coupled seasonal predictions compares with estimates based on the AMIP simulations. The results indicate that differences in the set up of AMIP simulations and coupled predictions, for example, representation of air?Csea interactions, and evolution of forecast spread from initial conditions do not change fundamental conclusion about the seasonal predictability. A discussion of the analysis presented herein, and its implications for the use of AMIP simulations for climate attribution, and for time-slice experiments to provide regional information, is also included. 相似文献
8.
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
9.
初始条件记忆和下垫面条件是延伸期可预报性的主要来源,它们在不同时段、不同区域的相对作用存在明显不同。利用中国国家气候中心最新一代大气环流模式BCC_AGCM,设计了由4组不同大气初值与海温边值构成的组合试验,研究了（大气）初值与（海温）边值对全球不同区域延伸期预报的相对作用。结果显示,模式预测技巧在3周以内强烈依赖于初值。在相同的边值条件强迫下,不同初值在月内尺度上的预测技巧差异非常明显,且在更长的时间尺度上,初值仍然能够提供一定的预测信息。从全球来看,边值强迫对预测技巧的影响从一周左右开始。在低层的850 hPa高度场上,边值的作用在热带地区于第4-5候与初值相当,其他区域的边值影响达到与初值相当的时间滞后于热带地区;在北半球500 hPa高度场上,边值的作用在热带地区第5候前后达到与初值作用相当,其他区域这个时间则推迟至第6候前后,比对低层的影响时间滞后1-2候;对于东亚地区而言,边值的贡献在第2候就已显现,对预测技巧产生了明显的改进。在延伸期尺度上,边值强迫主要作用的区域为低纬度区域,且对500 hPa高度场的影响更为稳定,在该区域第5候以后有较为明显的改进。初值与边值对延伸期预报都具有相当重要的作用,认识初、边值条件的相对作用能够为延伸期预报的改进奠定基础。 相似文献
10.
Sea surface temperature (SST) variations include negative feedbacks from the atmosphere, whereas SST anomalies are specified in stand-alone atmospheric general circulation simulations. Is the SST forced response the same as the coupled response? In this study, the importance of air–sea coupling in the Indian and Pacific Oceans for tropical atmospheric variability is investigated through numerical experiments with a coupled atmosphere-ocean general circulation model. The local and remote impacts of the Indian and Pacific Ocean coupling are obtained by comparing a coupled simulation with an experiment in which the SST forcing from the coupled simulation is specified in either the Indian or the Pacific Ocean. It is found that the Indian Ocean coupling is critical for atmospheric variability over the Pacific Ocean. Without the Indian Ocean coupling, the rainfall and SST variations are completely different throughout most of the Pacific Ocean basin. Without the Pacific Ocean coupling, part of the rainfall and SST variations in the Indian Ocean are reproduced in the forced run. In regions of large mean rainfall where the atmospheric negative feedback is strong, such as the North Indian Ocean and the western North Pacific in boreal summer, the atmospheric variability is significantly enhanced when air–sea coupling is replaced by specified SST forcing. This enhancement is due to the lack of the negative feedback in the forced SST simulation. In these regions, erroneous atmospheric anomalies could be induced by specified SST anomalies derived from the coupled model. The ENSO variability is reduced by about 20% when the Indian Ocean air–sea coupling is replaced by specified SST forcing. This change is attributed to the interfering roles of the Indian Ocean SST and Indian monsoon in western and central equatorial Pacific surface wind variations. 相似文献
11.
利用典型相关分析(CCA)方法建立统计气候预测模型，对我国冬季气温进行了预测试验，采用历史资料独立样本检验的方法，对预报技巧给出合理的评定。结果表明，使用CCA方法对我国冬季气温进行短期气候预测，有一定的预报技巧，对于特定地区和特定时期优选的因子场组合，可以取得较为满意的预报效果。大部分地区的季平均预报时效在2个季以内时，最佳预报相关系数在0.5以上。季平均的预报水平明显高于月平均的预报。海温场是所有因子场中最好的预报因子，不仅单独海温场的预报效果较好，而且与其他因子场组合后的预报水平还可以得到进一步提高。 相似文献
12.
The influence of mean climate on the seasonal cycle and the El Ni?o-Southern Oscillation (ENSO) in the tropical Pacific climate is investigated using the Climate Community System Model Version 3 (CCSM3). An empirical time-independent surface heat flux adjustment over the tropical ocean is applied to the oceanic component of CCSM3. In comparison with the control run, the heat flux-adjusted run simulates a more realistic mean climate not only for the sea surface temperature (SST) but also for wind stress and precipitation. Even though the heat flux adjustment is time-independent, the seasonal cycles of SST, wind stress and precipitation over the equatorial eastern Pacific are more realistic in the flux-adjusted simulation. Improvements in the representation of the ENSO variability in the heat flux-adjusted simulation include that the Nino3.4 SST index is less regular than a strong biennial oscillation in the control run. But some deficiencies also arise. For example, the amplitude of the ENSO variability is reduced in the flux-adjusted run. The impact of the mean climate on ENSO prediction is further examined by performing a series of monthly hindcasts from 1982 to 1998 using CCSM3 with and without the heat flux adjustment. The flux-adjusted hindcasts show slightly higher predictive skill than the unadjusted hindcasts with January initial conditions at lead times of 7?C9?months and July initial conditions at lead times of 9?C11?months. However, their differences during these months are not statistically significant. 相似文献
13.
A hybrid coupled model (HCM) for the tropical Pacific ocean-atmosphere system is employed for ENSO prediction. The HCM consists
of the Geophysical Fluid Dynamics Laboratory ocean general circulation model and an empirical atmospheric model. In hindcast
experiments, a correlation skill competitive to other prediction models is obtained, so we use this system to examine the
effects of several initialization schemes on ENSO prediction. Initialization with wind stress data and initialization with
wind stress reconstructed from SST using the atmospheric model give comparable skill levels. In re-estimating the atmospheric
model in order to prevent hindcast-period wind information from entering through empirical atmospheric model, we note some
sensitivity to the estimation data set, but this is considered to have limited impact for ENSO prediction purposes. Examination
of subsurface heat content anomalies in these cases and a case forced only by the difference between observed and reconstructed
winds suggests that at the current level of prediction skill, the crucial wind components for initialization are those associated
with the slow ENSO mode, rather than with atmospheric internal variability. A “piggyback” suboptimal data assimilation is
tested in which the Climate Prediction Center data assimilation product from a related ocean model is used to correct the
ocean initial thermal field. This yields improved skill, suggesting that not all ENSO prediction systems need to invest in
costly data assimilation efforts, provided the prediction and assimilation models are sufficiently close.
Received: 17 April 1998 / Accepted: 22 July 1999 相似文献
14.
基于动力气候模式进行月一季尺度预报的“两步法”思想,提出一种新的预报海温场统计模型,并以该统计模型预报的海温场驱动NCAR CAM3.1模式对1981-2000年月时间尺度的东亚500 hPa高度距平场进行客观回报试验;在此基础上,提出了对预报结果的订正方法。结果表明:统计预报海温模型的预报海温场能够反映出全球海温空间分布的基本特征,并对表征ENSO事件的Ni?o3.4区海温变化的预报能力较强。该统计模型预报的海温场驱动的CAM3.1模式可以较好地预报出东亚500 hPa环流的主要分布特征,试验表明:适当的统计订正方法可以在一定程度上提高CAM3.1模式对东亚夏季500 hPa环流背景的预报技巧。 相似文献
15.
R. Justin Small Shang-Ping Xie Eric D. Maloney Simon P. de Szoeke Toru Miyama 《Climate Dynamics》2011,36(5-6):867-890
Intraseasonal variability in the eastern Pacific warm pool in summer is studied, using a regional ocean?Catmosphere model, a linear baroclinic model (LBM), and satellite observations. The atmospheric component of the model is forced by lateral boundary conditions from reanalysis data. The aim is to quantify the importance to atmospheric deep convection of local air?Csea coupling. In particular, the effect of sea surface temperature (SST) anomalies on surface heat fluxes is examined. Intraseasonal (20?C90?day) east Pacific warm-pool zonal wind and outgoing longwave radiation (OLR) variability in the regional coupled model are correlated at 0.8 and 0.6 with observations, respectively, significant at the 99% confidence level. The strength of the intraseasonal variability in the coupled model, as measured by the variance of outgoing longwave radiation, is close in magnitude to that observed, but with a maximum located about 10° further west. East Pacific warm pool intraseasonal convection and winds agree in phase with those from observations, suggesting that remote forcing at the boundaries associated with the Madden?CJulian oscillation determines the phase of intraseasonal convection in the east Pacific warm pool. When the ocean model component is replaced by weekly reanalysis SST in an atmosphere-only experiment, there is a slight improvement in the location of the highest OLR variance. Further sensitivity experiments with the regional atmosphere-only model in which intraseasonal SST variability is removed indicate that convective variability has only a weak dependence on the SST variability, but a stronger dependence on the climatological mean SST distribution. A scaling analysis confirms that wind speed anomalies give a much larger contribution to the intraseasonal evaporation signal than SST anomalies, in both model and observations. A LBM is used to show that local feedbacks would serve to amplify intraseasonal convection and the large-scale circulation. Further, Hovm?ller diagrams reveal that whereas a significant dynamic intraseasonal signal enters the model domain from the west, the strong deep convection mostly arises within the domain. Taken together, the regional and linear model results suggest that in this region remote forcing and local convection?Ccirculation feedbacks are both important to the intraseasonal variability, but ocean?Catmosphere coupling has only a small effect. Possible mechanisms of remote forcing are discussed. 相似文献
16.
Over the mid-latitude North Pacific, there is a close relationship between interannual variations of the sea surface temperature (SST) and surface shortwave radiation during boreal summer. The present study evaluates this relationship in coupled model simulations, forced model simulations, and retrospective forecasts. It is found that the simulation of this relationship in climate models is closely related to the model biases in the meridional gradients of mean SST and surface shortwave radiation. A southward shift in the region of large mean meridional gradients leads to a similar southward shift in the region of large correlation between the SST and shortwave radiation variations. The relationship is enhanced (weakened) when the mean meridional gradients are stronger (weaker) compared to observations. The shortwave radiation?CSST correlation is weak in individual forced simulations because of the interference of internally generated shortwave radiation variations. The shortwave radiation?CSST correlation increases significantly in the ensemble mean due to reduction of internally generated variability. The long-lead Climate Forecast System (CFS) forecasts have a better simulation of the shortwave radiation?CSST correlation compared to the short-lead forecasts. Estimation based on the CFS ensemble forecasts indicates that the high-frequency atmospheric variations contribute importantly to the SST variability over the mid-latitude North Pacific during boreal summer. 相似文献
17.
Seasonality and time scales in the relationship between global SST and African rainfall 总被引：1，自引：0，他引：1
The main goal of this study is to determine the oceanic regions corresponding to variability in African rainfall and seasonal differences in the atmospheric teleconnections. Canonical correlation analysis (CCA) has been applied in order to extract the dominant patterns of linear covariability. An ensemble of six simulations with the global atmospheric general circulation model ECHAM4, forced with observed sea surface temperatures (SSTs) and sea ice boundary variability, is used in order to focus on the SST-related part of African rainfall variability. Our main finding is that the boreal summer rainfall (June–September mean) over Africa is more affected by SST changes than in boreal winter (December–March mean). In winter, there is a highly significant link between tropical African rainfall and Indian Ocean and eastern tropical Pacific SST anomalies, which is closely related to El Niño-Southern Oscillation (ENSO). However, long-term changes are found to be associated with SST changes in the Indian and tropical Atlantic Oceans, thus, showing that the tropical Atlantic plays a critical role in determining the position of the intertropical convergence zone (ITCZ). Since ENSO is less in summer, the tropical Pacific and the Indian Oceans are less important for African rainfall. The African summer monsoon is strongly influenced by SST variations in the Gulf of Guinea, with a response of opposite sign over the Sahelian zone and the Guinean coast region. SST changes in the subtropical and extratropical oceans mostly take place on decadal time scales and are responsible for low-frequency rainfall fluctuations over West Africa. The modelled teleconnections are highly consistent with the observations. The agreement for most of the teleconnection patterns is remarkable and suggests that the modelled rainfall anomalies serve as suitable predictors for the observed changes. 相似文献
18.
Summary ?The interannual variability of broad-scale Asian summer monsoon was studied using a general circulation model (GCM) and NCEP
(National Center for Environmental Prediction) data set during 1979–95. In the GCM experiment, the main emphasis was given
to isolate the individual role of surface boundary conditions on the existence of winter-spring time circulation anomalies
associated with the interannual variability of Asian summer monsoon.
In order to understand the role of sea-surface temperatures (SSTs) alone on the existence of precursory signals, we have conducted
17 years numerical integration with a GCM forced with the real-time monthly averaged SSTs of 1979 to 1995. In this experiment,
among the many surface boundary conditions only SSTs are varying interannually. The composite circulation anomalies simulated
by the GCM have good resemblance with the NCEP circulation anomalies over subtropical Asia. This suggests that the root cause
of the existence of winter-spring time circulation anomalies associated with the interannual variability of Asian summer monsoon
is the interannual variability of SST.
Empirical Orthogonal Functions (EOFs) of 200-mb winds and OLR were constructed to study the dynamic coupling between SST anomalies
and winter-spring time circulation anomalies. It is found that the convective heating anomalies associated with SST anomalies
and stationary eddies undergo systematic and coherent interannual variations prior to summer season. We have identified Matsuno-Gill
type mode in the velocity potential and stream function fields. This suggests the existence of dynamic links between the SST
anomalies and the precursory signals of Asian summer monsoon.
Received June 9, 1999/Revised April 7, 2000 相似文献
19.
Ensembles of boreal summer atmospheric simulations, spanning a 15-year period (1979–1993), are performed with the ARPEGE climate model to investigate the influence of soil moisture on climate variability and potential predictability. All experiments are forced with observed monthly mean sea surface temperatures. In addition to a control experiment with interactive soil moisture boundary conditions, two sensitivity experiments are performed. In the first, the interannual variability of the deep soil moisture is removed during the whole season, through a relaxation toward the monthly mean model climatology. In the second, only the variability of the initial soil moisture conditions is suppressed. While it is shown that soil moisture strongly contributes to the climate variability simulated in the control experiment, an analysis of variance indicates that soil moisture does not represent a significant source of predictability in most continental areas. The main exception is the North American continent, where climate predictability is clearly reduced through the use of climatological initial conditions. Using climatological soil moisture boundary conditions does not lead to strong and homogeneous impacts on potential predictability, thereby suggesting that the climate signals driven by the sea surface temperature variability are not generally amplified by interactive soil moisture and that the relevance of soil moisture for seasonal forecasting is mainly an initial value problem. 相似文献
20.
Influence of SST biases on future climate change projections 总被引：1，自引：0，他引：1
We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977?C1999 in the historical period and 2077?C2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean?Catmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection. 相似文献