Hydro-climatic forecasting using sea surface temperatures: methodology and application for the southeast US

Sea surface temperatures (SSTs) are often used for the development of hydro-climatic variable forecasts based on teleconnection methods. Such methods rely on projections or linear combinations of teleconnection indices [e.g. El Niño-Southern Oscillation (ENSO)] and other predictor fields. This study introduces a new hydro-climatic forecasting method identifying SST “dipole” predictors motivated by major teleconnection patterns. An SST dipole is defined as a function of average SST anomalies over two oceanic areas of specific sizes and geographic locations. An optimization algorithm is developed to search for the most significant SST dipole predictors of an external hydro-climatic series based on the Gerrity Skill Score. The significant dipoles are cross-validated and used to generate multiple forecast values. The new method is applied to the forecasting of seasonal precipitation over the southeast US. Hindcasting results show that significant dipoles related to ENSO as well as other prominent patterns at different lead times can indeed be identified. The dipole method also compares favorably with existing statistical forecasting schemes with respect to multiple skill measures. Furthermore, an operational forecasting framework able to produce ensemble forecast traces and uncertainty intervals that can support regional water resources planning and management is also developed.     

Deficiencies and possibilities for long-lead coupled climate prediction of the Western North Pacific-East Asian summer monsoon

Long-lead prediction of waxing and waning of the Western North Pacific (WNP)-East Asian (EA) summer monsoon (WNP-EASM) precipitation is a major challenge in seasonal time-scale climate prediction. In this study, deficiencies and potential for predicting the WNP-EASM precipitation and circulation one or two seasons ahead were examined using retrospective forecast data for the 26-year period of 1981–2006 from two operational couple models which are the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) and the Bureau of Meteorology Research Center (BMRC) Predictive Ocean–Atmosphere Model for Australia (POAMA). While both coupled models have difficulty in predicting summer mean precipitation anomalies over the region of interest, even for a 0-month lead forecast, they are capable of predicting zonal wind anomalies at 850 hPa several months ahead and, consequently, satisfactorily predict summer monsoon circulation indices for the EA region (EASMI) and for the WNP region (WNPSMI). It should be noted that the two models’ multi-model ensemble (MME) reaches 0.40 of the correlation skill for the EASMI with a January initial condition and 0.75 for the WNPSMI with a February initial condition. Further analysis indicates that prediction reliability of the EASMI is related not only to the preceding El Niño and Southern Oscillation (ENSO) but also to simultaneous local SST variability. On other hand, better prediction of the WNPSMI is accompanied by a more realistic simulation of lead–lag relationship between the index and ENSO. It should also be noted that current coupled models have difficulty in capturing the interannual variability component of the WNP-EASM system which is not correlated with typical ENSO variability. To improve the long-lead seasonal prediction of the WNP-EASM precipitation, a statistical postprocessing was developed based on the multiple linear regression method. The method utilizes the MME prediction of the EASMI and WNPSMI as predictors. It is shown that the statistical postprocessing is able to improve forecast skill for the summer mean precipitation over most of the WNP-EASM region at all forecast leads. It is noteworthy that the MME prediction, after applying statistical postprocessing, shows the best anomaly pattern correlation skill for the EASM precipitation at a 4-month lead (February initial condition) and for the WNPSM precipitation at a 5-month lead (January initial condition), indicating its potential for improving long-lead prediction of the monsoon precipitation.     

Role of the Indian Ocean sea surface temperature in shaping the natural variability in the flow of Nile River

A significant fraction of the inter-annual variability in the Nile River flow is shaped by El Niño Southern Oscillation (ENSO). Here, we investigate a similar role for the Indian Ocean (IO) sea surface temperature (SST) in shaping the inter-annual variability of the Nile River flow. Using observations of global SST distribution and river flow in addition to atmospheric general circulation model sensitivity experiments, we show that North and Middle IO SSTs play a significant intermediate role in the teleconnection between ENSO and the Nile flow. Applying partial coherency analyses, we demonstrate that the connection between North and Middle IO SSTs and Nile flow is strongly coupled to ENSO. During El Niño events, SST in the North and Middle IO increases in response to the warming in the Tropical Eastern Pacific Ocean and forces a Gill-type circulation with enhanced westerly low-level flow over East Africa and the Western IO. This anomalous low-level flow enhances the low-level flux of air and moisture away from the Upper Blue Nile (UBN) basin resulting in reduction of rainfall and river flow. SSTs in the South IO also play a significant role in shaping the variability of the Nile flow that is independent from ENSO. A warming over the South IO, generates a cyclonic flow in the boundary layer, which reduces the cross-equatorial meridional transport of air and moisture towards the UBN basin, favoring a reduction in rainfall and river flow. This independence between the roles of ENSO and South IO SSTs allows for development of new combined indices of SSTs to explain the inter-annual variability of the Nile flow. The proposed teleconnections have important implications regarding mechanisms that shape the regional impacts of climate change over the Nile basin.     

Seasonal prediction of African precipitation with ECHAM4–T42 ensemble simulations using a multivariate MOS re-calibration scheme

A 15 member ensemble of 20th century simulations using the ECHAM4–T42 atmospheric GCM is utilized to investigate the potential predictability of interannual variations of seasonal rainfall over Africa. Common boundary conditions are the global sea surface temperatures (SST) and sea ice extent. A canonical correlation analysis (CCA) between observed and ensemble mean ECHAM4 precipitation over Africa is applied in order to identify the most predictable anomaly patterns of precipitation and the related SST anomalies. The CCA is then used to formulate a re-calibration approach similar to model output statistics (MOS) and to derive precipitation forecasts over Africa. Predictand is the climate research unit (CRU) gridded precipitation over Africa. As predictor we use observed SST anomalies, ensemble mean precipitation over Africa and a combined vector of mean sea level pressure, streamfunction and velocity potential at 850 hPa. The different forecast approaches are compared. Most skill for African precipitation forecasts is provided by tropical Atlantic (Gulf of Guinea) SST anomalies which mainly affect rainfall over the Guinean coast and Sahel. The El Niño/Southern Oscillation (ENSO) influences southern and East Africa, however with a lower skill. Indian Ocean SST anomalies, partly independent from ENSO, have an impact particularly on East Africa. As suggested by the large agreement between the simulated and observed precipitation, the ECHAM4 rainfall provides a skillful predictor for CRU precipitation over Africa. However, MOS re-calibration is needed in order to provide skillful forecasts. Forecasts using MOS re-calibrated model precipitation are at least as skillful as forecast using dynamical variables from the model or instantaneous SST. In many cases, MOS re-calibrated precipitation forecasts provide more skill. However, differences are not systematic for all regions and seasons, and often small.     

A Non-Linear Dynamical–Statistical Model for Reconstruction of the Air–Sea Element Fields in the Tropical Pacific Ocean

Aiming at tackling the difficulty in establishing a sea surface temperature (SST) dynamical model, this study develops a non-linear dynamical–statistical model of SST fields and their correlative factors based on Genetic Algorithms (GA) and the dynamical system reconstruction idea, which greatly improves the El Niño–Southern Oscillation (ENSO) forecast model. Using Hadley SST data, sea surface wind (SSW) and sea level pressure (SLP) data from the National Centers for Environmental Prediction-National Center for Environmental Research (NCEP-NCAR), with empirical orthogonal function (EOF) time-space for reconstruction, we carry out numerical integral forecasting experiments for SST, SSW, and SLP fields. By statistical analysis of the forecasting experiments, we find that forecasts for less than 25 months perform better than longer term forecasts. Based on the model, we forecast SST, SSW, and SLP fields in September, October, and November 2014 and predict a weak La Niña event. This study explores a novel method for the complex atmosphere–ocean system.     

两广地区夏季降水异常与澳大利亚东侧海温异常的联系及可能机制

广东省和广西壮族自治区(两广地区)夏季降水时空分布很不均匀,存在显著的年际变化。利用站点观测降水资料、海洋及大气再分析资料,研究了近40 a两广地区夏季降水年际异常与澳大利亚东侧海温异常的联系及机理。在年际时间尺度上,两广夏季降水异常与澳大利亚东侧的海温异常存在显著的负相关关系。当澳大利亚东侧海温异常偏高时,一方面,部分水汽由热带中太平洋向澳大利亚东侧海区辐合,部分沿西太平洋副热带高压边缘向东亚地区输送,两广地区为水汽辐散区域,另一方面,澳大利亚东侧海区的对流活动增强,该地区上空的上升运动异常增强,通过"大气桥"遥相关使得海洋性大陆地区的异常上升运动增强,从而加强了东亚地区的局地Hadley环流,使得两广地区下沉运动增强,二者共同作用致使两广地区夏季干旱少雨;反之亦然。     

Interaction between equatorially symmetric and asymmetric tropical eastern Pacific SSTs

The third version of the extended reconstructed sea surface temperature (SST) data spanning from 1880 to 2007 was used to investigate the interaction between equatorially symmetric and asymmetric tropical eastern Pacific SSTs. Principal component analysis and wavelet spectrum analysis showed that the asymmetric SST was dominated by an amplitude-modulated annual cycle, while the symmetric SST was a mixture of amplitude-modulated annual cycle and El Niño-Southern Oscillation (ENSO). The symmetric and asymmetric components were significantly correlated, particularly in March and October. In March, when ENSO is usually weak, the interaction between two components is mainly due to the interaction between the amplitude-modulated annual cycles of each component. On the other hand, in October, when ENSO is dominant, the interaction between amplitude-modulated asymmetric annual cycle and ENSO becomes dominant. The interaction in March is partly explained by anomalous southeasterly winds associated with the symmetric SST pattern reducing wind speed over the southeastern Pacific, causing an intensification of the asymmetric SST component. In October, the equatorial asymmetrical development of ENSO causes a significant correlation between the symmetric and asymmetric components.     

ENSO及其组合模态对中国东部各季节降水的影响

近期的研究发现,热带太平洋低层大气存在两种主要模态,即经向对称ENSO模态和ENSO与海表温度(SST)年循环相互作用产生的经向反对称组合模态。主要探讨了这两种不同ENSO模态对中国东部各季节降水的影响。结果表明,厄尔尼诺年秋季,中国西南、长江及华南大部分区域呈现显著正降水异常;冬季,正降水异常范围扩大,覆盖华南、华东及华北东南部地区。这两个季节的异常降水都主要受ENSO模态的影响。与ENSO模态相关的正异常海温局地强迫导致120°E以西出现反气旋性环流,其西北侧增强的西南暖湿气流使得中国东部地区降水增多。次年春季,从中国华南延伸到东北出现正的异常降水,主要是ENSO组合模态的贡献。因为次年春季热带太平洋地区ENSO模态信号只局限于赤道地区,并没有对中国东部降水有显著的影响,而ENSO与海温年循环相互作用的组合模态使得与ENSO相关的赤道大气异常可以扩展到赤道以外地区。ENSO组合模态对中国降水异常有重要影响,在今后的研究和短期预测中需引起重视。      

ENSO及其年代际异常对中国东部气候异常影响的观测分析

在不同的ＳＳＴ年代际背景下,东亚季风和ＥＮＳＯ事件的关系是不同的。中国东部降水异常在冷态和暖态下,不是简单的线性反相关关系。在冷态时,最大的正距平中心发生在第二年早夏的长江以南地区;在暖态时,发生在第二年冬春季的华南地区。气温变化与降水变化并不对应,高温高湿的相关性不明显。不同的年代际海温背景使海气交换发生变换,改变了海陆热力对比,从而改变了海陆气压差,也就改变了季风的强度,使ＥＮＳＯ和东亚季风的     

A deep learning–based U-Net model for ENSO-related precipitation responses to sea surface temperature anomalies over the tropical Pacific

SST–precipitation feedback plays an important role in ENSO evolution over the tropical Pacific and thus it is critically important to realistically represent precipitation-induced feedback for accurate simulations and predictions of ENSO. Typically, in hybrid coupled modeling for ENSO predictions, statistical atmospheric models are adopted to determine linear precipitation responses to interannual SST anomalies. However, in current coupled climate models, the observed precipitation–SST relationship is not well represented. In this study, a data-driven deep learning-based U-Net model was used to construct a nonlinear response model of interannual precipitation variability to SST anomalies. It was found that the U-Net model outperformed the traditional EOF-based method in calculating the precipitation variability. Particularly over the western-central tropical Pacific, the mean-square error (MSE) of the precipitation estimates in the U-Net model was smaller than that in the EOF model. The performance of the U-Net model was further improved when additional tendency information on SST and precipitation variability was also introduced as input variables, leading to a pronounced MSE reduction over the ITCZ.摘要SST–降水反馈过程在热带太平洋ENSO演变过程中起着重要作用, 能否真实地在数值模式中表征SST–降水年际异常之间的关系及相关反馈过程, 对于准确模拟和预测ENSO至关重要. 例如, 在一些模拟ENSO的混合型耦合模式中, 通常采用大气统计模型 (如经验正交函数; EOF) 来表征降水 (海气界面淡水通量的一个重要分量) 对SST年际异常的线性响应. 然而在当前的耦合模式中, 真实观测到的降水–SST统计关系还不能被很好地再现出来, 从而引起 ENSO模拟误差和不确定性. 在本研究中, 使用基于深度学习的U-Net模型来构建热带太平洋降水异常场对SST年际异常的非线性响应模型. 研究发现: U-Net模型的性能优于传统的基于EOF方法的模型. 特别是在热带西太平洋海区, U-Net模型估算的降水误差远小于EOF模型的模拟. 此外, 当SST和降水异常的趋势信息作为输入变量也被同时引入以进一步约束模式训练时, U-Net模型的性能可以进一步提高, 如能使热带辐合带区域的误差显著降低.     

Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO

The provision of timely and reliable climate information on which to base management decisions remains a critical component in drought planning for southern Africa. In this observational study, we have not only proposed a forecasting scheme which caters for timeliness and reliability but improved relevance of the climate information by using a novel drought index called the standardised precipitation evapotranspiration index (SPEI), instead of the traditional precipitation only based index, the standardised precipitation index (SPI). The SPEI which includes temperature and other climatic factors in its construction has a more robust connection to ENSO than the SPI. Consequently, the developed ENSO-SPEI prediction scheme can provide quantitative information about the spatial extent and severity of predicted drought conditions in a way that reflects more closely the level of risk in the global warming context of the sub region. However, it is established that the ENSO significant regional impact is restricted only to the period December–March, implying a revisit to the traditional ENSO-based forecast scheme which essentially divides the rainfall season into the two periods, October to December and January to March. Although the prediction of ENSO events has increased with the refinement of numerical models, this work has demonstrated that the prediction of drought impacts related to ENSO is also a reality based only on observations. A large temporal lag is observed between the development of ENSO phenomena (typically in May of the previous year) and the identification of regional SPEI defined drought conditions. It has been shown that using the Southern Africa Regional Climate Outlook Forum’s (SARCOF) traditional 3-month averaged Nino 3.4 SST index (June to August) as a predictor does not have an added advantage over using only the May SST index values. In this regard, the extended lead time and improved skill demonstrated in this study could immensely benefit regional decision makers.     

北太平洋海温异常对中国东北地区旱涝的影响

文中利用 196 1～ 2 0 0 0年中国东北地区 80个测站 4 0a的月降水和同一时期的北太平洋海温资料以及奇异值分解 (SVD)技术 ,分析了北太平洋海温异常对中国东北地区夏季旱涝的影响。结果表明 :东北地区夏季降水与北太平洋海温异常之间存在着较为密切的联系 ,当前期冬季和春季甚至是前一年夏季赤道中东太平洋海温如果处于异常偏暖 (或偏冷 )状态 ,并且西风漂流区具有较明显的SST负 (或正 )距平分布时 ,则东北大部分地区夏季降水具有整体偏多 (或偏少 )的倾向。当然 ,东北地区降水与北太平洋海温异常之间的这种联系也并非是简单的一一对应的关系     

新疆季降水与太平洋海温的相关分析

用相关分析法分析了新疆南北疆各季降水与前一年及当年太平洋各区海温的关系，结果表明太平洋海温对新疆季降水的影响因季节不同而影响的相关区域、相关时间、相关程度也不同。太平洋海温对北疆季降水的影响明显大于南疆，对北疆汛期降水的影响明显大于其他季节。最后重点分析了ENSO事件与北疆汛期降水的关系，结果表明汛期降水异常易出现在ENSO爆发年的次年或结束年的次年。     

The extratropical sensitivity to the meridional extent of tropical ENSO forcing

The extratropical response to tropical remote forcing has been examined with so-called tropical ocean-global atmosphere experiments, which use prescribed sea surface temperature (SST) in the tropical Pacific and a slab mixed-layer ocean model elsewhere. In this study we have revisited this experimental design and found that the extratropical response is quite sensitive to the meridional extent of tropical prescribed SST domain. Even in the case of a prescribed annual cycle only (i.e., no ENSO), the differences in the prescribed SST regions lead to different atmospheric motions in the adjacent extratropics. When the tropical forcing includes ENSO, the sensitivity to the meridional domain is more prominent, especially during La Niña events. In La Niña, the prescribed SST is warmer than the simulated SST in the northern subtropics, and the warmer SST differences continue to 30°N. This broad SST differences accompany enhanced atmospheric meridional circulation that directly connects the tropics and extratropics within the Pacific basin. Moreover, the Rossby wave excitation also increases, so the effect of prescribed region difference is felt beyond the Pacific basin. On the other hand, the effect of ENSO sea surface temperature anomalie (i.e., ENSO experiment composite minus control experiment annual cycle, both of which have the same prescribed SST domain) is stronger in the broad tropical forcing experiment. However, the ENSO anomaly composite from own annual cycle is similar regardless of the meridional extent of forcing region, and commonly mimics the Northern Hemisphere El Niño composite of nature in the boreal winter season.     

Summer monsoon circulation and precipitation over the tropical Indian Ocean during ENSO in the NCEP climate forecast system

This study investigates the El Niño Southern Oscillation (ENSO) teleconnections to tropical Indian Ocean (TIO) and their relationship with the Indian summer monsoon in the coupled general circulation model climate forecast system (CFS). The model shows good skill in simulating the impact of El Niño over the Indian Oceanic rim during its decay phase (the summer following peak phase of El Niño). Summer surface circulation patterns during the developing phase of El Niño are more influenced by local Sea Surface Temperature (SST) anomalies in the model unlike in observations. Eastern TIO cooling similar to that of Indian Ocean Dipole (IOD) is a dominant model feature in summer. This anomalous SST pattern therefore is attributed to the tendency of the model to simulate more frequent IOD events. On the other hand, in the model baroclinic response to the diabatic heating anomalies induced by the El Niño related warm SSTs is weak, resulting in reduced zonal extension of the Rossby wave response. This is mostly due to weak eastern Pacific summer time SST anomalies in the model during the developing phase of El Niño as compared to observations. Both eastern TIO cooling and weak SST warming in El Niño region combined together undermine the ENSO teleconnections to the TIO and south Asia regions. The model is able to capture the spatial patterns of SST, circulation and precipitation well during the decay phase of El Niño over the Indo-western Pacific including the typical spring asymmetric mode and summer basin-wide warming in TIO. The model simulated El Niño decay one or two seasons later, resulting long persistent warm SST and circulation anomalies mainly over the southwest TIO. In response to the late decay of El Niño, Ekman pumping shows two maxima over the southern TIO. In conjunction with this unrealistic Ekman pumping, westward propagating Rossby waves display two peaks, which play key role in the long-persistence of the TIO warming in the model (for more than a season after summer). This study strongly supports the need of simulating the correct onset and decay phases of El Niño/La Niña for capturing the realistic ENSO teleconnections. These results have strong implications for the forecasting of Indian summer monsoon as this model is currently being adopted as an operational model in India.     

Modulation of Convectively Coupled Kelvin Wave Activity in the Tropical Pacific by ENSO

The influence of El Nio-Southern Oscillation (ENSO) on the convectively coupled Kelvin waves over the tropical Pacific is investigated by comparing the Kelvin wave activity in the eastern Pacific (EP) El Nio, central Pacific (CP) El Nio, and La Nia years, respectively, to 30-yr (1982-2011) mean statistics. The convectively coupled Kelvin waves in this study are represented by the two leading modes of empirical orthogonal function (EOF) of 2-25-day band-pass filtered daily outgoing longwave radiation (OLR), with the estimated zonal wavenumber of 3 or 4, period of 8 days, and eastward propagating speed of 17 ms-1 . The most significant impact of ENSO on the Kelvin wave activity is the intensification of the Kelvin waves during the EP El Nios. The impact of La Nia on the reduction of the Kelvin wave intensity is relatively weaker, reflecting the nonlinearity of tropical deep convection and the associated Kelvin waves in response to ENSO sea surface temperature (SST) anomalies. The impact of the CP El Nio on the Kelvin waves is less significant due to relatively weaker SST anomalies and smaller spatial coverage. ENSO may also alter the frequency, wavelength, and phase speed of the Kelvin waves. This study demonstrates that low-frequency ENSO SST anomalies modulate high-frequency tropical disturbances, an example of weather-climate linkage.     

一个新的ENSO监测指标的研究

利用1982～1996年逐月平均SST和OLR资料,首先通过奇异值分解（SVD）技术研究了热带太平洋大气对流活动和海温场的时间和空间结构及其相互关系。结果表明,第一模态都明显地反映出ENSO信息,两场间具有很高的相关。分析了80年代以来的E1 Ni?o/La Ni?a盛期的热带太平洋对流活动场以及NINO 3指数与OLR场的点相关,结果指出,中东太平洋和西太平洋上存在类似偶极子型的两个符号相反的相关区,与SVD第一模态空间分布型十分相似。由此建立了反映ENSO期间热带中东太平洋和西太平洋反向变化的对流涛动     

On the dependence of ENSO simulation on the coupled model mean state

Systematic model error remains a difficult problem for seasonal forecasting and climate predictions. An error in the mean state could affect the variability of the system. In this paper, we investigate the impact of the mean state on the properties of ENSO. A set of coupled decadal integrations have been conducted, where the mean state and its seasonal cycle have been modified by applying flux correction to the momentum-flux and a combination of heat and momentum fluxes. It is shown that correcting the mean state and the seasonal cycle improves the amplitude of SST inter-annual variability and also the penetration of the ENSO signal into the troposphere and the spatial distribution of the ENSO teleconnections are improved. An analysis of a multivariate PDF of ENSO shows clearly that the flux correction affects the mean, variance, skewness and tails of the distribution. The changes in the tails of the distribution are particularly noticeable in the case of precipitation, showing that without the flux correction the model is unable to reproduce the frequency of large events. For the inter-annual variability the momentum-flux correction alone has a large impact, while the additional heat-flux correction is important for the teleconnections. These results suggest that the current forecasts practices of removing the forecast bias a-posteriori or anomaly initialisation are by no means optimal, since they can not deal with the strong nonlinear interactions. A consequence of the results presented here is that the predictability on annual time-ranges could be higher than currently achieved. Whether or not the correction of the model mean state by some sort of flux correction leads to better forecasts needs to be addressed. In any case, flux correction may be a powerful tool for diagnosing coupled model errors and predictability studies.     

The role of the intra-daily SST variability in the Indian monsoon variability and monsoon-ENSO–IOD relationships in a global coupled model

The impact of diurnal SST coupling and vertical oceanic resolution on the simulation of the Indian Summer Monsoon (ISM) and its relationships with El Ni?o-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events are studied through the analysis of four integrations of a high resolution Coupled General Circulation Model (CGCM), but with different configurations. The only differences between the four integrations are the frequency of coupling between the ocean and atmosphere for the Sea Surface Temperature (SST) parameter (2 vs. 24?h coupling) and/or the vertical oceanic resolution (31 vs. 301 levels) in the CGCM. Although the summer mean tropical climate is reasonably well captured with all the configurations of the CGCM and is not significantly modified by changing the frequency of SST coupling from once to twelve per day, the ISM–ENSO teleconnections are rather poorly simulated in the two simulations in which SST is exchanged only once per day, independently of the vertical oceanic resolution used in the CGCM. Surprisingly, when 2?h SST coupling is implemented in the CGCM, the ISM–ENSO teleconnection is better simulated, particularly, the complex lead-lag relationships between the two phenomena, in which a weak ISM occurs during the developing phase of an El Ni?o event in the Pacific, are closely resembling the observed ones. Evidence is presented to show that these improvements are related to changes in the characteristics of the model’s El Ni?o which has a more realistic evolution in its developing and decaying phases, a stronger amplitude and a shift to lower frequencies when a 2-hourly SST coupling strategy is implemented without any significant changes in the basic state of the CGCM. As a consequence of these improvements in ENSO variability, the lead relationships between Indo-Pacific SSTs and ISM rainfall resemble the observed patterns more closely, the ISM–ENSO teleconnection is strengthened during boreal summer and ISM rainfall power spectrum is in better agreement with observations. On the other hand, the ISM–IOD teleconnection is sensitive to both SST coupling frequency and the vertical oceanic resolution, but increasing the vertical oceanic resolution is degrading the ISM–IOD teleconnection in the CGCM. These results highlight the need of a proper assessment of both temporal scale interactions and coupling strategies in order to improve current CGCMs. These results, which must be confirmed with other CGCMs, have also important implications for dynamical seasonal prediction systems or climate change projections of the monsoon.     

不同区域海温异常对中国夏季旱涝影响的诊断研究和预测试验

利用季降水异常的典型集合相关预测模式, 研究了前期和同期不同季节全球海表温度距平场与中国夏季旱涝的遥相关分布特征以及这种相关型随季节的变化, 揭示了全球海温的异常变化在中国夏季旱涝中的信号特征.研究表明, 全球不同区域海温对我国夏季降水的影响存在着明显的季节差异.全球特定的海温分布可以作为中国夏季旱涝预报的信号因子.选取不同区域及不同时段的海温场作为因子场分别对1998、 1999年这两个典型年份的我国夏季降水进行了诊断研究和预测试验, 并通过不同区域海温的影响权重做集成预测.试验结果表明:不同区域海温的集成预测不仅可以有效地提高预测的准确性, 而且可以揭示不同时段不同区域海温的异常变化在夏季旱涝中的强信号现象.