Using CMIP5 model outputs to investigate the initial errors that cause the “spring predictability barrier” for El Nio events

Most ocean-atmosphere coupled models have difficulty in predicting the El Nio-Southern Oscillation(ENSO) when starting from the boreal spring season. However, the cause of this spring predictability barrier(SPB) phenomenon remains elusive. We investigated the spatial characteristics of optimal initial errors that cause a significant SPB for El Nio events by using the monthly mean data of the pre-industrial(PI) control runs from several models in CMIP5 experiments. The results indicated that the SPB-related optimal initial errors often present an SST pattern with positive errors in the central-eastern equatorial Pacific, and a subsurface temperature pattern with positive errors in the upper layers of the eastern equatorial Pacific, and negative errors in the lower layers of the western equatorial Pacific. The SPB-related optimal initial errors exhibit a typical La Ni-a-like evolving mode, ultimately causing a large but negative prediction error of the Nio-3.4 SST anomalies for El Nio events. The negative prediction errors were found to originate from the lower layers of the western equatorial Pacific and then grow to be large in the eastern equatorial Pacific. It is therefore reasonable to suggest that the El Nio predictions may be most sensitive to the initial errors of temperature in the subsurface layers of the western equatorial Pacific and the Nio-3.4 region, thus possibly representing sensitive areas for adaptive observation. That is, if additional observations were to be preferentially deployed in these two regions, it might be possible to avoid large prediction errors for El Nio and generate a better forecast than one based on additional observations targeted elsewhere. Moreover, we also confirmed that the SPB-related optimal initial errors bear a strong resemblance to the optimal precursory disturbance for El Nio and La Nia events. This indicated that improvement of the observation network by additional observations in the identified sensitive areas would also be helpful in detecting the signals provided by the precursory disturbance, which may greatly improve the ENSO prediction skill.     

Genesis of the 2014–2016 El Nio events

The 2015/2016 El Nio was one of the strongest El Nio events in history, and this strong event was preceded by a weak El Nio in 2014. This study systematically analyzed the dynamical processes responsible for the genesis of these events. It was found that the weak 2014 El Nio had two warming phases, the spring-summer warming was produced by zonal advection and downwelling Kelvin waves driven by westerly wind bursts(WWBs), and the autumn-winter warming was produced by meridional advection, surface heating as well as downwelling Kelvin waves. The 2015/2016 extreme El Nio, on the other hand, was primarily a result of sustained zonal advection and downwelling Kelvin waves driven by a series of WWBs, with enhancement from the Bjerknes positive feedback. The vast difference between these two El Nio events mainly came from the different amount of WWBs in 2014 and 2015. As compared to the 1982/1983 and 1997/1998 extreme El Nio events, the 2015/2016 El Nio exhibited some distinctive characteristics in its genesis and spatial pattern. We need to include the effects of WWBs to the theoretical framework of El Nio to explain these characteristics, and to improve our understanding and prediction of El Nio.     

Evolution of the 2015/16 El Nio and historical perspective since 1979

The 2015/16 El Nio developed from weak warm conditions in late 2014 and NINO3.4 reached 3℃ in November 2015. We describe the characteristics of the evolution of the 2015/16 El Nio using various data sets including SST, surface winds,outgoing longwave radiation and subsurface temperature from an ensemble operational ocean reanalyses, and place this event in the context of historical ENSO events since 1979. One salient feature about the 2015/16 El Nio was a large number of westerly wind bursts and downwelling oceanic Kelvin waves(DWKVs). Four DWKVs were observed in April-November 2015 that initiated and enhanced the eastern-central Pacific warming. Eastward zonal current anomalies associated with DWKVs advected the warm pool water eastward in spring/summer. An upwelling Kelvin wave(UWKV) emerged in early November 2015 leading to a rapid decline of the event. Another outstanding feature was that NINO4 reached a historical high(1.7℃), which was 1℃(0.8℃) higher than that of the 1982/83(1997/98) El Nio . Although NINO3 was comparable to that of the 1982/83 and 1997/98 El Nio , NINO1+2 was much weaker. Consistently, enhanced convection was displaced 20 degree westward, and the maximum D20 anomaly was about 1/3.1/2 of that in 1997 and 1982 near the west coast of South America.     

Extracting predictable components and forecasting techniques in extended-range numerical weather prediction

This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scales.Model variables are divided into predictable components and unpredictable chaotic components from the angle of model prediction error growth.The predictable components are defined as those with a slow error growth at a given range.A targeted numerical model for predictable components is established based on the operational dynamical extended-range forecast(DERF)model of the National Climate Center.At the same time,useful information in historical data are combined to find the fields for predictable components in the numerical model that are similar to those for the predictable components in historical data,reducing the variable dimensions in a similar judgment process and further correcting prediction errors of predictable components.Historical data is used to obtain the expected value and variance of the chaotic components through the ensemble forecast method.The numerical experiment results show that this method can effectively improve the forecast skill of the atmospheric circulation field in the 10–30 days extended-range numerical model and has good prospects for operational applications.     

Processes involved in the second-year warming of the 2015 El Nio event as derived from an intermediate ocean model

The tropical Pacific experienced a sustained warm sea surface condition that started in 2014 and a very strong El Nio event in 2015. One striking feature of this event was the horseshoe-like pattern of positive subsurface thermal anomalies that was sustained in the western-central equatorial Pacific throughout 2014–2015. Observational data and an intermediate ocean model are used to describe the sea surface temperature(SST) evolution during 2014–2015. Emphasis is placed on the processes involved in the 2015 El Nio event and their relationships with SST anomalies, including remote effects associated with the propagation and reflection of oceanic equatorial waves(as indicated in sea level(SL) signals) at the boundaries and local effects of the positive subsurface thermal anomalies. It is demonstrated that the positive subsurface thermal anomaly pattern that was sustained throughout 2014–2015 played an important role in maintaining warm SST anomalies in the equatorial Pacific. Further analyses of the SST budget revealed the dominant processes contributing to SST anomalies during 2014–2015. These analyses provide an improved understanding of the extent to which processes associated with the 2015 El Nio event are consistent with current El Nio and Southern Oscillation theories.     

The unusual 2014–2016 El Ni?o events: Dynamics,prediction and enlightenments

The 2014–2016 El Ni?o events consist of a stalled El Ni?o event in the winter of 2014/2015 and a following extreme El Ni?o event in the end of 2015. Neither event was successfully predicted in operational prediction models. Because of the unusual evolutions of these events that rarely happened in the historical observations, few experience was ready for understanding and predicting the two El Ni?o events when they occurred. Also due to their specialties, considerable attention were attracted with aims to reveal the hidden mechanisms. This article reviews the recent progresses and knowledge that were obtained in these studies. Emerging from these studies, it was argued that the key factor that was responsible for the stalled El Ni?o in 2014 was the unexpected summertime Easterly Wind Surges(EWSs) or the lack of summertime Westerly Wind Bursts(WWBs). Most operational prediction models failed to reproduce such stochastic winds and thus made unrealistic forecasts. The two El Ni?o events awakened the research community again to incorporate the state-of-the-art climate models to simulate the stochastic winds and investigate their roles in the development of El Ni?o.     

Impact of El Nio on atmospheric circulations over East Asia and rainfall in China: Role of the anomalous western North Pacific anticyclone

This paper presents a review on the impact of El Nio on the interannual variability of atmospheric circulations over East Asia and rainfall in China through the anomalous anticyclone over western North Pacific(WNPAC). It explains the formation mechanisms of the WNPAC and physical processes by which the WNPAC affects the rainfall in China. During the mature phase of El Nio, the convective cooling anomalies over western tropical Pacific caused by the weakened convections trigger up an atmospheric Rossby wave response, resulting in the generation of the WNPAC. The WNPAC can persist from the winter when the El Nio is in its peak to subsequent summer, which is maintained by multiple factors including the sustained presence of convective cooling anomalies and the local air-sea interaction over western tropical Pacific, and the persistence of sea surface temperature anomalies(SSTA) in tropical Indian and tropical North Atlantic. The WNPAC can influence the atmospheric circulations over East Asia and rainfall in China not only simultaneously, but also in the subsequent summer after an El Nio year, leading to more rainfall over southern China. The current paper also points out that significant anomalies of atmospheric circulations over East Asia and rainfall over southern China occur in El Nio winter but not in La Nio winter, suggesting that El Nio and La Nio have an asymmetric effect. Other issues, including the impact of El Nio diversity and its impact as well as the relations of the factors affecting the persistence of the WNPAC with summer rainfall anomalies in China, are also discussed. At the end of this paper some issues calling for further investigation are discussed.     

超强厄尔尼诺事件“春季可预报性障碍”及其误差增长动力学分析

基于一个中等复杂程度模式(ICM)集合预报系统(EPS)产生的海表温度距平(SSTA)预报产品,从误差增长的角度探讨了2015/16超强El Nio事件的"春季可预报性障碍"(SPB)问题.通过分析集合预报成员预报误差的增长倾向,发现了2015/16 El Nio事件的预报误差增长呈现显著的季节依赖性,且在春/夏季具有最大增长率,表明ICM-EPS对2015/16 El Nio事件的预报发生了明显的SPB现象.进一步分析表明,上述SPB现象不是由ICM初始场的不确定性引起,而是由其模式误差导致,而ICM-EPS集合预报成员的平均滤掉了部分模式误差的影响,减弱了SPB现象,从而使得2015/16 El Nio事件的预报产生较小的预报误差.通过探讨由海温方程的倾向误差表征的模式误差,该研究揭示了导致SPB现象发生的倾向误差的主要空间特征,并阐明了ICM-EPS低估2015/16El Nio事件强度的原因.此外,本文也揭示了导致显著SPB现象,尤其是导致最大预报误差的SSTA倾向误差的结构特征.该倾向误差的SSTA分量具有赤道中东太平洋负异常,西太平洋正异常的纬向偶极子结构,与Duan等提出的最敏感非线性强迫奇异向量(NFSV)-倾向误差高度相似,从而表明NFSV-型倾向误差也存在于实际的El Nio预报中.该研究也探讨了其他超强El Nio事件,如1982/83和1997/98事件,得到了类似的结果.因此,如果利用NFSV-型倾向误差校正ICM模式误差,ICM-EPS可大大提高超强El Nio事件的预报技巧.     

A new LS+AR model with additional error correction for polar motion forecast

Polar motion depicts the slow changes in the locations of the poles due to the earth’s internal instantaneous axis of rotation. The LS+AR model is recognized as one of the best models for polar motion prediction.Through statistical analysis of the time series of the LS+AR model’s short-term prediction residuals,we found that there is a good correlation of model prediction residuals between adjacent terms.These indicate that the preceding model prediction residuals and experiential adjustment matrixes can be used to correct the next prediction results,thereby forming a new LS+AR model with additional error correction that applies to polar motion prediction.Simulated predictions using this new model revealed that the proposed method can improve the accuracy and reliability of polar motion prediction.In fact,the accuracies of ultra short-term and short-term predictions using the new model were equal to the international best level at present.     

A multi-model prediction system for ENSO

The El Ni?o and Southern Oscillation(ENSO) is the primary source of predictability for seasonal climate prediction.To improve the ENSO prediction skill, we established a multi-model ensemble(MME) prediction system, which consists of 5 dynamical coupled models with various complexities, parameterizations, resolutions, initializations and ensemble strategies, to account for the uncertainties as sufficiently as possible. Our results demonstrated the superiority of the MME over individual models, wi...     

The role of constant optimal forcing in correcting forecast models

In this paper,the role of constant optimal forcing(COF) in correcting forecast models was numerically studied using the well-known Lorenz 63 model.The results show that when we only consider model error caused by parameter error,which also changes with the development of state variables in a numerical model,the impact of such model error on forecast uncertainties can be offset by superimposing COF on the tendency equations in the numerical model.The COF can also offset the impact of model error caused by stochastic processes.In reality,the forecast results of numerical models are simultaneously influenced by parameter uncertainty and stochastic process as well as their interactions.Our results indicate that COF is also able to significantly offset the impact of such hybrid model error on forecast results.In summary,although the variation in the model error due to physical process is time-dependent,the superimposition of COF on the numerical model is an effective approach to reducing the influence of model error on forecast results.Therefore,the COF method may be an effective approach to correcting numerical models and thus improving the forecast capability of models.     

Design and testing of a global climate prediction system based on a coupled climate model

A global climate prediction system(PCCSM4) was developed based on the Community Climate System Model, version 4.0, developed by the National Center for Atmospheric Research(NCAR), and an initialization scheme was designed by our group. Thirty-year(1981–2010) one-month-lead retrospective summer climate ensemble predictions were carried out and analyzed. The results showed that PCCSM4 can efficiently capture the main characteristics of JJA mean sea surface temperature(SST), sea level pressure(SLP), and precipitation. The prediction skill for SST is high, especially over the central and eastern Pacific where the influence of El Ni?o-Southern Oscillation(ENSO) is dominant. Temporal correlation coefficients between the predicted Ni?o3.4 index and observed Ni?o3.4 index over the 30 years reach 0.7, exceeding the 99% statistical significance level. The prediction of 500-hPa geopotential height, 850-hPa zonal wind and SLP shows greater skill than for precipitation. Overall, the predictability in PCCSM4 is much higher in the tropics than in global terms, or over East Asia. Furthermore, PCCSM4 can simulate the summer climate in typical ENSO years and the interannual variability of the Asian summer monsoon well. These preliminary results suggest that PCCSM4 can be applied to real-time prediction after further testing and improvement.     

Enlightenments from researches and predictions of 2014–2016 super El Nio event

<正>El Nio is a remarkable climate phenomenon with a basinwide warming of sea surface temperatures(SST) in the easterncentral tropical Pacific. El Nio means The Little Boy, or Christ Child in Spanish, and on the contrary, a basinwide cooling of the tropical Pacific SST is called La Nia that means The Little Girl in Spanish. Always, a large-scale SST change in the tropical     

Contrast of tropical cyclone frequency in the western North Pacific between two types of La Nia events

According to the different pattern of sea surface temperature anomaly(SSTA) in the previous year of La Nia events,we categorized La Nia events into two types to investigate the different characteristics of tropical cyclone(TC) activity over the western North Pacific(WNP) in TC peak season of two types La Nia events.One type is following the previous El Nio event(La Nia I);the other is following the previous neutral phase or developing La Nia event(La Nia II).Results show that TC genesis frequency in the WNP during TC peak season of La Nia I is less than normal year,whereas it has no differences from normal year during La Nia II.The main reason is attributed to the different amplitude SSTA in the East Indian Ocean(EIO) and the western Pacific Ocean(WPO).Similar to the capacitor effect,strongly positive SSTA in the EIO-WPO during La Nia I triggers an equatorial baroclinic Kelvin wave,which intensifies the easterly in the lower troposphere and weakens the East Asian summer monsoon,and thus the TC frequency decreased during La Nia I.However,the easterly anomaly shows a weak response to the SSTA in the EIO-WPO during La Nia II,and there is no significant change in the environmental pattern over the WNP;so is TC frequency.The modulation of strong EIO-WPO SSTA on large-scale circulation over the WNP reduces the environmental barotropic energy conversion into synoptic-scale disturbances during La Nia I,and also suppresses TC disturbances.The understanding of two different types of La Nia events could help improve the seasonal prediction of TC activity in the WNP during La Nia.     

Joint statistical-dynamical approach to decadal prediction of East Asian surface air temperature

A joint statistical-dynamical method addressing both the internal decadal variability and effect of anthropogenic forcing was developed to predict the decadal components of East Asian surface air temperature(EATs)for three decades(2010–2040).As previous studies have revealed that the internal variability of EATs(EATs_int)is influenced mainly by the ocean,we first analyzed the lead-lag connections between EATs_int and three sea surface temperature(SST)multidecadal modes using instrumental records from 1901 to 1999.Based on the lead-lag connections,a multiple linear regression was constructed with the three SST modes as predictors.The hindcast for the years from 2000 to 2005 indicated the regression model had high skill in simulating the observational EATs_int.Therefore,the prediction for EATs_int(Re_EATs_int)was obtained by the regression model based on quasi-periods of the decadal oceanic modes.External forcing from greenhouse gases is likely associated with global warming.Using monthly global land surface air temperature from historical and projection simulations under the Representative Concentration Pathway(RCP)4.5 scenario of 19 Coupled General Circulation Models participating in the fifth phase of the Coupled Model Intercomparison Project(CMIP5),we predicted the curve of EATs(EATs_trend)relative to1970–1999 by a second-order fit.EATs_int and EATs_trend were combined to form the reconstructed EATs(Re_EATs).It was expected that a fluctuating evolution of Re_EATs would decrease slightly from 2015 to 2030 and increase gradually thereafter.Compared with the decadal prediction in CMIP5 models,Re_EATs was qualitatively in agreement with the predictions of most of the models and the multi-model ensemble mean,indicating that the joint statistical-dynamical approach for EAT is rational.     

Seasonal compensation implied no weakening of the land carbon sink in the Northern Hemisphere under the 2015/2016 El Ni?o

The recurrent extreme El Ni?o events are commonly linked to reduced vegetation growth and the land carbon sink over many but discrete regions of the Northern Hemisphere(NH). However, we reported here a pervasive and continuous vegetation greening and no weakened land carbon sink in the maturation phase of the 2015/2016 El Ni?o event over the NH(mainly in the extra-tropics), based on multiple evidences from remote sensing observations, global ecosystem model simulations and atmospheric CO₂     

Strategy and methodology of dynamical analogue prediction

In order to effectively improve numerical prediction level by using current models and data, the strategy and methodology of dynamical analogue prediction (DAP) is deeply studied in the present paper. A new idea to predict the prediction errors of dynamical model on the basis of historical analogue information is put forward so as to transform the dynamical prediction problem into the estimation problem of prediction errors. In terms of such an idea, a new prediction method of final analogue correction of errors (FACE) is developed. Furthermore, the FACE is applied to extra-seasonal prediction experiments on an operational atmosphere-ocean coupled general circulation model. Prediction results of summer mean circulation and total precipitation show that the FACE can to some extent reduce prediction errors, recover prediction variances, and improve prediction skills. Besides, sensitive experiments also show that predictions based on the FACE are evidently influenced by the number of analogues, analogue-selected variables and analogy metric.     

Application of synoptic-scale anomalous winds predicted by medium-range weather forecast models on the regional heavy rainfall in China in 2010

Atmospheric winds from observations and medium-range weather forecast model predictions can be physically decomposed as daily climate wind,planetary-scale anomalous wind,and synoptic-scale anomalous wind.The 850 hPa synoptic-scale anomalous winds were extracted from the numerical model outputs of the European Centre for Medium-Range Weather Forecasts(ECMWF) and the NCEP Global Forecast System(GFS).The results showed that most rain bands in eastern China in 2010 were located along the anomalous convergence lines.To predict the major rain bands by these convergence lines in 2010,the accuracies of the ECMWF products were 100%,85%,and 15% for leading 3,6,and 9 days,while the GFS products showed 53%,15%,and 6% accuracies,respectively.In comparison of the regional heavy rainfalls between observation and the ECMWF model prediction,the useful leading information was about 3.1 days for direct model rain prediction and 6.7 days for convergence systems predicted by ECMWF model.     

New predictors and a new prediction model for the typhoon frequency over western North Pacific

In this paper, the impacts of the atmospheric circulation during boreal winter-spring on the western North Pacific (WNP) typhoon frequency (WNPTF) are studied. Several new factors in winter-spring in- fluencing the typhoon frequency were identified, including the sea ice cover in the North Pacific and the North Pacific oscillation. Based on these results, the multi-linear regression was applied to establishing a new forecast model for the typhoon frequency by using the datasets of 1965―1999. The forecast model shows a high correlation coefficient (0.79) between the model simulated and the actual typhoon frequencies in the period of 1965―1999. The forecast model also exhibits reasonable hindcasts for the typhoon frequencies for the years 2000―2006. Therefore, this work demonstrates that the new pre- dictors are significant for the prediction of the interannual variability of the WNPTF, which could be potentially used in the operational seasonal forecast of the typhoon frequency in the WNP to get a more physically based operational prediction model and higher forecast skill.     

Review of Research Progresses on the Science of Earthquake Underground Fluid in China During the Last 40 Years

This paper presents a review of the development of scientific research and practice of earthquake underground fluid in China during the last 40 years, summaries early constructive research and primary achievements in this field. The science of earthquake underground fluid is closely correlated with earthquake monitoring and prediction, such as innovations in observation techniques and theoretical methods, and analysis of diversified parameters and research into predictive methods. The historical evolution of observation networks for underground fluid indicates that the demand for strong earthquake monitoring and prediction has become the driving force of the construction and development of the observation network. The development of observation techniques represents the trend based on multiform measurement, syntheses, and digitization. The study results of underground fluid theory and precursory mechanisms suggest that the precursory model, numerical simulation and in-door or field experimental research are the main technological approaches promoting innovation. Research results of earthquake forecast methods use physics based forecast techniques and the ideas of combination of usability and scientific advance. It has been proved by forecast practice that studying underground fluid is a very important subject in earthquake prediction on the Chinese mainland. Finally, the primary work and technical criterion on underground fluid are introduced, and some major scientific issues and development trends in different historical stages are summarized.