The ENSO Events in the Tropical Pacific and Dipole Events in the Indian Ocean

A depth map (close to that of the thermocline as defined by 20℃) of climatically maximum seatemperature anomaly was created at the subsurface of the tropical Pacific and Indian Ocean, based on which the evolving sea-temperature anomaly at this depth map from 1960 to 2000 was statistically analyzed. It is noted that the evolving sea temperature anomaly at this depth map can be better analyzed than the evolving sea surface one. For example, during the ENSO event in the tropical Pacific, the seatemperature anomaly signals travel counter-clockwise within the range of 10°S-10°N, and while moving, the signals change in intensity or even type. If Dipole is used in the tropical Indian Ocean for analyzing the depth map of maximum sea-temperature anomaly, the sea-temperature anomalies of the eastern and western Indian Oceans would be negatively correlated in statistical sense (Dipole in real physical sense), which is unlike the sea surface temperature anomaly based analysis which demonstrates that the inter-annual positive and negative changes only occur on the gradients of the western and eastern temperature anomalies. Further analysis shows that the development of ENSO and Dipole has a time lag features statistically, with the sea-temperature anomaly in the eastern equatorial Pacific changing earlier (by three months or so). And the linkage between these two changes is a pair of coupled evolving Walker circulations that move reversely in the equatorial Pacific and Indian Oceans.     

The Spatial Patterns of Initial Errors Related to the ＂Winter Predictability Barrier＂ of the Indian Ocean Dipole

In this study, using the Geophysical Fluid Dynamics Laboratory Climate Model version 2pl （GFDL CM2pl） coupled model, the winter predictability barrier （WPB） is found to exist in the model not only in the growing phase but also the Indian Ocean dipole （IOD） decaying phase of positive events due to the effect of initial errors. In particular, the WPB is stronger in the growing phase than in the decaying phase. These results indicate that initial errors can cause the WPB. The domi- nant patterns of the initial errors that cause the occurrence of the WPB often present an eastern-western dipole both in the surface and subsurface temperature components. These initial errors tend to concentrate in a few areas, and these areas may represent the sensitive areas of the predictions of positive IOD events. By increasing observations over these areas and eliminating initial errors here, the WPB phenomenon may be largely weakened and the forecast skill greatly improved.     

Role of Parameter Errors in the Spring Predictability Barrier for ENSO Events in the Zebiak–Cane Model

ABSTRACT The impact of both initial and parameter errors on the spring predictability barrier （SPB） is investigated using the Zebiak Cane model （ZC model）. Previous studies have shown that initial errors contribute more to the SPB than parameter errors in the ZC model. Although parameter errors themselves are less important, there is a possibility that nonlinear interactions can occur between the two types of errors, leading to larger prediction errors compared with those induced by initial errors alone. In this case, the impact of parameter errors cannot be overlooked. In the present paper, the optimal combination of these two types of errors [i.e., conditional nonlinear optimal perturbation （CNOP） errors] is calculated to investigate whether this optimal error combination may cause a more notable SPB phenomenon than that caused by initial errors alone. Using the CNOP approach, the CNOP errors and CNOP-I errors （optimal errors when only initial errors are considered） are calculated and then three aspects of error growth are compared： （1） the tendency of the seasonal error growth; （2） the prediction error of the sea surface temperature anomaly; and （3） the pattern of error growth. All three aspects show that the CNOP errors do not cause a more significant SPB than the CNOP-I errors. Therefore, this result suggests that we could improve the prediction of the E1 Nifio during spring by simply focusing on reducing the initial errors in this model.     

Can the Uncertainties of Madden–Jullian Oscillation Cause a Significant “Spring Predictability Barrier” for ENSO Events?

With the Zebiak-Cane model and a parameterized stochastic representation of intraseasonal forcing, the impact of the uncertainties of Madden–Jullian Oscillation (MJO) on the “Spring Predictability Barrier (SPB)” for El Ni?no–Southern Oscillation (ENSO) prediction is studied. The parameterized form of MJO forcing is added physically to the Zebiak-Cane model to obtain the so-called Zebiak-Cane-MJO model and then the effects of initial error, stochastic model error, and their joint error mode on the SPB associated with El Ni?no prediction are estimated. The results show that the model errors caused by stochastic MJO forcing could hardly lead to a significant SPB while initial errors can do; furthermore, the joint error mode of initial error and model error associated with the stochastic MJO forcing can also lead to a significant SPB. These demonstrate that the initial error is probably the main error source of the SPB, which may provide a theoretical foundation of data assimilation for ENSO forecasts.     

The Predictability of Ocean Environments that Contributed to the 2020/21 Extreme Cold Events in China:2020/21 La Niña and 2020 Arctic Sea Ice Loss

Several consecutive extreme cold events impacted China during the first half of winter 2020/21,breaking the low-temperature records in many cities.How to make accurate climate predictions of extreme cold events is still an urgent issue.The synergistic effect of the warm Arctic and cold tropical Pacific has been demonstrated to intensify the intrusions of cold air from polar regions into middle-high latitudes,further influencing the cold conditions in China.However,climate models failed to predict these two ocean environments at expected lead times.Most seasonal climate forecasts only predicted the 2020/21 La Ni?a after the signal had already become apparent and significantly underestimated the observed Arctic sea ice loss in autumn 2020 with a 1-2 month advancement.In this work,the corresponding physical factors that may help improve the accuracy of seasonal climate predictions are further explored.For the 2020/21 La Ni?a prediction,through sensitivity experiments involving different atmospheric-oceanic initial conditions,the predominant southeasterly wind anomalies over the equatorial Pacific in spring of 2020 are diagnosed to play an irreplaceable role in triggering this cold event.A reasonable inclusion of atmospheric surface winds into the initialization will help the model predict La Ni?a development from the early spring of 2020.For predicting the Arctic sea ice loss in autumn 2020,an anomalously cyclonic circulation from the central Arctic Ocean predicted by the model,which swept abnormally hot air over Siberia into the Arctic Ocean,is recognized as an important contributor to successfully predicting the minimum Arctic sea ice extent.     

Can the uncertainties of Madden-Jullian Oscillation cause a significant “Spring Predictability Barrier” for ENSO events?

With the Zebiak-Cane model and a parameterized stochastic representation of intraseasonal forcing, the impact of the uncertainties of Madden-Jullian Oscillation (MJO) on the ??Spring Predictability Barrier (SPB)?? for El Ni?o-Southern Oscillation (ENSO) prediction is studied. The parameterized form of MJO forcing is added physically to the Zebiak-Cane model to obtain the so-called Zebiak-Cane-MJO model and then the effects of initial error, stochastic model error, and their joint error mode on the SPB associated with El Ni?o prediction are estimated. The results show that the model errors caused by stochastic MJO forcing could hardly lead to a significant SPB while initial errors can do; furthermore, the joint error mode of initial error and model error associated with the stochastic MJO forcing can also lead to a significant SPB. These demonstrate that the initial error is probably the main error source of the SPB, which may provide a theoretical foundation of data assimilation for ENSO forecasts.     

Is Model Parameter Error Related to a Significant Spring Predictability Barrier for El Nio events？ Results from a Theoretical Model

Within a theoretical ENSO model, the authors investigated whether or not the errors superimposed on model parameters could cause a significant ``spring predictability barrier' (SPB) for El Nino events. First, sensitivity experiments were respectively performed to the air--sea coupling parameter, α and the thermocline effect coefficient μ. The results showed that the uncertainties superimposed on each of the two parameters did not exhibit an obvious season-dependent evolution; furthermore, the uncertainties caused a very small prediction error and consequently failed to yield a significant SPB. Subsequently, the conditional nonlinear optimal perturbation (CNOP) approach was used to study the effect of the optimal mode (CNOP-P) of the uncertainties of the two parameters on the SPB and to demonstrate that the CNOP-P errors neither presented a unified season-dependent evolution for different El Nino events nor caused a large prediction error, and therefore did not cause a significant SPB. The parameter errors played only a trivial role in yielding a significant SPB. To further validate this conclusion, the authors investigated the effect of the optimal combined mode (i.e. CNOP error) of initial and model errors on SPB. The results illustrated that the CNOP errors tended to have a significant season-dependent evolution, with the largest error growth rate in the spring, and yielded a large prediction error, inducing a significant SPB. The inference, therefore, is that initial errors, rather than model parameter errors, may be the dominant source of uncertainties that cause a significant SPB for El Nino events. These results indicate that the ability to forecast ENSO could be greatly increased by improving the initialization of the forecast model.     

Spring asymmetric mode in the tropical Indian Ocean: role of El Niño and IOD

The spring asymmetric mode over the Tropical Indian Ocean (TIO) is characterized by contrasting patterns of rainfall and surface wind anomalies north and south of Equator. The asymmetric pattern in rainfall has evolved as a leading mode of variability in the TIO and is strongly correlated with El Niño-Southern Oscillation (ENSO) and positive Indian Ocean Dipole (IOD). The evolution of the asymmetric pattern in rainfall and surface wind during pure El Niño/IOD and co-occurrence years are examined in the twentieth century reanalysis for the period of 1871–2008 and atmospheric general circulation model (AGCM) simulations. The study revealed that spring asymmetric mode is well developed when El Niño co-occurred with IOD (positive) and is driven by the associated meridional gradients in sea surface temperature (SST) and sea level pressure (SLP). The pure El Niño composites are characterized by homogeneous (spatially) SST anomalies (positive) and weaker SLP gradients and convection, leading to weak asymmetric mode. The asymmetric mode is absent in the pure IOD (positive) composites due to the persistence of east west SST gradient for a longer duration than the co-occurrence years. The meridional gradient in SST anomalies over the TIO associated with the ENSO-IOD forcing is therefore crucial in developing/strengthening the spring asymmetric mode. The northwest Pacific anticyclonic circulation further strengthen the asymmetric mode in surface winds by inducing northeasterlies in the north Indian Ocean during pure El Niño and co-occurrence years. The simulations based on AGCM, forced by observed SSTs during the period of 1871–2000 supported the findings. The analysis of available station and ship track data further strengthens our results.     

The Role of Nonlinear Forcing Singular Vector Tendency Error in Causing the “Spring Predictability Barrier” for ENSO

With the Zebiak–Cane model, the present study investigates the role of model errors represented by the nonlinear forcing singular vector(NFSV) in the "spring predictability barrier"(SPB) phenomenon in ENSO prediction. The NFSV-related model errors are found to have the largest negative effect on the uncertainties of El Nio prediction and they can be classified into two types: the first is featured with a zonal dipolar pattern of SST anomalies(SSTA), with the western poles centered in the equatorial central–western Pacific exhibiting positive anomalies and the eastern poles in the equatorial eastern Pacific exhibiting negative anomalies; and the second is characterized by a pattern almost opposite to the first type. The first type of error tends to have the worst effects on El Nin?o growth-phase predictions, whereas the latter often yields the largest negative effects on decaying-phase predictions. The evolution of prediction errors caused by NFSVrelated errors exhibits prominent seasonality, with the fastest error growth in spring and/or summer; hence,these errors result in a significant SPB related to El Nin?o events. The linear counterpart of NFSVs, the(linear) forcing singular vector(FSV), induces a less significant SPB because it contains smaller prediction errors. Random errors cannot generate an SPB for El Nio events. These results show that the occurrence of an SPB is related to the spatial patterns of tendency errors. The NFSV tendency errors cause the most significant SPB for El Nio events. In addition, NFSVs often concentrate these large value errors in a few areas within the equatorial eastern and central–western Pacific, which likely represent those areas sensitive to El Nio predictions associated with model errors. Meanwhile, these areas are also exactly consistent with the sensitive areas related to initial errors determined by previous studies. This implies that additional observations in the sensitive areas would not only improve the accuracy of the initial field but also promote the reduction of model errors to greatly improve ENSO forecasts.     

Interannual Thermocline Signals and El Nio-La Nia Turnabout in the Tropical Pacific Ocean

One of the fundamental questions concerning the nature and prediction of the oceanic states in the equatorial eastern Pacific is how the turnabout from a cold water state (La Nina) to a warm water state (El Nino) takes place, and vice versa. Recent studies show that this turnabout is directly linked to the interannual thermocline variations in the tropical Pacific Ocean basin. An index, as an indicator and precursor to describe interannual thermocline variations and the turnabout of oceanic states in our previous paper (Qian and Hu, 2005), is also used in this study. The index, which shows the maximum subsurface temperature anomaly (MSTA), is derived from the monthly 21-year (1980-2000) expendable XBT dataset in the present study. Results show that the MSTA can be used as a precursor for the occurrences of El Nino (or La Nina) events. The subsequent analyses of the MSTA propagations in the tropical Pacific suggest a one-year potential predictability for El Nino and La Nina events by identifying ocean temperature anomalies in the thermocline of the western Pacific Ocean. It also suggests that a closed route cycle with the strongest signal propagation is identified only in the tropical North Pacific Ocean. A positive (or negative) MSTA signal may travel from the western equatorial Pacific to the eastern equatorial Pacific with the strongest signal along the equator. This signal turns northward along the tropical eastern boundary of the basin and then moves westward along the north side of off-equator around 16°N. Finally, the signal returns toward the equator along the western boundary of the basin. The turnabout time from an El Nino event to a La Nina event in the eastern equatorial Pacific depends critically on the speed of the signal traveling along the closed route, and it usually needs about 4 years. This finding may help to predict the occurrence of the El Nino or La Nina event at least one year in advance.     

Response of the tropical Indian Ocean SST to decay phase of La Niña and associated processes

Delayed impact of El Niño on Tropical Indian Ocean (TIO) Sea Surface Temperature (SST) variations and associated physical mechanisms are well documented by several studies. However, TIO SST evolution during the decay phase of La Niña and related processes are not adequately addressed before. Strong cooling associated with La Niña decay over the TIO could influence climate over the Indian Oceanic rim including Indian summer monsoon circulation and remotely northwest Pacific circulation. Thus understanding the TIO basin-wide cooling and related physical mechanisms during decaying La Niña years is important. Composite analyses revealed that negative SST anomalies allied to La Niña gradually dissipate from its mature phase (winter) till subsequent summer in central and eastern Pacific. In contrast, magnitude of negative SST anomalies in TIO, induced by La Niña, starts increasing from winter and attains their peak values in early summer. It is found that variations in heat flux play an important role in SST cooling over the central and eastern equatorial Indian Ocean, Bay of Bengal and part of Arabian Sea from late winter to early summer during the decay phase of La Niña. Ocean dynamical processes are mainly responsible for the evolution of southern TIO SST cooling. Strong signals of westward propagating upwelling Rossby waves between 10°S to 20°S are noted throughout (the decaying phase of La Niña) spring and summer. Anomalous cyclonic wind stress curl to the south of the equator is responsible for triggering upwelling Rossby waves over the southeastern TIO. Further, upwelling Rossby waves are also apparent in the Arabian Sea from spring to summer and partly contributing to the SST cooling. Heat budget analysis reveals that negative SST/MLT (mixed layer temperature) anomalies over the Arabian Sea are mostly controlled by heat flux from winter to spring and vertical advection plays an important role during early summer. Vertical and horizontal advection terms primarily contribute to the SST cooling anomalies over southern TIO and the Bay of Bengal cooling is primarily dominated by heat flux. Further we have discussed influence of TIO cooling on local rainfall variations.     

How Are El Nio and La Nia Events Improved in an Eddy-Resolving Ocean General Circulation Model?

The present study compares the performance of two versions of the LASG/IAP(State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics) Climate System Ocean Model(LICOM) in reproducing the interannual variability associated with El Nio and La Nia events in the tropical Pacific. Both versions are forced with the identical boundary conditions from observed or reanalysis data, in which one version has a finer spatial resolution of(1/10)° in the horizontal domain and 55 vertical layers, and the other version has a coarse resolution of 1° in the horizontal domain and 30 vertical layers. ENSO simulations form the two versions are compared with observations and, in particular, the improvements with regard to ENSO by the finer resolution ocean model are emphasized. As a result of the finer spatial resolution, both the vertical temperature gradient and vertical velocity are better represented in the equatorial Pacific than they are by the coarse resolution model; and thus, the corresponding vertical advections of temperature are more reasonable. Besides the mean climatology, simulated ENSO events and relevant feedbacks are much improved in the finer resolution model. A heat budget analysis suggests that both thermocline feedback and Ekman feedback are mainly responsible for the rapid increase in temperature anomalies during the developing and mature phases of ENSO events.     

The Asymmetric Effects of El Ni?o and La Ni?a on the East Asian Winter Monsoon and Their Simulation by CMIP5 Atmospheric Models

El Ni?o–Southern Oscillation(ENSO) events significantly affect the year-by-year variations of the East Asian winter monsoon(EAWM). However, the effect of La Ni?a events on the EAWM is not a mirror image of that of El Ni?o events. Although the EAWM becomes generally weaker during El Ni?o events and stronger during La Ni?a winters, the enhanced precipitation over the southeastern China and warmer surface air temperature along the East Asian coastline during El Ni?o years are more significant. These asymmetric effects are caused by the asymmetric longitudinal positions of the western North Pacific(WNP) anticyclone during El Ni?o events and the WNP cyclone during La Ni?a events; specifically, the center of the WNP cyclone during La Ni?a events is westward-shifted relative to its El Ni?o counterpart. This central-position shift results from the longitudinal shift of remote El Ni?o and La Ni?a anomalous heating, and asymmetry in the amplitude of local sea surface temperature anomalies over the WNP.However, such asymmetric effects of ENSO on the EAWM are barely reproduced by the atmospheric models of Phase 5 of the Coupled Model Intercomparison Project(CMIP5), although the spatial patterns of anomalous circulations are reasonably reproduced. The major limitation of the CMIP5 models is an overestimation of the anomalous WNP anticyclone/cyclone, which leads to stronger EAWM rainfall responses. The overestimated latent heat flux anomalies near the South China Sea and the northern WNP might be a key factor behind the overestimated anomalous circulations.     

Proposed scheme for modeling of ocean equatorial currents in the phase of El Niño and La Niña: Implementation of the mesoscale turbulence theory

El Niño is a phenomenon of the catastrophic increase of surface temperature in the eastern part of the Pacific Ocean. It has a significant impact to weather of the American continent and western regions of the tropical Pacific, as well as on the weather and climate of entirely the Earth. Most important factors influencing El Niño are the wind, ocean currents and slope of the water surface (and temperature resulting from these factors) at the equator in the Pacific Ocean. The paper considers results of mathematical modeling of the equatorial Pacific Ocean currents in the El Niño and La Niña phases using the theory of mesoscale turbulence. This theory has been successfully tested in modeling of global circulation of atmosphere and ocean (Arsen’yev et al., 2010) and it has been able to calculate the ocean current changes at equator under changing external conditions. It is shown that the water currents at the equator have a four-tier vertical structure. The surface trade-wind current is located above the subsurface undercurrent, below which we observe the intermediate current, turning into the equatorial deep counter flow. When El Niño begins, the currents are rearranged, change signs and sometimes merge with each other. In the phase of maximum development of the phenomenon there is a two-tier structure: (1) surface current heading the American coast is underlain (below the depth of 440 m) by (2) deep equatorial current directed to the Indonesian coast. The theoretical calculations are compared with the physical observations of ocean currents in the El Niño and La Niña phases. The obtained results indicate that the proposed mathematical apparatus makes it possible to explain the set of physical observations in the Pacific Ocean.     

The 2020/21 Extremely Cold Winter in China Influenced by the Synergistic Effect of La Niña and Warm Arctic

In the first half of winter 2020/21,China has experienced an extremely cold period across both northern and southern regions,with record-breaking low temperatures set in many stations of China.Meanwhile,a moderate La Ni?a event which exceeded both oceanic and atmospheric thresholds began in August 2020 and in a few months developed into its mature phase,just prior to the 2020/21 winter.In this report,the mid?high-latitude large-scale atmospheric circulation anomalies in the Northern Hemisphere,which were forced by the negative phase of Arctic Oscillation,a strengthened Siberian High,an intensified Ural High and a deepened East Asian Trough,are considered to be the direct reason for the frequent cold surges in winter 2020/21.At the same time,the synergistic effect of the warm Arctic and the cold tropical Pacific(La Ni?a)provided an indispensable background,at a hemispheric scale,to intensify the atmospheric circulation anomalies in middle-to-high latitudes.In the end,a most recent La Ni?a prediction is provided and the on-coming evolution of climate is discussed for the remaining part of the 2020/21 winter for the purpose of future decision-making and early warning.     

Extremely Active Tropical Cyclone Activities over the Western North Pacific and South China Sea in Summer 2018: Joint Effects of Decaying La Ni?a and Intraseasonal Oscillation

In summer 2018, a total of 18 tropical cyclones(TCs) formed in the western North Pacific(WNP) and South China Sea(SCS), among which 8 TCs landed in China, ranking respectively the second and the first highest since 1951.Most of these TCs travelled northwest to northward, bringing in heavy rainfall and strong winds in eastern China and Japan. The present study investigates the impacts of decaying La Ni?a and intraseasonal oscillation(ISO) on the extremely active TCs over the WNP and SCS in summer 2018 by use of correlation and composite analyses. It is found that the La Ni?a episode from October 2017 to March 2018 led to above-normal sea surface temperature(SST) over central–western Pacific, lower sea level pressure and 500-hPa geopotential height over WNP, and abnormally strong convective activities over the western Pacific in summer 2018. These preceding oceanic thermal conditions and their effects on circulation anomalies are favorable to TC genesis in summer. Detailed examination reveals that the monsoon trough was located further north and east, inducing more TCs in northern and eastern WNP; and the more eastward WNP subtropical high as well as the significant wave train with a "-+-+" height anomaly pattern over the midlatitude Eurasia–North Pacific region facilitated the northwest to northward TC tracks. Further analyses reveal that two successively active periods of Madden–Julian Oscillation(MJO) occurred in summer 2018 and the boreal summer intraseasonal oscillation(BSISO) was also active over WNP, propagating northward significantly, corresponding to the more northward TC tracks. The MJO was stagnant over the Maritime Continent to western Pacific,leading to notably enhanced convection in the lower troposphere and divergence in the upper troposphere, conducive to TC occurrences. In a word, the extremely active TC activities over the WNP and SCS in summer 2018 are closely linked with the decaying La Ni?a, and the MJO and BSISO; their joint effects result in increased TC occurrences and the TC tracks being shifted more northwest to northward than normal.     

Heterogeneity-Induced Heat-Flux Patterns in the Convective Boundary Layer: Can they be Detected from Observations and is There a Blending Height?—A Large-Eddy Simulation Study for the LITFASS-2003 Experiment

An understanding of how the convective boundary layer (CBL) is mixed under heterogeneous surface forcing is crucial for the interpretation of area-averaged turbulence measurements. To determine the height and degree to which a complex heterogeneous surface affects the CBL, large-eddy simulations (LES) for two days of the LITFASS-2003 experiment representing two different wind regimes were undertaken. Spatially-lagged correlation analysis revealed the turbulent heat fluxes to be dependent on the prescribed surface flux pattern throughout the entire CBL including the entrainment layer. These findings prompted the question of whether signals induced by surface heterogeneity can be measured by airborne systems. To examine this question, an ensemble of virtual flights was conducted using LES, according to Helipod flight measurements made during LITFASS-2003. The resulting ensemble-averaged heat fluxes indicated a clear dependence on the underlying surface up to the top of the CBL. However, a large scatter between the flux measurements in different ensemble runs was observed, which was the result of insufficient sampling of the largest turbulent eddies. The random and systematic errors based on the integral length scale did not indicate such a large scatter. For the given flight leg lengths, at least 10–15 statistically independent flight measurements were necessary to give a significant estimate of heterogeneity-induced signals in the CBL. The need for ensemble averaging suggests that the observed blending of heterogeneity-induced signals in the CBL can be partly attributed to insufficient averaging.