Variational iteration method for solving the mechanism of the Equatorial Eastern Pacific El Nino-Southern Oscillation

A class of coupled system for the E1 Nifio-Southern Oscillation （ENSO） mechanism is studied. Using the method of variational iteration for perturbation theory, the asymptotic expansions of the solution for ENSO model are obtained and the asymptotic behaviour of solution for corresponding problem is considered.

Impacts of El Nino-Southern Oscillation events on China＇s rice production

This paper aims to demonstrate the relationships between ENSO and rice production of Jiangxi province in order to identify the reason that ENSO might have little effect on Chinese rice production. Using a data set with measures of Jiangxi＇s climate and rice production, we find the reason that during 1985 and 2004 ENSO＇s well correlated with rainfall did not promote Chinese rice production. First, the largest effects of ENSO mostly occur in the months when there is no rice in the field. Second, there is almost no temperature effect. Finally, the monthly distribution of rainfall is almost the same in ENSO and neutral years because the largest effects are during months when there is the least rain. In addition, due to the high irrigation share and reliable and effective irrigation facilities of cultivated land, China＇s rice production is less climate-sensitive.

Unpacking the black box of deep learning for identifying El Nino-Southern oscillation

By training a convolutional neural network(CNN) model, we successfully recognize different phases of the El Nino-Southern oscillation. Our model achieves high recognition performance,with accuracy rates of 89.4% for the training dataset and 86.4% for the validation dataset.Through statistical analysis of the weight parameter distribution and activation output in the CNN, we find that most of the convolution kernels and hidden layer neurons remain inactive,while only two convolution kernels and two hidden layer neurons play active roles. By examining the weight parameters of connections between the active convolution kernels and the active hidden neurons, we can automatically differentiate various types of El Nino and La Nina,thereby identifying the specific functions of each part of the CNN. We anticipate that this progress will be helpful for future studies on both climate prediction and a deeper understanding of artificial neural networks.

El Niño-Southern Oscillation (ENSO) Variations and Climate Changes Worldwide

This investigation aims to study the El-Niño-Southern Oscillation (ENSO) events in these three phases: El Niño, La Niña, and neutral. Warm and cold events relate to the Spring/Summer seasons. This paper will search for connections between the ENSO events and climate anomalies worldwide. There is some speculation that those events would be necessary for the climate anomalies observed worldwide. After analyzing the data from the reports to the ENSO, it shows almost periodicity from 1950-2023. We emphasized the occurrence of El Niño two years, when it was most prominent, and the climate anomalies (following NOAA maps), 2015 and 2023. The results indicated that the observed climate anomalies couldn’t be linked to the abnormal events observed. The worldwide temperatures in those years enhanced mostly in 2023. It shows an abnormal behavior compared with all the years scrutinized and analyzed since the records began. Therefore, there must be unknown factors beyond ENSO that rule the worldwide temperatures and the climate anomalies observed.

Correlation of Rainfall Anomalies in Rwanda from September to December (SOND) with Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) Events

Understanding the relationship between rainfall anomalies and large-scale systems is critical for driving adaptation and mitigation strategies in socioeconomic sectors. This study therefore aims primarily to investigate the correlation between rainfall anomalies in Rwanda during the months of September to December (SOND) with the occurrences of Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) events. The study is useful for early warning and forecasting of negative effects associated with extreme rainfall anomalies across the country, using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), the National Centers for Environmental Prediction (NCEP) National Center for Atmospheric Research (NCAR) reanalysis sea surface temperature and ERA5 reanalysis datasets, during the period of 1983-2021. Both empirical orthogonal function (EOF), correlation analysis and composite analysis were used to delineate variability, relationship and the related atmospheric circulation between Rwanda seasonal rainfall September to December (SOND) with Indian Ocean Dipole (IOD) and El-Nino Southern Oscillation (ENSO). The results for Empirical Orthogonal Function (EOF) for the reconstructed rainfall data set showed three modes. EOF-1, EOF-2 and EOF-3 with their total variance of 63.6%, 16.5% and 4.8%, Indian ocean dipole (IOD) events resulted to a strong positive correlation of rainfall anomalies and Dipole model index (DMI) (r = 0.42, p value = 0.001, DF = 37) significant at 95% confidence level. The composite analysis for the reanalysis dataset was carried out to show the circulation patterns during four different events correlated with September to December seasonal rainfall in Rwanda using T-test at 95% confidence level. Wind anomaly revealed that there was a convergence of south westerly winds and easterly wind over the study area during positive Indian Ocean Diploe (PIOD) and PIOD with El Nino concurrence event years. The finding of this study will contribute to the enhancement of SOND seasonal rainfall forecasting and the reduction of vulnerability during IOD (ENSO) event years.

Asymptotic solution for EI Nino-southern oscillation of nonlinear model

A class of nonlinear coupled system for EI Nino-Southern Oscillation （ENSO） model is considered. Using the asymptotic theory and method of variational iteration, the asymptotic expansion of the solution for ENSO models is obtained.

Seasonal evolution of the effects of the El Nino–Southern Oscillation on lower stratospheric water vapor:Delayed effects in late winter and early spring

Water vapor in the stratosphere makes a significant contribution to global climate change by altering the radiative energy budget of the Earth’s climate system.Although many previous studies have shown that the El Ni?o–Southern Oscillation(ENSO)has significant effects on the water vapor content of the stratosphere in terms of the annual or seasonal mean,a comprehensive analysis of the seasonal evolution of these effects is still required.Using reanalysis data and satellite observations,we carried out a composite analysis of the seasonal evolution of stratospheric water vapor during El Ni?o/La Ni?a peaks in winter and decays in spring.The ENSO has a distinct hysteresis effect on water vapor in the tropical lower stratosphere.The El Ni?o/La Ni?a events moisten/dry out the tropical lower stratosphere in both winter and spring,whereas this wetting/dehydration effect is more significant in spring.This pattern is due to a warmer temperature in the upper troposphere and lower stratosphere during the El Ni?o spring phase,which causes more water vapor to enter the stratosphere,and vice versa for La Ni?a.This delayed warming/cooling in the lower stratosphere during the El Ni?o/La Ni?a decay in spring leads to the seasonal evolution of ENSO effects on water vapor in the lower stratosphere.

Asymptotic solution for a class of sea-air oscillator model for El Nio-southern oscillation

The El Nifio-Southern Oscillation （ENSO） is an interannual phenomenon involved in the tropical Pacific Oceanatmosphere interactions. In this paper, an asymptotic method of solving the nonlinear equation for the ENSO model is used. And based on a class of oscillator of ENSO model, the approximate solution of a corresponding problem is studied by employing the perturbation method. Firstly, an ENSO model of nonlinear time delay equation of equatorial Pacific is introduced, Secondly, by using the perturbed method, the zeroth and first order asymptotic perturbed solutions are constructed. Finally, from the comparison of the values for a figure, it is seen that the first asymptotic perturbed solution using the perturbation method has a good accuracy. And it is proved from the results that the perturbation method can be used as an analytic operation for the sea surface temperature anomaly in the equatorial Pacific of the atmosphere-ocean oscillation for the ENSO model.

The periodic solution to a delayed sea-air oscillator coupling model for the El Nifio-Southern Oscillation （ENSO）

A time-delay sea-air oscillator coupling model is studied. Using Mawhin＇s continuation theorem, the result on the existence of periodic solutions for the sea-air oscillator model is obtained.

Perturbation method of studying the EI Nifio oscillation with two parameters by using the delay sea-air oscillator model

The EI Nino-southern oscillation （ENSO） is an interannual phenomenon involved in tropical Pacific ocean- atmosphere interactions. In this paper, we develop an asymptotic method of solving the nonlinear equation using the ENSO model. Based on a class of the oscillator of the ENSO model, a approximate solution of the corresponding problem is studied employing the perturbation method.

PERTURBED SOLUTION OF SEA-AIR OSCILLATOR FOR THE EL NI O/LA NI O-SOUTHERN OSCILLATION MECHANISM

A class of coupled system to oscillate of the E1 Nino/La Nino-Southern Oscillation （ENSO） mechanism is studied. Using the perturbed theory, the asymptotic expansions and asymptotic behavior of the solution for an ENSO model are obtained.

Response of Growing Season Gross Primary Production to El Nino in Different Phases of the Pacific Decadal Oscillation over Eastern China Based on Bayesian Model Averaging

Gross primary production(GPP) plays a crucial part in the carbon cycle of terrestrial ecosystems.A set of validated monthly GPP data from 1957 to 2010 in 0.5°× 0.5° grids of China was weighted from the Multi-scale Terrestrial Model Intercomparison Project using Bayesian model averaging(BMA).The spatial anomalies of detrended BMA GPP during the growing seasons of typical El Nino years indicated that GPP response to El Nino varies with Pacific Decadal Oscillation(PDO) phases: when the PDO was in the cool phase,it was likely that GPP was greater in northern China(32°–38°N,111°–122°E) and less in the Yangtze River valley(28°–32°N,111°–122°E);in contrast,when PDO was in the warm phase,the GPP anomalies were usually reversed in these two regions.The consistent spatiotemporal pattern and high partial correlation revealed that rainfall dominated this phenomenon.The previously published findings on how El Nino during different phases of PDO affecting rainfall in eastern China make the statistical relationship between GPP and El Nino in this study theoretically credible.This paper not only introduces an effective way to use BMA in grids that have mixed plant function types,but also makes it possible to evaluate the carbon cycle in eastern China based on the prediction of El Nino and PDO.

Air-sea interactions associated with tropospheric biennial oscillation in South China Sea summer monsoon and their effects on El Nio-Southern Oscillation

The South China Sea summer monsoon （SCSSM） behaves with prominent climate variability from the in- traseasonal to interdecadal time scales. On the interannual time scale, the biennial variability （so-called tropospheric biennial oscillation, TBO） is as important as the E1 Nifio-Southem Oscillation （ENSO） period. Some observed data sets, including reanalysis data, are used to explore the associated air-sea interactive physical processes and how the SCSSM TBO affects the ENSO. The results show that the shearing vorticity induced by the north Indian Ocean sea surface temperature anomalies （SSTAs） and the anomalous Philip- pine Sea anticyclone both contribute to the TBO in the SCSSM. The results also indicate that the ENSO has a weak effect on the SCSSM TBO, whereas the latter affects the ENSO to some extent.

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

THE EXCITING MECHANISM OF TROPICAL INTRASEASONAL OSCILLATION TO EL NINO EVENT

The data analyses indicated that the occurrence of D Nino event is closely related to intraseasonal oscillation (ISO) in the tropical atmosphere : The intraseasonal oscillation is very strong in tile tropics (particularly over the equatorial western Pacific) prior to the occurrence of El Nino; But the ISO is evidently reduced and the quasistationary system is enhanced after the outbreak of El Nino. A simple air-sea coupled model study shows that the periodical self-excited oscillation can be produced in the air-sea-coupled system, but the pattern is different from the observed ENSO mode. When there is external (atmospheric) forcing with interannual time scale, a coupled mode, which looks like the ENSO mode, will be excited in the air-sea system. Synthesizing the results in data analyses and the theoretical investigation. the mechanism of ISO in the tropical atmosphere exciting the EI Nino event can be suggested : The interannual anomalies (variations) of the tropical ISO play an important role in the exciting EI Nino event through the air-sea interaction.

CMIP 6 models simulation of the connection between North/South Pacific Meridional Mode and ENSO

The subtropical North and South Pacific Meridional Modes(NPMM and SPMM)are well known precursors of El Niño-Southern Oscillation(ENSO).However,relationship between them is not constant.In the early 1980,the relationship experienced an interdecadal transition.Changes in this connection can be attributed mainly to the phase change of the Pacific decadal oscillation(PDO).During the positive phase of PDO,a shallower thermocline in the central Pacific is responsible for the stronger trade wind charging(TWC)mechanism,which leads to a stronger equatorial subsurface temperature evolution.This dynamic process strengthens the connection between NPMM and ENSO.Associated with the negative phase of PDO,a shallower thermocline over southeastern Pacific allows an enhanced wind-evaporation-SST(WES)feedback,strengthening the connection between SPMM and ENSO.Using 35 Coupled Model Intercomparison Project Phase 6(CMIP6)models,we examined the NPMM/SPMM performance and its connection with ENSO in the historical runs.The great majority of CMIP6 models can reproduce the pattern of NPMM and SPMM well,but they reveal discrepant ENSO and NPMM/SPMM relationship.The intermodal uncertainty for the connection of NPMM-ENSO is due to different TWC mechanism.A stronger TWC mechanism will enhance NPMM forcing.For SPMM,few models can simulate a good relationship with ENSO.The intermodel spread in the relationship of SPMM and ENSO owing to SST bias in the southeastern Pacific,as WES feedback is stronger when the southeastern Pacific is warmer.

The low frequency oscillations of the sea surface temperature in the Equatorial Eastern Pacific and El Nino formation

-In this paper the variations of the sea surface temperature anomalies (SSTA) in the Equatorial Eastern Pacific are analysed. The results show that there are two peaks in the spectrum. One is the low frequency oscillation with a period of 3 - 5 years, and the other is the quasi-biennial oscillation. The former shows a westward migration in the warm episode of SSTA and the latter has the opposite trend. The El Nino events will be formed while the two frquency bands are in phase in the warming stage of SSTA in the Equatorial Eastern Pacific

Effect of El Nino Southern Oscillations on the incidence of enteric fever in Ahmedabad,India from 1985 to 2017

Objective:To explore the relationship between climate variables and enteric fever in the city of Ahmedabad and report preliminary findings regarding the influence of El Nino Southern Oscillations and Indian Ocean Dipole over enteric fever incidence.Method:A total of 29808 Widal positive enteric fever cases reported by the Ahmedabad Municipal Corporation and local climate data in 1985-2017 from Ahmedabad Meteorology Department were analysed.El Nino,La Nina,neutral and Indian Ocean Dipole years as reported by the National Oceanic and Atmospheric Administration for the same period were compared for the incidence of enteric fever.Results:Population-normalized average monthly enteric fever case rates were the highest for El Nino years(25.5),lower for La Nina years(20.5)and lowest for neutral years(17.6).A repeated measures ANOVA analysis showed no significant difference in case rates during the three yearly El Nino Southern Oscillations categories.However,visual profile plot of estimated marginal monthly means showed two distinct characteristics:an early rise and peaking of cases in the El Nino and La Nina years,and a much more restrained rise without conspicuous peaks in neutral years.Further analysis based on monthly El Nino Southern Oscillations categories was conducted to detect differences in median monthly case rates.Median case rates in strong and moderate El Nino months and strong La Nina months were significantly dissimilar from that during neutral months(P<0.001).Conclusions:El Nino Southern Oscillations events influence the incidence of enteric fever cases in Ahmedabad,and further investigation from more cities and towns is required.

The homotopic method of travelling wave solution for El Nio tropic sea-air coupled oscillator

The EI Nimo and Southern Oscillation （ENSO） is an interannual phenomenon involved in the tropical Pacific sea-air interactions. In this paper, an asymptotic method of solving nonlinear equations for the ENSO model is proposed. And based on a class of oscillator of the ENSO model and by employing the method of homotopic mapping, the approximate solution of equations for the corresponding ENSO model is studied. It is proved from the results that homotopic method can be used for analysing the sea surface temperature anomaly in the equatorial Pacific of the sea-air oscillator for the ENSO model.

Asymptotic solution for the El Nio time delay sea-air oscillator model

A sea-air oscillator model is studied using the time delay theory. The aim is to find an asymptotic solving method for the El Nino-southern oscillation （ENSO） model. Employing the perturbed method, an asymptotic solution of the corresponding problem is obtained. Thus we can obtain the prognoses of the sea surface temperature （SST） anomaly and the related physical quantities.