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1
Lu, Bo, Fei-Fei Jin, and Hong-Li Ren. "A Coupled Dynamic Index for ENSO Periodicity." Journal of Climate 31, no. 6 (2018): 2361–76. http://dx.doi.org/10.1175/jcli-d-17-0466.1.
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El Niño–Southern Oscillation (ENSO) is the most active interannual climatic mode, with great global impacts. The state-of-the-art climate models can simulate this dominant mode variability to a large extent. Nevertheless, some of ENSO’s fundamental time–space characteristics still have a large spread in the simulations across the array of recent climate models. For example, the large biases of ENSO periodicity still exist among model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Based on the recharge oscillator framework, a coupled dynamic index for ENSO periodicity is proposed in this study, referred to as the Wyrtki index, in parallel to the Bjerknes index for ENSO instability. The Wyrtki index provides an approximate dynamic measure for ENSO linear periodicity. It has two main contribution terms: the thermocline and zonal advective feedbacks (or F factor) multiplied by the efficiency factor B of discharging–recharging of the equatorial heat content driven by ENSO wind stress anomalies. It is demonstrated that the diversity of simulated ENSO periodicity in CMIP5 models results from the biases in mean state and several key parameters that control ENSO dynamics. A larger F factor would result in a shorter ENSO period [e.g., BCC_CSM1.1(m)], whereas a smaller B factor would lead to a longer ENSO period (e.g., HadGEM2-ES). The Wyrtki index serves as a useful tool for a quantitative assessment of the sources for ENSO periodicity in reanalysis data and its biases in CMIP5 model simulations.
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Lv, Aifeng, Lei Fan, and Wenxiang Zhang. "Impact of ENSO Events on Droughts in China." Atmosphere 13, no. 11 (2022): 1764. http://dx.doi.org/10.3390/atmos13111764.
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The El Niño Southe58rn Oscillation (ENSO) is a typical oscillation affecting climate change, and its stable periodicity, long-lasting effect, and predictable characteristics have become important indicators for regional climate prediction. In this study, we analyze the Standardized Precipitation Evapotranspiration Index (SPEI), the Niño3.4 index, the Southern Oscillation Index (SOI), and the Multivariate ENSO Index (MEI). Additionally, we explore the spatial and temporal distribution of the correlation coefficients between ENSO and SPEI and the time lag between ENSO events of varying intensities and droughts. The results reveal that the use of Nino3.4, MEI, and SOI produces differences in the occurrence time, end time, and intensity of ENSO events. Nino3.4 and MEI produce similar results for identifying ENSO events, and the Nino3.4 index accurately identifies and describes ENSO events with higher reliability. In China, the drought-sensitive areas vulnerable to ENSO events include southern China, the Jiangnan region, the middle and lower reaches of the Yangtze River, and the arid and semi-arid areas of northwestern China. Droughts in these areas correlate significantly with meteorological drought, and time-series correlations between ENSO events and droughts are significantly stronger in regions close to the ocean. Drought occurrence lags ENSO events: when using the Niño3.4 index to identify ENSO, droughts lag the strongest and weakest El Niño events by 0–12 months. However, when using the MEI as a criterion for ENSO, droughts lag the strongest and weakest El Niño events by 0–7 months. The time lag between the strongest ENSO event and drought is shorter than that for the weakest ENSO event, and droughts have a wider impact. The results of this study can provide a climate-change-compatible basis for drought monitoring and prediction.
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Evans, M. N., R. G. Fairbanks, and J. L. Rubenstone. "A proxy index of ENSO teleconnections." Nature 394, no. 6695 (1998): 732–33. http://dx.doi.org/10.1038/29424.
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Aprilia, Bunga, Marzuki Marzuki, and Imam Taufiq. "Prediksi El Nino Southern Oscillation (ENSO) Menggunakan Jaringan Saraf Tiruan (JST)-Backpropagation." Jurnal Fisika Unand 9, no. 4 (2021): 421–27. http://dx.doi.org/10.25077/jfu.9.4.421-427.2020.
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Penelitian ini bertujuan untuk memprediksi nilai indeks ENSO yaitu Sea Surface Temperature (Nino 1.2, Nino 3, Nino 3.4 dan Nino 4), Southern Oscillation Index (SOI) dan Multivariate ENSO Index versi 2 (MEI.v2) yang diambil dari tahun 1979-2018. Prediksi dilakukan dengan menggunakan metode JST-backpropagation dengan memvariasikan learning rate dan momentum. Semua indeks menghasilkan nilai akurasi prediksi ENSO yang tinggi, namun indeks Nino 4 merupakan indeks yang memiliki akurasi tertinggi karena nilai Mean Square Error (MSE) pelatihan dan pengujiannya yang relatif lebih kecil dibandingkan dengan indeks lainnya. Indeks Nino 4 memiliki MSE pelatihan 0,0072739 yang berhenti pada epoch ke-69 dan MSE pengujian 0,0085917 dengan akurasi prediksi 99,9989%. Hasil ini diperoleh dari arsitektur JST-backpropagation 12-10-1 dengan nilai learning rate 0,10 dan momentum 0,40. Prediksi ENSO berdasarkan indeks Nino 4 untuk tahun 2021 menunjukkan keadaan iklim dunia dalam kondisi normal. This study aims to predict ENSO index using Sea Surface Temperature (Nino 1.2, Nino 3, Nino 3.4 and Nino 4 indexes), Southern Oscillation Index (SOI), and Multivariate ENSO Index version 2 (MEI.v2) during 1979 - 2018. The prediction was carried out using the ANN-backpropagation method by varying the learning rate and momentum. All indices produce high ENSO prediction accuracy values, but the Nino 4 index is the best one because the Mean Square Error (MSE) for training and testing steps are relatively smaller than other indexes. The Nino 4 index has a training MSE of 0.0072739 which stops at the 69th epoch and a testing MSE of 0.0085917 with a predictive accuracy of 99.9989%. These results were obtained from the back-propagation architecture ANN 12-10-1 with a learning rate of 0.10 and a momentum of 0.40. The prediction of ENSO in 2021 based on the Nino 4 index shows that the world climate condition is under normal conditions.
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Westra, Seth, Benjamin Renard, and Mark Thyer. "The ENSO–Precipitation Teleconnection and Its Modulation by the Interdecadal Pacific Oscillation." Journal of Climate 28, no. 12 (2015): 4753–73. http://dx.doi.org/10.1175/jcli-d-14-00722.1.
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Abstract This study evaluates the role of the interdecadal Pacific oscillation (IPO) in modulating the El Niño–Southern Oscillation (ENSO)–precipitation relationship. The standard IPO index is described together with several alternatives that were derived using a low-frequency ENSO filter, demonstrating that an equivalent IPO index can be obtained as a low-frequency version of ENSO. Several statistical artifacts that arise from using a combination of raw and smoothed ENSO indices in modeling the ENSO–precipitation teleconnection are then described. These artifacts include the potentially spurious identification of low-frequency variability in a response variable resulting from the use of smoothed predictors and the potentially spurious modulation of a predictor–response relationship by the low-frequency version of the predictor under model misspecification. The role of the IPO index in modulating the ENSO–precipitation relationship is evaluated using a global gridded precipitation dataset, based on three alternative statistical models: stratified, linear, and piecewise linear. In general, the information brought by the IPO index, beyond that already contained in the Niño-3.4 index, is limited and not statistically significant. An exception is in northeastern Australia using annual precipitation data, and only for the linear model. Stratification by the IPO index induces a nonlinear ENSO–precipitation relationship, suggesting that the apparent modulation by the IPO is likely to be spurious and attributable to the combination of sample stratification and model misspecification. Caution is therefore required when using smoothed climate indices to model or explain low-frequency variability in precipitation.
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Lin, Chen-Chih, Yi-Jiun Liou, and Shih-Jen Huang. "Impacts of Two-Type ENSO on Rainfall over Taiwan." Advances in Meteorology 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/658347.
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Impacts of two-type ENSO (El Niño/Southern Oscillation), canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI). The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different depending on the effects of two-type ENSO. In canonical El Niño episode, the rainfall increases in winter and spring while it reduces in summer and autumn. On the contrary, the rainfall increases in summer and autumn but reduces in winter and spring in El Niño Modoki episode. Nevertheless, two types of La Niña cause similar effects on the rainfall over Taiwan. It increases in autumn only. The rainfall variations in different types of ENSO are mainly caused by the monsoon and topography.
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Koem, S., R. J. Lahay, and S. K. Nasib. "The sensitivity of meteorological drought index towards El Nino-Southern Oscillation." IOP Conference Series: Earth and Environmental Science 1089, no. 1 (2022): 012005. http://dx.doi.org/10.1088/1755-1315/1089/1/012005.
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Abstract El Nino-Southern Oscillation (ENSO) contributes to the regional climates, such as precipitation and droughts. The objectives of the present work were to: (1) identify the severity index; (2) analyze the correlation of SPI and RDI, and; (3) identify the response of SPI and RDI towards ENSO. SPI and RDI were calculated for time scales (3, 6, and 12 months), and these represented the seasonal and annual drought. The identification of the responses of the drought severity index, based on ENSO, consisted of several thresholds, namely weak, moderate, and strong. The correlational value and RMSE only represented the performance of SPI and RDI on different time scales. The drought severity index would decline along with an increase in the time scales. The strong El Nino phase could be significant to the seasonal and annual drought. In other words, ENSO was impactful on the precipitation and dynamics of drought. Drought periods were due to the moderate and strong El Nino phase, while the weak phase led to a normal condition. For this reason, ENSO could be functioned as an indicator to predict drought.
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Ziemke, J. R., S. Chandra, L. D. Oman, and P. K. Bhartia. "A new ENSO index derived from satellite measurements of column ozone." Atmospheric Chemistry and Physics Discussions 10, no. 2 (2010): 2859–87. http://dx.doi.org/10.5194/acpd-10-2859-2010.
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Abstract. Column Ozone measured in tropical latitudes from Nimbus 7 TOMS, Earth Probe TOMS, NOAA SBUV, and Aura OMI satellite instruments are used to derive an El Niño-Southern Oscillation (ENSO) index. This index, which covers a time period from 1979 to the present, is defined as the Ozone ENSO Index (OEI) and is the first developed from atmospheric trace gas measurements. Using a data mining technique with existing ENSO indices of surface pressure and sea-surface temperature, the OEI is constructed by first averaging monthly mean column ozone over two broad regions in the western and eastern Pacific and taking their difference. This differencing yields a self-calibrating ENSO index which is independent of individual instrument calibration offsets and drifts in measurements over the long record. The combined Aura OMI and MLS ozone data confirm that zonal variability in total column ozone in the tropics caused by ENSO events lies almost entirely in the troposphere. As a result, the OEI can be derived directly from total column ozone instead of tropospheric column ozone. For clear-sky ozone measurements a +1 K change in Nino 3.4 index corresponds to +2.9 DU (Dobson Unit) change in the OEI, while a +1 hPa change in SOI coincides with a −1.7 DU change in the OEI. For ozone measurements under all cloud conditions these numbers are +2.4 DU and −1.4 DU, respectively. As an ENSO index based upon ozone, it is potentially useful in evaluating climate models predicting long term changes in ozone and other trace gases.
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Xu, Zhen, and G. Cornelis van Kooten. "The El Niño Southern Oscillation index and wildfire prediction in British Columbia." Forestry Chronicle 90, no. 05 (2014): 592–98. http://dx.doi.org/10.5558/tfc2014-122.
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This study investigates the potential to predict monthly wildfires and area burned in British Columbia's interior using El Niño Southern Oscillation (ENSO). The zero-inflated negative binomial (ZINB) and the generalized Pareto (GP) distributions are used, respectively, to account for uncertainty in wildfire frequency and area burned. Results indicate that a four-month lag of the ENSO index has a strong positive influence on monthly wildfire occurrence. Upon fitting the GP distribution with a logit model regressed on the ENSO index, we predict the probabilities that monthly area burned exceeds 1700 ha and find that risks of large fires are significantly higher in northwestern BC. However, the ENSO is likely unable to provide consistent predictions of the total area burned in any month. Sensitivity analysis indicates that increases in the mean value of the monthly ENSO index result in a small increase in the predicted number of fires and an increase in the probability of large burns. This study has several implications for decision-making regarding firefighting budget planning and insurance for firefighting expenditures.
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Beckers, Joost V. L., Albrecht H. Weerts, Erik Tijdeman, and Edwin Welles. "ENSO-conditioned weather resampling method for seasonal ensemble streamflow prediction." Hydrology and Earth System Sciences 20, no. 8 (2016): 3277–87. http://dx.doi.org/10.5194/hess-20-3277-2016.
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Abstract. Oceanic–atmospheric climate modes, such as El Niño–Southern Oscillation (ENSO), are known to affect the local streamflow regime in many rivers around the world. A new method is proposed to incorporate climate mode information into the well-known ensemble streamflow prediction (ESP) method for seasonal forecasting. The ESP is conditioned on an ENSO index in two steps. First, a number of original historical ESP traces are selected based on similarity between the index value in the historical year and the index value at the time of forecast. In the second step, additional ensemble traces are generated by a stochastic ENSO-conditioned weather resampler. These resampled traces compensate for the reduction of ensemble size in the first step and prevent degradation of skill at forecasting stations that are less affected by ENSO. The skill of the ENSO-conditioned ESP is evaluated over 50 years of seasonal hindcasts of streamflows at three test stations in the Columbia River basin in the US Pacific Northwest. An improvement in forecast skill of 5 to 10 % is found for two test stations. The streamflows at the third station are less affected by ENSO and no change in forecast skill is found here.
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SINGH, O. P., TARIQ MASOOD ALI KHAN, SAZEDUR RAHMAN, and SALAH UDDIN. "Summer monsoon rainfall over Bangladesh in relation to Multivariate ENSO Index." MAUSAM 51, no. 3 (2021): 255–60. http://dx.doi.org/10.54302/mausam.v51i3.1783.
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The relationship between monthly rainfall over Bangladesh during monsoon season and bi-monthly Multivariate ENSO Index (MEI) pertaining to the period from first week of previous month to first week of the month under consideration, has been investigated. The MEI is calculated as the first Principal Component (PC) of six variables over the tropical Pacific, viz., sea surface temperature, sea level pressure, zonal and meridional components of the surface wind, surface air temperature and total cloudiness fraction of the sky. The MEI values for prognostic purposes are available by the first week of every month. MEI is better for monitoring ENSO than other indices like Southern Oscillation Index (SOI) or various SST indices as it integrates complete information on ENSO and reflects the nature of complete ocean atmosphere system. Positive values of MEI indicate warm ENSO phase (EI-Nino) and negative ones represent cold phase (La-Nina).
 
 The results of the present study show that June rainfall of Bangladesh is adversely affected by the ENSO. But interestingly Bangladesh seems to receive more than normal rainfall during August of ENSO years. ENSO does not seem to have any significant adverse impact on July and September rainfall of Bangladesh. The results of the study may find applications in foreshadowing monsoon rainfall over Bangladesh on a monthly scale.
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CHATTOPADHYAY, J., and R. BHATLA. "A re-examination of ENSO/ anti-ENSO events and simultaneous performance of the Indian summer monsoon." MAUSAM 47, no. 1 (2021): 59–66. http://dx.doi.org/10.54302/mausam.v47i1.3686.
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The relationship between ENSO/anti-ENSO events in the Pacific basin and simultaneous all India monsoon has been re-examined for the period 1901-1990 using Southern Oscillation Index (SOI). The result shows that there is fairly strong association between ENSO events and dry monsoon years. There exists a weak teleconnection between anti-ENSO events and wet monsoon indicating that anti-ENSO events have only a moderate impact on the Indian monsoon rainfall. Developing ENSO (anti-ENSO) episodes during the monsoon season indicates non-occurrence of simultaneous floods (droughts) with a very high degree of confidence 70 (50) percent of the droughts (floods) during the above period have occurred during ENSO (anti-ENSO) events indicating that extreme monsoon activities in the form of droughts (floods) might be important factors for the occurrence of simultaneous ENSO/anti-ENSO events.
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Liu, Zhiqing, and Jianjun Xu. "Increase in the Intensity of Air–Sea Coupling in the Key ENSO Region during 1955–2020." Atmosphere 13, no. 12 (2022): 2025. http://dx.doi.org/10.3390/atmos13122025.
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The El Niño and Southern Oscillation (ENSO), a phenomenon of air–sea coupling in the tropical Pacific, has strong response to global climate change. In this study, the primary region where ENSO occurred during the period 1955–2020 was selected as the key ENSO region, and the changes in air–sea coupling in this region were explored. The New Southern Oscillation Index (NSOI), modified from the previous Southern Oscillation Index, represents atmospheric changes, and the Niño-3.4 index represents oceanic changes. The absolute value of the running correlation coefficient between the Niño-3.4 index and NSOI in the 121-month time window was defined as the Intensity of Air–Sea Coupling (IASC) in the key ENSO region. The results showed that the IASC has significantly increased, with a confidence level of 95%, during the period 1955–2020, and the range where the correlation coefficient between the Niño-3.4 index and the sea level pressure anomaly over the key ENSO region was greater than 0.6 has evidently expanded in the context of global warming, which corresponded to the increase in IASC. Moreover, the coupling positions of sea surface temperature and wind anomalies changed, tending to the east of the equatorial Pacific during 1977–1998, and to the west during 1999–2020.
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Kemarau, Ricky Anak, and Oliver Valentine Eboy. "The Impact of El Niño–Southern Oscillation (ENSO) on Temperature: A Case Study in Kuching, Sarawak." Malaysian Journal of Social Sciences and Humanities (MJSSH) 6, no. 1 (2021): 289–97. http://dx.doi.org/10.47405/mjssh.v6i1.602.
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The El Niño–Southern Oscillation (ENSO) event is a climate event that has an impact on the world climate. The effects of ENSO are often associated with prolonged droughts and floods since 1980 following global climate change. In addition to causing flooding and drought. Indirectly, the occurrence of ENSO causes health problems, environmental destruction, affecting economic activities such as agriculture and fisheries. Many studies on ENSO have been conducted. However, there is still a lack of research on the effect of ENSO on temperature in local knowledge areas, especially urban areas because the urban environment especially building materials that can absorb and release heat. In addition, previous studies have focused on large-scale areas. Beside that there still gap to understand and increase knowledge about the effect of ENSO on local temperatures, especially in urban areas. This study uses meteorological data and Oceanic Nino Index (ONI) from 1988 to 2019. This study found that the occurrence of ENSO has an effect on the value of daily temperature but differs based on the value of the ONI index. In addition, this study uses linear regression in predicting the effect of ENSO on temperature. The results of this study are useful to those responsible for understanding the impact of ENSO on temperature in urban areas to provide infrastructure in reducing the impact of ENSO as well as adjustment measures during the occurrence of ENSO.
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Choi, Jung, Soon-Il An, Sang-Wook Yeh, and Jin-Yi Yu. "ENSO-Like and ENSO-Induced Tropical Pacific Decadal Variability in CGCMs." Journal of Climate 26, no. 5 (2013): 1485–501. http://dx.doi.org/10.1175/jcli-d-12-00118.1.
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Abstract Outputs from coupled general circulation models (CGCMs) are used in examining tropical Pacific decadal variability (TPDV) and their relationships with El Niño–Southern Oscillation (ENSO). Herein TPDV is classified as either ENSO-induced TPDV (EIT) or ENSO-like TPDV (ELT), based on their correlations with a decadal modulation index of ENSO amplitude and spatial pattern. EIT is identified by the leading EOF mode of the low-pass filtered equatorial subsurface temperature anomalies and is highly correlated with the decadal ENSO modulation index. This mode is characterized by an east–west dipole structure along the equator. ELT is usually defined by the first EOF mode of subsurface temperature, of which the spatial structure is similar to ENSO. Generally, this mode is insignificantly correlated with the decadal modulation of ENSO. EIT closely interacts with the residuals induced by ENSO asymmetries, both of which show similar spatial structures. On the other hand, ELT is controlled by slowly varying ocean adjustments analogous to a recharge oscillator of ENSO. Both types of TPDV have similar spectral peaks on a decadal-to-interdecadal time scale. Interestingly, the variances of both types of TPDV depend on the strength of connection between El Niño–La Niña residuals and EIT, such that the strong two-way feedback between them enhances EIT and reduces ELT. The strength of the two-way feedback is also related to ENSO variability. The flavors of El Niño–La Niña with respect to changes in the tropical Pacific mean state tend to be well simulated when ENSO variability is larger in CGCMs. As a result, stronger ENSO variability leads to intensified interactive feedback between ENSO residuals and enhanced EIT in CGCMs.
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Conti, G., A. Navarra, and J. Tribbia. "The ENSO Transition Probabilities." Journal of Climate 30, no. 13 (2017): 4951–64. http://dx.doi.org/10.1175/jcli-d-16-0490.1.
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ENSO is investigated here by considering it as a transition from different states. Transition probability matrices can be defined to describe the evolution of ENSO in this way. Sea surface temperature anomalies are classified into four categories, or states, and the probability to move from one state to another has been calculated for both observations and a simulation from a GCM. This could be useful for understanding and diagnosing general circulation models elucidating the mechanisms that govern ENSO in models. Furthermore, these matrices have been used to define a predictability index of ENSO based on the entropy concept introduced by Shannon. The index correctly identifies the emergence of the spring predictability barrier and the seasonal variations of the transition probabilities. The transition probability matrices could also be used to formulate a basic prediction model for ENSO that was tested here on a case study.
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Suhaila, Jamaludin. "Functional Data Visualization and Outlier Detection on the Anomaly of El Niño Southern Oscillation." Climate 9, no. 7 (2021): 118. http://dx.doi.org/10.3390/cli9070118.
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The El Niño Southern Oscillation (ENSO) is a well-known cause of year-to-year climatic variations on Earth. Floods, droughts, and other natural disasters have been linked to the ENSO in various parts of the world. Hence, modeling the ENSO’s effects and the anomaly of the ENSO phenomenon has become a main research interest. Statistical methods, including linear and nonlinear models, have intensively been used in modeling the ENSO index. However, these models are unable to capture sufficient information on ENSO index variability, particularly on its temporal aspects. Hence, this study adopted functional data analysis theory by representing a multivariate ENSO index (MEI) as functional data in climate applications. This study included the functional principal component, which is purposefully designed to find new functions that reveal the most important type of variation in the MEI curve. Simultaneously, graphical methods were also used to visualize functional data and capture outliers that may not have been apparent from the original data plot. The findings suggest that the outliers obtained from the functional plot are then related to the El Niño and La Niña phenomena. In conclusion, the functional framework was found to be more flexible in representing the climate phenomenon as a whole.
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Ziemke, J. R., S. Chandra, L. D. Oman, and P. K. Bhartia. "A new ENSO index derived from satellite measurements of column ozone." Atmospheric Chemistry and Physics 10, no. 8 (2010): 3711–21. http://dx.doi.org/10.5194/acp-10-3711-2010.
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Abstract. Column Ozone measured in tropical latitudes from Nimbus 7 total ozone mapping spectrometer (TOMS), Earth Probe TOMS, solar backscatter ultraviolet (SBUV), and Aura ozone monitoring instrument (OMI) are used to derive an El Nino-Southern Oscillation (ENSO) index. This index, which covers a time period from 1979 to the present, is defined as the "Ozone ENSO Index" (OEI) and is the first developed from atmospheric trace gas measurements. The OEI is constructed by first averaging monthly mean column ozone over two broad regions in the western and eastern Pacific and then taking their difference. This differencing yields a self-calibrating ENSO index which is independent of individual instrument calibration offsets and drifts in measurements over the long record. The combined Aura OMI and MLS ozone data confirm that zonal variability in total column ozone in the tropics caused by ENSO events lies almost entirely in the troposphere. As a result, the OEI can be derived directly from total column ozone instead of tropospheric column ozone. For clear-sky ozone measurements a +1 K change in Nino 3.4 index corresponds to +2.9 Dobson Unit (DU) change in the OEI, while a +1 hPa change in SOI coincides with a −1.7 DU change in the OEI. For ozone measurements under all cloud conditions these numbers are +2.4 DU and −1.4 DU, respectively. As an ENSO index based upon ozone, it is potentially useful in evaluating climate models predicting long term changes in ozone and other trace gases.
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Bogning, Sakaros, Frédéric Frappart, Gil Mahé, et al. "Investigating links between rainfall variations in the Ogooué River basin and ENSO in the Pacific Ocean over the period 1940–1999." Proceedings of the International Association of Hydrological Sciences 384 (November 16, 2021): 181–86. http://dx.doi.org/10.5194/piahs-384-181-2021.
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Abstract. This paper investigates links between rainfall variability in the Ogooué River Basin (ORB) and El Niño Southern Oscillation (ENSO) in the Pacific Ocean. Recent hydroclimatology studies of the ORB and surrounding areas resulting in contrasting conclusions about links between rainfall variability and ENSO. Thus, to make the issue clearer, this study investigates the links between ENSO and rainfall in the ORB over the period 1940–1999. The principal component analysis of monthly rainfall in the ORB was done. The temporal mode of the first component corresponds to the interannual variations of rainfall on the ORB. Also, the pattern of the spatial mode of the first component shows that the ORB is a homogeneous hydroclimatic zone. However, no leading mode is significantly correlated to the ENSO index. A cross-wavelet analysis of the time series of basin-scale rainfall and the ENSO index was therefore carried out. The result is a set of periodogram structures corresponding to some ENSO episodes recorded over the study period. And wavelet coherence analysis of both time series confirms that there are significant links between ENSO and rainfall in the ORB.
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Compo, Gilbert P., and Prashant D. Sardeshmukh. "Removing ENSO-Related Variations from the Climate Record." Journal of Climate 23, no. 8 (2010): 1957–78. http://dx.doi.org/10.1175/2009jcli2735.1.
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Abstract An important question in assessing twentieth-century climate change is to what extent have ENSO-related variations contributed to the observed trends. Isolating such contributions is challenging for several reasons, including ambiguities arising from how ENSO itself is defined. In particular, defining ENSO in terms of a single index and ENSO-related variations in terms of regressions on that index, as done in many previous studies, can lead to wrong conclusions. This paper argues that ENSO is best viewed not as a number but as an evolving dynamical process for this purpose. Specifically, ENSO is identified with the four dynamical eigenvectors of tropical SST evolution that are most important in the observed evolution of ENSO events. This definition is used to isolate the ENSO-related component of global SST variations on a month-by-month basis in the 136-yr (1871–2006) Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST). The analysis shows that previously identified multidecadal variations in the Pacific, Indian, and Atlantic Oceans all have substantial ENSO components. The long-term warming trends over these oceans are also found to have appreciable ENSO components, in some instances up to 40% of the total trend. The ENSO-unrelated component of 5-yr average SST variations, obtained by removing the ENSO-related component, is interpreted as a combination of anthropogenic, naturally forced, and internally generated coherent multidecadal variations. The following two surprising aspects of these ENSO-unrelated variations are emphasized: 1) a strong cooling trend in the eastern equatorial Pacific Ocean and 2) a nearly zonally symmetric multidecadal tropical–extratropical seesaw that has amplified in recent decades. The latter has played a major role in modulating SSTs over the Indian Ocean.
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Feng, Jiaxin, Zhaohua Wu, and Xiaolei Zou. "Sea Surface Temperature Anomalies off Baja California: A Possible Precursor of ENSO." Journal of the Atmospheric Sciences 71, no. 5 (2014): 1529–37. http://dx.doi.org/10.1175/jas-d-13-0397.1.
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Abstract Many recent studies have shown that observed El Niño–Southern Oscillation (ENSO) events are spatially and temporally diverse and that they have undergone changes in characteristics. To quantitatively capture these features, multidimensional ensemble empirical mode decomposition (MEEMD) is employed to isolate the temporal–spatial evolution of the sea surface temperature anomalies (SSTAs) on naturally separated time scales. An alternative Niño-3.4 index is also defined to reflect more on the interannual variability of equatorial Pacific SSTAs. Using this alternative index, 27 ENSO warm events are identified and the spatial–temporal evolution of each event is examined. It is found that a patch of SSTAs off Baja California appears to extend southwestward and reach the equatorial region near the international date line in about 1 year. This warm signal then amplifies and extends eastward, developing into an ENSO warm event. This type of development has been dominant in recent decades. For this type of ENSO warm event, it appears that SSTAs off Baja California are instrumental to ENSO development, possibly serving as a precursor of an ENSO event.
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Park, J., and G. Dusek. "ENSO components of the Atlantic multidecadal oscillation and their relation to North Atlantic interannual coastal sea level anomalies." Ocean Science 9, no. 3 (2013): 535–43. http://dx.doi.org/10.5194/os-9-535-2013.
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Abstract. The El Niño Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO) are known to influence coastal water levels along the East Coast of the United States. By identifying empirical orthogonal functions (EOFs), which coherently contribute from the Multivariate ENSO Index (MEI) to the AMO index (AMOI), we characterize both the expression of ENSO in the unsmoothed AMOI, and coherent relationships between these indices and interannual sea level anomalies at six stations in the Gulf of Mexico and western North Atlantic. Within the ENSO band (2–7 yr periods) the total contribution of MEI to unsmoothed AMOI variability is 79%. Cross correlation suggests that the MEI leads expression of the ENSO signature in the AMOI by six months, consistent with the mechanism of an atmospheric bridge. Within the ENSO band, essentially all of the coupling between the unsmoothed AMOI and sea level anomalies is the result of ENSO expression in the AMOI. At longer periods we find decadal components of sea level anomalies linked to the AMOI at three southern stations (Key West, Pensacola, Charleston), but not at the northern stations (Baltimore, Boston, Portland), with values of coherence ranging from 20 to 50%. The coherence of MEI to coastal sea level anomalies has a different structure and is generally weaker than that of the ENSO expressed AMOI influence, suggesting distinct physical mechanisms are influencing sea level anomalies due to a direct ENSO teleconnection when compared to teleconnections based on ENSO expression in the AMOI. It is expected that applying this analysis to extremes of sea level anomalies will reveal additional influences.
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Park, J., and G. Dusek. "ENSO components of the Atlantic multidecadal oscillation and their relation to North Atlantic interannual coastal sea level anomalies." Ocean Science Discussions 9, no. 6 (2012): 3673–99. http://dx.doi.org/10.5194/osd-9-3673-2012.
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Abstract. The El Niño Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO) are known to influence coastal water levels along the east coast of the United States. By identifying empirical orthogonal functions (EOFs) which coherently contribute from the Multivariate ENSO Index (MEI) to the AMO index (AMOI), we characterize both the expression of ENSO in the unsmoothed AMOI, and coherent relationships between these indices and interannual sea level anomalies at six stations in the Gulf of Mexico and Western North Atlantic. Within the ENSO band (2–7 yr periods) the total contribution of MEI to unsmoothed AMOI variability is 79%. Cross correlation suggests that the MEI leads expression of the ENSO signature in the AMOI by six months, consistent with the mechanism of an atmospheric bridge. Within the ENSO band, essentially all of the coupling between the unsmoothed AMOI and sea level anomalies is the result of ENSO expression in the AMOI. At longer periods we find decadal components of sea level anomalies linked to the AMOI at three southern stations (Key West, Pensacola, Charleston), but not at the northern stations (Baltimore, Boston, Portland), with values of coherence ranging from 20 to 50%. The coherence of MEI to coastal sea level anomalies has a different structure and is generally weaker than that of the ENSO expressed AMOI influence, suggesting distinct physical mechanisms are influencing sea level anomalies due to a direct ENSO teleconnection when compared to teleconnections based on ENSO expression in the AMOI. It is expected that applying this analysis to extremes of sea level anomalies will reveal additional influences.
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Zubair, Lareef, and Janaki Chandimala. "Epochal Changes in ENSO–Streamflow Relationships in Sri Lanka." Journal of Hydrometeorology 7, no. 6 (2006): 1237–46. http://dx.doi.org/10.1175/jhm546.1.
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Abstract In an effort to use climate predictions for streamflow and malaria hazard prediction, the decadal variability of the El Niño–Southern Oscillation (ENSO) influence on streamflow and rainfall in the Kelani River in Sri Lanka was investigated based on records from 1925 to 1995. In the last half century, the warm ENSO phase was associated with decreased annual streamflow and the cold ENSO phase with increased streamflow. The annual streamflow had a negative correlation (warm ENSO associated with low streamflow) with the concurrent ENSO index of Niño-3.4 that was significant at the 5% level. This negative correlation with Niño-3.4 is enhanced to a 1% significance level if the aggregate streamflow from January to September alone is considered. There has been a transition in correlation between January–September streamflow and ENSO between the 1950s and 1970s from near or above zero to negative values that have 95% significance levels reminiscent of an epochal shift. This shift was evident when considering the period when the southwest monsoon dominates (April–September) or when correlations were undertaken between the seasonal streamflow and rainfall and the ENSO index in the month prior to each season. Since the relationship between ENSO and Sri Lankan streamflow has strengthened in recent decades the potential for ENSO-based prediction is retained. The epochal shift may also explain why malaria epidemics ceased to co-occur frequently with El Niño episodes after 1945.
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Sugiarto, Yon, and Dori Kurniawan. "ANALISIS DAMPAK ENSO (EL-NINO SOUTHERN OSCILLATION) TERHADAP TINGKAT KEKERINGAN UNTUK TANAMAN PANGAN DAN PALAWIJA (STUDI KASUS : SULAWESI SELATAN)." Agromet 23, no. 2 (2009): 182. http://dx.doi.org/10.29244/j.agromet.23.2.182-198.
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<p>Weather and climate variability is a long-term weather changes that are characterized by fluctuations and deviations from normal conditions. One possible cause is the ENSO (El-Nino Southern Oscillation) which affected in drought events. This research was conducted to determine and analyze the level of drought in South Sulawesi due to the influence of ENSO and compare the production of food crops and secondary food crops in normal years and ENSO.<br />Drought index is calculated based on the Palmer method by using data of rainfall, air temperature and soil moisture as input. Based on the calculations using the method of Palmer drought index, the regions with monsoon rain patterns have a range of values between -22.71 drought until 18:23, Equatorial patterns ranging from -4.03 to 5:07, and on local patterns ranged<br />from -8.57 until 10:07. Verification test results on the drought index of crop production data showed that each ENSO event is always followed by a decline in rice production, especially of rice fields. Food crop production generally tends to increase at each ENSO event because most crops are plants that are resistant to drought, particularly local varieties that have adapted well to their environment. Thus, the drought caused by the influence of ENSO can affect the production of food crops and secondary food crops.</p>
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Fang, Xiang-Hui, and Fei Zheng. "Effect of the air–sea coupled system change on the ENSO evolution from boreal spring." Climate Dynamics 57, no. 1-2 (2021): 109–20. http://dx.doi.org/10.1007/s00382-021-05697-w.
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AbstractRealistic simulation and accurate prediction of El Niño-Southern Oscillation (ENSO) is still a challenge. One fundamental obstacle is the so-called spring predictability barrier (SPB), which features a low predictive skill of the ENSO with prediction across boreal spring. Our observational analysis shows that the leading empirical orthogonal function mode of the seasonal Niño3.4 index evolution (i.e., from May to the following April) explains nearly 90% of its total variance, and the principle component is almost identical to the Niño3.4 index in the mature phase. This means a good ENSO prediction for a year ranging May-next April can be achieved if the Niño3.4 index in the mature phase is accurately obtained in advance. In this work, by extracting physically oriented variables in the spring, a linear regression approach that can reproduce the mature ENSO phases in observation is firstly proposed. Further investigation indicates that the specific equation, however, is significantly modulated by an interdecadal regime shift in the air–sea coupled system in the tropical Pacific. During 1980–1999, ocean adjustment and vertical processes were dominant, and the recharge oscillator theory was effective to capture the ENSO evolutions. While, during 2000–2018, zonal advection and thermodynamics became important, and successful prediction essentially relies on the wind stress information and their controlled processes, both zonally and meridionally. These results imply that accounting for the interdecadal regime shift of the tropical Pacific coupled system and the dominant processes in spring in modulating the ENSO evolution could reduce the impact of SPB and improve ENSO prediction.
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Pacheco, Jheimy, Abel Solera, Alex Avilés, and María Dolores Tonón. "Influence of ENSO on Droughts and Vegetation in a High Mountain Equatorial Climate Basin." Atmosphere 13, no. 12 (2022): 2123. http://dx.doi.org/10.3390/atmos13122123.
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Several studies have assessed droughts and vegetation considering climatic factors, particularly El Niño-Southern Oscillation (ENSO) at different latitudes. However, there are knowledge gaps in the tropical Andes, a region with high spatiotemporal climatic variability. This research analyzed the relationships between droughts, vegetation, and ENSO from 2001–2015. Meteorological drought was analyzed using the Standardized Precipitation Evapotranspiration Index (SPEI) for 1, 3 and 6 months. Normalized Difference Vegetation Index (NDVI) was used to evaluate vegetation, and ENSO indexes were used as climate drivers. The Wavelet coherence method was used to establish time-frequency relationships. This approach was applied in the Machángara river sub-basin in the Southern Ecuadorian Andes. The results showed significant negative correlations during 2009–2013 between the SPEI and NDVI, with the SPEI6 lagging by nine months and a return period of 1.5 years. ENSO–SPEI presented the highest negative correlations during 2009–2014 and a return period of three years, with ENSO leading the relationship for around fourteen months. ENSO-NDVI showed the highest positive correlations during 2004–2008 and a return period of one year, with the ENSO indexes continually delayed by approximately one month. These results could be a benchmark for developing advanced studies for climate hazards.
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Berner, Judith, Hannah M. Christensen, and Prashant D. Sardeshmukh. "Does ENSO Regularity Increase in a Warming Climate?" Journal of Climate 33, no. 4 (2020): 1247–59. http://dx.doi.org/10.1175/jcli-d-19-0545.1.
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AbstractThe impact of a warming climate on El Niño–Southern Oscillation (ENSO) is investigated in large-ensemble simulations of the Community Earth System Model (CESM1). These simulations are forced by historical emissions for the past and the RCP8.5-scenario emissions for future projections. The simulated variance of the Niño-3.4 ENSO index increases from 1.4°C2 in 1921–80 to 1.9°C2 in 1981–2040 and 2.2°C2 in 2041–2100. The autocorrelation time scale of the index also increases, consistent with a narrowing of its spectral peak in the 3–7-yr ENSO band, raising the possibility of greater seasonal to interannual predictability in the future. Low-order linear inverse models (LIMs) fitted separately to the three 60-yr periods capture the CESM1 increase in ENSO variance and regularity. Remarkably, most of the increase can be attributed to the increase in the 23-month damping time scale of a single damped oscillatory ENSO eigenmode of these LIMs by 5 months in 1981–2040 and 6 months in 2041–2100. These apparently robust projected increases may, however, be compromised by CESM1 biases in ENSO amplitude and damping time scale. An LIM fitted to the 1921–80 observations has an ENSO eigenmode with a much shorter 8-month damping time scale, similar to that of several other eigenmodes. When the mode’s damping time scale is increased by 5 and 6 months in this observational LIM, a much smaller increase of ENSO variance is obtained than in the CESM1 projections. This may be because ENSO is not as dominated by a single ENSO eigenmode in reality as it is in the CESM1.
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Xie, Kenny, and Bin Liu. "An ENSO-Forecast Independent Statistical Model for the Prediction of Annual Atlantic Tropical Cyclone Frequency in April." Advances in Meteorology 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/248148.
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Statistical models for preseason prediction of annual Atlantic tropical cyclone (TC) and hurricane counts generally include El Niño/Southern Oscillation (ENSO) forecasts as a predictor. As a result, the predictions from such models are often contaminated by the errors in ENSO forecasts. In this study, it is found that the latent heat flux (LHF) over Eastern Tropical Pacific (ETP, defined as the region 0°–5°N, 115°–125°W) in spring is negatively correlated with the annual Atlantic TC and hurricane counts. By using stepwise backward elimination regression, it is further shown that the March value of ETP LHF is a better predictor than the spring or summer ENSO index for Atlantic TC counts. Leave-one-out cross validation indicates that the annual Atlantic TC counts predicted by this ENSO-independent statistical model show a remarkable correlation with the actual TC counts (R=0.72;Pvalue<0.01). For Atlantic hurricanes, the predictions using March ETP LHF and summer (July–September) ENSO indices show only minor differences except in moderate to strong El Niño years. Thus, March ETP LHF is an excellent predictor for seasonal Atlantic TC prediction and a viable alternative to using ENSO index for Atlantic hurricane prediction.
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Hu, Zeng-Zhen, Arun Kumar, Jieshun Zhu, Peitao Peng, and Bohua Huang. "On the Challenge for ENSO Cycle Prediction: An Example from NCEP Climate Forecast System, Version 2." Journal of Climate 32, no. 1 (2018): 183–94. http://dx.doi.org/10.1175/jcli-d-18-0285.1.
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Abstract This work demonstrates the influence of the initial amplitude of the sea surface temperature anomaly (SSTA) associated with El Niño–Southern Oscillation (ENSO) following its evolutionary phase on the forecast skill of ENSO in retrospective predictions of the Climate Forecast System, version 2. It is noted that the prediction skill varies with the phase of the ENSO cycle. The averaged skill (linear correlation) of Niño-3.4 index is in a range of 0.15–0.55 for the amplitude of Niño-3.4 index smaller than 0.5°C (e.g., initial phase or neutral condition of ENSO), and 0.74–0.93 for the amplitude larger than 0.5°C (e.g., mature condition of ENSO) for 0–6-month lead predictions. The dependence of the prediction skills of ENSO on its phase is linked to the variation of signal-to-noise ratio (SNR). This variation is found to be mainly due to the changes in the amplitude of the signal (prediction of the ensemble mean) during different phases of the ENSO cycle, as the noise (forecast spread among the ensemble members), both in the Niño-3.4 region and the whole Pacific, does not depend much on the Niño-3.4 amplitude. It is also shown that the spatial pattern of unpredictable noise in the Pacific is similar to the predictable signal. These results imply that skillful prediction of the ENSO cycle, either at the initial time of an event or during the transition phase of the ENSO cycle, when the anomaly signal is weak and the SNR is small, is an inherent challenge.
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Kellner, Olivia, and Dev Niyogi. "Climate Variability and the U.S. Corn Belt: ENSO and AO Episode-Dependent Hydroclimatic Feedbacks to Corn Production at Regional and Local Scales*." Earth Interactions 19, no. 6 (2015): 1–32. http://dx.doi.org/10.1175/ei-d-14-0031.1.
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Abstract El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) climatology (1980–2010) is developed and analyzed across the U.S. Corn Belt using state climate division weather and historic corn yield data using analysis of variance (ANOVA) and correlation analysis. Findings provide insight to agroclimatic conditions under different ENSO and AO episodes and are analyzed with a perspective for potential impacts to agricultural production and planning, with findings being developed into a web-based tool for the U.S. Corn Belt. This study is unique in that it utilizes the oceanic Niño index and explores two teleconnection patterns that influence weather across different spatiotemporal scales. It is found that the AO has a more frequent weak to moderate correlation to historic yields than ENSO when correlated by average subgrowing season index values. Yield anomaly and ENSO and AO episode analysis affirms the overall positive impact of El Niño events on yields compared to La Niña events, with neutral ENSO events in between as found in previous studies. Yields when binned by the AO episode present more uncertainty. While significant temperature and precipitation impacts from ENSO and AO are felt outside of the primary growing season, correlation between threshold variables of episode-specific temperature and precipitation and historic yields suggests that relationships between ENSO and AO and yield are present during specific months of the growing season, particularly August. Overall, spatial climatic variability resulting from ENSO and AO episodes contributes to yield potential at regional to subregional scales, making generalization of impacts difficult and highlighting a continued need for finescale resolution analysis of ENSO and AO signal impacts on corn production.
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Hashidu, U. S., and S. I. Badaru. "Relationship between El-Niño southern oscillation and rainfall in Sudano-Sahelian Region of Northern Nigeria." JOURNAL OF AGRICULTURAL ECONOMICS, ENVIRONMENT AND SOCIAL SCIENCES 7, no. 2 (2021): 211–16. http://dx.doi.org/10.56160/jaeess202172019.
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El Nino Southern-Oscillation (ENSO) refers to the cycle of coherent and sometimes very strong variations in the sea surface temperature (SST), convective rainfall, surface pressure and atmospheric circulation across the equatorial Pacific Ocean. The research investigated the relationship between ENSO and rainfall across the Sudano-Sahelian region of northern Nigeria. Rainfall data for seven (7) locations were sourced from the Nigerian Meteorological Agency (NIMET) covering the period from 1950 to 2019 and El-Nino Southern Oscillation (ENSO) data which comprised of Southern Oscillation Index (SOI) covering the same period. The Southern Oscillation Index (SOI) data was obtained from National Oceanographic Atmospheric Administration (NOAA) Climate Prediction Centre. A bivariate correlation analysis between rainfall and SOI were computed for all the seven locations to determine the relationship between ENSO and Sudano-Sahelian rainfall. The result shows a significant relationship for Potiskum, Maiduguri and Katsina with correlation coefficient (r) values of 0.25, 0.26 and 0.27 respectively while Kano Gusau Nguru and Sokoto show no significant relationship. It is therefore concluded that there is no strong relationship between rainfall and ENSO in Sudano-Sahelian part of northern Nigeria. It is recommended that further research could be carried out to investigate the influence of ENSO on other climate parameters such as temperature, humidity and evapotranspiration in the study area.
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Chandrasekara, Sewwandhi, Venkatraman Prasanna, and Hyun-Han Kwon. "Monitoring Water Resources over the Kotmale Reservoir in Sri Lanka Using ENSO Phases." Advances in Meteorology 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/4025964.
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In this study, the El Nino Southern Oscillation (ENSO) phase index is used for water management over the Kotmale reservoir in Sri Lanka. Daily rainfall data of 9 stations over the Kotmale catchment during 1960–2005 June-September (JJAS) season is investigated over the Kotmale catchment. The ENSO phases are identified based on the 0.5°C sea surface temperature (SST) anomaly over Nino 3 region. The study has brought out few stations showing increasing and a few decreasing seasonal rainfall trends for JJAS season, while there is no change in the annual rainfall for the catchment. Monthly and seasonal rainfall of all the selected stations showed negative correlation with the sea surface temperature (SST) over the Nino-3 region index during JJAS season with varying magnitudes. During the warm phase of ENSO, below average rainfall is prominent for JJAS season over many stations. The rainfall especially during early September showed a significant below average rainfall during the warm ENSO phase. The seasonal rainfall during neutral and cold ENSO phases does not experience similar significant changes as seen during warm ENSO phase. Inflow of the Kotmale reservoir shows decreasing trend for the period of 1960–2005 in the observation from all stations collectively.
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Schulte, Justin, Frederick Policelli, and Benjamin Zaitchik. "A waveform skewness index for measuring time series nonlinearity and its applications to the ENSO–Indian monsoon relationship." Nonlinear Processes in Geophysics 29, no. 1 (2022): 1–15. http://dx.doi.org/10.5194/npg-29-1-2022.
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Abstract. Many geophysical time series possess nonlinear characteristics that reflect the underlying physics of the phenomena the time series describe. The nonlinear character of times series can change with time, so it is important to quantify time series nonlinearity without assuming stationarity. A common way of quantifying the time evolution of time series nonlinearity is to compute sliding skewness time series, but it is shown here that such an approach can be misleading when time series contain periodicities. To remedy this deficiency of skewness, a new waveform skewness index is proposed for quantifying local nonlinearities embedded in time series. A waveform skewness spectrum is proposed for determining the frequency components that are contributing to time series waveform skewness. The new methods are applied to the El Niño–Southern Oscillation (ENSO) and the Indian monsoon to test a recently proposed hypothesis that states that changes in the ENSO–Indian monsoon relationship are related to ENSO nonlinearity. We show that the ENSO–Indian rainfall relationship weakens during time periods of high ENSO waveform skewness. The results from two different analyses suggest that the breakdown of the ENSO–Indian monsoon relationship during time periods of high ENSO waveform skewness is related to the more frequent occurrence of strong central Pacific El Niño events, supporting arguments that changes in the ENSO–Indian rainfall relationship are not solely related to noise.
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Williams, Ian N., and Christina M. Patricola. "Diversity of ENSO Events Unified by Convective Threshold Sea Surface Temperature: A Nonlinear ENSO Index." Geophysical Research Letters 45, no. 17 (2018): 9236–44. http://dx.doi.org/10.1029/2018gl079203.
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Lü, A., S. Jia, W. Zhu, H. Yan, S. Duan, and Z. Yao. "El Niño-Southern Oscillation and water resources in the headwaters region of the Yellow River: links and potential for forecasting." Hydrology and Earth System Sciences 15, no. 4 (2011): 1273–81. http://dx.doi.org/10.5194/hess-15-1273-2011.
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Abstract. This research explores the rainfall-El Niño-Southern Oscillation (ENSO) and runoff-ENSO relationships and examines the potential for water resource forecasting using these relationships. The Southern Oscillation Index (SOI), Niño1.2, Niño3, Niño4, and Niño3.4 were selected as ENSO indicators for cross-correlation analyses of precipitation and runoff. There was a significant correlation (95% confidence level) between precipitation and ENSO indicators during three periods: January, March, and from September to November. In addition, monthly streamflow and monthly ENSO indictors were significantly correlated during three periods: from January to March, June, and from October to December (OND), with lag periods between one and twelve months. Because ENSO events can be accurately predicted one to two years in advance using physical modeling of the coupled ocean-atmosphere system, the lead time for forecasting runoff using ENSO indicators in the Headwaters Region of the Yellow River could extend from one to 36 months. Therefore, ENSO may have potential as a powerful forecasting tool for water resources in the headwater regions of Yellow River.
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Rosyidah, Rosyidah, Kunarso Kunarso, and Elis Indrayanti. "Relationship of ENSO (El Niño – Southernoscillation ) and monsoon index on variability of rainfall and sea surface height in coastal City Semarang, Central Java." Depik 11, no. 3 (2022): 455–62. http://dx.doi.org/10.13170/depik.11.3.26699.
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The city of Semarang is one of the coastal areas in Indonesia that is prone to flooding. Flood events that often occur in the Semarang City area can be triggered by high rainfall. Variations in rainfall and sea level are closely related to global atmospheric circulation such as ENSO and regional atmospheric circulation, Monsoon. This study aims to examine the relationship between ENSO and Monsoon with the distribution of rainfall and sea level in coastal city Semarang from 2012 to 2021. Correlation and composite analysis were used to analyze the relationship and impact of ENSO and Monsoon phenomena on rainfall and sea level. The results showed the strong correlation of the ENSO index (Southern Oscillation Index) to rainfall in the JJA and SON periods. Generally, El Niño (La Niña) has an impact on increasing (decreasing) rainfall. Meanwhile, Australian Summer Monsoon Index (AUSMI) only strongly correlates with rainfall in the SON period. The westerly (eastern) wind indicated by a positive (negative) monsoon index in the SON period has the effect of increasing (reducing) rainfall. The ENSO phenomenon with sea level during the JJA period has a strong relationship. In JJA, the highest sea level (maximum tide) rises by 12.6 cm during El Niño and decreases by 0.6 cm during La Niña. Meanwhile, the lowest sea level (minimum low tide) decreased by 16.6 cm during El Niño and increased by 0.7 cm during La Niña. These results can explain the influence of global and regional atmospheric circulation on a local scale on the coast of Semarang City.Keywords:RainfallSea levelEl NiñoLa NiñaMonsoon
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Mo, Kingtse C., Jae-Kyung E. Schemm, and Soo-Hyun Yoo. "Influence of ENSO and the Atlantic Multidecadal Oscillation on Drought over the United States." Journal of Climate 22, no. 22 (2009): 5962–82. http://dx.doi.org/10.1175/2009jcli2966.1.
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Abstract Composites based on observations and model outputs from the Climate Variability and Predictability (CLIVAR) drought experiments were used to examine the impact of El Niño–Southern Oscillation (ENSO) and the Atlantic multidecadal oscillation (AMO) on drought over the United States. Because drought implies persistent dryness, the 6-month standardized precipitation index, standardized runoff index, and soil moisture anomalies are used to represent drought. The experiments were performed by forcing an AGCM with prescribed sea surface temperature anomalies (SSTAs) superimposed on the monthly mean SST climatology. Four model outputs from the NCEP Global Forecast System (GFS), NASA’s Seasonal-to-Interannual Prediction Project, version 1 (NSIPP1), GFDL’s global atmospheric model, version 2.1 (AM2.1), and the Lamont-Doherty Earth Observatory (LDEO)/NCAR Community Climate System Model, version 3 (CCM3) were analyzed in this study. Each run lasts from 36 to 51 yr. The impact of ENSO on drought over the United States is concentrated over the Southwest, the Great Plains, and the lower Colorado River basin, with cold (warm) ENSO events favoring drought (wet spells). Over the East Coast and the Southeast, the impact of ENSO is small because the precipitation responses to ENSO are opposite in sign for winter and summer. For these areas, a prolonged ENSO does not always favor either drought or wet spells. The direct influence of the AMO on drought is small. The major influence of the AMO is to modulate the impact of ENSO on drought. The influence is large when the SSTAs in the tropical Pacific and in the North Atlantic are opposite in phase. A cold (warm) event in a positive (negative) AMO phase amplifies the impact of the cold (warm) ENSO on drought. The ENSO influence on drought is much weaker when the SSTAs in the tropical Pacific and in the North Atlantic are in phase.
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DE, U. S., and R. K. MUKHOPADHYAY. "The effect of ENSO / Anti ENSO on northeast monsoon rainfall." MAUSAM 50, no. 4 (2021): 343–54. http://dx.doi.org/10.54302/mausam.v50i4.1947.
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Northeast monsoon precipitation data of 5 meteorological sub-divisions in India, spanning the period 1901-97, were analysed to identify the effect of ENSO/Anti ENSO events on the rainfall over southern peninsular India. ENSO/Anti ENSO years were selected on the basis of seasonal Southern Oscillation Index (SOI). The analysis revealed that ENSO years were generally associated with enhanced northeast monsoon precipitation while there was reduced precipitation during Anti ENSO years, the reduction in Anti ENSO years being significant for Tamil Nadu (at 0.1% level), for Kerala (at 1% level) and for South Peninsular India (at 1% level). Of 22 ENSO years, 18 years were found to be either flood or wet years, while 11 years out of 15 Anti ENSO years were found to be either drought or dry years.
 
 During ENSO years, the Sea Surface Temperature (SST) anomalies both over the Arabian Sea and the Bay of Bengal were positive during the months October to December, while the reverse was the case during Anti ENSO years. A concurrent significant positive correlation was noted between SST over east central Arabian Sea and the north central Bay regions and northeast monsoon rainfall.
 
 The cyclonic systems were observed to form relatively at lower latitudes during ENSO years as compared to those during Anti ENSO years. These systems were also found to move in a more westerly direction, hit Tamil Nadu and south Andhra coast, thus giving more rain over peninsula during ENSO years. The ridge line at 200 hPa level during ENSO years was located 3° south as compared to its location during Anti ENSO years.
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Erasmi, Stefan, Pavel Propastin, Martin Kappas, and Oleg Panferov. "Spatial Patterns of NDVI Variation over Indonesia and Their Relationship to ENSO Warm Events during the Period 1982–2006." Journal of Climate 22, no. 24 (2009): 6612–23. http://dx.doi.org/10.1175/2009jcli2460.1.
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Abstract The present study is based on the assumption that vegetation in Indonesia is significantly affected by climate anomalies that are related to El Niño–Southern Oscillation (ENSO) warm phases (El Niño) during the past decades. The analysis builds upon a monthly time series from the normalized difference vegetation index (NDVI) gridded data from the Advanced Very High Resolution Radiometer (AVHRR) and two ENSO proxies, namely, sea surface temperature anomalies (SSTa) and Southern Oscillation index (SOI), and aims at the analysis of the spatially explicit dimension of ENSO impact on vegetation on the Indonesian archipelago. A time series correlation analysis between NDVI anomalies and ENSO proxies for the most recent ENSO warm events (1982–2006) showed that, in general, anomalies in vegetation productivity over Indonesia can be related to an anomalous increase of SST in the eastern equatorial Pacific and to decreases in SOI, respectively. The net effect of these variations is a significant decrease in NDVI values throughout the affected areas during the ENSO warm phases. The 1982/83 ENSO warm episode was rather short but—in terms of ENSO indices—the most extreme one within the study period. The 1997/98 El Niño lasted longer but was weaker. Both events had significant impact on vegetation in terms of negative NDVI anomalies. Compared to these two major warm events, the other investigated events (1987/88, 1991/92, 1994/95, and 2002/03) had no significant effect on vegetation in the investigated region. The land cover–type specific sensitivity of vegetation to ENSO anomalies revealed thresholds of vegetation response to ENSO warm events. The results for the 1997/98 ENSO warm event confirm the hypothesis that the vulnerability of vegetated tropical land surfaces to drought conditions is considerably affected by land use intensity. In particular, it could be shown that natural forest areas are more resistant to drought stress than degraded forest areas or cropland. Comparing the spatially explicit patterns of El Niño–related vegetation variation during the major El Niño phases, the spatial distribution of affected areas reveals distinct core regions of ENSO drought impact on vegetation for Indonesia that coincide with forest conversion and agricultural intensification hot spots.
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Tuo, Pengfei, Jin-Yi Yu, and Jianyu Hu. "The Changing Influences of ENSO and the Pacific Meridional Mode on Mesoscale Eddies in the South China Sea." Journal of Climate 32, no. 3 (2019): 685–700. http://dx.doi.org/10.1175/jcli-d-18-0187.1.
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This study finds that the correlation between El Niño–Southern Oscillation (ENSO) and the activity of mesoscale oceanic eddies in the South China Sea (SCS) changed around 2004. The mesoscale eddy number determined from satellite altimetry observations using a geometry of the velocity vector method was significantly and negatively correlated with the Niño-3.4 index before 2004, but the correlation weakened and became insignificant afterward. Further analyses reveal that the ENSO–eddy relation is controlled by two major wind stress forcing mechanisms: one directly related to ENSO and the other indirectly related to ENSO through its subtropical precursor—the Pacific meridional modes (PMMs). Both mechanisms induce wind stress curl variations over the SCS that link ENSO to SCS eddy activities. While the direct ENSO mechanism always induces a negative ENSO–eddy correlation through the Walker circulation, the indirect mechanism is dominated by the northern PMM (nPMM), resulting in a negative ENSO–eddy correlation before 2004, and by the southern PMM (sPMM) after 2004, resulting in a positive ENSO–eddy correlation. As a result, the direct and indirect mechanisms enhance each other to produce a significant ENSO–eddy relation before 2004, but they cancel each other out, resulting in a weak ENSO–eddy relation afterward. The relative strengths of the northern and southern PMMs are the key to determining the ENSO–eddy relation and may be related to a phase change of the interdecadal Pacific oscillation.
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He, Shengping, and Huijun Wang. "Oscillating Relationship between the East Asian Winter Monsoon and ENSO." Journal of Climate 26, no. 24 (2013): 9819–38. http://dx.doi.org/10.1175/jcli-d-13-00174.1.
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Abstract This work investigates the interdecadal variations of the relationship between the El Niño–Southern Oscillation (ENSO) and the East Asian winter monsoon (EAWM), further explores possible mechanisms, and finally considers a recent switch in the ENSO–EAWM relationship. The 23-yr sliding correlation between the Niño-3.4 index and the EAWM index reveals an obvious low-frequency oscillation with a period of about 50 yr in the ENSO–EAWM relationship. Warm ENSO events during high-correlation periods are associated with an unusually weak East Asian trough, a positive phase of the North Pacific Oscillation (NPO), significant southerly wind anomalies along coastal East Asia, and warmer East Asian continent and adjacent oceans. However, there are no robust and significant anomalies in the EAWM-related circulation during low-correlation periods. Because of the southeastward shift of the Walker circulation, the area of anomalously high pressure in the western Pacific retreats south of 25°N, confining it to the region of the Philippine Sea. In this sense, the Pacific–East Asian teleconnection is not well established. Consequently, ENSO’s impact on the EAWM is suppressed. Additionally, the low-frequency oscillation of the ENSO–EAWM relationship might be attributable to the combined effect of the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation owing to their modulation on the establishment of the NPO teleconnection. The observation of two full cycles of the ENSO–EAWM relationship, a transition to negative PDO in the early 2000s and an enhancement of the Walker circulation in the late 1990s, suggests a recovery of the ENSO–EAWM relationship.
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Zhao, Tongtiegang, Haoling Chen, Yu Tian, et al. "Quantifying overlapping and differing information of global precipitation for GCM forecasts and El Niño–Southern Oscillation." Hydrology and Earth System Sciences 26, no. 16 (2022): 4233–49. http://dx.doi.org/10.5194/hess-26-4233-2022.
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Abstract. While El Niño–Southern Oscillation (ENSO) teleconnection has long been used in statistical precipitation forecasting, global climate models (GCMs) provide increasingly available dynamical precipitation forecasts for hydrological modeling and water resources management. It is not yet known to what extent dynamical GCM forecasts provide new information compared to statistical teleconnection. This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts). A case study is devised for the Climate Forecast System version 2 (CFSv2) seasonal forecasts of global precipitation in December–January–February. The results show that the overlapping information for GCM forecasts and the Niño3.4 index is significant for 34.94 % of the global land grid cells, that the differing information in GCM forecasts from the Niño3.4 index is significant for 31.18 % of the grid cells and that the differing information in the Niño3.4 index from GCM forecasts is significant for 11.37 % of the grid cells. These results confirm the effectiveness of GCMs in capturing the ENSO-related variability of global precipitation and illustrate where there is room for improvement of GCM forecasts. Furthermore, the bootstrapping significance tests of the three types of information facilitate in total eight patterns to disentangle the close but divergent associations of GCM forecast correlation skill with ENSO teleconnection.
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Liu, Guanyu, Jing Li, and Tong Ying. "Atlantic Multidecadal Oscillation modulates the relationship between El Niño–Southern Oscillation and fire weather in Australia." Atmospheric Chemistry and Physics 23, no. 16 (2023): 9217–28. http://dx.doi.org/10.5194/acp-23-9217-2023.
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Abstract. The El Niño–Southern Oscillation (ENSO) is a crucial driver of fire weather in Australia, with the correlation between ENSO and Australian fire weather having intensified over the past 2 decades. However, the underlying causes for this change have not been thoroughly investigated. In this study, we utilize reanalysis datasets and numerical model simulations to demonstrate that the Atlantic Multidecadal Oscillation (AMO) could potentially modulate the ENSO–Australian fire weather relationship. The correlation between ENSO and the Australian Fire Weather Index (FWI) increases from 0.17 to 0.70 as the AMO transitions from its negative to positive phase. This strengthening effect can be attributed to atmospheric teleconnection mechanisms. Specifically, the positive AMO phase, characterized by warming in the northern and tropical Atlantic, generates Rossby wave trains, leading to high-pressure systems over Australia. Consequently, local temperature and wind speed increase, while precipitation decreases. This signal, superimposed on ENSO, serves to amplify the ENSO effect on Australian fire weather.
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Gonzales, Edgard, and Eusebio Ingol. "Determination of a New Coastal ENSO Oceanic Index for Northern Peru." Climate 9, no. 5 (2021): 71. http://dx.doi.org/10.3390/cli9050071.
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In 2017, extreme rainfall events occurred in the northern portion of Peru, causing nearly 100,000 victims, according to the National Emergency Operations Center (COEN). This climatic event was attributed to the occurrence of the El Niño Southern Oscillation (ENSO). Therefore, the main objective of this study was to determine and differentiate between the occurrence of canonical ENSO, with a new type of ENSO called “El Niño Costero” (Coastal El Niño). The polynomial equation method was used to analyze the data from the different types of existing ocean indices to determine the occurrence of ENSO. It was observed that the anomalies of sea surface temperature (SST) 2.5 °C (January 2016) generated the “Modoki El Niño” and that the anomaly of SST −0.3 °C (January 2017) generated the “Modoki La Niña”; this sequential generation generated El Niño Costero. This new knowledge about the sui generis origin of El Niño Costero, based on the observations of this analysis, will allow us to identify and obtain important information regarding the occurrence of this event. A new oceanic index called the Pacific Regional Equatorial Index (PREI) was proposed to follow the periodic evolution and forecast with greater precision a new catastrophic event related to the occurrence of El Niño Costero and to implement prevention programs.
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Woli, Prem, James Jones, Keith Ingram, and Joel Paz. "Forecasting Drought Using the Agricultural Reference Index for Drought (ARID): A Case Study." Weather and Forecasting 28, no. 2 (2013): 427–43. http://dx.doi.org/10.1175/waf-d-12-00036.1.
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Abstract Drought forecasting can aid in developing mitigation strategies and minimizing economic losses. Drought may be forecast using a drought index, which is an indicator of drought. The agricultural reference index for drought (ARID) was used as a tool to investigate the possibility of using climate indices (CIs) as predictors to improve the current level of forecasting, which is El Niño–Southern Oscillation (ENSO) based. The performances of models that are based on linear regression (LR), artificial neural networks (ANN), adaptive neuron-fuzzy inference systems (ANFIS), and autoregressive moving averages (ARMA) models were compared with that of the ENSO approach. Monthly values of ARID spanning 56 yr were computed for five locations in the southeastern United States, and monthly values of the CIs having significant connections with weather in this region were obtained. For the ENSO approach, the ARID values were separated into three ENSO phases and averaged by phase. For the ARMA models, monthly time series of ARID were used. For the ANFIS, ANN, and LR models, ARID was predicted 1, 2, and 3 months ahead using the past values of the first principal component of the CIs. Model performances were assessed with the Nash–Sutcliffe index. Results indicated that drought forecasting could be improved for the southern part of the region using ANN models and CIs. The ANN outperformed the other models for most locations in the region. The CI-based models and the ENSO approach performed better during the winter, whereas the efficiency of ARMA models depended on precipitation periodicities. All models performed better for southern locations. The CIs showed good potential for use in forecasting drought, especially for southern locations in the winter.
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Puspasari, R., P. F. Rahmawati, and E. Prianto. "The Effect of ENSO (El Nino Southern Oscillation) phenomenon on Fishing Season of Small Pelagic Fishes in Indonesia Waters." IOP Conference Series: Earth and Environmental Science 934, no. 1 (2021): 012018. http://dx.doi.org/10.1088/1755-1315/934/1/012018.
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Abstract The El Nino Southern Oscillation (ENSO) phenomenon causes changes in environmental conditions such as water temperature, salinity, and rainfall. In fisheries sector, the changing environment has affected the fishing seasons and Catch per Unit Effort (CPUE) of some pelagic species. This research was conducted by calculating CPUE and fishing season index for several small pelagic fishes in Makassar Strait, Bali Strait, and Aceh waters, then comparing the index value with the fishing season pattern in two extreme periods that are 2010-2011 and 2016 - 2017. An ANOVA test was conducted to assess the significant difference between normal and extreme conditions. The results of the analysis showed that there was a significant different in CPUE between average normal condition and ENSO period. Every single species showed different response to ENSO event, mostly decreased in CPUE relate to El Nino event, except for sardine in Bali and Makassar Strait and scad in Makassar Strait. ENSO affects shift in the fishing season of big-eye scad, scad, sardine, and neritic tuna in Makassar Strait, Bali Strait, and around Aceh waters. Indian mackerel in Makassar Strait showed no change in fishing season but the CPUE showed lower than normal condition. This study shows that ENSO was significantly affected fisheries in Indonesia waters.
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Jien, Jerry Y., William A. Gough, and Ken Butler. "The Influence of El Niño–Southern Oscillation on Tropical Cyclone Activity in the Eastern North Pacific Basin." Journal of Climate 28, no. 6 (2015): 2459–74. http://dx.doi.org/10.1175/jcli-d-14-00248.1.
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Abstract The interannual variability of tropical cyclone (TC) activity due to El Niño–Southern Oscillation (ENSO) in the main development region of the eastern North Pacific basin has received scant attention. Herein the authors classify years of El Niño, La Niña, and neutral conditions using the multivariate ENSO index (MEI). Storm measurements of the net tropical cyclone activity index and power dissipation index are used to summarize the overall seasonal TC activity and TC intensity between 1971 and 2012. Both measures are found to be statistically dependent on the ENSO phases in the basin’s main development region. However, when the area is longitudinally divided, only the western portion of the development region experienced a significant difference (p &lt; 0.05). Specifically, El Niño years are characterized by more frequent, more intense events compared to La Niña conditions for this subregion. Correlation analyses on the relationships between the MEI and both TC indices demonstrate correlations between ENSO and TC activity and intensity that are statistically significant (p &lt; 0.05) only in the western region. These relationships have the potential to improve the short-term forecast of the local TC activity and intensity on a seasonal basis for public awareness and disaster preparation.
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Patricola, Christina M., John P. O’Brien, Mark D. Risser, et al. "Maximizing ENSO as a source of western US hydroclimate predictability." Climate Dynamics 54, no. 1-2 (2019): 351–72. http://dx.doi.org/10.1007/s00382-019-05004-8.
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Abstract Until recently, the El Niño–Southern Oscillation (ENSO) was considered a reliable source of winter precipitation predictability in the western US, with a historically strong link between extreme El Niño events and extremely wet seasons. However, the 2015–2016 El Niño challenged our understanding of the ENSO-precipitation relationship. California precipitation was near-average during the 2015–2016 El Niño, which was characterized by warm sea surface temperature (SST) anomalies of similar magnitude compared to the extreme 1997–1998 and 1982–1983 El Niño events. We demonstrate that this precipitation response can be explained by El Niño’s spatial pattern, rather than internal atmospheric variability. In addition, observations and large-ensembles of regional and global climate model simulations indicate that extremes in seasonal and daily precipitation during strong El Niño events are better explained using the ENSO Longitude Index (ELI), which captures the diversity of ENSO’s spatial patterns in a single metric, compared to the traditional Niño3.4 index, which measures SST anomalies in a fixed region and therefore fails to capture ENSO diversity. The physically-based ELI better explains western US precipitation variability because it tracks the zonal shifts in tropical Pacific deep convection that drive teleconnections through the response in the extratropical wave-train, integrated vapor transport, and atmospheric rivers. This research provides evidence that ELI improves the value of ENSO as a predictor of California’s seasonal hydroclimate extremes compared to traditional ENSO indices, especially during strong El Niño events.
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Arana Ruedas, Del Piero Raphael, and Nabilt Moggiano. "ENSO Influence on Agricultural Drought Identified by SPEI Assessment in the Peruvian Tropical Andes, Mantaro Valley." Manglar 20, no. 2 (2023): 157–67. http://dx.doi.org/10.57188/manglar.2023.018.
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Agricultural drought is a serious threat for those locations where one of the most important economic activities is crop production, which occurrence has been rising due to climate change. In addition, different kinds of phenomena could exacerbate agricultural drought frequency, duration, and severity. For example, El Niño Southern Oscillation (ENSO), which mostly occurs in the tropical western and central pacific, directly affects the Peruvian territory. This study aims to understand ENSO's influence on agricultural drought in the Mantaro Valley, Peru since it is one of the most important agricultural lands in the country without clear scientific information linked to drought and ENSO events. For drought assessment using the Standardized Precipitation Evapotranspiration (SPEI) index and for ENSO events through a documentary and numerical analysis under Oceanic Niño Index (ONI) with information from several scientific recent papers to integrate information and formulate a clear event influence understanding. The results show that within Mantaro Valley along its four provinces and their six meteorological stations, 70% of agricultural drought events occurred when ENSO was present between 1990-2021. Also, the severity straight correlation percentage between both, ENSO and SPEI events is quite variable between 9.09%-70%. It is important to keep analyzing those stations with few data since it can provide a new scenario deportment and track new ENSO forecasting methods to rise adaptive capacity and guarantee national and international food security which has as an important supplier to the Mantaro Valley, Peru.