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Статті в журналах з теми "ENSO-index"

1

Lu, Bo, Fei-Fei Jin, and Hong-Li Ren. "A Coupled Dynamic Index for ENSO Periodicity." Journal of Climate 31, no. 6 (March 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 (October 26, 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 (August 1998): 732–33. http://dx.doi.org/10.1038/29424.

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4

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 (January 25, 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 (June 11, 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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7

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 (November 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 (February 4, 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 (October 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 (August 12, 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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Дисертації з теми "ENSO-index"

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Luciani, Riccardo. "Study of Europe-ENSO teleconnection in an El Niño index phase analysis framework." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18807/.

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El Niño/Southern Oscillation (ENSO) is the most important coupled ocean-atmosphere phenomenon to cause global climate variability on seasonal to interannual time scales. Therefore understanding some of its most important features may help to shed light on the field of climate predictions. Here the focus is put on the seasonal precipitation patterns which respond to persistent thermal forcing happening thousands of kilometers far away. The first objective of this work is to look for and describe the correlation patterns between seasonal rainfall anomalies over Northern Italy and global seasonal Sea Surface Temperature anomalies (SSTA). Tri-monthly means of precipitation and tri-monthly means of SSTA from observational datasets are used in an anomaly correlation study in order to explore this teleconnection. The study is developed in the Nino Index Phase Analysis (NIPA) framework, as presented by Zimmerman et al., which consists in separating the positive and negative ENSO phase years in the computation of the anomaly correlation. The second objective of the work is to check if the correlations found are consistent with the shift of the circulation pattern which is due to a non-weak ENSO state. The anomaly means of the main ocean-atmospheric variables are examined in order to characterise the way in which the circulation works when the system is under El Niño or La Niña conditions and when the precipitation over the basins is higher or lower. Then, a Rossby waves simulation software is used to show that the propagation of a Rossby wave train, in a basic state with zonally varying middle latitude or low latitude jet, may be the cause of the correlations in the area under exam and for the seasons chosen, and how. This is an indication of the fact that the ENSO state and its spatial features can influence the tropospheric pathways through which planetary waves can propagate and this, in turn, could have an effect on midlatitudes large-scale circulation.
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Lopes, Fábio Ziemann, and Fábio Ziemann Lopes. "Relação entre o MEI (Multivariate Enso Index) e a precipitação pluvial no estado do Rio Grande do Sul." Universidade Federal de Pelotas, 2006. http://guaiaca.ufpel.edu.br:8080/handle/prefix/3992.

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No Rio Grande do Sul, as estações do ano são bem definidas sendo sentidos, em suas características peculiares, o inverno, a primavera, o verão e o outono. O regime pluviométrico é bastante regular e as chuvas são bem distribuídas durante todo o ano no Estado. O Índice Multivariado do El Niño Oscilação Sul (MEI) carece de um estudo de sua relação com a precipitação. Ele é um índice numérico que integra a ação de diferentes fatores que caracterizam o fenômeno e que oscila entre valores positivos para a fase quente, o El Niño, e valores negativos para a fase fria, a La Niña. Considera na sua composição, as seguintes variáveis: pressão ao nível do mar, as componentes zonal e meridional do vento em superfície, a Temperatura da Superfície do Mar (TSM), a temperatura do ar em superfície e um indicador de nebulosidade. Este trabalho teve como objetivo, estudar as relações entre o MEI e a TSM das regiões dos Niños com as precipitações pluviais no Estado do Rio Grande do Sul. Para isso, foram utilizados dados de totais mensais de precipitação pluvial de 40 estações meteorológicas do Rio Grande do Sul, dados bimestrais do MEI e de TSM das regiões dos Niños para o período de 1950 a 2002. Os coeficientes de correlação entre precipitação pluvial do Rio Grande do Sul com o MEI e as regiões dos Niños apresentaram valores baixos devido ao fato de se utilizar apenas os meses do início e final do evento. O MEI, apesar de ser um índice mais complexo do ponto de vista metodológico, não melhora os coeficientes de correlação com a precipitação pluvial do Estado do Rio Grande do Sul, e sempre apresenta valores menores ou iguais aos obtidos ao utilizar a TSM das regiões dos Niños nos bimestres de out/nov e nov/dez. As regiões dos Niños 3 e 4 são as mais influentes nas anomalias positivas de precipitação pluvial do Rio Grande do Sul para o bimestre out/nov. A região do Niño 4, por sua vez, é a mais influente para o caso das anomalias negativas da precipitação pluvial para o mesmo bimestre. Em relação ao bimestre nov/dez somente o Niño 3 tem maior influência nas anomalias positivas da precipitação pluvial no Rio Grande do Sul.
On Rio Grande do Sul the seasons of the year are well defined being felt, in its peculiar characteristics, the winter, the spring, the summer and the autumn. The pluviometric regime is quite regular and the precipitations are well distributed during all the year on the State. The Multivariate Enso Index (MEI) lacks of a study about its relations with the precipitation. It is a numeric index that integrates the action of different factors that characterize the phenomenon and that oscilate between positive values for the hot phase, the El Niño, and negative values for the cold phase, the La Niña. It considers, in its composition, the following variables: sea level pressure, zonal and meridional wind components at the surface, the Sea Surface Temperature (SST), the air temperature at the surface and a cloudiness indicator. This work had the objective to study the relations between the MEI and the SST of the Niño regions with the pluvial precipitations on Rio Grande do Sul State. For this, it were utilized total monthly data of pluvial precipitation from 40 meteorological stations of Rio Grande do Sul, bimonthly data of MEI and SST of the Niño regions for the period 1950 to 2002. The correlation coefficients between pluvial precipitation of Rio Grande do Sul with MEI and the Niños regions showed low values due to the fact of using only the months of the beginning and end of the event. The MEI, although being an index more complex in relation to the metodologic point of view, it does not improve the correlation coefficients with the pluvial precipitation of the State of Rio Grande do Sul and always presents lesser or equal values to that obtained when using the TSM of Niños regions in the bimonths of oct/nov and nov/dec.The Niños 3 and 4 regions are the most influents in the pluvial precipitation positive anomalies of Rio Grande do Sul for the bimonth oct/nov. On the other hand, the Niño 4 region is the most influent in the case of pluvial precipitation negative anomalies for the same bimonth. In relation to the bimonth nov/dec only the Niño 3 has more influence in the pluvial precipitation positive anomalies in Rio Grande do Sul.
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Paula, Gizelli Moiano de. "O FENÔMENO EL NIÑO OSCILAÇÃO SUL E A EROSIVIDADE DAS CHUVAS EM SANTA MARIA, RS." Universidade Federal de Santa Maria, 2009. http://repositorio.ufsm.br/handle/1/7510.

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Анотація:
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A large-scale phenomenon that greatly affects the weather and the climate of different locations of the Globe and that has been widely studied during the last three decades is the El Niño Southern Oscilation (ENSO). ENSO leads to changes in the atmospheric circulation and affects climate variables, mainly rainfall, in all regions of Brazil. During El Niño years (the positive phase of ENSO), rainfall is often above normal in Southern Brazil whereas during La Niña years (the negative phase of ENSO), rainfall is often below normal. Some of the rainfall properties are affected by ENSO like frequency, intensity and amount. These properties are important to define if rainfall events are erosive. There are some methods of determining rainfall erosivity, among them the best and most used in Rio Grande do Sul State is the EI30 erosivity index. The objective of this dissertation was to determine and associate the EI30 erosivity index of rainfalls with the ENSO phenomenon in Santa Maria, RS, Brazil. Daily precipitation data recorded from 01 July 1978 to 30 July 2008 collected in a standard Climatological Station in Santa Maria, RS, were used. Individual erosive rainfall events were identified in the records, grouped into El Niño, La Niña and Neutral years, and had their EI30 calculated. Rainfalls were also grouped into three patterns: Advanced, Intermediate and Delayed. Pearson correlation and regression analyses between the EI30 erosivity index and the Niño Oceanic Index (NOI) were performed and the regression was tested with the t test in order to quantify the relationship between the two variables, aiming a possible predictability of the erosion potential of rainfall events from Sea Surface Temperature (SST) in the Pacific Ocean. Rainfall erosion potential in Santa Maria is affected by ENSO, so that a greater number of rainfall events have higher erosion potential during El Niño and neutral years. The variability of the rainfall erosion potential is greater during Neutral years than during years with SST anomalies. The frequency distribution of the EI30 erosivity index is skewed to the right in El Niño, La Niña and Neutral years. Rainfalls pattern is changed in years with SST anomalies, so that there is a slight increase in Advanced rainfalls during El Niño years and a slight decrease in Delayed rainfalls during La Niña years, whereas there is a decrease in rainfall events with Intermediate pattern during El Niño and La Niña years compared to Neutral years. The predictive capability of the erosion potential of rainfall events in Santa Maria from NOI index is weak or not possible.
Um dos fenômenos de grande escala que mais afetam o tempo e o clima de diferentes locais na superfície terrestre e que tem sido bastante estudado nas últimas três décadas é o fenômeno El Niño Oscilação Sul (ENOS). O ENOS provoca alterações na circulação atmosférica que afetam os elementos meteorológicos, principalmente a precipitação pluviométrica, em todas as regiões do Brasil. Em anos de El Niño, fase positiva do fenômeno, a precipitação pluviométrica é freqüentemente acima da normal na Região Sul do Brasil e em anos de La Niña, fase negativa do fenômeno, a precipitação pluviométrica é freqüentemente abaixo da normal. Algumas características das precipitações pluviométricas são afetadas pelo ENOS como a freqüência, a intensidade e a quantidade. Essas características são importantes para se definir se as chuvas são erosivas. Existem alguns métodos de determinação da erosividade das chuvas, através de índices de erosividade, entre os quais, o melhor e mais usado no Rio Grande do Sul (RS) é o Índice de Erosividade EI30. O objetivo desta dissertação foi determinar e associar o Índice de Erosividade EI30 das chuvas com o fenômeno ENOS para Santa Maria, RS. Usaram-se os dados de precipitação diária retirados de pluviogramas a partir de 01 de julho de 1978 a 30 de junho de 2008 coletados na Estação Climatológica Principal de Santa Maria, RS. As chuvas individuais e erosivas foram identificadas nos pluviogramas, classificadas em anos de El Nino, La Niña e Neutros e calculado o seu índice EI30. Também foram classificadas as chuvas em padrões de chuvas Avançado, Intermediário e Atrasado. Foi realizada a análise de correlação de Pearson e análise de regressão entre o Índice de Erosividade EI30 e o Índice Oceânico do Niño (ION) e a significância da regressão foi testada com o teste t com o objetivo de quantificar a associação entre as duas variáveis, com vistas à possível previsibilidade do potencial erosivo das chuvas a partir de anomalias de Temperatura da Superfície do Mar (TSM) no Oceano Pacífico. O potencial erosivo das chuvas em Santa Maria é afetado pelo fenômeno ENOS, de modo que um maior número de chuvas tem maior potencial erosivo em anos de El Niño e em anos Neutros. A variabilidade do potencial erosivo das chuvas em Santa Maria é maior nos anos Neutros do que nos anos de anomalia da TSM. A distribuição de freqüência do índice de erosividade EI30 de chuvas individuais é assimétrica positiva em anos de El Niño, La Niña e Neutros. O padrão das chuvas é alterado em anos de anomalia da TSM no sentido de que nos anos El Niño há um leve acréscimo nas chuvas de padrão avançado e em anos de La Niña há um leve acréscimo nas chuvas de padrão atrasado, e no padrão intermediário, decrescem o número de chuvas em anos de El Niño e La Niña comparado com anos Neutros. A capacidade preditiva do potencial erosivo das chuvas em Santa Maria pelo Índice ION é fraca ou inexistente.
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4

Krois, Joachim, Achim Schulte, Vigo Edwin Pajares, and Moreno Carlos Cerdan. "Temporal and spatial characteristics of rainfall patterns in the Northern Sierra of Peru – A case study for La Niña to El Niño transitions from 2005 to 2010." Pontificia Universidad Católica del Perú. Centro de Investigación en Geografía Aplicada, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/119763.

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The climatic conditions of the northern Sierra of Peru are marked by the interaction of different macro- to mesoscale climatic features such as the El Niño Southern Oscillation (ENSO) or Mesoscale Convective Complexes (MCCs) and the seasonally shifting Intertropical Convergence Zone (ITCZ), but also by local scale climatic features such as inhomogeneous topography and local wind fields. The region under investigation, located in the vicinity of the South America Continental Water Divide (CWD), provides the opportunity to study interactions of western and eastern disturbances in a high mountain environment and their effects on rainfall variability. In general, rainfall variability is related to diurnal convection patterns, enhanced by valley breeze systems and modulated by local scale wind anomalies. Spillover of low-level air masses of Pacific origin passing over the Andean ridges is frequent. Although direct effects of ENSO on high Andean rainfall variability are in debate, our findings show that the majority of rain gauges used in this study follow an El Niño/dry and a La Niña/wet signal. However, high elevation areas on the western escarpment of the Andes benefit from abundant nocturnal rainfall that partly offsets the rainfall deficits during El Niño. Our data suggest that the spatial extent of this easterly wet pulse is limited to areas located above 3000 m asl. ENSO cycles contribute to rainfall variability near the CWD in the northern Sierra of Peru by modulating the seasonal rainfall regime and causing a positive temperature anomaly.
Las condiciones climáticas de la sierra norte del Perú están marcadas por la interacción de diferentes rasgos climáticos a escalas macro y meso, tal como el fenómeno ENSO o los Complejos Convectivos a Meso-escala (MCC) y la estacionalmente móvil Zona de Interconvergencia Intertropical (ITCZ), pero también por rasgos climáticos a escala local tales como la heterogeneidad topográfica y los campos de vientos locales. La zona de estudio se ubica en las cercanías de la divisoria de aguas continentales de Sudamérica (CWD), provee la oportunidad de estudiar las interacciones de las disturbancias occidental y oriental en un ambiente de alta montaña y sus efectos en la variabilidad de las precipitaciones. En general la variabilidad de las precipitaciones se relaciona con patrones de convección diurna, reforzada por los sistemas de brisas de valle y modulada por anomalías de vientos a escala local. El desplazamiento de masas de aire a baja altura provenientes del Pacífico que remontan los Andes es frecuente. Aunque los efectos directos del ENSO en la variabilidad de las precipitaciones andinas está todavía en debate, nuestras investigaciones muestran que la mayoría de las mediciones hechas para este estudio siguen una señal El Niño/seco y La Niña/húmedo. Sin embargo, las zonas altas de lasescarpas occidentales de los Andes se benefician de abundante lluvia nocturna que parcialmente completa los déficits de precipitaciones durante El Niño. Nuestros datos sugieren que la cobertura espacial de este pulso húmedo del Este se limita a áreas que se ubican encima de los 3000 msnm. Los ciclos ENSO contribuyen a la variabilidad de las precipitaciones cerca del CWD en la sierra norte del Perú mediante la modulación del régimen estacional de lluvias que causa una anomalía de temperatura positiva.
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5

Karlina. "ASSESSMENT OF HYDRO-METEOROLOGICAL DROUGHTS RELATED TO ENSO IN LOMBOK AND SUMATRA ISLANDS, INDONESIA." Kyoto University, 2018. http://hdl.handle.net/2433/231991.

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付記する学位プログラム名: グローバル生存学大学院連携プログラム
Kyoto University (京都大学)
0048
新制・課程博士
博士(工学)
甲第21058号
工博第4422号
新制||工||1687(附属図書館)
京都大学大学院工学研究科社会基盤工学専攻
(主査)教授 寶 馨, 教授 堀 智晴, 准教授 佐山 敬洋
学位規則第4条第1項該当
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6

Chen, Maosi, William J. Parton, Grosso Stephen J. Del, Melannie D. Hartman, Ken A. Day, Compton J. Tucker, Justin D. Derner, et al. "The signature of sea surface temperature anomalies on the dynamics of semiarid grassland productivity." WILEY, 2017. http://hdl.handle.net/10150/626547.

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We used long-term observations of grassland aboveground net plant production (ANPP, 19392016), growing seasonal advanced very-high-resolution radiometer remote sensing normalized difference vegetation index (NDVI) data (1982-2016), and simulations of actual evapotranspiration (1912-2016) to evaluate the impact of Pacific Decadal Oscillation (PDO) and El Nino-Southern Oscillation (ENSO) sea surface temperature (SST) anomalies on a semiarid grassland in northeastern Colorado. Because ANPP was well correlated (R-2 = 0.58) to cumulative April to July actual evapotranspiration (iAET) and cumulative growing season NDVI (iNDVI) was well correlated to iAET and ANPP (R-2 = 0.62 [quadratic model] and 0.59, respectively), we were able to quantify interactions between the long-duration (15-30 yr) PDO temperature cycles and annual-duration ENSO SST phases on ANPP. We found that during cold-phase PDOs, mean ANPP and iNDVI were lower, and the frequency of low ANPP years (drought years) was much higher, compared to warm-phase PDO years. In addition, ANPP, iNDVI, and iAET were highly variable during the cold-phase PDOs. When NINO-3 (ENSO index) values were negative, there was a higher frequency of droughts and lower frequency of wet years regardless of the PDO phase. PDO and NINO-3 anomalies reinforced each other resulting in a high frequency of above-normal iAET (52%) and low frequency of drought (20%) when both PDO and NINO-3 values were positive and the opposite pattern when both PDO and NINO-3 values were negative (24% frequency of above normal and 48% frequency of drought). Precipitation variability and subsequent ANPP dynamics in this grassland were dampened when PDO and NINO-3 SSTs had opposing signs. Thus, primary signatures of these SSTs in this semiarid grassland are (1) increased interannual variability in ANPP during cold-phase PDOs, (2) drought with low ANPP occurring in almost half of those years with negative values of PDO and NINO-3, and (3) high precipitation and ANPP common in years with positive PDO and NINO-3 values.
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7

Hammill, Allison L. "Effects of Localized NAO, ONI (ENSO) and AMO Events on Reproductive Patterns in Loggerhead (Caretta caretta) Sea Turtles in Broward County, FL, USA." NSUWorks, 2013. http://nsuworks.nova.edu/occ_stuetd/135.

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A variety of anthropomorphic and environmental stresses are threatening the existence of all seven species of sea turtles. There is growing evidence that alterations in surface waters and sediment temperatures are negatively impacting reproductive success of loggerhead sea turtles (Caretta caretta). Fluctuations in water temperature associated with localized climate oscillations heavily alter the food web dynamics of the ocean. Feeding conditions are expected to be a critical factor in determining body mass and productivity for breeding seasons. An increase in regional temperatures could lead to prolonged reduction in food sources, as well as reduced nesting and recruitment. Loggerhead sea turtle nesting data from 1995-2011 werre compared with the average yearly North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO) which are important climatic events impacting the SST in the Atlantic Ocean. Because El Niño Southern Oscillation (ENSO) is a global event, it was proposed that turtles in the Atlantic may follow a similar trend. ENSO was quantified using Oceanic Nino Index (ONI). Analysis of loggerhead sea turtle nest frequencies from the years 1995-2011 in comparison to seasonal climate changes showed a significant inverse relationship between the detrended loggerhead nests and average yearly NAO when lagged two years, suggesting loggerheads may spend years prior breeding obtaining optimum body mass to increase successful reproduction. The detrended nesting data showed a tendency toward higher occurrence of nests during La Niña years while nest frequencies decreased during El Niño year; when the yearly detrended loggerhead nesting data was compared with the average yearly ONI; showing a significant inverse relationship without a lag. This may also suggest a relationship between changes of productivity of the ocean influenced by smaller scale climate changes and loggerhead nest frequencies.
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8

Keeling, Travis B. "Modified JMA ENSO index and its improvements to ENSO classification." 2009. http://etd.lib.fsu.edu/theses/available/etd-12222008-094254/.

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Thesis (M.S.)--Florida State University, 2009.
Advisor: James J. O'Brien, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed June 25, 2009). Document formatted into pages; contains xiv, 117 pages. Includes bibliographical references.
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9

"Relationbetween MEI (Multivariate Enso Index) and the pluvial precipitation on RioGrande do Sul State." Tese, Biblioteca Digital da Universidade Federal de Pelotas, 2006. http://www.ufpel.edu.br/tede/tde_busca/arquivo.php?codArquivo=161.

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10

Cumming, Rebecca Miville. "Beach-dune morphodynamics and climatic variability in Gwaii Haanas National Park and Haida Heritage Site, British Columbia, Canada." Thesis, 2007. http://hdl.handle.net/1828/180.

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This thesis describes the geomorphology and morphodynamics of two embayed, sandy, macrotidal beach-dune systems in the Cape St. James region of Gwaii Haanas National Park Reserve and Haida Heritage Site. Gilbert Bay beach is a small embayment with a southwest aspect that exhibits prograding dune ridges. Woodruff Bay beach, a larger system with a SE aspect, is characterized by large erosional scarps on the established foredune. Aspect to erosive conditions and embayment size control the distinct morphologic responses of these beach-dune systems. The morphodynamic regime at Cape St. James consists of high onshore sediment transport potential combined with an increasingly erosive water level regime that is forced by PDO and ENSO climatic variability events. Conceptual models of potential future responses of these beaches to sea level rise show a possible landward migration of up to 3.5 m at Gilbert Bay beach and up to 4 m at Woodruff Bay beach.
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Частини книг з теми "ENSO-index"

1

Raut, Shrishail, Sadegh Modiri, Robert Heinkelmann, Kyriakos Balidakis, Santiago Belda, Chaiyaporn Kitpracha, and Harald Schuh. "Investigating the Relationship Between Length of Day and El-Niño Using Wavelet Coherence Method." In International Association of Geodesy Symposia. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/1345_2022_167.

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AbstractThe relationship between the length of day (LOD) and El-Niño Southern Oscillation (ENSO) has been well studied since the 1980s. LOD is the negative time-derivative of UT1-UTC, which is directly proportional to Earth Rotation Angle (ERA), one of the Earth Orientation Parameters (EOP). The EOP can be determined using Very Long Baseline Interferometry (VLBI), which is a space geodetic technique. In addition, satellite techniques such as the Global Navigation Satellite System (GNSS), Satellite Laser Ranging (SLR), Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) can provide Earth Rotation Parameters, i.e., polar motion and LOD. ENSO is a climate phenomenon occurring over the tropical eastern Pacific Ocean that mainly affects the tropics and the subtropics. Extreme ENSO events can cause extreme weather like flooding and droughts in many parts of the world. In this work, we investigated the effect of ENSO on the LOD from January 1979 to April 2022 using the wavelet coherence method. This method computes the coherence between the two non-stationary time-series in the time-frequency domain using the real-valued Morlet wavelet. We used the Multivariate ENSO index version 2 (MEI v.2) which is the most robust series as the climate index for the ENSO, and LOD time-series from IERS (EOP 14 C04 (IAU2000A)). We also used Oceanic Niño and Southern Oscillation index in this study for comparison. The results show strong coherence of 0.7 to 0.9 at major ENSO events for the periods 2–4 years between LOD and MEI.v2.
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2

Smith, Raymond C. "Introductory Overview." In Climate Variability and Ecosystem Response in Long-Term Ecological Research Sites. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195150599.003.0014.

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The El Niño–Southern Oscillation (ENSO) is a coupled ocean–atmosphere phenomena that has a worldwide impact on climate. An aperiodic phenomena that reoccurs every 2 to 7 years, the ENSO is second only to seasonal variability in driving worldwide weather patterns. As Greenland notes in chapter 6, the term “quasi-quintennial” is chosen to recognize that climatic events other than ENSO-related events might occur at this timescale, although it is widely recognized that ENSO contributes the lion’s share of the higher frequency variability in paleorecords of the past several thousand years. In this section, we consider variability with cycles of 2 to 7 years and the resulting ecological response. Although we emphasize the ENSO timescale in this section, there is growing evidence that this phenomena is neither spatially nor temporally stable over longer time periods. Indeed, Allan (2000) suggests the ENSO climatic variability must be viewed within the context of climate fluctuations at decadal to interdecadal timescales, which often modulate the higher frequency ENSO variability. As a consequence, results in this and the next section often display overlapping patterns of variability, and their separation is not sharply defined. An important theme in this section is the worldwide influence of ENSO-related climate variability. Greenland (chapter 6) provides an LTER network overview with an analysis of ENSO-related variability of temperature and precipitation records for many LTER sites from the Arctic to the Antarctic. He discusses the general nature of ENSO and its climatic effects, summarizes previous climate-related work in the LTER network, and provides a cross-site analysis of the correlations between the Southern Oscillation Index (SOI) and temperature and precipitation at LTER sites. His results are consistent with the expected patterns of the geography of ENSO effects on the climate. Greenland’s cross-site analysis provides the basis for studying climate variability and ecosystem response within the context of the series of framework questions that form an underlying theme for this volume. Brazel and Ellis (chapter 7) provide an excellent analysis of climate-related parameters within the context of ENSO indices. Reporting on the Central Arizona and Phoenix (CAP) LTER urban-rural ecosystem, these authors provide a comprehensive analysis linking water-related parameters to climate forcing, as indicated by these indexes. Their studies show a strong connection between ENSO and winter moisture in Arizona, perhaps making it possible to forecast impending conditions.
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3

Greenland, David. "An LTER Network Overview and Introduction to El Niño–Southern Oscillation (ENSO) Climatic Signal and Response." In Climate Variability and Ecosystem Response in Long-Term Ecological Research Sites. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195150599.003.0015.

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Part II of this book deals with the quasi-quintennial timescale that is dominated by the El Niño–Southern Oscillation (ENSO) phenomenon. During the last 50 years, ENSO has operated with a recurrence interval between peak values of 2–7 years. The term quasi-quintennial is chosen to recognize that climatic events other than ENSO-related ones might occur at this timescale. The general significance of the ENSO phenomenon lies in its influence on natural and human ecosystems. It has been estimated that severe El Niño–related flooding and droughts in Africa, Latin America, North America, and Southeast Asia resulted in more than 22,000 lives lost and more than $36 billion in damages during 1997– 1998 (Buizer et al. 2000). The specific significance of ENSO within the context of this book is that it provides fairly well-bounded climatic events for which specific ecological responses may be identified. In the other chapters in part II, we first look at the U.S. Southwest. The Southwest is home to an urban LTER site, the Central Arizona-Phoenix (CAP) site. Tony Brazel and Andrew Ellis describe the clear ENSO climatic signal at this site and identify surprising responses that cascade into the human/economic system. Ray Smith, Bill Fraser, and Sharon Stammerjohn provide more details of the fascinating ecological responses of the Palmer Antarctic ecosystem to ENSO. World maps of ENSO climatic signals do not usually show the Antarctic, and the LTER program provides some groundbreaking results at this location, with Smith and coworkers (see the Synthesis at the end of this part) providing such maps (figures S.1 and S.2). Kathy Welch and her colleagues present equally new discoveries related to freshwater aquatic ecosystems from the other Antarctic LTER site at the McMurdo Dry Valleys. This chapter gives a general introduction to ENSO and its climatic effects. How ever, these general patterns may mask the detailed responses that occur at individual locations. This is one reason for presenting the principal results of previous findings related to El Niños and LTER sites and one particular analysis focused on LTER sites. This analysis for the period 1957–1990 investigates the response of monthly mean temperature and monthly total precipitation standardized anomaly values to El Niño and La Niña events as indicated by the Southern Oscillation Index (SOI) (Greenland 1999).
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4

Brazel, Anthony J., and Andrew W. Ellis. "The Climate of the Central Arizona and Phoenix Long-Term Ecological Research Site (CAP LTER) and Links to ENSO." In Climate Variability and Ecosystem Response in Long-Term Ecological Research Sites. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195150599.003.0016.

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The Central Arizona and Phoenix LTER (CAP LTER) is one of two urban LTERs in the world network (Grimm et al. 2000; see http://caplter.asu.edu). Many LTER sites display a detectable climatic signal related to the El Niño–Southern Oscillation (ENSO) phenomenon (Greenland 1999). The purpose of this chapter is twofold: (1) to provide some insight into the role of the tropical Pacific Ocean as a driver of several climatic (and thus, ecologically related) variables in the CAP LTER location of central Arizona, and (2) to suggest the linkages of ENSO events to selected ecosystem processes near and within the geographical region of CAP LTER (figure 7.1a). From past studies, it is clear that the seasonal and annual climate regimes of the southwestern United States, particularly water-related parameters, are linked to the periodicities and anomalies of what is known as the Multivariate ENSO Index (MEI) and Southern Oscillation Index (SOI) (e.g., Wolter 1987; Molles and Dahm 1990; Redmond and Koch 1991; Woolhiser and Keefer 1993; Wolter and Timlin 1993; Cayan and Redmond 1994; Redmond and Cayan 1994; Cayan et al. 1999; Redmond and Cayan 1999; Simpson and Colodner 1999; Redmond 2000; and Mason and Goddard 2001). In Arizona, and especially in the CAP LTER region, precipitation is bimodal during the year with peaks in winter (mostly midlatitudederived frontal storms) and in mid-to-late summer, mostly in the form of convective thunderstorms during the North American monsoon season. Recent studies show a strong connection between ENSO and winter moisture in Arizona, such that it is even possible to forecast impending conditions in advance (Pagano et al. 1999). These studies have established relationships between the climate of the southwest ern United States and ENSO by demonstrating monthly and daily timescale effects on inputs of moisture and resultant streamflow in Arizona (e.g., Molles and Dahm 1990; Cayan et al. 1999; and Simpson and Colodner 1999). The synoptic- and largescale circulation patterns associated with anomalies of MEI/SOI in the southwestern United States provide additional insight into regional forces that drive the CAPLTER climate (e.g., Redmond and Koch 1991). Generally, when the warm phase of the tropical Pacific Ocean occurs (El Niño, thus negative SOI, positive MEI), across the Southwest precipitation is generally anomalously high.
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5

Schaefer, Douglas. "Watershed Hydrological and Chemical Responses to Precipitation Variability in the Luquillo Mountains of Puerto Rico." In Climate Variability and Ecosystem Response in Long-Term Ecological Research Sites. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195150599.003.0017.

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Variations in temperature and precipitation are both components of climate variability. Based on coral growth rates measured near Puerto Rico, the Caribbean was 2–3ºC cooler during the “Little Ice Age” during the seventeenth century (Winter et al. 2000). At the millennial scale, temperature variations in tropical regions have been inferred to have substantial biological effects (such as speciation and extinction), but not at the multidecadal timescales considered here. My focus is on precipitation variability in particular, because climate models examining effects of increased greenhouse gases suggest greater changes in precipitation than in temperature patterns in tropical regions. Some correspondence between both the El Niño–Southern Oscillation (ENSO) and the Northern Atlantic Oscillation (NAO) and average temperatures and total annual precipitation have been reported for the LTER site at Luquillo (Greenland 1999; Greenland and Kittel 2002), but those studies did not refer to extreme events. Based on climate records for Puerto Rico since 1914, Malmgren et al. (1997) found small increases in air temperature during El Niño years and somewhat greater total rainfall during the positive phase of the NAO. Similar to ENSO, the NAO index is characterized by differences in sea-level atmospheric pressure, in this case based on measurements in Iceland and Portugal (Walker and Bliss 1932). Its effects on climate have largely been described in terms of temperature and precipitation anomalies in countries bordering the North Atlantic (e.g., Hurrell 1995). Puerto Rico is in the North Atlantic hurricane zone, and hurricanes clearly play a major role in precipitation variability. The association between extreme rainfall events and hurricanes is discussed in detail in this chapter. I examine the degree to which extreme rainfall events are associated with hurricanes and other tropical storms. I discuss whether the occurrence of these extreme events has changed through time in Puerto Rico or can be linked to the recurrent patterns of the ENSO or the NAO. I examine the 25-year daily precipitation record for the Luquillo LTER site, the 90-year monthly record from the nearest site to Luquillo with such a long record, Fajardo, and those of the two other Puerto Rico stations with the longest daily precipitation records, Manati and Mayaguez (figure 8.1).
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6

Bouri, Elie, Rangan Gupta, and Luca Rossini. "The role of the monthly ENSO in forecasting the daily Baltic Dry Index." In Reference Module in Social Sciences. Elsevier, 2023. http://dx.doi.org/10.1016/b978-0-44-313776-1.00089-1.

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7

Goodin, Douglas G., and Philip A. Fay. "Climate Variability in Tallgrass Prairie at Multiple Timescales: Konza Prairie Biological Station." In Climate Variability and Ecosystem Response in Long-Term Ecological Research Sites. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195150599.003.0038.

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Climate is a fundamental driver of ecosystem structure and function (Prentice et al. 1992). Historically, North American grassland and forest biomes have fluctuated across the landscape in step with century- to millennialscale climate variability (Axelrod 1985; Ritchie 1986). Climate variability of at decadal scale, such as the severe drought of the 1930s in the Central Plains of North America, caused major shifts in grassland plant community composition (Weaver 1954, 1968). However, on a year-to-year basis, climate variability is more likely to affect net primary productivity (NPP; Briggs and Knapp 1995; Knapp et al. 1998; Briggs and Knapp 2001). This is especially true for grasslands, which have recently been shown to display greater variability in net primary production in response to climate variability than forest, desert, or arctic/alpine systems (Knapp and Smith 2001). Although the basic relationships among interannual variability in rainfall, temperature, and grassland NPP have been well studied (Sala et al. 1988; Knapp et al. 1998; Alward et al. 1999), the linkages to major causes of climate variability at quasi-quintennial (~5 years) or interdecadal (~10 year) timescales in the North American continental interior, such as solar activity cycles, the El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the North Pacific Index (NP), are less well understood. In this chapter, we will examine how interannual, quasi-quintennial, and interdecadal variation in annual precipitation and mean annual temperature at a tallgrass prairie site (Konza Prairie Biological Station) may be related to indexes of solar activity, ENSO, NAO, and NP, and in turn how these indexes may be related to aboveground net primary productivity (ANPP). Specifically, we present (1) period-spectrum analyses to characterize the predominant timescales of temperature and precipitation variability at Konza Prairie, (2) correlation analyses of quantitative indexes of the major atmospheric processes with Konza temperature and precipitation records, and (3) the implications of variation in major atmospheric processes for seasonal and interannual patterns of ANPP. The Konza Prairie Biological Station (KNZ), which lies in the Flint Hills (39º05' N, 96º35' W), is a 1.6-million-ha region spanning eastern Kansas from the Nebraska border to northeastern Oklahoma (figure 20.1). This region is the largest remaining tract of unbroken tallgrass prairie in North America (Samson and Knopf 1994) and falls in the more mesic eastern portion of the Central Plains grasslands.
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8

Goodin, Douglas G. "Introductory Overview." In Climate Variability and Ecosystem Response in Long-Term Ecological Research Sites. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195150599.003.0022.

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Timescale is the organizing framework of this volume. In various sections, we consider the effects of climate variability on ecosystems at timescales ranging from weeks or months to centuries. In part III, we turn our attention to interdecadal-scale events. The timescales we consider are not absolutely defined, but for our purposes we define the interdecadal scale to encompass effects occurring with recurring cycles generally ranging from 10 to 50 years. A recurring theme in many of the chapters in this section is the effect on ecosystem response of teleconnection patterns associated with recognized quasi-periodic atmospheric circulation modes. These circulation modes include the well-known El Niño– Southern Oscillation (ENSO) phenomenon, which is generally thought to recur at shorter, interdecadal timescales but also includes some longer-term periodicities. Several other climate variability modes, including the Pacific North American index (PNA), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and North Pacific index (NP) also show strong interdecadal scale signatures and figure prominently in the chapters of part III. McHugh and Goodin begin the section by examining the climate record at several North American LTER sites for evidence of interdecadal-scale fluctuation. They note that interdecadal-scale contributions to climate variability can best be described in terms of two types of variation: (1) discontinuities in mean value, and (2) the presence of trends in the data. Evaluation of interdecadal periodicities in LTER data is complicated by the relatively short time series of observations available. McHugh and Goodin approach the problem mainly through the use of power spectrum analysis, a widely used tool for evaluating the periodicity in a time series of data. Principal components analysis is used to decompose the time series of growing-season climate data for each of the LTER sites into their principal modes of variability. These modes are then subjected to power spectrum analysis to evaluate the proportions of the variance in the data occurring at various timescales. McHugh and Goodin’s results suggest that significant effects on precipitation and temperature at interdecadal timescales are uncommon in these data, although significant periodicities at both shorter and longer frequencies do emerge from the data (a finding of relevance to other sections of this volume).
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Тези доповідей конференцій з теми "ENSO-index"

1

Díaz, Diana, Diana Díaz, Nancy Villegas, and Nancy Villegas. "CANONICAL CORRELATION AMONG LARGE SCALE OSCILLATIONS, TEMPERATURE AND PRECIPITATION IN COASTAL REGIONS OF COLOMBIA." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.31519/conferencearticle_5b1b93a05a4f25.66586448.

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This study examines relationships between available surface meteorology variables and climatic oscillations by using canonical correlation analysis (CCA). Canonical loadings and cross loadings from CCA are evaluated for meteorological stations located over coastal regions of Colombia. The tests, used for these studies, consider the temperature, the precipitation data, three of the main oscillations – the Ocean Niño Index (ONI), North Atlantic Oscillation (NAO), and the Quasi-biennial oscillation (QBO). The results show the power of the statistical method used to identify associations on the data set with an acceptable level of confidence using multivariate approach. The analysis reveals relations mostly between the variables and the ENSO for all cases and a discrete connection with the NAO and QBO. To add climate indices to the group of independent variables increased the variance rates between 5 and 7%.
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2

Díaz, Diana, Diana Díaz, Nancy Villegas, and Nancy Villegas. "CANONICAL CORRELATION AMONG LARGE SCALE OSCILLATIONS, TEMPERATURE AND PRECIPITATION IN COASTAL REGIONS OF COLOMBIA." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.21610/conferencearticle_58b4316f0ce3f.

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Анотація:
This study examines relationships between available surface meteorology variables and climatic oscillations by using canonical correlation analysis (CCA). Canonical loadings and cross loadings from CCA are evaluated for meteorological stations located over coastal regions of Colombia. The tests, used for these studies, consider the temperature, the precipitation data, three of the main oscillations – the Ocean Niño Index (ONI), North Atlantic Oscillation (NAO), and the Quasi-biennial oscillation (QBO). The results show the power of the statistical method used to identify associations on the data set with an acceptable level of confidence using multivariate approach. The analysis reveals relations mostly between the variables and the ENSO for all cases and a discrete connection with the NAO and QBO. To add climate indices to the group of independent variables increased the variance rates between 5 and 7%.
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Звіти організацій з теми "ENSO-index"

1

Yeates, Elissa, Kayla Cotterman, and Angela Rhodes. Hydrologic impacts on human health : El Niño Southern Oscillation and cholera. Engineer Research and Development Center (U.S.), January 2020. http://dx.doi.org/10.21079/11681/39483.

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A non-stationary climate imposes considerable challenges regarding potential public health concerns. The El Niño Southern Oscillation (ENSO) cycle, which occurs every 2 to 7 years, correlates positively with occurrences of the waterborne disease cholera. The warm sea surface temperatures and extreme weather associated with ENSO create optimal conditions for breeding the Vibrio cholerae pathogen and for human exposure to the pathogenic waters. This work explored the impacts of ENSO on cholera occurrence rates over the past 50 years by examining annual rates of suspected cholera cases per country in relation to ENSO Index values. This study provides a relationship indicating when hydrologic conditions are optimal for cholera growth, and presents a statistical approach to answer three questions: Are cholera outbreaks more likely to occur in an El Niño year? What other factors impact cholera outbreaks? How will the future climate impact cholera incidence rates as it relates to conditions found in ENSO? Cholera outbreaks from the 1960s to the present are examined focusing on regions of Central and South America, and southern Asia. By examining the predictive relationship between climate variability and cholera, we can draw conclusions about future vulnerability to cholera and other waterborne pathogenic diseases.
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