No description available.

No description available.

No description available.

El Ni??o-Southern Oscillation (ENSO) is the most important coupled ocean-atmospheric phenomenon to cause global climate variability on interannual time scales. Efforts to understand recent, apparently anomalous ENSO behaviour are hampered by the lack of long, high-quality climate records. While instrumental data generally covers the past 150 years, record length is insufficient for the assessment of past changes in the frequency, magnitude, and duration of ENSO. Here, multiproxy networks of high-resolution tree-ring, coral, ice and documentary records derived from eastern and western Pacific ENSO ???centres of action??? are analysed (A.D. 1525-2002). Considerable improvements in ENSO reconstruction are achieved from expanding the use of records from the western Pacific. In particular, ~500 years of a continuous 3,722 year ENSO sensitive tree-ring record from New Zealand is introduced. Although extreme ENSO events are seen throughout a 478-year discrete event analysis, 43% of extreme, 20% of very strong and 28% of all protracted ENSO events occur within the 20th century. Principal component analysis was used to extend instrumental records of the Southern Oscillation Index (SOI) Ni??o 3.4 Sea Surface Temperature (Ni??o 3.4 SST) and a newly developed coupled ocean-atmospheric ENSO index (CEI) by 347 years. Significantly, of the three indices reconstructed here, CEI reconstructions were largely found to be the best predictors of ENSO. The results suggest that ENSO may be more effectively characterised using a coupled ocean-atmosphere index, particularly for December-May periods. Compared to the pre-instrumental period, the late 19th and early 20th centuries indicate a clear trend toward increased ENSO variability over the past 150 years. Significantly, spectral analysis of reconstructed indices reveals a marked change in the frequency and intensity of ENSO beginning ~A.D. 1850, coinciding with the end of the Little Ice Age and the boom in global industrialisation. This suggests that ENSO may operate differently under natural (pre-industrial) and anthropogenically influenced background states. This study asserts that recent ENSO variability appears anomalous in the context of the past five centuries. Given the considerable socio-economic impacts of ENSO events, future investigation into the implications an increasingly anthropogenically-warmed world may have on ENSO is vital.

El Ni??o-Southern Oscillation (ENSO) is the most important coupled ocean-atmospheric phenomenon to cause global climate variability on interannual time scales. Efforts to understand recent, apparently anomalous ENSO behaviour are hampered by the lack of long, high-quality climate records. While instrumental data generally covers the past 150 years, record length is insufficient for the assessment of past changes in the frequency, magnitude, and duration of ENSO. Here, multiproxy networks of high-resolution tree-ring, coral, ice and documentary records derived from eastern and western Pacific ENSO ???centres of action??? are analysed (A.D. 1525-2002). Considerable improvements in ENSO reconstruction are achieved from expanding the use of records from the western Pacific. In particular, ~500 years of a continuous 3,722 year ENSO sensitive tree-ring record from New Zealand is introduced. Although extreme ENSO events are seen throughout a 478-year discrete event analysis, 43% of extreme, 20% of very strong and 28% of all protracted ENSO events occur within the 20th century. Principal component analysis was used to extend instrumental records of the Southern Oscillation Index (SOI) Ni??o 3.4 Sea Surface Temperature (Ni??o 3.4 SST) and a newly developed coupled ocean-atmospheric ENSO index (CEI) by 347 years. Significantly, of the three indices reconstructed here, CEI reconstructions were largely found to be the best predictors of ENSO. The results suggest that ENSO may be more effectively characterised using a coupled ocean-atmosphere index, particularly for December-May periods. Compared to the pre-instrumental period, the late 19th and early 20th centuries indicate a clear trend toward increased ENSO variability over the past 150 years. Significantly, spectral analysis of reconstructed indices reveals a marked change in the frequency and intensity of ENSO beginning ~A.D. 1850, coinciding with the end of the Little Ice Age and the boom in global industrialisation. This suggests that ENSO may operate differently under natural (pre-industrial) and anthropogenically influenced background states. This study asserts that recent ENSO variability appears anomalous in the context of the past five centuries. Given the considerable socio-economic impacts of ENSO events, future investigation into the implications an increasingly anthropogenically-warmed world may have on ENSO is vital.

El Niño Southern Oscillation (ENSO) is the most important interannual mode of climate variability in the tropical Pacific affecting the globe through teleconnections. The evolution of ENSO is studied with focus on individual El Nino (EN) events; factors and processes explaining the behaviours of different EN flavours are identified. The comparison to model simulations reveals a number of biases that explain differences in model behaviour. Based on reanalysis data, ENs are divided into Central Pacific (CPEN), Eastern Pacific (EPEN), and Hybrid (HBEN). ENs are found to form a continuous spectrum of events with CPEN and EPEN as its end members depending on: (1) the Western Pacific subsurface potential temperature anomaly (PTA) about 1 year before the EN peak, and (2) the Western to Central Pacific cumulative zonal wind anomaly (ZWA) between the onset and peak of the EN. Using these two parameters, about 70% of the total variance of the maximum EN SSTA can be explained up to 6 months in advance. ZWA describes the potential for triggering Kelvin waves for a given initial West Pacific recharge state as captured by PTA. A cross-validated statistical model is developed to hindcast the 1980-2016 Nov-Dec-Jan (NDJ) mean Niño3.4 SSTA based on the two parameters. The model is comparable to, or even outperforms, many NOAA Climate Prediction Centre's statistical models during the boreal spring predictability barrier. The explained variance between observed and predicted NDJ Niño3.4 SSTA at a lead-time of 8 months is 57% using five years for cross-validation. Predictive skills are lower after 2000 when the mean climate state is more La Niña-like due to stronger equatorial easterly ZWA caused by an intensification of both, Walker and Hadley cell. The ability of climate models to simulate and predict EN is assessed with data from the Climate Model Inter-comparison Project 5 (CMIP5). Most models are able to capture the main features of different EN types. But models struggle to reproduce large intensity ENs as found in observations. This issue can be traced back to a failure to realistically simulate the oceanic recharged state and the subsequent Kelvin waves for intense EN. Causes of EN involve Kelvin waves that are triggered by westerly wind bursts (WWB). From higher temporal resolution of reanalysis data, WWBs above a certain threshold are required to trigger a Kelvin wave. Kelvin waves are triggered in locations of positive Ocean Heat Content (OHC) anomalies. Intensity, longitudinal coverage and duration of a WWB, the strength of the OHC anomaly and gradient influence the amplitude of Kelvin waves as they propagate. Synoptic pattern analysis suggests that most WWBs are caused by cyclones with the combination of an active Madden-Julian Oscillation. The NorESM is able to reproduce many characteristics of observed WWBs, OHC anomalies and their relation to Kelvin waves. However, differences are noticeable for the distribution of synoptic patterns causing WWBs in the model. In future work, climate models can be used to disentangle causes and effects of EN for correlations identified here with the ultimate goal to advance our understanding of ENSO, its variability and future changes.

No description available.

El Niño is typically viewed as an episode of destructive weather anomalies that can last from a few months to several years. The majority of research looks at the negative impacts of this event. However, not all impacts of El Niño are necessarily bad. This study outlines areas of the United States that are most highly impacted by anomalous temperature and rainfall during El Niño years and determines whether these anomalies affect energy consumption. These effects will be examined on both a national and regional scale. Areas of the northwestern and southeastern United States exhibit anomalous temperatures during El Niño years. The southern US and Great Plains area receives positive anomalous precipitation during El Niño years while an area of the east central US experiences negative anomalous precipitation. Natural gas consumption in the northwestern US is reduced by the El Niño/Southern Oscillation (ENSO). During an ENSO event consumers actually save money because less is spent on natural gas for home heating purposes. Hydroelectricity may also be affected by ENSO in the southeastern US but the results at this time are inconclusive. At the national level, ENSO influences the consumption of nuclear electricity.

El Niño is typically viewed as an episode of destructive weather anomalies that can last from a few months to several years. The majority of research looks at the negative impacts of this event. However, not all impacts of El Niño are necessarily bad. This study outlines areas of the United States that are most highly impacted by anomalous temperature and rainfall during El Niño years and determines whether these anomalies affect energy consumption. These effects will be examined on both a national and regional scale. Areas of the northwestern and southeastern United States exhibit anomalous temperatures during El Niño years. The southern US and Great Plains area receives positive anomalous precipitation during El Niño years while an area of the east central US experiences negative anomalous precipitation. Natural gas consumption in the northwestern US is reduced by the El Niño/Southern Oscillation (ENSO). During an ENSO event consumers actually save money because less is spent on natural gas for home heating purposes. Hydroelectricity may also be affected by ENSO in the southeastern US but the results at this time are inconclusive. At the national level, ENSO influences the consumption of nuclear electricity.

The El Nino event causes the changes of the ocean and atmosphere system that induces the rainfall unusual increasing or reduction in some areas and then cause local lives and economical losses. Previous studies have found that the El Nino actually applies impact on the rainfall, however most of the studies focus on the impact of separated stations but little on regional variation. The study on the other hand focus on the variation of the rainfall based on the climatic classification primarily and the physiographic region position auxiliary during the El Nino event and La Nina events. The main method of this research is the correlation analysis, when the correlation coefficient draws close to +1, it mean that the rainfall is positive relative with the parameter of the El Nino, and when the correlation coefficient draws close to -1, it mean that the rainfall is negativity relative with the parameter of the El Nino event. The analysis parameters of the El Nino event index include the sea water temperature and anomaly of every area in Pacific Ocean, sea water surface temperature difference of two areas opposite, Southern Oscillation index and Multivariate ENSO Index. It is found in the study that the best parameter of the El Nino event is the sea water temperature difference of (Nino1¡Ï2- Nino34). The result showed the most climatic classifications have good relation with the parameter of the El Nino, especially winter-dry climatic classifications is the best. Because the result of the research influence on the season variation, it is not to conclude the relation with the El Nino event. It is need to study deeply for calculating the rainfall of the areas where influenced by the El Nino event.