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Grey-faced Petrels (Pterodroma gouldi) are a colonial burrowing seabird predominantly nesting on offshore islands of the upper North Island of New Zealand. We studied their annual breeding biology and the impact of Southern Oscillation Index climatic effects by measuring colony productivity and chick growth rates from 2011 to 2015 on Te Hāwere-a-Maki as unfavorable warmer La Niña conditions changed to favorable cooler El Niño conditions. Across all five years, annual chick hatching consistently occurred within a one-week period at the end of August but fledging variably occurred over a three-week period following Christmas. Because ship rats are pest controlled on Te Hāwere-a-Maki, we found only a slight reduction in breeding success with nearby predator-free islands. However, chick growth and fledging rates were significantly higher under El Niño conditions occurring towards the end of our study, rather than La Niña conditions at the start of our study. Our regular handling of chicks for monitoring had no discernible impact compared to a set of control chicks. The combined impacts of annual variation in predation and climate mean the Grey-faced Petrel colony on Te Hāwere-a-Maki maintains a constant population size of around 100 burrows.

Accurate prediction of EI Nino-southern oscillation (ENSO) is of great significance to seasonal climate forecast. Recently, a convolutional neural network (CNN) has shown an optimal skill for ENSO prediction. However, it is difficult for the convolutional kernel to capture long-range precursors of ENSO due to its build-in local property. The transformer model has long been used in natural language processing (NLP) for its ability to focus on global features. Here, we introduce it to the ENSO research community and propose the ENSO transformer (ENSOTR). We show that using the ENSOTR model, the monthly average Nino3.4 index can be skillfully predicted up to one and a half years ahead. The model can also predict strong EI Nino cases more than a year ahead, such as 1997-1998. Experimental results show that our model achieves better skill than CNN for ENSO prediction.

A majority of El Nino/Southern Oscillation (ENSO) events are preceded by the North Pacific Meridional Mode (NPMM), a dominant coupled ocean–atmospheric mode of variability. How the precursory NPMM forcing on ENSO responds to greenhouse warming remains unknown. Here, using climate model ensembles under high-emissions warming scenarios, we find an enhanced future impact on ENSO by the NPMM. This is manifested by increased sensitivity of boreal-winter equatorial Pacific winds and sea surface temperature (SST) anomalies to the NPMM three seasons before. The enhanced NPMM impact translates into an increased frequency of NPMM that leads to an extreme El Nino or La Nina. Under greenhouse warming, higher background SSTs cause a nonlinear evaporation–SST relationship to more effectively induce surface wind anomalies in the equatorial western Pacific, conducive to ENSO development. Thus, NPMM contributes to an increased frequency of future extreme ENSO events and becomes a more influential precursor for their predictability. The North Pacific Meridional Mode (NPMM) can trigger El Nino/Southern Oscillation (ENSO) events. Climate simulations suggest that with warming ocean temperatures, the NPMM’s impact on future ENSO strengthens, contributing to increased frequency of future extreme ENSO events and their predictability.

Geological evidence from the last millennium indicates that multidecadal megadroughts may have occurred simultaneously in California and Patagonia at least once. However, it is unclear whether or not megadroughts were common in South America, whether or not simultaneous megadroughts in North and South America occurred repeatedly, and what would cause their simultaneous occurrence. Here we use a data-assimilation-based global hydroclimate reconstruction, which integrates palaeoclimate records with constraints from a climate model, to show that there were about a dozen megadroughts in the South American Southwest over the last millennium. Using dynamical variables from the hydroclimate reconstruction, we show that these megadroughts were driven by the El Nino/Southern Oscillation (ENSO). We also find that North American Southwest and South American Southwest megadroughts have occurred simultaneously more often than expected by chance. These coincident megadroughts were driven by an increased frequency of cold ENSO states relative to the last millennium-average frequency. Our results establish the substantial risk that exists for ENSO-driven, coupled megadroughts in two critical agricultural regions. Cold ENSO states can lead to the simultaneous occurrence of megadroughts in southwestern North and South America, according to a hydroclimate reconstruction of the last thousand years assimilating palaeoclimate records with climate model constraints.

One of the greatest challenges for the sustainability of soybean production in Brazil is the control of Asian soybean rust (ASR). This study aimed to assess the climate risk of ASR occurrence throughout the period recommended for sowing in four locations of Rio Grande do Sul, considering different soybean relative maturity groups and the phases of the El Nino–Southern Oscillation phenomenon. The soybean development cycle and the climate favorability for ASR occurrence were simulated for the recommended sowing dates in the period from 1961 to 2020 in four locations of Rio Grande do Sul. Early cultivars, sown at the beginning of the period recommended by Agricultural Zoning of Climate Risk, usually exhibit less favorable climate conditions for ASR occurrence and less interannual variability in their cycle. The effect of the El Nino/Southern Oscillation phenomenon varies across the studied locations, with the prevalence of more favorable conditions for ASR occurrence during El Nino years. However, neutral years show greater interannual variability for the risk of ASR occurrence.

The aim of this study was to assess the effects of El Nino and the Southern Oscillation (ENSO) on the temperature in southern Vietnam (TSV) and to establish a new ENSO index for the study area (named southern Vietnam Enso Index, VEI). Data used in this study included TSV, sea surface temperature (SST) in Nino regions, sea level pressure (SLP) at Tahiti and Darwin, and ENSO indices. The results showed that, among all ENSO indices, the oceanic Nino Index (ONI) and Japan Meteorological Agency ENSO index (JEI) gave a better correlation with TSV, but their correlation coefficients (R) were relatively low. That may suggest that these indices could be used with low efficiency for climate monitoring and prediction. The VEI was built based on the pair of SST in Nino 3.4 and Nino.West, which gained a higher correlation coefficient with the temperature in southern Vietnam in comparison with other ENSO indices. The lag time between VEI and TSV was about 5 months, which was one month longer than the one between ONI and TSV. Moreover, analyzing the temperature difference between the warm and cold phases also indicated that using VEI led to a higher contrast than using ONI. In brief, the newly established VEI could be more suitable for the study area.

There is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

Severe thunderstorms can have devastating impacts. Concurrently high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are known to be conducive to severe weather, so high values of PROD = (CAPE)1/2 × SRH have been used to indicate high risk of severe thunderstorms. We consider the extreme values of these three variables for a large area of the contiguous United States over the period 1979–2015 and use extreme-value theory and a multiple testing procedure to show that there is a significant time trend in the extremes for PROD maxima in April, May, and August, for CAPE maxima in April, May, and June, and for maxima of SRH in April and May. These observed increases in CAPE are also relevant for rainfall extremes and are expected in a warmer climate but have not previously been reported. Moreover, we show that El Niño–Southern Oscillation explains variation in the extremes of PROD and SRH in February. Our results suggest that the risk from severe thunderstorms in April and May is increasing in parts of the United States where it was already high and that the risk from storms in February is increased over the main part of the region during La Niña years.

Between 1883 and 1898, 24 intense tropical cyclones and extra tropical cyclones directly impacted on the southern Queensland and northern New South Wales coasts, with at least 200 fatalities in what was then a sparsely populated area. These events also caused record floods and rainfall, for example Brisbane City experienced its two largest ever floods over this period and Brisbane City set a 24-h rainfall record that still stands today. Additionally, a 24-h rainfall total of 907 mm occurred in a tributary of the upper Brisbane River resulting in a 15-m wall of water advancing down the river. Recent studies have shown that this part of Australia incurs the largest weather-related insurance losses. A major focus in this study is the seas these storms generated, leading to the loss of many marine craft and changes these waves brought to coastal areas. As a famous example of coastal erosion near Brisbane, the continual impacts from large waves caused a channel to form through Stradbroke Island to the open ocean forming two separate islands. Details of how this channel formed are described in relation to the storms. A climatology study of 239 Australian east coast storms that caused severe ocean damage between Brisbane and the Victorian border over the period between 1876 and February 2020 showed that 153 events occurred with a positive Southern Oscillation Index (SOI) trend and 86 events with a negative trend. The most active years were 1893 and 1967, both during positive SOI periods and both dominated by tropical cyclone activity. The 1893 events caused unparalleled floods and strongly contributed to the Jumpinpin breakthrough on Stradbroke Island, and the 1967 event was associated with historical Gold Coast beach erosion causing 9 billion normalised Australian dollars of insurance losses. The study also showed how direct tropical cyclone impacts in the study area decreased markedly following the June 1976 climate shift.

Isoprene is the dominant non-methane organic compound emitted to the atmosphere1-3. It drives ozone and aerosol production, modulates atmospheric oxidation and interacts with the global nitrogen cycle4-8. Isoprene emissions are highly uncertain1,9, as is the nonlinear chemistry coupling isoprene and the hydroxyl radical, OH-its primary sink10-13. Here we present global isoprene measurements taken from space using the Cross-track Infrared Sounder. Together with observations of formaldehyde, an isoprene oxidation product, these measurements provide constraints on isoprene emissions and atmospheric oxidation. We find that the isoprene-formaldehyde relationships measured from space are broadly consistent with the current understanding of isoprene-OH chemistry, with no indication of missing OH recycling at low nitrogen oxide concentrations. We analyse these datasets over four global isoprene hotspots in relation to model predictions, and present a quantification of isoprene emissions based directly on satellite measurements of isoprene itself. A major discrepancy emerges over Amazonia, where current underestimates of natural nitrogen oxide emissions bias modelled OH and hence isoprene. Over southern Africa, we find that a prominent isoprene hotspot is missing from bottom-up predictions. A multi-year analysis sheds light on interannual isoprene variability, and suggests the influence of the El Nino/Southern Oscillation.

Global warming is changing the global wave climate, making waves stronger. In this study, we find that the wave climate in the South China Sea (SCS) undergoes an intensifying trend under global warming background, by examining the ERA-5 wave reanalysis data over 1979–2018. Results show a significant increase in most of the SCS, of 0.2% per year in significant wave height (SWH) and 0.15% per year in wave period (WP), but there is no significant change in surface wind speed (WS), which may correspond to the weakening of the Asian monsoon. The increase of the swell is the main characteristic of wave climate change in the SCS. We further examined the possible factors to cause the increasing of SWH, and found that the frequency of gale events occurring in the SCS and its adjacent regions increased over study period. The more frequent gale events can explain the significant increasing tendency of the SWH in the SCS by causing the occurrence of swell. The increasing appearance of gale events is closely related to the intensification of El Nino/Southern Oscillation (ENSO). ENSO activities also can regulate the interannual variability of wave climate in the SCS through the surface wind. Therefore, ENSO activities play an important role in the change of wave climate in the SCS.

This work aims to investigate the effect of solar-geomagnetic activities on atmospheric circulation and to examine their influences on global surface temperature (GST). Used data are the sunspot number (Rz) as a solar activity index, geomagnetic activity index (aa), the North Atlantic Oscillation index (NAO), and GST. We have performed an extensive analysis by using the wavelet power spectra (WPS) and global wavelet spectra (GWS). Results from WPS showed that both NAO and GST exhibited periodicities of ~ 22 years and 11 years, indicating the imprint of solar activity on both parameters. Additionally, the WPS of NAO exhibited three dominant modes; firstly, periodicity of 2 to 4 years appeared in the time intervals: (1954–1967), (1987–1997), and (2007–2015), possibly related to El-Nino Southern Oscillation. Secondly, sporadic oscillation of 1 to 2.5 years observed during the whole period, which corresponding to quasi-biennial oscillation. Finally, oscillatory modes with high power on the band 7 to 8.5 years are observed on NAO spectrum: 7.6 years for the period (1872–1892) and 8.3 years for 1996–2005. This oscillatory mode with enhanced power in the 8.3 years has been detected significantly on the GWS of GST, indicating the influence of climatic pattern on GST. Our results showed that the solar-geomagnetic activities influence partially and indirectly on GST through atmospheric circulation pattern.

This paper examines the relationship between El Nino/Southern Oscillation (ENSO) and rainfall patterns in Nigeria. Annual rainfall totals, growing season rainfall totals and annual raindays of 27 Nigerian meteorological stations with varying lengths of records from 1903 to 2012 were collected from the Nigerian Meteorological Agency (NIMET). Monthly Sea Surface Temperatures (SSTs) anomalies data over Atlantic and Pacific Oceans and Southern Oscillation Index (SOI) were obtained from Climatic Prediction Centre (CPC). Kendall tau statistics and Step-Wise Multiple Regression model were used for data analyses. Results from this study showed that annual rainfall totals, growing season rainfall and annual raindays series exhibited a significant downward trend at most of the stations over the period of the study. It was observed that annual rainfall pattern changed from a positive pattern within 1931- 1960 period to a negative pattern within 1961-1990 period and then, to a positive pattern within 1991-2012 period. It was concluded that he alternating wet and dry patterns in inter-annual rainfall fluctuations and by extension, the droughts and floods over Nigeria within the study period, were caused by sea surface temperature anomalies over the Atlantic and Pacific Oceans. The paper therefore concludes that SSTs should be integrated in the seasonal rainfall prediction models in Nigeria for an improved forecast. Oladejo, K. M. | Department of Geography, Usmanu Danfodiyo University, Sokoto, Nigeria

The Indian Ocean Dipole (IOD) affects climate and rainfall across the world, and most severely in nations surrounding the Indian Ocean1–4. The frequency and intensity of positive IOD events increased during the twentieth century5 and may continue to intensify in a warming world6. However, confidence in predictions of future IOD change is limited by known biases in IOD models7 and the lack of information on natural IOD variability before anthropogenic climate change. Here we use precisely dated and highly resolved coral records from the eastern equatorial Indian Ocean, where the signature of IOD variability is strong and unambiguous, to produce a semi-continuous reconstruction of IOD variability that covers five centuries of the last millennium. Our reconstruction demonstrates that extreme positive IOD events were rare before 1960. However, the most extreme event on record (1997) is not unprecedented, because at least one event that was approximately 27 to 42 per cent larger occurred naturally during the seventeenth century. We further show that a persistent, tight coupling existed between the variability of the IOD and the El Nino/Southern Oscillation during the last millennium. Indo-Pacific coupling was characterized by weak interannual variability before approximately 1590, which probably altered teleconnection patterns, and by anomalously strong variability during the seventeenth century, which was associated with societal upheaval in tropical Asia. A tendency towards clustering of positive IOD events is evident in our reconstruction, which—together with the identification of extreme IOD variability and persistent tropical Indo-Pacific climate coupling—may have implications for improving seasonal and decadal predictions and managing the climate risks of future IOD variability. Coral records indicate that the variability of the Indian Ocean Dipole over the last millennium is strongly coupled to variability in the El Nino/Southern Oscillation and that recent extremes are unusual but not unprecedented.

The intraseasonal timescale is attractive in Central Africa (CA) where socio-economic activities are highly based on rainfall. The parameterization of intraseasonal oscillations (ISO) then remains a great challenge for the improvement of sub-seasonal to seasonal (S2S) prediction in this region. In this paper, we applied wavelet analysis on the 2.5° × 2.5° daily Outgoing Longwave Radiation (OLR, used here as rainfall proxy) to study the variations in the intensity of the 30 - 60-day intraseasonal rainfall oscillations over Central Africa within the last three decades (1980-2009). Results showed that the mean ISO intensity (ISOI) strongly fluctuates from day to another. The plots of monthly mean ISOIs revealed that the ISO activity is highly seasonal with above-normal ISO intensity during December-May and below-normal activity during June-November. The analysis of yearly mean ISOI showed that the ISOI exhibits strong interannual variations with the years of very low ISOIs such as 1982, 1994, 2001, 2007, 2009, 2015 and the years of very high ISOIs such as 1981, 1985, 1986, 989/1990, 1997, 2003, 2005. The regression analysis between ISOI and El Ni&#241o Southern Oscillation (ENSO) indices showed that even though the relationship between ISO and ENSO is nonlinear, warm ENSO (El Ni&#241o) events tend to reduce the ISOIs while cold ENSO (La Ni&#241a) events tend to increase it.

Analysis of the monthly average temperature data of the Barents Sea at various depths for the period 1948-2016 showed its growth, which accelerated significantly since the mid-1980s. Against the background of this growth, interannual variability was found over periods of 2 to 7 years and about 10 years. It is shown that periods of this variability can be associated, respectively, with El Nino - Southern Oscillation and the North Atlantic Oscillation. It has been hypothesized that the Global Atmospheric Oscillation may be the synchronizing mechanism of the interannual variability of the tropics of the Pacific Ocean, the North Atlantic and the Barents Sea. Interdecadal changes with a period of about 15 years were also found, which are most likely related to surface temperature anomalies carried by the North Atlantic Current.

The article examines the nature and the possibility of predicting the onset and strength of the El Nino climatic phenomenon. The analysis of the internal structure of the surface temperature of the ocean and air, pressure, amount of precipitation in the region of the tropical Pacific Ocean during the onset and absence of the El Nino (La Nina) phenomenon is carried out, according to the interactive system Giovanni, the spatial and temporal variability of these characteristics is considered. The results obtained do not contradict theoretical hypotheses.

The hydroclimate of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly the phase of the El Nino/Southern Oscillation (ENSO), via teleconnections, wh...

Understanding teleconnections of a region's climate can be beneficial to seasonal outlooks and hydro-climate services. This study aims at analyzing the teleconnections of seasonal rainfall over Bangladesh with selected climate indices, including El Niño/Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO) indices. Rainfall data spanning from 1965–2017 in the seven hydrological regions are used to derive three seasonal rains, namely the pre-monsoon (March–May), monsoon (June–September), and post-monsoon (October and November) rains, for correlation- and wavelet coherence (WC)-based teleconnection analyses. Among the three seasonal rains, the post-monsoon rain shows the negative correlations, strongest with the IOD and ENSO indices. Correlations between the pre-monsoon/monsoon rain and climate indices are subject to notable spatial and temporal variations. For instance, correlations between the pre-monsoon (monsoon) rain in the South Central (South West) region and the IOD (ENSO) index shift from negative to positive after the 1980s, whereas the comprehensive negative correlations of the post-monsoon rain with the IOD and ENSO indices further enhanced from the early to recent epochs. WC analysis not only corroborates the findings of correlation analysis at shorter time scales (e.g., 1–4 years), but also reveals significant coherence at longer time scales (e.g., 8–16 years). We find that the pre-monsoon and monsoon rains experience the phase change in WC from shorter to longer scales. In contrast, the post-monsoon rain shows the consistent anti-phase WC, more dominant at the longer time scale. Both correlation and WC analyses indicate that the association patterns of the PDO mimic those of ENSO. Lastly, the analysis results of the AMO suggest quite distinct and significant association between Bangladesh's rainfall and the Atlantic Ocean.

Variations in the El Nino/Southern Oscillation (ENSO) are associated with a wide array of regional climate extremes and ecosystem impacts1. Robust, long-lead forecasts would therefore be valuable for managing policy responses. But despite decades of effort, forecasting ENSO events at lead times of more than one year remains problematic2. Here we show that a statistical forecast model employing a deep-learning approach produces skilful ENSO forecasts for lead times of up to one and a half years. To circumvent the limited amount of observation data, we use transfer learning to train a convolutional neural network (CNN) first on historical simulations3 and subsequently on reanalysis from 1871 to 1973. During the validation period from 1984 to 2017, the all-season correlation skill of the Nino3.4 index of the CNN model is much higher than those of current state-of-the-art dynamical forecast systems. The CNN model is also better at predicting the detailed zonal distribution of sea surface temperatures, overcoming a weakness of dynamical forecast models. A heat map analysis indicates that the CNN model predicts ENSO events using physically reasonable precursors. The CNN model is thus a powerful tool for both the prediction of ENSO events and for the analysis of their associated complex mechanisms.

Motivated by the Millennium Drought and the current drought over much of southern and eastern Australia, this detailed statistical study compares trends in annual wet season precipitation and temperature between a coastal site (Newcastle) and an inland site (Scone). Bootstrap permutation tests reveal Scone precipitation has decreased significantly over the past 40 years (p-value=0.070) whereas Newcastle has recorded little to no change (p-value=0.800). Mean maximum and minimum temperatures for Newcastle have increased over the past 40 years (p-values of 0.002 and 0.015, respectively) while the mean maximum temperature for Scone has increased (p-value = 0.058) and the mean minimum temperature has remained stable. This suggests mean temperatures during the wet season for both locations are increasing. Considering these trends along with those for precipitation, water resources in the Hunter region will be increasingly strained as a result of increased evaporation with either similar or less precipitation falling in the region. Wavelet analysis reveals that both sites have similar power spectra for precipitation and mean maximum temperature with a statistically significant signal in the two to seven year period, typically indicative of the El-Nino Southern Oscillation climate driver. The El-Nino Southern Oscillation also drives the Newcastle mean minimum temperature, whereas the Scone power spectra has no indication of a definitive driver for mean minimum temperature. References R. A., R. L. Kitching, F. Chiew, L. Hughes, P. C. D. Newton, S. S. Schuster, A. Tait, and P. Whetton. Climate change 2014: Impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution of Working Group II to the Fifth Assessment of the Intergovernmental Panel on Climate Change. Technical report, Intergovernmental Panel on Climate Change, 2014. URL https://www.ipcc.ch/report/ar5/wg2/. Bureau of Meteorology. Climate Glossary-Drought. URL http://www.bom.gov.au/climate/glossary/drought.shtml. K. M. Lau and H. Weng. Climate signal detection using wavelet transform: How to make a time series sing. B. Am. Meteorol. Soc., 76:23912402, 1995. doi:10.1175/1520-0477(1995)0762391:CSDUWT>2.0.CO;2. M. B. Richman and L. M. Leslie. Uniqueness and causes of the California drought. Procedia Comput. Sci., 61:428435, 2015. doi:10.1016/j.procs.2015.09.181. M. B. Richman and L. M. Leslie. The 20152017 Cape Town drought: Attribution and prediction using machine learning. Procedia Comput. Sci., 140:248257, 2018. doi:10.1016/j.procs.2018.10.323.

Changes in terrestrial water storage anomalies (TWSA) are not only influenced by local climate conditions but also by teleconnection factors. To date, how teleconnection factors including sunspot activities could affect TWSA has been under-examined. In this study, we investigate the TWSA dynamics in the Yunnan Province (YP), China, and assess their relationships with teleconnection factors at multiple timescales. Results show that: (1) GRACE data is able to reflect TWSA dynamics in the study region, as demonstrated by its high correlations with soil moisture, precipitation, and groundwater anomalies; (2) GRACE-based TWSA shows a downward trend of varying degrees at the monthly, seasonal, annual and multi-year scales, with obvious periodic changes of 11 and around 60 months; (3) precipitation magnitude and its distribution characteristics in humid areas are the main driving factors of TWSA, and teleconnection factors have stronger association with precipitation-concentration degree (PCD) than precipitation magnitude; (4) the 2009 extreme drought has caused a sharp decrease in TWSA, and the correlations between TWSA with Arctic Oscillation (AO) and El-Nino Southern Oscillation (ENSO) were 0.88 (a = 0.01) and −0.58 (a = 0.01). This study sheds new insights into how teleconnection factors could TWSA dynamics in a changing environment.

El Niño Southern Oscillation (ENSO) merupakan fenomena interaksi antara laut dan atmosfer di Samudera Pasifik yang menyebabkan beda tekanan antara keduanya sehingga terjadi aliran angin zonal dan meridional. ENSO menyebabkan anomali iklim di Indonesia, seperti perubahan arah dan kecepatan angin. Tujuan penelitiannya adalah untuk mengetahui kondisi angin zonal dan meridional di lapisan 850 mb saat ENSO serta dampaknya di Jawa bagian Utara. Data yang digunakan adalah data bulanan vektor angin, arah dan kecepatan angin zonal-meridional Januari 1950-September 2016 serta Ocean Niño Index. Metode penelitiannya adalah membandingkan angin zonal dan meridional saat ENSO dengan Netral serta menganalisis dampak ENSO untuk wilayah Jawa. Hasil penelitiannya adalah saat El Niño kecepatan angin timuran lebih kuat dibanding netralnya dan sebaliknya untuk angin baratan. Kecepatan angin selatan lebih kuat dibanding netralnya dan sebaliknya untuk angin utara. Pada saat La Niña, kecepatan angin timuran lebih lemah dibanding netralnya dan sebaliknya untuk angin baratan. Kecepatan angin selatan dan utara lebih lemah dibanding netralnya. Pada lapisan 850 mb kecepatan angin saat El Niño 2-6 m/s, La Niña 0-3 m/s, dan Netral 0-4 m/s. Pada Juni-Agustus pengaruh El Niño tidak terlihat, tetapi pada September-November dapat terlihat. Pada September-November pengaruh La Niña tidak terlihat karena angin baratan lebih kuat.

We present a study of changes in winter precipitation over a region in tropical northeast Africa during 1951–2015. A persistent drying trend is present in this region in addition to interannual variability. We present evidence that the changes in precipitation are primarily influenced by a strengthening of Azores high (AH) pressure. The correlation of AH pressure to changes in precipitation in tropical northeast Africa is statistically more significant than correlations between precipitation and the Arctic Oscillation (AO), the Southern Oscillation (SO), or the North Atlantic Oscillation (NAO). It is also shown that the AH pressure in winter has steadily increased in recent decades which explains the drying trend over tropical northeast Africa over the same period. The AH represents the subsiding branch of Hadley circulation over the north Atlantic sector, i.e., increasing pressure of the AH is evidence of intensification of Hadley circulation in the north Atlantic region since the 1950s.

Ethiopia is a rain fed agriculture country, which is subjected to high climate variability in space and time, leading to hydrological extremes causing loss of life and property more frequently. Droughts are more common and sometime floods are experienced in various parts of the country. Being a tropical country, the inter-annual climate variability in Ethiopia is dominated by ENSO (ElNino and Southern Oscillation).In this study, an attempt has been made to determine the occurrence of droughts and floods on monthly basis, by calculating the monthly SPI (Standardized Precipitation Index) using the available rainfall data during (1975-2005) at selected 26 stations that spread across the country. Based on the monthly SPI values computed, the droughts and floods of different intensities; extreme, severe and dry have been determined for all stations. The frequencies of the droughts and floods on monthly scale during the two rainy seasons, Belg (Feb-May) and Kiremt (Jun-Sep) seasons have been determined. For instance, during Belg season, there were 11 extreme (SPI < −2.0) droughts at Nazreth, 10 severe (SPI between −1.99 and −1.50) droughts at Diredawa and 14 moderate (SPI between −1.49 and −1.00) droughts at Kulumsa. Total number of droughts of all intensities over the study period is also highest (22) at Kulumsa and lowest (8) at Mekelle. Moreover, at Kulumsa both the numbers of droughts (22) and floods (22) during Belg are more, which shows that the rainfall variability is the highest at this station.The association of the hydrological extremes during the two rainy seasons, belg and kiremt with the ENSO phases has also been examined, which forms a basis for the prediction of the occurrence of droughts (dry conditions) and floods (wet conditions) at individual stations using ENSO phases.

Precipitation is one of the most important meteorological variables in climatic studies in the different regions of Brazil. Such importance is due to the consequences of what it can cause, when in excess or in deficiency for the productive sectors of the society. The objective of this study is to study the behavior of the pluviometric regime in the Piranhas- Acu river basin, located between the states of Paraiba and Rio Grande do Norte, between 1970 and 2015, and to analyze a rainfall quality in the rainy season of Some years dry and humid without identification intention a possible influence of the El Nino- Southern Oscillation (ENSO) in these years. As a main result, the pluviometric regime was characterized by a total annual average value of 247 mm, with a certain trend of increasing annual totals in recent years. In relation to the dry and humid years, it was observed that two years (1980 and 1984) presented conditions of neutrality in the Pacific Ocean, but rainfall in the rainy season were different: rainy and dry, respectively. This is because the dipole of the Atlantic Ocean Surface Temperature (SST) was favorable / unfavorable (negative / positive) to the rainfall, contributing / impairing rainfall quality in the FMA quarter of the region.

The El Nino Southern Oscillation (ENSO) is a major source of interannual climate variability. ENSO life cycles and the associated teleconnections evolve over multiple years at a global scale. This analysis is the first attempt to characterize the structure of the risk posed by trans-Pacific ENSO teleconnections to crop production in the greater Pacific Basin region. In this analysis we identify the large-scale atmospheric dynamics of ENSO teleconnections that affect heat and moisture stress during the growing seasons of maize, wheat and soy. We propose a coherent framework for understanding how trans-Pacific ENSO teleconnections pose a correlated risk to crop yields in major agricultural belts of the Americas, Australia and China over the course of an ENSO life cycle by using observations and a multi-model ensemble of climate anomalies during crop flowering seasons. Trans-Pacific ENSO teleconnections are often (but not always) offsetting between major producing regions in the Americas and those in northern China or Australia. El Ninos tend to create good maize and soybean growing conditions in the US and southeast South America, but poor growing conditions in northern China, southern Mexico and the Cerrado in Brazil. The opposite is true during La Nina. Wheat growing conditions in southeast South America generally have the opposite sign of those in Australia. Furthermore, multi-year La Ninas can force multi-year growing season anomalies in Argentina and Australia. Most ENSO teleconnections relevant for crop flowering seasons are the result of a single trans-Pacific circulation anomaly that develops in boreal summer and persists through the following spring. During the late summer and early fall of a developing ENSO event, the tropical Pacific forces an atmospheric anomaly in the northern midlatitudes that spans the Pacific from northern China to North America and in the southern midlatitudes from Australia to southeast South America. This anomaly directly links the soybean and maize growing seasons of the US, Mexico and China and the wheat growing seasons of Argentina, southern Brazil and Australia. The ENSO event peaks in boreal winter, when the atmospheric circulation anomalies intensify and affect maize and soybeans in southeast South America. As the event decays, the ENSO-induced circulation anomalies persist through the wheat flowering seasons in China and the US.

The variability in rainfall amounts in India draws much attention because it strongly influences the country’s ecological and social systems. Indian rainfall is associated with climate factors, including El Niño/Southern Oscillation and the Indian Ocean Dipole. Here we identified the Southern Annular Mode (SAM), the primary pattern of climate variability in the Southern Hemisphere, as the ultimate forcing leading to decadal changes in Indian rainfall. Through statistical analyses using observational data covering the period from 1979 to 2015, we show an increase in the decadal rainfall amount in the early 1990s over the Indian region. Examining atmospheric environmental conditions, we demonstrate that conditions have become more favorable over the past few decades. Specifically, during the positive SAM phase since the early 1990s, changes in the atmospheric fields have evoked anomalous vertical motion over the continent and the Indian Ocean, enhancing the southerly cross-equatorial flow by increased land–sea thermal contrast, thereby increasing decadal rainfall in the region.

The Indian summer monsoon (ISM) plays a crucial role in the well-being of billion Indians. This study discusses teleconnection between ISM with two dominant tropical sea surface temperature modes, namely, the El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Results are analyzed for observation and CMIP5 simulations in both historical and future scenarios. ENSO and IOD exert an offsetting impact on ISM. Due to an overly strong control by ENSO, the majority of CMIP5 models simulate an unrealistic IOD and ISM rainfall correlation, that might contribute to major uncertainties in ISM simulations in both historical as well as in future projections. For ENSO, the further focus was on the East Pacific type or Canonical ENSO and the Central Pacific type or ENSO Modoki, and their regional teleconnection was explored. Regions of Central North East India suggest strong teleconnection in models that matches with observation, though for ENSO Modoki case that completely disappears in the future. In terms of mechanism, tropic and mid-latitude connection, the influence of regional Hadley circulation, and the role of the Sun were addressed. Finally, a hypothesized mechanism was proposed for disruption of ISM–ENSO teleconnection in the latter two decades of the last century.

The El Nino/Southern Oscillation (ENSO) is one of the dominant modes of climate variations with widespread global impacts. The ENSO research has come a long way from its early days in the 1980s when the event of 1982 was not even recognized until its late developments. Since then, rapid progresses are made in the monitoring, data analyses, theory, and modeling to improve our understanding of the phenomenon and its prediction. Several mechanisms are proposed to explain the ENSO cycle and its seasonal to decadal variability. It appears that a combination of all those proposed mechanisms that could explain the reality and the nonlinearity inherent in the system is affected by nonlinear interactions among several processes not only in the tropical Pacific but also in the neighboring basins. This creates a challenge for developing skillful predictions of the phenomenon at long lead times. Nevertheless, the present generations of climate models are able to predict it at least a couple of seasons ahead. Some of the models, like the Scale Interaction Experiment-Frontier Research Center for Global change Version 1 model, are able to predict it even 15–18 months ahead. The changes in the mean state owing to global warming have brought changes in the ENSO behavior. More numbers of ENSO Modoki events are seen in recent decades. Also, a change in the tropical Pacific Walker circulation aided by the warming in the Indian and Atlantic Oceans has helped in developing a La Nina-like state since 2000. How the ENSO will behave in a changed climate remains quite uncertain owing to lack of long observations and uncertainties in model-based projections.

Atmosphere and oceans are the major components of the Earth’s climate system and play important roles in determining the intra-seasonal to inter-decadal climate variations discussed in this book. This introductory chapter broadly discusses the internal physical and dynamical processes in both systems in addition to the air–sea interactions that form the basis for basin-scale climate variations such as the El Nino/Southern Oscillation and the Indian Ocean Dipole discussed in the subsequent chapters. The variations in coastal processes are also important for the regional marine ecosystems and regional climate variations. These are also briefly introduced here and covered in some of the chapters of this book.

El Niño–Southern Oscillation (ENSO) teleconnections have been recognized as possible negative influences on crop yields in the United States during the summer growing season, especially in a developing La Niña summer. This study examines the physical processes of the ENSO summer teleconnections and remote impacts on the United States during a multiyear La Niña life cycle. Since 1950, a developing La Niña summer is either when an El Niño is transitioning to a La Niña or when a La Niña is persisting. Due to the distinct prior ENSO conditions, the oceanic and atmospheric characteristics in the tropics are dissimilar in these two different La Niña summers, leading to different teleconnection patterns. During the transitioning summer, the decaying El Niño and the developing La Niña induce suppressed deep convection over both the subtropical western Pacific (WP) and the tropical central Pacific (CP). Both of these two suppressed convection regions induce Rossby wave propagation extending toward North America, resulting in a statistically significant anomalous anticyclone over northeastern North America and, therefore, a robust warming signal over the Midwest. In contrast, during the persisting summer, only one suppressed convection region is present over the tropical CP induced by the La Niña SST forcing, resulting in a weak and insignificant extratropical teleconnection. Experiments from a stationary wave model confirm that the suppressed convection over the subtropical WP during the transitioning summer not only contributes substantially to the robust warming over the Midwest but also causes the teleconnections to be different from those in the persisting summer.

Previous chapters discuss methods with no particular predictive power. This chapter describes further advanced linear methods that are more related to prediction. Three related methods, involving extrapolation (or prediction) and interpolation, with climate applications are discussed in this chapter.

Climate models disagree on how the year-to-year variability of the El Nino/Southern Oscillation will change in a warmer world. Using a high-resolution climate model with an improved tropical Pacific mean state, research now suggests that El Nino activity tends to get weaker under GHG-induced warming.

The El-Nino Southern Oscillation (ENSO) modulates the lightning flash rate (LFR) variability over India during pre-monsoon, monsoon, and post-monsoon seasons. The impact of ENSO phases on the LFR over the Indian subcontinent is studied using the data obtained from Optical Transient Detector and Lightning Imaging Sensors onboard the TRMM satellite. The study shows that irrespective of ENSO phases, the LFR is maximum over northeast India (NEI) in the pre-monsoon season, and the peak is shifted to the north of northwest India (NNWI) in the monsoon season. The LFR over Northeast India (NEI) and southern peninsular India (SPI) intensified (reduced) during the warm (cold) phase of ENSO in the pre-monsoon season. In the monsoon season, NEI (NNWI) is showing above normal LFR in the warm (cold) ENSO phase. It is fascinating that the three hotspots of LFR over the Indian land region became more prominent in the last decade of the monsoon season. A widespread increase of LFR is observed all over India during the warm phase of ENSO in the post-monsoon season. However, a marked increase in the LFR is confined mostly over the NNWI in the cold ENSO phase. The subtropical westerly jet stream is shifted south in association with the warm phase, and an increase in the geopotential height (GPH) is also noticed all over India in the same period. ENSO’s warm phase indirectly influences the LFR over India during the post-monsoon season by pushing the mean position of subtropical westerly towards south latitudes.

La reconstrucción de variables hidroclimáticas es importante para comprender el funcionamiento de las cuencas forestales y tomar decisiones sobre su manejo. En este trabajo se reconstruyó la precipitación y el caudal medio a partir de información de anillos de crecimiento de Pseudostuga menziesii en la cuenca del río Piaxtla. Con la información de siete series dendrocronologías, se construyó una sola cronología regional. Se probó la correlación de la cronología regional con eventos de fenómenos océano-atmósfera como El Niño Oscilación del Sur, Oscilación Decadal del Pacífico, Oscilación Multidecadal del Atlántico e Índices de la Severidad de Sequía de Palmer. Los resultados mostraron que fue posible la reconstrucción de la precipitación de noviembre-abril y el caudal medio noviembre-agosto a partir de la serie de madera temprana con ecuaciones verificadas y validadas: Precipitación = -271.538 + 447.764*(índice de madera temprana), (r = 0.85, n = 49, p < 0.0001) y caudal medio = 5.123 + 0.623*log10(índice de madera temprana), (r = 0.68, n = 46, p < 0.001). Excepto por la Oscilación Multidecadal del Atlántico, todos los fenómenos globales mostraron correlación significativa con la información de los anillos de crecimiento. Este estudio confirma que los bosques de P. menziesii de la Sierra Madre Occidental son altamente sensibles al clima, lo que se refleja en la anchura de anillos de crecimiento y a su vez en la variabilidad del caudal medio de la cuenca. Por lo anterior se debe aprovechar el potencial de este tipo de trabajos para prever los cambios en la disponibilidad de recursos hídricos, así como ampliar su uso en la valoración de servicios ambientales hidrológicos.

This study explores the spatiotemporal rainfall variability in the Northeast region of India combined with an analysis of the effects of temperature and natural climatic indices [El-Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO)] on rainfall. The multi-timescale features of rainfall time series for periods 1871–2016 were analysed based on the continuous wavelet transform method. Cross-wavelet and wavelet coherence explore cross-correlation between temperature, natural climatic indices, and rainfall during 1950–2016. Results of the continuous wavelet transform revealed a significant cycle of 12 months on a monthly scale and 2–8-year period on an annual and seasonal scale. The cross-wavelet and wavelet coherence results showed that temperature affects rainfall only on intra-annual (0.5–1 years) scale. ENSO affects rainfall on both intra-annual (0.5–1 years) and inter-annual (1–10 years) scale. PDO affects rainfall on both inter-annual (1–10 years) and decadal (10–21 years) scale. AMO affects rainfall only on the decadal (10–21 years) scale. The result that comes out from this study is useful for climate change assessment, agriculture, and water resources management points of view of the Northeast region of India.

The frequency and magnitude of extreme summer temperature events in the United States have increased in the past few decades. Long‐term exposure to extreme summer temperatures can be detrimental to human health, due to potential risks of dehydration and thermoregulation strains on the cardiovascular system, which may often lead to heat‐related mortality (HRM). The summer climate of the United States is influenced by variability in Atlantic and Pacific sea surface temperatures, driven in part by Atlantic Multidecadal Oscillation (AMO) and El‐Nino Southern Oscillation (ENSO), respectively. However, the influence of AMO and ENSO on HRM in the United States has not been investigated. Here the longest time series of HRM spanning the past five decades is analyzed in relation with AMO and ENSO. We find that HRM doubled in the early‐1990s, coinciding with the positive phase of the AMO. Furthermore, we note a positive association between the variability in HRM and summer temperatures across all regions of the United States, with the strongest association found over the Southern United States. Therefore, this research suggests that variability in Atlantic and Pacific sea surface temperatures has both a nationwide and regional impact on HRM in the United States. Hence, by understanding variability in sea surface temperatures, the future burden of heat‐attributed emergencies during extreme summer temperature events can be reduced not only for the United States, but also worldwide., Key Points U.S. heat‐related mortality is positively associated with rising summer temperatures, particularly in Southern regionsU.S. heat‐related mortality is influenced more by variability in Atlantic than Pacific sea surface temperaturesIn combination the variability of Atlantic Multidecadal Oscillation and El Niño/La Niña explains ~20% of variance on heat‐related mortality

This chapter places droughts in historic context. Since the beginning of history, periodic droughts have had large impacts on many societies. These impacts have been especially severe in agricultural civilizations that depend heavily on precipitation for bountiful harvests. Historically, these harvests provided the critical resources that enabled the advancement of ancient humanity, allowing our ancestors to build cities, pursue trades, and develop sophisticated religious and cultural systems. Droughts have long played a major disruptive role in history, threatening the stability of human society. Here, we briefly review the relationship between civilizations and drought, stressing the link between agriculture and drought impacts. We then introduce the topic of modern drought prediction, highlighting the seminal contributions of Sir Gilbert Walker, and describing climate mechanisms associated with the Southern Oscillation and the Indo-Pacific Warm Pool. To conclude, we will provide a summary description of the phases of early warning.

According to long-term hydrometeorological data obtained at the Black Sea Hydrophysical Proving Ground (BSHPG) located on the Southern Coast of Crimea, the analysis of annual, monthly and daily average anomalies of surface air temperature for the period 2012–2016 is performed. The correlations of the of the surface air temperature anomalies with the North Atlantic Oscillation (NAO) and Southern Oscillation (SOI) indices are considered, and an increase in the absolute value of air temperature anomalies in the summer period has been revealed. The negative air temperature anomalies during the winter period, their connection with the regional factor of climate variability (Bora) and atmospheric processes in the European region are considered. A general increase in surface air temperature over South Coast of Crimea during the study period is observed.

A historical rainfall index, relevant to the grazing industries of Queensland, Australia, is described. We refer to our index as the Queensland grazing lands rainfall index (QGLRI), which is a long-term (1890/91–present) time series of austral summer (November–March) rainfall, spatially averaged over a region we define as the Queensland grazing lands region. We argue that our QGLRI better represents historical summer rainfall variability faced by the majority of the grazing industry in Queensland than does area-averaged statewide rainfall. The geographical boundaries of our region were chosen to 1) better represent the spatial patterns of land use, settlement, and livestock densities and 2) coincide with spatial patterns of airmass dominance. The selected region covers 59% of Queensland’s mainland area but carries more than 80% of the state’s livestock. The region’s boundaries also closely match the mean summer location of the boundaries of the “tropical maritime Pacific” air mass. The selected 5-month season (November–March) was chosen based on summer rainfall dominance, seasonal climatic effects restricting pasture and animal growth, and pasture management implications such as burning and the risk of overgrazing. We find that this season also corresponds to the timing of tropical maritime airmass dominance. The remaining regions of Queensland, far-northern and far-western Queensland, also correspond to well-defined dominant air masses, with properties that are markedly different from those of the tropical maritime Pacific air mass. We demonstrate that the rainfall regime in far-northern Queensland makes a strong contribution to statewide totals, resulting in statewide summer rainfall having lower variability than our QGLRI.

The dominant modes of the Asian summer monsoon (ASM) rainfall variability, as well as their seasonal predictive skill and predictability, are investigated using two sets of seasonal hindcasts made with the NCEP Climate Forecast System (CFSv2): one from the NCEP CFS Reanalysis and Reforecast Project (CFS_RR) and the other using a Multi-ocean Analyses Ensemble initialization scheme (CFS_MAE). The 1st and 2nd empirical orthogonal function (EOF) modes of the observed ASM rainfall anomalies correspond respectively to the contemporaneous and delayed responses to El Nino and the Southern Oscillation (ENSO) in its developing and decaying years. In general, CFSv2 is capable of skillfully predicting these two dominant ASM modes on the seasonal time scale up to 5 months in advance. Moreover, the predictive skill of the ASM rainfall in CFS_MAE is much higher with respect to the delayed ENSO mode than the contemporaneous one. The predicted principal component of the former maintains high correlation skill and small ensemble spread about two seasons ahead while the latter is significantly degraded in both measures after one season. A maximized signal-to-noise EOF analysis further shows that the delayed ASM response to ENSO is also the most predictable pattern at long leads in CFS_RR. The improved predictive skill of the ASM rainfall following ENSO events originates from the enhanced predictability associated with the active air-sea feedback in the Indo-northwestern Pacific domain from the ENSO peak to the ENSO demise phase, which are well captured in the CFSv2 hindcasts.

Multidecadal hydroclimate variability has been expressed as “megadroughts” (dry periods more severe and prolonged than observed over the twentieth century) and corresponding “megapluvial” wet periods in many regions around the world. The risk of such events is strongly affected by modes of coupled atmosphere–ocean variability and by external impacts on climate. Accurately assessing the mechanisms for these interactions is difficult, since it requires large ensembles of millennial simulations as well as long proxy time series. Here, the Community Earth System Model (CESM) Last Millennium Ensemble is used to examine statistical associations among megaevents, coupled climate modes, and forcing from major volcanic eruptions. El Niño–Southern Oscillation (ENSO) strongly affects hydroclimate extremes: larger ENSO amplitude reduces megadrought risk and persistence in the southwestern United States, the Sahel, monsoon Asia, and Australia, with corresponding increases in Mexico and the Amazon. The Atlantic multidecadal oscillation (AMO) also alters megadrought risk, primarily in the Caribbean and the Amazon. Volcanic influences are felt primarily through enhancing AMO amplitude, as well as alterations in the structure of both ENSO and AMO teleconnections, which lead to differing manifestations of megadrought. These results indicate that characterizing hydroclimate variability requires an improved understanding of both volcanic climate impacts and variations in ENSO/AMO teleconnections.

Satellite and ground-based observations are used to explore the composite oceanic–atmospheric link known as the El Nino/La Nina Southern Oscillation (ENSO) phenomenon, which is closely associated w...

Intraseasonal tropical variability has important implications for the mid- and high-latitude atmosphere, and in recent studies has been shown to modulate a number of weather processes in the Northern Hemisphere, such as snow depth, sea ice concentration, precipitation, atmospheric rivers, and air temperature. In such studies, the extratropical atmosphere has tended to respond to the tropical convection of the leading mode of intraseasonal variability, the Madden–Julian oscillation (MJO), with a time lag of approximately 7 days. However, the time lag between the MJO and the Antarctic atmosphere has been found to vary between less than 7 and greater than 20 days. This study builds on previous work by further examining the time-lagged response of Southern Hemisphere tropospheric circulation to tropical MJO forcing, with specific focus on the latitude belt associated with the Antarctic Oscillation, during the months of June (austral winter) and December (austral summer) using NCEP–DOE Reanalysis 2 data for the years 1979–2016. Principal findings indicate that the time lag with the strongest height anomalies depends on both the location of the MJO convection (e.g., the MJO phase) and the season, and that the lagged height anomalies in the Antarctic atmosphere are fairly consistent across different vertical levels and latitudinal bands. In addition, certain MJO phases in December displayed lagged height anomalies indicative of blocking-type atmospheric patterns, with an approximate wavenumber of 4, whereas in June most phases were associated with more progressive height anomaly centers resembling a wavenumber-3-type pattern.

El Niño Southern Oscillation events (ENSO) and the subsequent opposite weather patterns in the following months and years (La Niña) have major climatic impacts, especially on oceanic habitats, affecting breeding success of both land and sea birds. We assessed corticosterone concentrations from blood samples during standardized protocols of capture, handling and restraint to simulate acute stress from 12 species of Galapagos Island birds during the ENSO year of 1998 and a La Niña year of 1999. Plasma levels of corticosterone were measured in samples collected at capture (to represent non-stressed baseline) and subsequently up to 1 h post-capture to give maximum corticosterone following acute stress, and total amount of corticosterone that the individual was exposed to during the test period (integrated corticosterone). Seabird species that feed largely offshore conformed to the brood value hypothesis whereas inshore feeding species showed less significant changes. Land birds mostly revealed no differences in the adrenocortical responses to acute stress from year to year with the exception of two small species (

The Central Pacific (CP) flavor of El Nino/Southern Oscillation (ENSO) may account for some of the Medieval Climate Anomaly (MCA) aridity in the highland Titicaca Basin of the South Central Andes observed by Arnold et al. (2021 in Quaternary Science Reviews). There is urgent need for a longer record of CP presence and frequency.