Documentation of a highly ENSO‐related sst region in the equatorial pacific: Research note

Bamston, Anthony G.; Chelliah, Muthuvel; Goldenberg, Stanley B.

doi:10.1080/07055900.1997.9649597

Cited by 385 publications

(277 citation statements)

References 27 publications

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“…The region in the east-central tropical Pacific whose areaaverage SST predictions are analyzed here is the Niño3.4 region (5°N-5°S, 120°-170°W), which has been shown to be closely related to the overall ENSO state (Barnston et al 1997). The Niño3.4 index has been used at some operational centers as a key oceanic component of the ENSO state (e.g., Kousky and Higgins 2007), although other centers use other SST indices more heavily (e.g., Japan Meteorological Agency uses Niño3) or a set of several indices together.…”

Section: Methodsmentioning

confidence: 99%

Deterministic skill of ENSO predictions from the North American Multimodel Ensemble

et al. 2017

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the presence of calibration errors in some of the models. In particular, the amplitudes of some model predictions are too high when predictability is limited by the northern spring ENSO predictability barrier and/or when the interannual variability of the SST is near its seasonal minimum. The skill of the NMME system is compared to that of the MME from the IRI/CPC ENSO prediction plume, both for a comparable hindcast period and also for a set of real-time predictions spanning 2002-2011. Comparisons are made both between the MME predictions of each model group, and between the average of the skills of the respective individual models in each group. Acknowledging a hindcast versus real-time inconcsistency in the 2002-2012 skill comparison, the skill of the NMME is slightly higher than that of the prediction plume models in all cases. This result reflects well on the NMME system, with its large total ensemble size and opportunity for possible complementary contributions to skill.Abstract Hindcasts and real-time predictions of the eastcentral tropical Pacific sea surface temperature (SST) from the North American Multimodel Ensemble (NMME) system are verified for 1982-2015. Skill is examined using two deterministic verification measures: mean squared error skill score (MSESS) and anomaly correlation. Verification of eight individual models shows somewhat differing skills among them, with some models consistently producing more successful predictions than others. The skill levels of MME predictions are approximately the same as the two best performing individual models, and sometimes exceed both of them. A decomposition of the MSESS indicates This paper is a contribution to the special collection on the North American Multi-Model Ensemble (NMME) seasonal prediction experiment. The special collection focuses on documenting the use of the NMME system database for research ranging from predictability studies, to multi-model prediction evaluation and diagnostics, to emerging applications of climate predictability for subseasonal to seasonal predictions

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Section: Methodsmentioning

confidence: 99%

Deterministic skill of ENSO predictions from the North American Multimodel Ensemble

et al. 2017

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“…The use of seasonal climate forecasts is promising given that Ecuador is located in a region of the world where seasonal forecasts show some skill (accuracy) because of the strong influence of ENSO events in the region. 55,56 Forecasting centers such as the ECMWF produce such forecasts with lead times up to 6 months. However, the greater the forecast lead time, the greater the uncertainty in the predictions of both the climate and the disease.…”

Section: Discussionmentioning

confidence: 99%

Climate and Non-Climate Drivers of Dengue Epidemics in Southern Coastal Ecuador

Stewart-Ibarra¹,

Lowe²

2013

The American Society of Tropical Medicine and Hygiene

141

162

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Abstract. We report a statistical mixed model for assessing the importance of climate and non-climate drivers of interannual variability in dengue fever in southern coastal Ecuador. Local climate data and Pacific sea surface temperatures (Oceanic Niñ o Index [ONI]) were used to predict dengue standardized morbidity ratios (SMRs;1995-2010. Unobserved confounding factors were accounted for using non-structured yearly random effects. We found that ONI, rainfall, and minimum temperature were positively associated with dengue, with more cases of dengue during El Niñ o events. We assessed the influence of non-climatic factors on dengue SMR using a subset of data (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and found that the percent of households with Aedes aegypti immatures was also a significant predictor. Our results indicate that monitoring the climate and non-climate drivers identified in this study could provide some predictive lead for forecasting dengue epidemics, showing the potential to develop a dengue early-warning system in this region.

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“…Ruling supreme until the 1980s, the Southern Oscillation Index (SOI) was defined by Troup (1965) as the normalized SLP difference between Tahiti and Darwin, and was extended several times by Jones and collaborators (Allan et al, 1991). Once the link between the SO and El Niño was established (Bjerknes, 1966(Bjerknes, , 1969, Rasmusson and Carpenter (1982) described so-called Niño regions (1, 2, 3, and 4) based on ship-tracks, but it was only just over a decade ago that Barnston et al (1997) defined the socalled Niño 3.4 SST region that maximizes the ENSO signal among SST-based indices, thus launching the most popular ENSO index of the last decade.…”

Section: Introductionmentioning

confidence: 99%

El Niño/Southern Oscillation behaviour since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext)

Wolter

Timlin

2011

Intl Journal of Climatology

971

696

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El Niño/Southern Oscillation (ENSO) remains the most important coupled ocean-atmosphere phenomenon to cause global climate variability on seasonal to interannual time scales. This paper addresses the need for a reliable ENSO index that allows for the historical definition of ENSO events in the instrumental record back to 1871. The Multivariate ENSO Index (MEI) was originally defined as the first seasonally varying principal component of six atmosphere-ocean (COADS) variable fields in the tropical Pacific basin. It provides for a more complete and flexible description of the ENSO phenomenon than single variable ENSO indices such as the SOI or Niño 3.4 SST. Here we describe our effort to boil the MEI concept down to its most essential components (based on SLP, SST) to enable historical analyses that more than double its period of record to 1871-2005. The new MEI.ext confirms that ENSO activity went through a lull in the earlyto mid-20th century, but was just about as prevalent one century ago as in recent decades. We diagnose strong relationships between peak amplitudes of ENSO events and their duration, as well as between their peak amplitudes and their spacing (periodicity). Our effort is designed to help with the assessment of ENSO conditions through as long a record as possible to be able to differentiate between 'natural' ENSO behaviour in all its rich facets, and the 'Brave New World' of this phenomenon under evolving GHG-related climate conditions. So far, none of the behaviour of recent ENSO events appears unprecedented, including duration, onset timing, and spacing in the last few decades compared to a full century before then.

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Documentation of a highly ENSO‐related sst region in the equatorial pacific: Research note

Cited by 385 publications

References 27 publications

Deterministic skill of ENSO predictions from the North American Multimodel Ensemble

Deterministic skill of ENSO predictions from the North American Multimodel Ensemble

Climate and Non-Climate Drivers of Dengue Epidemics in Southern Coastal Ecuador

El Niño/Southern Oscillation behaviour since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext)

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