Characterisations of Different El Nino Types, their Physical Causes and Predictions
type: CreativeWork
description: 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 re…
abstract: 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 re…
author: Lai, Wang Chun
language: en
keywords: El Nino, Climate variability, ENSO
license: https://www.repository.cam.ac.uk/bitstreams/871a0d9d-9601-43eb-b158-f1c9e6f41f29/download
license: https://www.rioxx.net/licenses/all-rights-reserved/
date published: 2018-07-15
date modified: 2026-07-22T22:23:54Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.18822