scholarly journals Enhanced ENSO Prediction via Augmentation of Multimodel Ensembles with Initial Thermocline Perturbations

2020 ◽  
Vol 33 (6) ◽  
pp. 2281-2293 ◽  
Author(s):  
Terence J. O’Kane ◽  
Dougal T. Squire ◽  
Paul A. Sandery ◽  
Vassili Kitsios ◽  
Richard J. Matear ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Tropical Pacific ◽  
Sign Test ◽  
Lead Times ◽  
Multimodel Ensemble ◽  
Coupled Models ◽  
Enso Prediction ◽  
Boreal Spring ◽  
The North ◽  
Forecast Lead Time

AbstractRecent studies have shown that regardless of model configuration, skill in predicting El Niño–Southern Oscillation (ENSO), in terms of target month and forecast lead time, remains largely dependent on the temporal characteristics of the boreal spring predictability barrier. Continuing the 2019 study by O’Kane et al., we compare multiyear ensemble ENSO forecasts from the Climate Analysis Forecast Ensemble (CAFE) to ensemble forecasts from state-of-the-art dynamical coupled models in the North American Multimodel Ensemble (NMME) project. The CAFE initial perturbations are targeted such that they are specific to tropical Pacific thermocline variability. With respect to individual NMME forecasts and multimodel ensemble averages, the CAFE forecasts reveal improvements in skill when predicting ENSO at lead times greater than 6 months, in particular when predictability is most strongly limited by the boreal spring barrier. Initial forecast perturbations generated exclusively as disturbances in the equatorial Pacific thermocline are shown to improve the forecast skill at longer lead times in terms of anomaly correlation and the random walk sign test. Our results indicate that augmenting current initialization methods with initial perturbations targeting instabilities specific to the tropical Pacific thermocline may improve long-range ENSO prediction.

scholarly journals Effect of the air–sea coupled system change on the ENSO evolution from boreal spring

2021 ◽  
Author(s):  
Xiang-Hui Fang ◽  
Fei Zheng
Keyword(s):  
Regime Shift ◽  
Southern Oscillation ◽  
Coupled System ◽  
Tropical Pacific ◽  
Enso Prediction ◽  
Boreal Spring ◽  
Mature Phase ◽  
Spring Predictability Barrier ◽  
The Impact ◽  
The Tropical Pacific

AbstractRealistic simulation and accurate prediction of El Niño-Southern Oscillation (ENSO) is still a challenge. One fundamental obstacle is the so-called spring predictability barrier (SPB), which features a low predictive skill of the ENSO with prediction across boreal spring. Our observational analysis shows that the leading empirical orthogonal function mode of the seasonal Niño3.4 index evolution (i.e., from May to the following April) explains nearly 90% of its total variance, and the principle component is almost identical to the Niño3.4 index in the mature phase. This means a good ENSO prediction for a year ranging May-next April can be achieved if the Niño3.4 index in the mature phase is accurately obtained in advance. In this work, by extracting physically oriented variables in the spring, a linear regression approach that can reproduce the mature ENSO phases in observation is firstly proposed. Further investigation indicates that the specific equation, however, is significantly modulated by an interdecadal regime shift in the air–sea coupled system in the tropical Pacific. During 1980–1999, ocean adjustment and vertical processes were dominant, and the recharge oscillator theory was effective to capture the ENSO evolutions. While, during 2000–2018, zonal advection and thermodynamics became important, and successful prediction essentially relies on the wind stress information and their controlled processes, both zonally and meridionally. These results imply that accounting for the interdecadal regime shift of the tropical Pacific coupled system and the dominant processes in spring in modulating the ENSO evolution could reduce the impact of SPB and improve ENSO prediction.

scholarly journals An Analysis of the Temporal Evolution of ENSO Prediction Skill in the Context of the Equatorial Pacific Ocean Observing System

2015 ◽  
Vol 143 (8) ◽  
pp. 3204-3213 ◽  
Author(s):  
Arun Kumar ◽  
Mingyue Chen ◽  
Yan Xue ◽  
David Behringer
Keyword(s):  
Pacific Ocean ◽  
Time Evolution ◽  
Tropical Pacific ◽  
Sea Surface ◽  
Prediction Skill ◽  
Steady Increase ◽  
Coupled Models ◽  
Enso Prediction ◽  
Subsurface Ocean ◽  
Ocean Observations

Abstract Subsurface ocean observations in the equatorial tropical Pacific Ocean dramatically increased after the 1990s because of the completion of the TAO moored array and a steady increase in Argo floats. In this analysis the question explored is whether a steady increase in ocean observations can be discerned in improvements in skill of predicting sea surface temperature (SST) variability associated with El Niño–Southern Oscillation (ENSO)? The analysis is based on the time evolution of skill of sea surface temperatures in the equatorial tropical Pacific since 1982 based on a seasonal prediction system. It is found that for forecasts up to a 6-month lead time, a clear fingerprint of increases in subsurface ocean observations is not readily apparent in the time evolution of prediction skill that is dominated much more by the signal-to-noise consideration of SSTs to be predicted. Finding no clear relationship between an increase in ocean observations and prediction skill of SSTs, various possibilities for why it may be so are discussed. This discussion is to motivate further exploration on the question of the tropical Pacific observing system, its influence on the skill of ENSO prediction, and the capabilities of the current generation of coupled models and ocean data assimilation systems to take advantage of ocean observations.

scholarly journals Forecast Comparison Based on Random Walks

2016 ◽  
Vol 144 (2) ◽  
pp. 615-626 ◽  
Author(s):  
Timothy DelSole ◽  
Michael K. Tippett
Keyword(s):  
Random Walks ◽  
Serial Correlation ◽  
Model Development ◽  
Sign Test ◽  
Forecast Errors ◽  
Dynamical Models ◽  
Multimodel Ensemble ◽  
The North ◽  
Forecast Comparison ◽  
North American Multimodel Ensemble

Abstract This paper proposes a procedure based on random walks for testing and visualizing differences in forecast skill. The test is formally equivalent to the sign test and has numerous attractive statistical properties, including being independent of distributional assumptions about the forecast errors and being applicable to a wide class of measures of forecast quality. While the test is best suited for independent outcomes, it provides useful information even when serial correlation exists. The procedure is applied to deterministic ENSO forecasts from the North American Multimodel Ensemble and yields several revealing results, including 1) the Canadian models are the most skillful dynamical models, even when compared to the multimodel mean; 2) a regression model is significantly more skillful than all but one dynamical model (to which it is equally skillful); and 3) in some cases, there are significant differences in skill between ensemble members from the same model, potentially reflecting differences in initialization. The method requires only a few years of data to detect significant differences in the skill of models with known errors/biases, suggesting that the procedure may be useful for model development and monitoring of real-time forecasts.

scholarly journals Analysis of the Atlantic Meridional Mode Using Linear Inverse Modeling: Seasonality and Regional Influences

2012 ◽  
Vol 25 (4) ◽  
pp. 1194-1212 ◽  
Author(s):  
Daniel J. Vimont
Keyword(s):  
High Latitude ◽  
Inverse Modeling ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
Boreal Summer ◽  
Tropical Atlantic ◽  
Boreal Spring ◽  
Meridional Mode ◽  
Atlantic Meridional Mode ◽  
Sst Anomalies

Abstract Predictability and variability of the tropical Atlantic Meridional Mode (AMM) is investigated using linear inverse modeling (LIM). Analysis of the LIM using an “energy” norm identifies two optimal structures that experience some transient growth, one related to El Niño–Southern Oscillation (ENSO) and the other to the Atlantic multidecadal oscillation (AMO)/AMM patterns. Analysis of the LIM using an AMM-norm identifies an “AMM optimal” with similar structure to the second energy optima (OPT2). Both the AMM-optimal and OPT2 exhibit two bands of SST anomalies in the mid- to high-latitude Atlantic. The AMM-optimal also contains some elements of the first energy optimal (ENSO), indicating that the LIM captures the well-known relationship between ENSO and the AMM. Seasonal correlations of LIM predictions with the observed AMM show enhanced AMM predictability during boreal spring and for long-lead (around 11–15 months) forecasts initialized around September. Regional LIMs were constructed to determine the influence of tropical Pacific and mid- to high-latitude Atlantic SST on the AMM. Analysis of the regional LIMs indicates that the tropical Pacific is responsible for the AMM predictability during boreal spring. Mid- to high-latitude SST anomalies contribute to boreal summer and fall AMM predictability, and are responsible for the enhanced predictability from September initial conditions. Analysis of the empirical normal modes of the full LIM confirms these physical relationships. Results indicate a potentially important role for mid- to high-latitude Atlantic SST anomalies in generating AMM (and tropical Atlantic SST) variations, though it is not clear whether those anomalies provide any societally useful predictive skill.

scholarly journals Enhanced interactions of Kuroshio Extension with tropical Pacific in a changing climate

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Youngji Joh ◽  
Emanuele Di Lorenzo ◽  
Leo Siqueira ◽  
Benjamin P. Kirtman
Keyword(s):  
Climate Model ◽  
Southern Oscillation ◽  
Kuroshio Extension ◽  
Reanalysis Data ◽  
Tropical Pacific ◽  
Decadal Time Scale ◽  
The North ◽  
Enso Teleconnections ◽  
Linear Inverse Model ◽  
Tropical Teleconnections

AbstractQuasi-decadal climate of the Kuroshio Extension (KE) is pivotal to understanding the North Pacific coupled ocean–atmosphere dynamics and their predictability. Recent observational studies suggest that extratropical-tropical coupling between the KE and the central tropical Pacific El Niño Southern Oscillation (CP-ENSO) leads to the observed preferred decadal time-scale of Pacific climate variability. By combining reanalysis data with numerical simulations from a high-resolution climate model and a linear inverse model (LIM), we confirm that KE and CP-ENSO dynamics are linked through extratropical-tropical teleconnections. Specifically, the atmospheric response to the KE excites Meridional Modes that energize the CP-ENSO (extratropicstropics), and in turn, CP-ENSO teleconnections energize the extratropical atmospheric forcing of the KE (tropicsextratropics). However, both observations and the model show that the KE/CP-ENSO coupling is non-stationary and has intensified in recent decades after the mid-1980. Given the short length of the observational and climate model record, it is difficult to attribute this shift to anthropogenic forcing. However, using a large-ensemble of the LIM we show that the intensification in the KE/CP-ENSO coupling after the mid-1980 is significant and linked to changes in the KE atmospheric downstream response, which exhibit a stronger imprint on the subtropical winds that excite the Pacific Meridional modes and CP-ENSO.

scholarly journals Oscillatory Climate Modes in the Indian Monsoon, North Atlantic, and Tropical Pacific

2013 ◽  
Vol 26 (23) ◽  
pp. 9528-9544 ◽  
Author(s):  
Yizhak Feliks ◽  
Andreas Groth ◽  
Andrew W. Robertson ◽  
Michael Ghil
Keyword(s):  
North Atlantic ◽  
Indian Monsoon ◽  
Southern Oscillation ◽  
Singular Spectrum Analysis ◽  
Time Lag ◽  
Tropical Pacific ◽  
Climate Modes ◽  
The North ◽  
The North Atlantic ◽  
The Tropical Pacific

This paper explores the three-way interactions between the Indian monsoon, the North Atlantic, and the tropical Pacific. Four climate records were analyzed: the monsoon rainfall in two Indian regions, the Southern Oscillation index for the tropical Pacific, and the NAO index for the North Atlantic. The individual records exhibit highly significant oscillatory modes with spectral peaks at 7–8 yr and in the quasi-biennial and quasi-quadrennial bands. The interactions between the three regions were investigated in the light of the synchronization theory of chaotic oscillators. The theory was applied here by combining multichannel singular-spectrum analysis (M-SSA) with a recently introduced varimax rotation of the M-SSA eigenvectors. A key result is that the 7–8-yr and 2.7-yr oscillatory modes in all three regions are synchronized, at least in part. The energy-ratio analysis, as well as time-lag results, suggests that the NAO plays a leading role in the 7–8-yr mode. It was found therewith that the South Asian monsoon is not slaved to forcing from the equatorial Pacific, although it does interact strongly with it. The time-lag analysis pinpointed this to be the case in particular for the quasi-biennial oscillatory modes. Overall, these results confirm that the approach of synchronized oscillators, combined with varimax-rotated M-SSA, is a powerful tool in studying teleconnections between regional climate modes and that it helps identify the mechanisms that operate in various frequency bands. This approach should be readily applicable to ocean modes of variability and to the problems of air–sea interaction as well.

scholarly journals Are Simulated Megadroughts in the North American Southwest Forced?*

2014 ◽  
Vol 28 (1) ◽  
pp. 124-142 ◽  
Author(s):  
Sloan Coats ◽  
Jason E. Smerdon ◽  
Benjamin I. Cook ◽  
Richard Seager
Keyword(s):  
North American ◽  
General Circulation ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
American Southwest ◽  
Climate System Model ◽  
Multidecadal Variability ◽  
The North ◽  
North American Southwest ◽  
The Tropical Pacific

Abstract Multidecadal drought periods in the North American Southwest (25°–42.5°N, 125°–105°W), so-called megadroughts, are a prominent feature of the paleoclimate record over the last millennium (LM). Six forced transient simulations of the LM along with corresponding historical (1850–2005) and 500-yr preindustrial control runs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are analyzed to determine if atmosphere–ocean general circulation models (AOGCMs) are able to simulate droughts that are similar in persistence and severity to the megadroughts in the proxy-derived North American Drought Atlas. Megadroughts are found in each of the AOGCM simulations of the LM, although there are intermodel differences in the number, persistence, and severity of these features. Despite these differences, a common feature of the simulated megadroughts is that they are not forced by changes in the exogenous forcing conditions. Furthermore, only the Community Climate System Model (CCSM), version 4, simulation contains megadroughts that are consistently forced by cooler conditions in the tropical Pacific Ocean. These La Niña–like mean states are not accompanied by changes to the interannual variability of the El Niño–Southern Oscillation system and result from internal multidecadal variability of the tropical Pacific mean state, of which the CCSM has the largest magnitude of the analyzed simulations. Critically, the CCSM is also found to have a realistic teleconnection between the tropical Pacific and North America that is stationary on multidecadal time scales. Generally, models with some combination of a realistic and stationary teleconnection and large multidecadal variability in the tropical Pacific are found to have the highest incidence of megadroughts driven by the tropical Pacific boundary conditions.

scholarly journals Evaluation of ENSO Prediction Skill Changes since 2000 Based on Multimodel Hindcasts

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 365
Author(s):  
Shouwen Zhang ◽  
Hui Wang ◽  
Hua Jiang ◽  
Wentao Ma
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Water Volume ◽  
Lead Times ◽  
The North ◽  
Spring Predictability Barrier ◽  
Sea Surface Temperature Anomalies ◽  
Warm Water Volume

In this study, forecast skill over four different periods of global climate change (1982–1999, 1984–1996, 2000–2018, and 2000–2014) is examined using the hindcasts of five models in the North American Multimodel Ensemble. The deterministic evaluation shows that the forecasting skills of the Niño3.4 and Niño3 indexes are much lower during 2000–2018 than during 1982–1999, indicating that the previously reported decline in forecasting skill continues through 2018. The decreases in skill are most significant for the target months from May to August, especially for medium to long lead times, showing that the forecasts suffer more from the effect of the spring predictability barrier (SPB) post-2000. Relationships between the extratropical Pacific signal and the El Niño-Southern Oscillation (ENSO) weakened after 2000, contributing to a reduction in inherent predictability and skills of ENSO, which may be connected with the forecasting skills decline for medium to long lead times. It is a great challenge to predict ENSO using the memory of the local ocean itself because of the weakening intensity of the warm water volume (WWV) and its relationship with ENSO. These changes lead to a significant decrease in the autocorrelation coefficient of the persistence forecast for short to medium lead months. Moreover, for both the Niño3.4 and Niño3 indexes, after 2000, the models tend to further underestimate the sea surface temperature anomalies (SSTAs) in the El Niño developing year but overestimate them in the decaying year. For the probabilistic forecast, the skills post-2000 are also generally lower than pre-2000 in the tropical Pacific, and in particular, they decayed east of 120° W after 2000. Thus, the advantages of different methods, such as dynamic modeling, statistical methods, and machine learning methods, should be integrated to obtain the best applicability to ENSO forecasts and to deal with the current low forecasting skill phenomenon.

scholarly journals The impact of El Niño-Southern Oscillation on the Canadian climate

2006 ◽  
Vol 6 ◽  
pp. 149-153 ◽  
Author(s):  
A. Shabbar
Keyword(s):  
North American ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Cold Season ◽  
Tropical Pacific ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The North ◽  
The Impact

Abstract. The quasi-periodic El Niño -Southern Oscillation (ENSO) phenomenon in the tropical Pacific Ocean produces the largest interannual variation in the cold season climate of Canada. The diabatic heating in the eastern tropical Pacific, associated with the warm phase of ENSO (El Niño), triggers Rossby waves which in turn gives rise to the Pacific-North American teleconnection (PNA) over the North American sector. The strongest cell of the PNA pattern lies over western Canada. In most of southern Canada, mean winter temperature distribution is shifted towards warmer values, and precipitation is below normal. The presence of El Niño provides the best opportunity to make skillful long-range winter forecast for Canada. A strong El Niño event, while bringing respite from the otherwise cold winter in Canada, can be expected to cost the Canadian economy two to five billion dollars.

scholarly journals Multimodel Ensemble Sea Level Forecasts for Tropical Pacific Islands

2017 ◽  
Vol 56 (4) ◽  
pp. 849-862 ◽  
Author(s):  
Matthew J. Widlansky ◽  
John J. Marra ◽  
Md. Rashed Chowdhury ◽  
Scott A. Stephens ◽  
Elaine R. Miles ◽  
...  
Keyword(s):  
Sea Level ◽  
El Niño ◽  
Pacific Islands ◽  
El Nino ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
Model Errors ◽  
Multimodel Ensemble ◽  
Sea Level Anomaly ◽  
Mean Sea Level

AbstractSea level anomaly extremes impact tropical Pacific Ocean islands, often with too little warning to mitigate risks. With El Niño, such as the strong 2015/16 event, comes weaker trade winds and mean sea level drops exceeding 30 cm in the western Pacific that expose shallow-water ecosystems at low tides. Nearly opposite climate conditions accompany La Niña events, which cause sea level high stands (10–20 cm) and result in more frequent tide- and storm-related inundations that threaten coastlines. In the past, these effects have been exacerbated by decadal sea level variability, as well as continuing global sea level rise. Climate models, which are increasingly better able to simulate past and future evolutions of phenomena responsible for these extremes (i.e., El Niño–Southern Oscillation, Pacific decadal oscillation, and greenhouse warming), are also able to describe, or even directly simulate, associated sea level fluctuations. By compiling monthly sea level anomaly predictions from multiple statistical and dynamical (coupled ocean–atmosphere) models, which are typically skillful out to at least six months in the tropical Pacific, improved future outlooks are achieved. From this multimodel ensemble comes forecasts that are less prone to individual model errors and also uncertainty measurements achieved by comparing retrospective forecasts with the observed sea level. This framework delivers online a new real-time forecasting product of monthly mean sea level anomalies and will provide to the Pacific island community information that can be used to reduce impacts associated with sea level extremes.

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