Understanding El Niño in Ocean–Atmosphere General Circulation Models: Progress and Challenges

Guilyardi, Éric; Wittenberg, Andrew T.; Fedorov, Alexey V.; Collins, Matthew; Wang, Chunzai; Capotondi, Antonietta; Oldenborgh, G. J. van; Stockdale, Tim

doi:10.1175/2008bams2387.1

Cited by 491 publications

(362 citation statements)

References 119 publications

(123 reference statements)

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“…These simulated patterns are especially sensitive to details of convective parametrizations, which are used to approximate the cumulative effects of small-scale convection using information at the scale of the model grid cell (Slingo et al, 1996;Lin et al, 2006;Chen et al, 2007;Guilyardi et al, 2009;Turner and Slingo, 2009). Recent advances in computer power are beginning to allow atmospheric simulations large enough to represent largescale tropical variability while explicitly simulating vertical motions associated with deep convection, thereby sidestepping the need to parametrize tropical rainfall.…”

Section: Introductionmentioning

confidence: 99%

Precipitation distributions for explicit versus parametrized convection in a large‐domain high‐resolution tropical case study

Holloway

Woolnough

Lister

2012

Quart J Royal Meteoro Soc

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Section: Introductionmentioning

confidence: 99%

Precipitation distributions for explicit versus parametrized convection in a large‐domain high‐resolution tropical case study

Holloway

Woolnough

Lister

2012

Quart J Royal Meteoro Soc

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“…Nevertheless, model simulations of ENSO remain very diverse (e.g. AchutaRao and Sperber 2006; Guilyardi et al 2009a), which contributes to large uncertainties in our ability to anticipate and explain potential changes in El Niño characteristics. In fact, differences between coupled models are usually larger than the changes projected by each model under global warming conditions (van Oldenborgh et al 2005;Guilyardi 2006Guilyardi , 2009aCollins et al 2010).…”

Section: Introductionmentioning

confidence: 99%

How well do coupled models replicate ocean energetics relevant to ENSO?

2010

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Accurate replication of the processes associated with the energetics of the tropical ocean is necessary if coupled GCMs are to simulate the physics of ENSO correctly, including the transfer of energy from the winds to the ocean thermocline and energy dissipation during the ENSO cycle. Here, we analyze ocean energetics in coupled GCMs in terms of two integral parameters describing net energy loss in the system using the approach recently proposed by Brown and Fedorov (J Clim 23:1563-1580, 2010a and Fedorov (J Clim 20:1108(J Clim 20: -1117(J Clim 20: , 2007. These parameters are (1) the efficiency c of the conversion of wind power into the buoyancy power that controls the rate of change of the available potential energy (APE) in the ocean and (2) the e-folding rate a that characterizes the damping of APE by turbulent diffusion and other processes. Estimating these two parameters for coupled models reveals potential deficiencies (and large differences) in how state-of-the-art coupled GCMs reproduce the ocean energetics as compared to ocean-only models and data assimilating models. The majority of the coupled models we analyzed show a lower efficiency (values of c in the range of 10-50% versus 50-60% for ocean-only simulations or reanalysis) and a relatively strong energy damping (values of a -1 in the range 0.4-1 years versus 0.9-1.2 years). These differences in the model energetics appear to reflect differences in the simulated thermal structure of the tropical ocean, the structure of ocean equatorial currents, and deficiencies in the way coupled models simulate ENSO.

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“…The impact of HS1 on interannual climate variability in the tropical Pacific, however, is poorly known, largely because of the low temporal resolution of available proxy records. However, a better knowledge of the glacial dynamics of the dominant mode of Pacific atmosphere-ocean variability on interannual timescales, the El Niño-Southern Oscillation (ENSO), is critical regarding its dramatic global climate and socioeconomic impacts and difficult to predict behaviour under future climate change 5,6 . Moreover, HS1 provides an opportunity to validate climate models under extreme boundary conditions of the past, which can help to constrain more reliable projections of future ENSO variability 5,6 .…”

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confidence: 99%

Pronounced interannual variability in tropical South Pacific temperatures during Heinrich Stadial 1

et al. 2012

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The early last glacial termination was characterized by intense North Atlantic cooling and weak overturning circulation. This interval between similar to 18,000 and 14,600 years ago, known as Heinrich Stadial 1, was accompanied by a disruption of global climate and has been suggested as a key factor for the termination. However, the response of interannual climate variability in the tropical Pacific (El Niño-Southern Oscillation) to Heinrich Stadial 1 is poorly understood. Here we use Sr/Ca in a fossil Tahiti coral to reconstruct tropical South Pacific sea surface temperature around 15,000 years ago at monthly resolution. Unlike today, interannual South Pacific sea surface temperature variability at typical El Niño-Southern Oscillation periods was pronounced at Tahiti. Our results indicate that the El Niño-Southern Oscillation was active during Heinrich Stadial 1, consistent with climate model simulations of enhanced El Niño-Southern Oscillation variability at that time. Furthermore, a greater El Niño-Southern Oscillation influence in the South Pacific during Heinrich Stadial 1 is suggested, resulting from a southward expansion or shift of El Niño-Southern Oscillation sea surface temperature anomalies

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Understanding El Niño in Ocean–Atmosphere General Circulation Models: Progress and Challenges

Abstract: New community strategies to improve understanding and modeling of El Nino in state-ofthe-art climate models provide opportunities for more accurate tropical climate predictions.

Cited by 491 publications

References 119 publications

Precipitation distributions for explicit versus parametrized convection in a large‐domain high‐resolution tropical case study

Precipitation distributions for explicit versus parametrized convection in a large‐domain high‐resolution tropical case study

How well do coupled models replicate ocean energetics relevant to ENSO?

Pronounced interannual variability in tropical South Pacific temperatures during Heinrich Stadial 1

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