Predictability and prediction of persistent cool states of the Tropical Pacific Ocean

Ramesh, N.; Seager, Richard; Lee, Dong Eun

doi:10.1007/s00382-016-3446-3

Cited by 8 publications

(16 citation statements)

References 48 publications

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“…To what degree the Walker circulation is enhanced or impeded by moist convection is therefore a matter of balance between the sensitivity of convection to low-to midtropospheric moisture convergence (CISK) and the effect of latent heating on the circulation, versus the sensitivity of convection to vertically integrated stability and related moist convective damping (convective quasi equilibrium). If the low-level moisture convergence mechanism is dominant, then the feedback will inevitably be positive, such as for instance in the simple Zebiak-Cane model (Cane and Zebiak 1985;Zebiak 1986;Ramesh et al 2017;Seager et al 2019). If the quasi-equilibrium mechanism prevails, a negative feedback on the circulation from the overall stabilizing effect of convection and related changes in clear-sky radiative cooling rates is possible.…”

Section: A Historical Perspectivementioning

confidence: 99%

The Interaction between Moist Convection and the Atmospheric Circulation in the Tropics

Tomassini

2020

Bulletin of the American Meteorological Society

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Theories of the interaction between moist convection and the atmospheric circulation in the tropics are reviewed. Two main schools of thought are highlighted: (i) one which emphasizes the lower-level control of convection through moisture convergence and variations in convective inhibition, and (ii) one which sees convection as an adjustment process in reaction to larger-scale instabilities, referred to as convective quasi-equilibrium theory. Conceptually the two views consider moist convection to have fundamentally different roles in the tropical circulation. In one case the presence of low-level inhibition and the conditional nature of the atmospheric instability allows for convective vertical motion and latent heating to drive and reinforce synoptic-scale disturbances and overturning circulations; in the other case, because low-level inhibition is not acknowledged to be a widespread controlling barrier, convection is believed to balance and dampen vertical instabilities at the rate they are created by larger-scale processes over the vertical extent of the atmosphere. More recently, investigations of the moisture dynamics surrounding organized convective structures have led to an emerging consensus on the theory of convection-circulation coupling in the tropics which acknowledges the important role of lower- to mid-tropospheric moisture variations, and the significance of moist convection and convective clouds for initiating and establishing circulations. However, the implementation of these new insights in numerical models lags behind. This is exemplified by the apparent inadequacy of climate models to correctly represent decadal variability in the tropical Pacific, a fact that potentially has implications for the confidence in climate change projections based on such models.

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Section: A Historical Perspectivementioning

confidence: 99%

The Interaction between Moist Convection and the Atmospheric Circulation in the Tropics

Tomassini

2020

Bulletin of the American Meteorological Society

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“…We represent the climate state variable x(t) through an index for ENSO, which has been shown to impact flood risk around the world (Ropelewski & Halpert, 1987;Ward et al, 2014) and has characteristic variability on time scales of 3 to 7 years (Sarachik & Cane, 2009) as well as a "staircase" of lower-frequency scales (Jin et al, 1994). We model ENSO variability by taking a 20,000-year integration of the Cane-Zebiak model (Zebiak & Cane, 1987) to produce a monthly NINO3 index (Ramesh et al, 2016). To create an annual time series, we average the October-December values of the NINO3 index for each year.…”

Section: Sampling Climate Riskmentioning

confidence: 99%

“…anonymous reviewer for comments which greatly improved this manuscript. The authors thank Nandini Ramesh of Columbia University for providing the synthetic NINO3 index from a 100,000-year run of the Cane-Zebiak model as described in Ramesh et al (2016). The authors thank John High of the U.S. Army Corps of Engineers for providing the naturalized daily streamflows at the Folsom Dam.…”

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confidence: 99%

Robust Adaptation to Multiscale Climate Variability

2019

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The assessment and implementation of structural or financial instruments for climate risk mitigation requires projections of future climate risk over the operational life of each proposed instrument. A point often neglected in the climate adaptation literature is that the physical sources of predictability differ between projects with long and short planning periods: While historical and paleo climate records emphasize low-frequency modes of variability, anthropogenic climate change is expected to alter their occurrence at longer time scales. In this paper we present a set of stylized experiments to assess the uncertainties and biases involved in estimating future climate risk over a finite future period, given a limited observational record. These experiments consider both quasi-periodic and secular change for the underlying risk, as well as statistical models for estimating this risk from an N-year historical record. The uncertainty of IPCC-like future scenarios is considered through an equivalent sample size N. The relative importance of estimating short-or long-term risk depends on the investment life M. Shorter design lives are preferred for situations where interannual to decadal variability can be successfully identified and predicted, highlighting the importance of sequential investment strategies for adaptation. Key Points: • Quasi-periodic and secular climate signals, with different identifiability and predictability, control future uncertainty and risk • Adaptation strategies must consider how uncertainties in risk projections influence success of decision pathways • Stylized experiments reveal how bias and variance of climate risk projections influence risk mitigation over a finite planning period Supporting Information: • Supporting Information S1

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“…In addition to these factors, the low signal-to-noise ratio in boreal spring (Sarachik and Cane 2010), the influence of high-frequency atmospheric winds (Fedorov et al 2003(Fedorov et al , 2015, as well as the natural irregularity of the climate system (Wittenberg 2009) all limit the long-term dynamical and statistical forecasting of the phenomenon. Some of the classical ENSO theories view the oscillation as self-sustained (Cane et al 1990;Jin et al 1994;Jin 1997), and support the claim that it is potentially predictable several years in advance (Cane et al 1986;Goswami and Shukla 1991;Latif et al 1999;Chen and Cane 2008;Wittenberg et al 2014;Gonzalez and Goddard 2016;Luo et al 2016;DiNezio et al 2017;Astudillo et al 2017), but only a handful of studies document such long-lead retrospective forecasts of past events (Latif et al 1999;Chen et al 2004;Luo et al 2008;Izumo et al 2010;Ludescher et al 2013Ludescher et al , 2014Petrova et al 2017;Gonzalez and Goddard 2016;Ramesh et al 2016;Luo et al 2017), and most of them use dynamical models. Statistical models are assumed to be less skilful at long lead times, and comparable in performance to dynamical schemes at shorter lead times of about half a year (Barnston 1994;Chen and Cane 2008).…”

Section: Introductionmentioning

confidence: 99%

Multiyear Statistical Prediction of ENSO Enhanced by the Tropical Pacific Observing System

et al. 2020

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The theoretical predictability limit of El Niño–Southern Oscillation has been shown to be on the order of years, but long-lead predictions of El Niño (EN) and La Niña (LN) are still lacking. State-of-the-art forecasting schemes traditionally do not predict beyond the spring barrier. Recent efforts have been dedicated to the improvement of dynamical models, while statistical schemes still need to take full advantage of the availability of ocean subsurface variables, provided regularly for the last few decades as a result of the Tropical Ocean–Global Atmosphere Program (TOGA). Here we use a number of predictor variables, including temperature at different depths and regions of the equatorial ocean, in a flexible statistical dynamic components model to make skillful long-lead retrospective predictions (hindcasts) of the Niño-3.4 index in the period 1970–2016. The model hindcasts the major EN episodes up to 2.5 years in advance, including the recent extreme 2015/16 EN. The analysis demonstrates that events are predicted more accurately after the completion of the observational array in the tropical Pacific in 1994, as a result of the improved data quality and coverage achieved by TOGA. Therefore, there is potential to issue long-lead predictions of this climatic phenomenon at a low computational cost.

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Predictability and prediction of persistent cool states of the Tropical Pacific Ocean

Cited by 8 publications

References 48 publications

The Interaction between Moist Convection and the Atmospheric Circulation in the Tropics

The Interaction between Moist Convection and the Atmospheric Circulation in the Tropics

Robust Adaptation to Multiscale Climate Variability

Multiyear Statistical Prediction of ENSO Enhanced by the Tropical Pacific Observing System

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