scholarly journals The Role of Stochastic Forcing in Modulating ENSO Predictability

2004 ◽  
Vol 17 (16) ◽  
pp. 3125-3140 ◽  
Author(s):  
Moritz Flügel ◽  
Ping Chang ◽  
Cécile Penland
2011 ◽  
Vol 38 (1-2) ◽  
pp. 87-107 ◽  
Author(s):  
Atul Kapur ◽  
Chidong Zhang ◽  
Javier Zavala-Garay ◽  
Harry H. Hendon

2020 ◽  
pp. 1-35
Author(s):  
Yishuai Jin ◽  
Zhengyu Liu

AbstractIn this paper, we investigate the role of El Niño-Southern Oscillation (ENSO) period in the spring persistence barrier (SPB) mainly using the neutral recharge oscillator (NRO) model both analytically and numerically. It is suggested that a shorter ENSO period strengthens the SPB. Moreover, in contrast to the strict phase locking of the SPB in the Langevin equation, the phase of a SPB is no longer locked exactly to a particular time of the calendar year in the NRO model. Instead, the phases of the SPB for different initial months shift earlier with the maximum persistence decline lag months. In particular, the phase of a SPB will be shifted from the early summer to early spring, corresponding to the initial months of the early half year and later half year. This feature demonstrates that for later half year, ENSO predictability decreases as the presence of ENSO period. For realistic parameters, the range of the phase change is modest, smaller than 2-3 months. Similar phase shift is also identified for the SPB in the damped ENSO regime, unstable ENSO regime and observation. Our theory provides a null hypothesis for the role of ENSO period in SPB.


2006 ◽  
Vol 33 (1) ◽  
pp. n/a-n/a ◽  
Author(s):  
G. A. Vecchi ◽  
A. T. Wittenberg ◽  
A. Rosati
Keyword(s):  
El Niño ◽  
El Nino ◽  

2021 ◽  
Author(s):  
Prasanth A Pillai ◽  
Ashish R Dhakate

Abstract The present study analyses the possible change in the seasonal prediction skill of El Nino Southern Oscillation (ENSO) in association with the reported climate modification in the tropical Pacific during the early 21st century. The hindcasts of nine models that participated in the National Multimodel Ensemble Project (NMME) are used for the analysis. Both the boreal summer (JJAS) and winter (DJF) seasons ENSO indices from 4 months and 1-month lead for the period 1981-2018/19 are studied. The analysis shows that all the models have reduced interannual variability as observations for both seasons. There is not much skill (both actual and potential) difference for DJF season for all the models for both the lead times. Summer skill loss for Feb IC is more for models such as CanSIPv2, CCSM3 and NEMO, while it is minimum for CCSM4. There is an increase of skill for Feb IC hindcasts for three GFDL models for JJAS season. Most of the models failed to simulate the ENSO events during the second period. The summer season ENSO pattern in the recent period are influenced by spring time north Atlantic SST anomalies. The models with maximum decrease of skill after 2000 fail to simulate the tropical Atlantic SST anomalies during the initialization months and also the summer season SST anomalies induced by these SST anomalies. The models with better or close to observed patterns with Atlantic SST induced ENSO patterns are only able to maintain the same skill as previous decades.


2018 ◽  
Vol 31 (22) ◽  
pp. 9125-9150 ◽  
Author(s):  
Erin E. Thomas ◽  
Daniel J. Vimont ◽  
Matthew Newman ◽  
Cécile Penland ◽  
Cristian Martínez-Villalobos

Abstract Numerous oceanic and atmospheric phenomena influence El Niño–Southern Oscillation (ENSO) variability, complicating both prediction and analysis of the mechanisms responsible for generating ENSO diversity. Predictability of ENSO events depends on the characteristics of both the forecast initial conditions and the stochastic forcing that occurs subsequent to forecast initialization. Within a linear inverse model framework, stochastic forcing reduces ENSO predictability when it excites unpredictable growth or interference after the forecast is initialized, but also enhances ENSO predictability when it excites optimal initial conditions that maximize deterministic ENSO growth. Linear inverse modeling (LIM) allows for straightforward separation between predictable signal and unpredictable noise and so can diagnose its own skill. While previous LIM studies of ENSO focused on deterministic dynamics, here we explore how noise forcing influences ENSO diversity and predictability. This study identifies stochastic forcing details potentially contributing to the development of central Pacific (CP) or eastern Pacific (EP) ENSO characteristics. The technique is then used to diagnose the relative roles of initial conditions and noise forcing throughout the evolution of several ENSO events. LIM results show varying roles of noise forcing for any given event, highlighting its utility in separating deterministic from noise-forced contributions to the evolution of individual ENSO events. For example, the strong 1982 event was considerably more influenced by noise forcing late in its evolution than the strong 1997 event, which was more predictable with long lead times due to its deterministic growth. Furthermore, the 2014 deterministic trajectory suggests that a strong event in 2014 was unlikely.


2008 ◽  
Vol 1146 (1) ◽  
pp. 60-86 ◽  
Author(s):  
M. N. Lorenzo ◽  
J. J. Taboada ◽  
I. Iglesias ◽  
I. Álvarez

2010 ◽  
Vol 23 (6) ◽  
pp. 1447-1455 ◽  
Author(s):  
Zhengyu Liu

Abstract The probabilistic modal response of vegetation to stochastic precipitation variability is studied in a conceptual climate–ecosystem model. It is found that vegetation can exhibit bimodality in a monostable climate–ecosystem under strong rainfall variability and with soil moisture memory comparable with that of the vegetation. The bimodality of vegetation is generated by a convolution of a nonlinear vegetation response and a colored stochastic noise. The nonlinear vegetation response is such that vegetation becomes insensitive to precipitation variability near either end state (green or desert), providing the potential for two preferred modes. The long memory of soil moisture allows the vegetation to respond to a slow stochastic forcing such that the vegetation tends to grow toward its equilibrium states. The implication of the noise-induced bimodality to abrupt changes in the climate–ecosystem is also discussed.


JAMA ◽  
1966 ◽  
Vol 195 (12) ◽  
pp. 1005-1009 ◽  
Author(s):  
D. J. Fernbach
Keyword(s):  

JAMA ◽  
1966 ◽  
Vol 195 (3) ◽  
pp. 167-172 ◽  
Author(s):  
T. E. Van Metre

Sign in / Sign up

Export Citation Format

Share Document