scholarly journals Recalculation of error growth models' parameters for the ECMWF forecast system

2021 ◽  
Vol 14 (12) ◽  
pp. 7377-7389
Author(s):  
Hynek Bednář ◽  
Aleš Raidl ◽  
Jiří Mikšovský
Keyword(s):  
Lyapunov Exponent ◽  
Growth Models ◽  
Model Error ◽  
Largest Lyapunov Exponent ◽  
Error Growth ◽  
Forecast System ◽  
Limit Values ◽  
Limit Value ◽  
Forecasting System ◽  
The Largest Lyapunov Exponent

Abstract. This article provides a new estimate of error growth models' parameters approximating predictability curves and their differentials, calculated from data of the ECMWF forecast system over the 1986 to 2011 period. Estimates of the largest Lyapunov exponent are also provided, along with model error and the limit value of the predictability curve. The proposed correction is based on the ability of the Lorenz (2005) system to simulate the predictability curve of the ECMWF forecasting system and on comparing the parameters estimated for both these systems, as well as on comparison with the largest Lyapunov exponent (λ=0.35 d−1) and limit value of the predictability curve (E∞=8.2) of the Lorenz system. Parameters are calculated from the quadratic model with and without model error, as well as by the logarithmic, general, and hyperbolic tangent models. The average value of the largest Lyapunov exponent is estimated to be in the < 0.32; 0.41 > d−1 range for the ECMWF forecasting system; limit values of the predictability curves are estimated with lower theoretically derived values, and a new approach for the calculation of model error based on comparison of models is presented.

scholarly journals Recalculation of error growth models’ parameters for the ECMWF forecast system

2020 ◽  
Author(s):  
Hynek Bednář ◽  
Aleš Raidl ◽  
Jiří Mikšovský
Keyword(s):  
Lyapunov Exponent ◽  
Growth Models ◽  
Model Error ◽  
Largest Lyapunov Exponent ◽  
Error Growth ◽  
Forecast System ◽  
Limit Values ◽  
Limit Value ◽  
Forecasting System ◽  
The Largest Lyapunov Exponent

Abstract. This article provides a new estimate of error growth models’ parameters approximating predictability curves and their differentials, calculated from data of the ECMWF forecast system over the 1986 to 2011 period. Estimates of the largest Lyapunov exponent are also provided, along with model error and the limit value of the predictability curve. The proposed correction is based on the ability of the Lorenz's (2005) system to simulate predictability curve of the ECMWF forecasting system and on comparing the parameters estimated for both these systems, as well as on comparison with the largest Lyapunov exponent (λ = 0.35 day−1) and limit value of the predictability curve (E∞ = 8.2) of the Lorenz's system. Parameters are calculated from the Quadratic model with and without model error, as well as by the Logarithmic and General models and by the hyperbolic tangent model. The average value of the largest Lyapunov exponent is estimated to be in the  day−1 range for the ECMWF forecasting system, limit values of the predictability curves are estimated with lower theoretically derived values and new approach of calculation of model error based on comparison of models is presented.

scholarly journals The futility of long-term predictions in bipolar disorder: mood fluctuations are the result of deterministic chaotic processes

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Abigail Ortiz ◽  
Kamil Bradler ◽  
Maxine Mowete ◽  
Stephane MacLean ◽  
Julie Garnham ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Fractal Dimension ◽  
Lyapunov Exponent ◽  
Detrended Fluctuation Analysis ◽  
Largest Lyapunov Exponent ◽  
Fluctuation Analysis ◽  
Mood Regulation ◽  
The Largest Lyapunov Exponent ◽  
Depressive Episodes ◽  
Detrended Fluctuation

Abstract Background Understanding the underlying architecture of mood regulation in bipolar disorder (BD) is important, as we are starting to conceptualize BD as a more complex disorder than one of recurring manic or depressive episodes. Nonlinear techniques are employed to understand and model the behavior of complex systems. Our aim was to assess the underlying nonlinear properties that account for mood and energy fluctuations in patients with BD; and to compare whether these processes were different in healthy controls (HC) and unaffected first-degree relatives (FDR). We used three different nonlinear techniques: Lyapunov exponent, detrended fluctuation analysis and fractal dimension to assess the underlying behavior of mood and energy fluctuations in all groups; and subsequently to assess whether these arise from different processes in each of these groups. Results There was a positive, short-term autocorrelation for both mood and energy series in all three groups. In the mood series, the largest Lyapunov exponent was found in HC (1.84), compared to BD (1.63) and FDR (1.71) groups [F (2, 87) = 8.42, p < 0.005]. A post-hoc Tukey test showed that Lyapunov exponent in HC was significantly higher than both the BD (p = 0.003) and FDR groups (p = 0.03). Similarly, in the energy series, the largest Lyapunov exponent was found in HC (1.85), compared to BD (1.76) and FDR (1.67) [F (2, 87) = 11.02; p < 0.005]. There were no significant differences between groups for the detrended fluctuation analysis or fractal dimension. Conclusions The underlying nature of mood variability is in keeping with that of a chaotic system, which means that fluctuations are generated by deterministic nonlinear process(es) in HC, BD, and FDR. The value of this complex modeling lies in analyzing the nature of the processes involved in mood regulation. It also suggests that the window for episode prediction in BD will be inevitably short.

Estimation of the Largest Lyapunov Exponent of Discontinuous Systems Using Chaos Synchronization

1999 ◽  
Author(s):  
Andrzej Stefanski ◽  
Jerzy Wojewoda ◽  
Tomasz Kapitaniak ◽  
John Brindley
Keyword(s):  
Lyapunov Exponent ◽  
Mechanical System ◽  
Dry Friction ◽  
Chaos Synchronization ◽  
Largest Lyapunov Exponent ◽  
Discontinuous Systems ◽  
System A ◽  
The Largest Lyapunov Exponent

Abstract Properties of chaos synchronization have been used for estimation of the largest Lyapunov exponent of a discontinuous mechanical system. A method for such estimation is proposed and an example is shown, based on coupling of two identical systems with dry friction which is modelled according to the Popp-Stelter formula.

Automatic identification of eye movements using the largest lyapunov exponent

2018 ◽  
Vol 41 ◽  
pp. 10-20 ◽  
Author(s):  
Alexandra I. Korda ◽  
Pantelis A. Asvestas ◽  
George K. Matsopoulos ◽  
Errikos M. Ventouras ◽  
Nikolaos Smyrnis
Keyword(s):  
Eye Movements ◽  
Lyapunov Exponent ◽  
Largest Lyapunov Exponent ◽  
Automatic Identification ◽  
The Largest Lyapunov Exponent

Improvement the Largest Lyapunov Exponent for Measurement the Northeast Monsoon Prediction

2018 ◽  
Vol 879 ◽  
pp. 217-221
Author(s):  
Sunisa Saiuparad
Keyword(s):  
Lyapunov Exponent ◽  
Measurement Method ◽  
Limit Theorems ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Largest Lyapunov Exponent ◽  
Northeast Monsoon ◽  
Medium Range Weather Forecast ◽  
The Largest Lyapunov Exponent

Thailand is an agricultural country. So that, the water resources are important. The water management is very important for keep the water used in necessary time. The monsoon is causes a heavy rain. So that, the monsoon prediction by the global climate model is important. The accuracy of the forecasts by the predictability measurement method is very important. In this research, the northeast monsoon prediction in Thailand by the global climate model. The data from The Bjerknes Centre for Climate Research (BCCR), University of Bergen, Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) and the European Centre for Medium Range Weather Forecast (ECMWF) are used. The largest Lyapunov exponent (LLE) is the predictability measurement method for verify the efficiency of the global climate model and improvement the LLE by limit theorems. The result to show that the improvement the LLE by limit theorems can be measure the accuracy of the northeast monsoon prediction in Thailand by the global climate model are suitable.

Stochastic Stability of Gyroscopic Systems Under Bounded Noise Excitation

2018 ◽  
Vol 18 (02) ◽  
pp. 1850022 ◽  
Author(s):  
Jian Deng
Keyword(s):  
Lyapunov Exponent ◽  
Parametric Resonance ◽  
Stochastic Stability ◽  
Largest Lyapunov Exponent ◽  
Gyroscopic System ◽  
Bounded Noise ◽  
Rotating Shaft ◽  
Dynamic Stochastic ◽  
The Largest Lyapunov Exponent ◽  
Gyroscopic Systems

Dynamic stochastic stability of a two-degree-of-freedom gyroscopic system under bounded noise parametric excitation is studied in this paper through moment Lyapunov exponent and the largest Lyapunov exponent. A rotating shaft subject to stochastically fluctuating thrust is taken as a typical example. To obtain these two exponents, the gyroscopic differential equation of motion is first decoupled into Itô stochastic differential equations by using the method of stochastic averaging. Then mathematical transformations are used in these Itô equation to obtain a partial differential eigenvalue problem governing moment Lyapunov exponents, the slope of which at the origin is equal to the largest Lyapunov exponent. Depending upon the numerical relationship between the natural frequency and the excitation frequencies, the gyroscopic system may fall into four types of parametric resonance, i.e. no resonance, subharmonic resonance, combination additive resonance, and combination differential resonance. The effects of noise and frequency detuning parameters on the parametric resonance are investigated. The results pave the way to utilize or control the vibration of gyroscopic systems under stochastic excitation.

Chaotic State of Physical Pendulum Driven by Anharmonic Periodic Force

2003 ◽  
Vol 17 (22n24) ◽  
pp. 4321-4326
Author(s):  
Xiao-Ping Qin ◽  
Zheng-Mao Sheng
Keyword(s):  
Lyapunov Exponent ◽  
Correlation Dimension ◽  
Largest Lyapunov Exponent ◽  
Physical Pendulum ◽  
Chaotic State ◽  
Periodic Force ◽  
The Largest Lyapunov Exponent ◽  
Experiment And Simulation

The chaotic movement of physical pendulum, which is driven by an anharmonic periodic force, is studied by experiment and simulation. The correlation dimension and the largest Lyapunov exponent is obtained by numerical simulation.It is found that there is an obvious difference of correlation dimensions between the systems driven by anharmonic periodic force and harmonic periodic force.

Sign in / Sign up

Export Citation Format

Share Document