Dynamical Predictability of Leading Interannual Variability Modes of the Asian-Australian Monsoon in Climate Models

The dynamical prediction of the Asian-Australian monsoon(AAM)has been an important and long-standing issue in climate science.In this study,the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide.Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences,especially for the second mode.The first AAM mode,from various seasonal sequences,coincides with the El Niño phase transition in the eastern-central Pacific.The second mode,initialized from boreal summer and autumn,leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring.Our findings hint that ENSO,as an early signal,is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes.Still,the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features.The multimodel ensemble(MME)mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features.The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes.The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services.

Variability Modes of the Winter Upper-Level Wind Field over Asian MidHigh Latitude Region

In this study,the NCEP/NCAR reanalysis dataset was used to analyze the variability modes of the winter upper-level wind field over Asian mid-high latitude region.As shown by the results,the dominant variability modes of the winter upper-level wind field over Asian mid-high latitude region are characterized by the out-of-phase variation in the intensity of the subtropical and temperate jets over East Asia and the meridional shift of the subtropical jet axis,on interannual and multiannual scales,respectively.The first leading variability mode can be used as a good measure to represent the integral variation of atmospheric general circulation in Asian mid-latitude region.Composite analyses suggest that the first leading variability mode of the winter upper-level wind field is intimately related to the atmospheric circulation and temperature anomalies in the northern hemispheric mid-latitude region.

Two interannual variability modes of the Northwestern Pacific Subtropical Anticyclone in boreal summer

Using the reanalysis data and 20th century simulation of coupled model FGOALS_gl developed by LASG/IAP, we identified two distinct interannual modes of Northwestern Pacific Subtropical Anticyclone （NWPAC） by performing Empirical Orthogonal Function （EOF） analysis on 850 hPa wind field over the northwestern Pacific in summer. Based on the associated anoma- lous equatorial zonal wind, these two modes are termed as ＂Equatorial Easterly related Mode＂ （EEM） and ＂Equatorial Westerly related Mode＂ （EWM）, respectively. The formation mechanisms of these two modes are similar, whereas the maintenance mechanisms, dominant periods, and the relationships with ENSO are different. The EEM is associated with E1 Nifio decaying phase, with the anomalous anticyclone established in the preceding winter and persisted into summer through local positive air-sea feedback. By enhancing equatorial upwelling of subsurface cold water, EEM favors the transition of ENSO from E1 Nifio to La Nifia. The EWM is accompanied by the E1 Nifio events with long persistence, with the anomalous anticyclone formed in spring and strengthened in summer due to the warm Sea Surface Temperature anomalies （SSTA） forcing from the equatorial central-eastern Pacific. The model well reproduces the spatial patterns of these two modes, but fails to simulate the percentage variance accounted for by the two modes. In the NCEP reanalysis （model result）, EEM （EWM） appears as the first mode, which accounts for 35.6% （68.2%） of the total variance.

Coordinating optimization-based sliding mode variable structure control for electro-hydraulic servo system

A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance indexes in the coordinating optimization, while the tuning rate of boundary layer width （BLW） is employed as the optimization parameter. Based on the mathematical relationship between the BLW and steady-state error, an optimized BLW tuning rate is added to the nonlinear control term of SMVSC. Simulation experiment results applied to the positioning control of an electro-hydraulic servo system show the comprehensive superiority in dynamical and static state performance by using the proposed controller is better than that by using SMVSC without optimized BLW tuning rate. This succeeds in coordinately considering both chattering reduction and high-precision control realization in SMVSC.

Slow and Intraseasonal Modes of the Boreal Winter Atmospheric Circulation Simulated by CMIP5 Models

Abstract The authors evaluate the performance of models from Coupled Model Intercomparison Project Phase 5(CMIP5)in simulating the historical(1951-2000)modes of interannual variability in the seasonal mean Northern Hemisphere(NH)500 hPa geopotential height during winter(December-January-February,DJF).The analysis is done by using a variance decomposition method,which is suitable for studying patterns of interannual variability arising from intraseasonal variability and slow variability(time scales of a season or longer).Overall,compared with reanalysis data,the spatial structure and variance of the leading modes in the intraseasonal component are generally well reproduced by the CMIP5 models,with few clear differences between the models.However,there are systematic discrepancies among the models in their reproduction of the leading modes in the slow component.These modes include the dominant slow patterns,which can be seen as features of the Pacific-North American pattern,the North Atlantic Oscillation/Arctic Oscillation,and the Western Pacific pattern.An overall score is calculated to quantify how well models reproduce the three leading slow modes of variability.Ten models that reproduce the slow modes of variability relatively well are identified.

Coordinated Control of Sliding Mode and Hamiltonian for PWM Rectifier

Aiming at the PWM rectifier control strategy of sliding mode control, steady state performance weak Hamiltonian control dynamic tracking performance is poor, the coordinated compound control is proposed, the feedback linearization controller and sliding mode controller Hamiltonian system is obtained, and the design of a coordinated control strategy. In order to verify the accuracy of this method, MATLAB/Simulink is used for simulation analysis. The simulation results show that the composite control can achieve the coordinated dynamic rapid tracking and constant DC output and unit power factor operation, and satisfy the control requirements of the rectifier, effectively reducing the disturbance effect on the system. Compared with Hamiltonian control, the proposed method combines the advantages of the two methods, which have the fast tracking performance and excellent steady-state characteristics, and the research prospect is broad.

Study of Denoising in the Electricity Anti-Stealing Detection Based on VMD-WTD Combination

In order to solve the failure of electricity anti-stealing detection device triggered by the noise mixed in high-frequency electricity stealing signals,a denoising method based on variational mode decomposition(VMD)and wavelet threshold denoising(WTD)was applied to extract the effective high-frequency electricity stealing signals.First,the signal polluted by noise was pre-decomposed using the VMD algorithm,the instantaneous frequency means of each pre-decomposed components was analyzed,so as to determine the optimal K value.The optimal K value was used to decompose the polluted signal into K intrinsic mode components,and the sensitive mode components were determined through the cross-correlation function.Next,each sensitive mode was reconstructed.Finally,the reconstructed signal denoised using the wavelet threshold to obtain the denoised signal.The simulation analysis and experimental results show that the proposed method is superior to the traditional VMD method,FFT method and EMD method,as it can effectively eliminate the noise and enhance the reliability of high-frequency electricity stealing signal detection.

VARIABLE STRUCTURE CONTROL OF INDEFINITE-DIMENSIONAL SYSTEMS

In lhis paper, we study the variable structure control of indefinite-dimensionalcontrol systems with the functional analysis method. The reaching conditions, stabilityconditions and the approximating conditions of sliding mode, as well as the generalform of the variable structure control law are given. and the elementary frame of thevariable structure control of indefinite-dimensional systems is built.