Effects of optimal initial errors on predicting the seasonal reduction of the upstream Kuroshio transport

2016 ◽  
Vol 116 ◽  
pp. 220-235 ◽  
Author(s):  
Kun Zhang ◽  
Qiang Wang ◽  
Mu Mu ◽  
Peng Liang
Keyword(s):  
Initial Errors ◽  
Kuroshio Transport

RACIAL STEREOTYPING OF HOMO SAPIENS AFRICANUS: A REVIEW OF ITS MYTH AND IMPACT ON DEVELOPMENTAL CAPACITY

2016 ◽  
Vol 45 (2) ◽  
pp. 49-71 ◽  
Author(s):  
Seth Oppong
Keyword(s):  
Immanuel Kant ◽  
David Hume ◽  
Negative Impact ◽  
Homo Sapiens ◽  
Supporting Evidence ◽  
White People ◽  
Negative Stereotypes ◽  
Initial Errors ◽  
Developmental Capacity ◽  
Lower Intelligence

Generally, negatives stereotypes have been shown to have negative impact on performance members of a social group that is the target of the stereotype (Schmader, Johns and Forbes 2008; Steele and Aronson, 1995). It is against the background of this evidence that this paper argues that the negative stereotypes of perceived lower intelligence held against Africans has similar impact on the general development of the continent. This paper seeks to challenge this stereotype by tracing the source of this negative stereotype to David Hume and Immanuel Kant and showing the initial errors they committed which have influenced social science knowledge about race relations. Hume and Kant argue that Africans are naturally inferior to white or are less intelligent and support their thesis with their contrived evidence that there has never been any civilized nation other than those developed by white people nor any African scholars of eminence. Drawing on Anton Wilhelm Amo’s negligence-ignorance thesis, this paper shows the Hume-Kantian argument and the supporting evidence to be fallacious. 

Dynamic and Positioning Performances of Linear Electromechanical Actuator

2015 ◽  
Vol 809-810 ◽  
pp. 682-687
Author(s):  
Vasile Nasui ◽  
Mihai Banica ◽  
Dinu Darabă
Keyword(s):  
Dynamic Characteristics ◽  
Practical Importance ◽  
Correct Identification ◽  
Positioning System ◽  
Positioning Error ◽  
Servo Motor ◽  
Positioning Accuracy ◽  
Electromechanical Actuator ◽  
Initial Errors ◽  
Selection For

This paper presents the dynamic characteristics and the proposed positioning performance of the system to them investigated experimentally. In this research, we developed the positioning system and we evaluated positioning accuracy. The developed system uses a servo motor for motion actuation. In this paper, we focused on studying the dependency of the positioning error – elementary errors – the position of the conducting element for the mechanism of the transformation of the rotation translation movement, representatively the mechanism screw – screwdriver and on emphasizing the practical consequences in the field of design, regulation and exploitation of the correct identification of all the initial errors in the structure of the mechanism, their character and the selection for an ultimate calculus of these which are of a real practical importance.

scholarly journals Optimally growing initial errors of El Niño events in the CESM

2021 ◽  
Author(s):  
Hui Xu ◽  
Lei Chen ◽  
Wansuo Duan
Keyword(s):  
El Niño ◽  
El Nino ◽  
Equatorial Pacific ◽  
Initial Error ◽  
Initial Errors ◽  
El Niño Events ◽  
Type 3 ◽  
El Nino Events

AbstractThe optimally growing initial errors (OGEs) of El Niño events are found in the Community Earth System Model (CESM) by the conditional nonlinear optimal perturbation (CNOP) method. Based on the characteristics of low-dimensional attractors for ENSO (El Niño Southern Oscillation) systems, we apply singular vector decomposition (SVD) to reduce the dimensions of optimization problems and calculate the CNOP in a truncated phase space by the differential evolution (DE) algorithm. In the CESM, we obtain three types of OGEs of El Niño events with different intensities and diversities and call them type-1, type-2 and type-3 initial errors. Among them, the type-1 initial error is characterized by negative SSTA errors in the equatorial Pacific accompanied by a negative west–east slope of subsurface temperature from the subsurface to the surface in the equatorial central-eastern Pacific. The type-2 initial error is similar to the type-1 initial error but with the opposite sign. The type-3 initial error behaves as a basin-wide dipolar pattern of tropical sea temperature errors from the sea surface to the subsurface, with positive errors in the upper layers of the equatorial eastern Pacific and negative errors in the lower layers of the equatorial western Pacific. For the type-1 (type-2) initial error, the negative (positive) temperature errors in the eastern equatorial Pacific develop locally into a mature La Niña (El Niño)-like mode. For the type-3 initial error, the negative errors in the lower layers of the western equatorial Pacific propagate eastward with Kelvin waves and are intensified in the eastern equatorial Pacific. Although the type-1 and type-3 initial errors have different spatial patterns and dynamic growing mechanisms, both cause El Niño events to be underpredicted as neutral states or La Niña events. However, the type-2 initial error makes a moderate El Niño event to be predicted as an extremely strong event.

scholarly journals Time Evolution of Initial Errors in Lorenz’s 05 Chaotic Model

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Hynek Bednář ◽  
Aleš Raidl ◽  
Jiří Mikšovský
Keyword(s):  
Weather Prediction ◽  
Prediction Method ◽  
Atmospheric Model ◽  
Ensemble Prediction ◽  
Asymptotic Value ◽  
Time Limits ◽  
Initial Errors ◽  
Asymptotic Values ◽  
Chaotic Model ◽  
Almost All

Initial errors in weather prediction grow in time and, as they become larger, their growth slows down and then stops at an asymptotic value. Time of reaching this saturation point represents the limit of predictability. This paper studies the asymptotic values and time limits in a chaotic atmospheric model for five initial errors, using ensemble prediction method (model’s data) as well as error approximation by quadratic and logarithmic hypothesis and their modifications. We show that modified hypotheses approximate the model’s time limits better, but not without serious disadvantages. We demonstrate how hypotheses can be further improved to achieve better match of time limits with the model. We also show that quadratic hypothesis approximates the model’s asymptotic value best and that, after improvement, it also approximates the model’s time limits better for almost all initial errors and time lengths.

Atmospheric Predictability: Why Butterflies Are Not of Practical Importance

2014 ◽  
Vol 71 (7) ◽  
pp. 2476-2488 ◽  
Author(s):  
Dale R. Durran ◽  
Mark Gingrich
Keyword(s):  
Kinetic Energy ◽  
Turbulence Model ◽  
Large Scale ◽  
Mesoscale Model ◽  
Practical Importance ◽  
Absolute Magnitude ◽  
Error Growth ◽  
Initial Error ◽  
Initial Errors ◽  
Relative Errors

Abstract The spectral turbulence model of Lorenz, as modified for surface quasigeostrophic dynamics by Rotunno and Snyder, is further modified to more smoothly approach nonlinear saturation. This model is used to investigate error growth starting from different distributions of the initial error. Consistent with an often overlooked finding by Lorenz, the loss of predictability generated by initial errors of small but fixed absolute magnitude is essentially independent of their spatial scale when the background saturation kinetic energy spectrum is proportional to the −5/3 power of the wavenumber. Thus, because the background kinetic energy increases with scale, very small relative errors at long wavelengths have similar impacts on perturbation error growth as large relative errors at short wavelengths. To the extent that this model applies to practical meteorological forecasts, the influence of initial perturbations generated by butterflies would be swamped by unavoidable tiny relative errors in the large scales. The rough applicability of the authors’ modified spectral turbulence model to the atmosphere over scales ranging between 10 and 1000 km is supported by the good estimate that it provides for the ensemble error growth in state-of-the-art ensemble mesoscale model simulations of two winter storms. The initial-error spectrum for the ensemble perturbations in these cases has maximum power at the longest wavelengths. The dominance of large-scale errors in the ensemble suggests that mesoscale weather forecasts may often be limited by errors arising from the large scales instead of being produced solely through an upscale cascade from the smallest scales.

scholarly journals Intrinsic Predictability of the 20 May 2013 Tornadic Thunderstorm Event in Oklahoma at Storm Scales

2016 ◽  
Vol 144 (4) ◽  
pp. 1273-1298 ◽  
Author(s):  
Yunji Zhang ◽  
Fuqing Zhang ◽  
David J. Stensrud ◽  
Zhiyong Meng
Keyword(s):  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Lead Times ◽  
Forecast Errors ◽  
Ensemble Forecasts ◽  
Positive Feedbacks ◽  
Convective Storms ◽  
Cold Pools ◽  
Initial Errors ◽  
Environmental Instability

Abstract Using a high-resolution convection-allowing numerical weather prediction model, this study seeks to explore the intrinsic predictability of the severe tornadic thunderstorm event on 20 May 2013 in Oklahoma from its preinitiation environment to initiation, upscale organization, and interaction with other convective storms. This is accomplished through ensemble forecasts perturbed with minute initial condition uncertainties that were beyond detection capabilities of any current observational platforms. It was found that these small perturbations, too small to modify the initial mesoscale environmental instability and moisture fields, will be propagated and evolved via turbulence within the PBL and rapidly amplified in moist convective processes through positive feedbacks associated with updrafts, phase transitions of water species, and cold pools, thus greatly affecting the appearance, organization, and development of thunderstorms. The forecast errors remain nearly unchanged even when the initial perturbations (errors) were reduced by as much as 90%, which strongly suggests an inherently limited predictability for this thunderstorm event for lead times as short as 3–6 h. Further scale decomposition reveals rapid error growth and saturation in meso-γ scales (regardless of the magnitude of initial errors) and subsequent upscale growth into meso-β scales.

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