scholarly journals A new dynamical mechanism for major climate shifts

2007 ◽  
Vol 34 (13) ◽  
pp. n/a-n/a ◽  
Author(s):  
Anastasios A. Tsonis ◽  
Kyle Swanson ◽  
Sergey Kravtsov
Keyword(s):  
Dynamical Mechanism ◽  
Climate Shifts

The Dynamical Mechanism for SMEs Evolution Under the Hologram Approach

2019 ◽  
Author(s):  
George X Yuan ◽  
Huiqin Wang ◽  
Tu Zeng ◽  
Tong Wu ◽  
Silong Gao ◽  
...  
Keyword(s):  
Dynamical Mechanism

scholarly journals Formation rate of LB-1-like systems through dynamical interactions

2020 ◽  
Vol 72 (3) ◽  
Author(s):  
Ataru Tanikawa ◽  
Tomoya Kinugawa ◽  
Jun Kumamoto ◽  
Michiko S Fujii
Keyword(s):  
Open Cluster ◽  
Formation Rate ◽  
Open Clusters ◽  
Type Star ◽  
Dynamical Mechanism ◽  
Milky Way Galaxy ◽  
Triple Systems ◽  
Stellar Collisions ◽  
Solar Metallicity ◽  
Helium Star

Abstract We estimate formation rates of LB-1-like systems through dynamical interactions in the framework of the theory of stellar evolution before the discovery of the LB-1 system. The LB-1 system contains a ∼70 ${M_{\odot}}$ black hole (BH), a so-called pair instability (PI) gap BH, and a B-type star with solar metallicity, and has nearly zero eccentricity. The most efficient formation mechanism is as follows. In an open cluster, a naked helium star (with ∼20 ${M_{\odot}}$) collides with a heavy main sequence star (with ∼50 ${M_{\odot}}$) which has a B-type companion. The collision results in a binary consisting of the collision product and the B-type star with a high eccentricity. The binary can be circularized through the dynamical tide with radiative damping of the collision product envelope. Finally, the collision product collapses to a PI-gap BH, avoiding pulsational pair instability and pair instability supernovae because its He core is as massive as the pre-colliding naked He star. We find that the number of LB-1-like systems in the Milky Way galaxy is ∼0.01(ρoc/104 ${M_{\odot}}$ pc−3), where ρoc is the initial mass densities of open clusters. If we take into account LB-1-like systems with O-type companion stars, the number increases to ∼0.03(ρoc/104 ${M_{\odot}}$ pc−3). This mechanism can form LB-1-like systems at least ten times more efficiently than the other mechanisms: captures of B-type stars by PI-gap BHs, stellar collisions between other types of stars, and stellar mergers in hierarchical triple systems. We conclude that no dynamical mechanism can explain the presence of the LB-1 system.

MULTIFRACTAL FLUCTUATIONS OF JIUZHAIGOU TOURISTS BEFORE AND AFTER WENCHUAN EARTHQUAKE

Fractals ◽  
2013 ◽  
Vol 21 (01) ◽  
pp. 1350001 ◽  
Author(s):  
KAI SHI ◽  
WEN-YONG LI ◽  
CHUN-QIONG LIU ◽  
ZHENG-WEN HUANG
Keyword(s):  
Wenchuan Earthquake ◽  
Moving Average ◽  
Long Term Memory ◽  
Short Term ◽  
Dynamical Mechanism ◽  
Before And After ◽  
Previous State ◽  
Multifractal Behavior ◽  
Multifractal Nature

In this work, multifractal methods have been successfully used to characterize the temporal fluctuations of daily Jiuzhai Valley domestic and foreign tourists before and after Wenchuan earthquake in China. We used multifractal detrending moving average method (MF-DMA). It showed that Jiuzhai Valley tourism markets are characterized by long-term memory and multifractal nature in. Moreover, the major sources of multifractality are studied. Based on the concept of sliding window, the time evolutions of the multifractal behavior of domestic and foreign tourists were analyzed and the influence of Wenchuan earthquake on Jiuzhai Valley tourism system dynamics were evaluated quantitatively. The study indicates that the inherent dynamical mechanism of Jiuzhai Valley tourism system has not been fundamentally changed from long views, although Jiuzhai Valley tourism system was seriously affected by the Wenchuan earthquake. Jiuzhai Valley tourism system has the ability to restore to its previous state in the short term.

scholarly journals Dynamical Mechanism for Coexistence of Dispersing Species

2001 ◽  
Vol 213 (1) ◽  
pp. 53-72 ◽  
Author(s):  
MARY ANN HARRISON ◽  
YING-CHENG LAI ◽  
ROBERT D. HOLT
Keyword(s):  
Dynamical Mechanism

Data-driven modeling decadal-to-centennial ENSO variability and its response to external forcing

2021 ◽  
Author(s):  
Aleksei Seleznev ◽  
Dmitry Mukhin ◽  
Andrey Gavrilov ◽  
Alexander Feigin
Keyword(s):  
Co2 Concentration ◽  
Data Driven ◽  
Time Interval ◽  
Solar Forcing ◽  
Russian Science ◽  
Dynamical Mechanism ◽  
Enso Variability ◽  
The Past ◽  
Sst Variability ◽  
Data Driven Modeling

<p>We investigate the decadal-to-centennial ENSO variability based on nonlinear data-driven stochastic modeling. We construct data-driven model of yearly Niño-3.4 indices reconstructed from paleoclimate proxies based on three different sea-surface temperature (SST) databases at the time interval from 1150 to 1995 [1]. The data-driven model is forced by the solar activity and CO2 concentration signals. We find the persistent antiphasing relationship between the solar forcing and Niño-3.4 SST on the bicentennial time scale. The dynamical mechanism of such a response is discussed.</p><p>The work was supported by the Russian Science Foundation (Grant No. 20-62-46056)</p><p>1. Emile-Geay, J., Cobb, K. M., Mann, M. E., & Wittenberg, A. T. (2013). Estimating Central Equatorial Pacific SST Variability over the Past Millennium. Part II: Reconstructions and Implications, Journal of Climate, 26(7), 2329-2352.</p>

scholarly journals The Decadal Climate Prediction Project

2016 ◽  
Author(s):  
George J. Boer ◽  
Douglas M . Smith ◽  
Christophe Cassou ◽  
Francisco Doblas-Reyes ◽  
Gokhan Danabasoglu ◽  
...  
Keyword(s):  
Decadal Variability ◽  
Climate Prediction ◽  
Decadal Prediction ◽  
Science And Society ◽  
Climate Data ◽  
Climate Shifts ◽  
Component C ◽  
Decadal Climate ◽  
Decadal Climate Prediction ◽  
Ensemble Generation

Abstract. The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from CMIP5 and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as part of CMIP6. The DCPP consists of three Components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, dissemination and analysis of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the "hiatus", volcanoes), including the study of the mechanisms that determine these behaviours. Groups are invited to participate in as many or as few of the Components of the DCPP, each of which are separately prioritized, as are of interest to them. The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.

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