Short-Term Variations of LBV’s

International Astronomical Union Colloquium ◽

10.1017/s0252921100072080 ◽

1999 ◽

Vol 169 ◽

pp. 251-254

Author(s):

Otmar Stahl

Keyword(s):

Time Scales ◽

Monitoring Program ◽

Short Term ◽

Star Group ◽

Different Time Scales

LBV’s are variable on many different time scales from weeks to years or even decades. The typical LBV variations on timescales of years or longer are covered in the paper by Humphreys (this volume). Here I discuss variations of LBV’s on timescales from weeks to years.Most classes of stars are little studied on these timescales. This also holds true for LBV’s. Therefore the hot star group of the Landessternwarte Heidelberg Started a monitoring program of a few bright LBV’s (and other objects) using the 70cm-telescopes at the Landessternwarte and later the ESO 50cm-telescope at La Silla. For more details about the project see the paper by Kaufer (this volume).

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Chaotic characteristic analysis of short-term wind speed time series with different time scales

Energy Sources Part A Recovery Utilization and Environmental Effects ◽

10.1080/15567036.2019.1649757 ◽

2019 ◽

pp. 1-15

Author(s):

Zhongda Tian

Keyword(s):

Time Series ◽

Wind Speed ◽

Time Scales ◽

Characteristic Analysis ◽

Short Term ◽

Chaotic Characteristic ◽

Different Time Scales

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Design droughts as planning tool for ecosystem establishment in post-mining landscapes

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-4809-2014 ◽

2014 ◽

Vol 11 (5) ◽

pp. 4809-4849 ◽

Cited By ~ 3

Author(s):

D. Halwatura ◽

A. M. Lechner ◽

S. Arnold

Keyword(s):

Time Scales ◽

Standardized Precipitation Index ◽

Distribution Functions ◽

Drought Indices ◽

Minor Role ◽

Short Term ◽

Eastern Australia ◽

Recurrence Intervals ◽

Different Time Scales

Abstract. Eastern Australia has considerable mineral and energy resources and areas of high biodiversity value co-occurring over a broad range of agro-climatic environments. Water is the primary abiotic stressor for (agro)ecosystems in many parts of Eastern Australia. In the context of mined land rehabilitation quantifying the severity-duration-frequency (SDF) of droughts is crucial for successful ecosystem rehabilitation to overcome challenges of early vegetation establishment and long-term ecosystem resilience. The objective of this study was to quantify the SDF of short-term and long-term drought events of 11 selected locations across a broad range of agro-climatic environments in Eastern Australia by using three drought indices at different time scales: the Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI), and the Standardized Precipitation-Evapotranspiration Index (SPEI). Based on the indices we derived bivariate distribution functions of drought severity and duration, and estimated the recurrence intervals of drought events at different time scales. The correlation between the simple SPI and the more complex SPEI or RDI was stronger for the tropical and temperate locations than for the arid locations, indicating that SPEI or RDI can be replaced by SPI if evaporation plays a minor role for plant available water. Both short-term and long-term droughts were most severe and prolonged, and occurred most frequently in arid regions, but were relatively rare in tropical and temperate regions. Our approach is similar to intensity-duration-frequency (IDF) analyses of rainfall crucial to design infrastructure. In this regard, we propose to apply SDF analyses of droughts to design ecosystem components in post-mining landscapes. Together with design rainfalls, design droughts should be used to assess rehabilitation strategies and ecological management based on drought recurrence intervals, thereby minimising the risk of failure of initial ecosystem establishment due to ignorance of fundamental abiotic and site-specific environmental barriers.

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Preliminary Research of Chaotic Characteristics and Prediction of Short-Term Wind Speed Time Series

International Journal of Bifurcation and Chaos ◽

10.1142/s021812742050176x ◽

2020 ◽

Vol 30 (12) ◽

pp. 2050176

Author(s):

Zhongda Tian

Keyword(s):

Time Series ◽

Wind Speed ◽

Time Scales ◽

Prediction Method ◽

Test Method ◽

Echo State Network ◽

Maximum Lyapunov Exponent ◽

Short Term ◽

Wind Speed Prediction ◽

Different Time Scales

Short-term wind speed prediction has its special significance in wind power industry. However, due to the characteristics of the wind system itself, it is not easy to predict the short-term wind speed accurately. In order to solve the problem, this paper studies the chaotic characteristics and prediction of short-term wind speed time series. The short-term wind speed data at four time scales are collected as the research object. The predictability of short-term wind speed time series is determined by the Hurst exponent. The chaotic characteristics of short-time wind speed at different time scales are analyzed by the 0–1 test method for chaos and the maximum Lyapunov exponent method. The results show that the short-term wind speed time series has chaotic characteristics at different time scales. The phase-space reconstruction technology is introduced; delay time is determined by the C–C method; embedding dimension is obtained by the G–P method. Echo state network is improved to suppress the influence of input noise on prediction performance. At the same time, an improved grey Wolf optimization algorithm is proposed to optimize the parameters of reserve pool of the echo state network. The results of a case study show that, compared with state-of-the-art methods, the proposed prediction method improves the prediction accuracy and reduces the predictive errors.

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Diurnal, seasonal and long-term behaviour of high arctic tundra-heath ecosystem dynamics inferred from model ensembles constrained by time-integrated CO<sub>2</sub> fluxes

10.5194/bg-2017-382 ◽

2017 ◽

Cited By ~ 1

Author(s):

Wenxin Zhang ◽

Per-Erik Jansson ◽

Bo Elberling

Keyword(s):

Time Scales ◽

High Arctic ◽

Ecosystem Dynamics ◽

Co2 Fluxes ◽

Short Term ◽

C Cycle ◽

Short And Long Term ◽

Model Ensembles ◽

Different Time Scales

Abstract. Ecosystem CO2 fluxes in high Arctic are rather dynamic, as they are sensitive to climatic variability through multiple ecosystem processes, for instance, vegetation and snow dynamics as well as permafrost thawing, operating at different time scales. Uncertainties from both high-frequency measurements and model assumptions challenge model calibration to describe both short- and long-term phenomena related to weather and climate variabilities. In this study, we generated three model ensembles using a Monte-Carlo based uncertainty approach with acceptance criteria for 15 years of eddy covariance CO2 measurements of a high Arctic heath ecosystem based on the time-integrated CO2 fluxes within the day, the year and the entire period. The temporal distribution of residuals between the model and measurements indicated that the three model ensembles reasonably simulated diurnal, seasonal and long-term behaviours of CO2 fluxes respectively. The inter-annual variation of CO2 fluxes over 15 years showed the current ecosystem is at a transition from being a C sink to a C neutral balance. The long-term behaviour model ensemble simulated a more intensified diurnal C cycle than the short-term behaviour model ensembles. The intensified C cycle was mainly attributed to a faster depletion of the soil C pools. The sensitivities of posterior parameters to the model performance index (coefficient of determination, R2) reflected that parameters in the processes of soil water and heat transfer and snow dynamics regulated the short-term behaviour of CO2 fluxes, while parameters in the process of soil decomposition regulated the long-term behaviour of CO2 fluxes. Our results suggest that the development of ecosystem models should diagnose their effectiveness in capturing ecosystem CO2 exchange behaviour across different time scales. A clear trade-off may exist when the model is tuned to capture both the short- and long-term variation of CO2 fluxes. To constrain the model with the time-integrated CO2 fluxes is a simple and useful method to reduce the non-explained errors and to identify the crucial link to controlling parameters and processes.

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Agent-Based Computational Model

10.23943/princeton/9780691158884.003.0003 ◽

2017 ◽

Cited By ~ 2

Author(s):

Joshua M. Epstein

Keyword(s):

Computational Model ◽

Bounded Rationality ◽

Time Scales ◽

Spatially Explicit ◽

Agent Based ◽

Affective Component ◽

Elementary Type ◽

Social Component ◽

Different Time Scales

This part describes the agent-based and computational model for Agent_Zero and demonstrates its capacity for generative minimalism. It first explains the replicability of the model before offering an interpretation of the model by imagining a guerilla war like Vietnam, Afghanistan, or Iraq, where events transpire on a 2-D population of contiguous yellow patches. Each patch is occupied by a single stationary indigenous agent, which has two possible states: inactive and active. The discussion then turns to Agent_Zero's affective component and an elementary type of bounded rationality, as well as its social component, with particular emphasis on disposition, action, and pseudocode. Computational parables are then presented, including a parable relating to the slaughter of innocents through dispositional contagion. This part also shows how the model can capture three spatially explicit examples in which affect and probability change on different time scales.

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