LS-Magazine-LS-Models-lsm-set.03-01.rar
The SOAWS (SLOW-AWAY-SUPPORT-MODEL) model is a modified version of the Advanced Research Weather Systems (ARWS) model, which is a cyclic long term atmospheric forecast model developed by NOAA. This modified model includes two improvements based on the SOAWS: a slower increase in the likelihood of the forecasted weather conditions at early dates and incorporation of an energy constraint (EC) approach, which holds the probability of a forecast at any date in time, as a function of the forecast probability at the previous date. The modified model is applied to measure the model's ability to generate realistic forecasts using a variety of synthetic and observed borehole temperature and precipitation datasets. In addition, the inclusion of the EC approach to the modified model proves an effective way to incorporate uncertainty into the model. With a sensible level of EC, the modified model can generate accurate forecasts, while the forecast approaches that don't account for a consistent level of EC can produce misleading results.
LS-Magazine-LS-Models-lsm-set.03-01.rar
A stochastic model for uncertainty propagation into sustainability indicator assessments is presented in this paper. The model allows the user to be able to select which stochastic methodology will be implemented into the model. The three stochastic models, including the poisson, lognormal and beta distributions, allow the user to do a quantitative and qualitative assessment of stochasticity. This evaluation allows the user to assess whether stochastic propagation is useful for an specific assessment. In this paper, the capability of each stochastic model will be evaluated in the same qualitative and quantitative manner. The model will be evaluated by assessing the probability of a hypothetical accident being triggered within a specific time period. The model will be used to evaluate the probability of a hypothetical accident being triggered within a specific time period. The stochastic models will be used to evaluate the probability of an accident being triggered within a specific time period. The results can be used to aid decision makers with their assessments of the chance of an incident occurring. Assessment of the relative probabilities can be used to compare the risk or vulnerability of different assets or activities.less