Traffic and environmental conditions (e.g., weather conditions), which frequently change with time, have a significant impact on crash occurrence. Traditional crash frequency models with large temporal scales and aggregated variables are not sufficient to capture the time-varying nature of driving environmental factors, causing significant loss of critical information on crash frequency modelin...

Numerical weather prediction models as well as the atmosphere itself can be viewed as nonlinear dynamical systems in which the evolution depends sensitively on the initial conditions. The fact that estimates of the current state are inaccurate and that numerical models have inadequacies, leads to forecast errors that grow with increasing forecast lead time. The growth of errors depends on the f...

Data assimilation has traditionally been employed to provide initial conditions for numerical weather prediction (NWP). A multi{year time sequence of objective analyses produced by data assimilation can also be used as an archival record from which to carry out a variety of atmospheric process studies. For this latter purpose, NWP analyses are not as accurate as they could be, for each analysis...

Inaccurate forecasting of photovoltaic (PV) power generation is a great concern in the planning and operation of stable and reliable electric grid systems as well as in promoting large-scale PV deployment. The paper proposes a generalized PV power forecasting model based on support vector regression, historical PV power output, and corresponding meteorological data. Weather conditions are broad...

The prediction of weather generally means the solution of differential equations on the base of the measured initial conditions where the data of close and distant neighboring points are used for the calculations. It requires the maintenance of expensive weather stations and supercomputers. However, if weather stations are not only capable of measuring but can also communicate with each other, ...

Operational forecasting is hampered both by the rapid divergence of nearby initial conditions and by error in the underlying model. Interest in chaos has fuelled much work on the first of these two issues; this paper focuses on the second. A new approach to quantifying state-dependent model error, the local model drift, is derived and deployed both in examples and in operational numerical weath...

Many operational NWP centres now produce global medium-range (≤ 14 day) and higher-resolution, limited-area, shorter-range (≤ 3 day) ensemble forecasts. These provide probabilistic guidance and early warning of the likelihood of high-impact weather. There are two main challenges in the design of ensemble prediction systems: (1) properly simulating the initial condition uncertainty, including th...

The key factor enabling control of the weather is that the atmosphere is sensitive to small perturbations. That is, it is the very instability of the atmosphere’s dynamics that makes global weather control a possibility. The Earth’s atmosphere may be chaotic, and very likely is very sensitive to small perturbations. Certainly very simple nonlinear dynamical models of the atmosphere are chaotic,...

kochia is one of those plants which have capability to grow in different environments and can be used as a valuable plant to produce biomass and seed. the purpose of this study was to evaluate the possibility of kochia planting in different dates as well as its resistance to cold weather of mashhad winter. seven sowing dates including 10th october, november, march, april, may, june and july and...

Many industries are exposed to weather risk. Weather derivatives can play a key role in hedging and diversifying such risk because the uncertainty in a company’s profit function can be correlated to weather condition which affects diverse industry sectors differently. Unfortunately the weather derivatives market is a classical example of an incomplete market that is not amenable to standard met...