Scientists are starting to produce experimental subseasonal climate forecasts, exploring, for example, the prediction of conditions related to the recent hurricanes to strike the United States.
Thus, it is of necessity to study the characteristics, formation, preservation, change and effects of the atmospheric circulation and master its evolution law, which is not only the essential part of human's understanding of nature, but also a helpful method of changing and improving the accuracy of weather forecasts, exploring global climate change, and making effective use of climate resources.
From the BBC's synopsis: Weather forecasting: Laurie Taylor explores a scientific art form rooted in unpredictability.
In this work, the potential value of satellite observations to initialize hydraulic forecasts is explored, using the Ensemble Sensitivity method.
Though the creative and social implications of this forecast have been explored by generative artists for years now, we have yet to see any fully automated programs emerge wherein the computer creates art completely independently of the artist (even in generative art, humans still outline the parameters for the ensuing visuals through code).
Their primary job is to explore and forecast all possibilities, particularly in the sites that hang on high plateaus and dot the mountains above the valley floor, which is at an elevation of roughly 1,800 feet, or 500 meters.
A web-based portal with an intuitive visual interface was developed for end-users to conveniently explore the forecast products.
In considering issues of ethics and emergence, we will forecast future civilizations and explore possible ways of archiving our past and present digital expression.
Drawing together histories of science, technology, capitalism, environment, and culture, Looking Forward explores how forecasts functioned as new forms of knowledge and risk management tools that sometimes mitigated, but at other times exacerbated, the very uncertainties they were designed to conquer.
We demonstrate the suitability of online support vector regression (SVR) method to short term power load forecasting and thoroughly explore its pros and cons.
