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This volume is the outcome of contributions from 51 scientists who were invited to expose their latest findings on precipitation research and in particular, on the measurement, estimation and prediction of precipitation. The reader is presented with a blend of theoretical, mathematical and technical treatise of precipitation science but also with authentic applications, ranging from local field experiments and country-scale campaigns to multinational space endeavors.
This book presents state of the art applications of artificial intelligence in energy and renewable energy systems design and modelling. It covers such topics as solar energy, wind energy, biomass and hydrogen as well as building services systems, power generation systems, combustion processes and refrigeration. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities dealing with modelling and performance prediction of energy and renewable energy systems.
Multiscale Hydrologic Remote Sensing: Perspectives and Applications integrates advances in hydrologic science and innovative remote sensing technologies. Raising the visibility of interdisciplinary research on water resources, it offers a suite of tools and platforms for investigating spatially and temporally continuous hydrological variables and p
Precipitation Science: Measurement, Remote Sensing, Microphysics and Modeling addresses the latest key concerns for researchers in precipitation science, mainly observing, measuring, modeling and forecasting. Using case studies and global examples, the book demonstrates how researchers are addressing these issues using state-of-the-art methods and models to improve accuracy and output across the field. In the process, it covers such topics as discrepancies between models and observations, precipitation estimations, error assessment, droplet size distributions, and using data in forecasting and simulations. Other sections cover improved standard approaches, novel approaches, and coverage of a...
Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne.
This topical volume of the Journal of Pure and Applied Geophysics utilizes new information not previously accessible for fog related research. It focuses on surface and remote sensing observations of fog, various numerical model applications using new parameterizations, fog climatology, and new statistical methods. The results presented in this special issue come from research efforts in North America and Europe.
The Universal Soil Loss Equation (USLE) enables planners to predict the average rate of soil erosion for each feasible alternative combination of crop system and management practices in association with a specified soil type, rainfall pattern, and topography. When these predicted losses are compared with given soil loss tolerances, they provide specific guidelines for effecting erosion control within specified limits. The equation groups the numerous interrelated physical and management parameters that influence erosion rate under six major factors whose site-specific values can be expressed numerically. A half century of erosion research in many States has supplied information from which at least approximate values of the USLE factors can be obtained for specified farm fields or other small erosion prone areas throughout the United States. Tables and charts presented in this handbook make this information readily available for field use. Significant limitations in the available data are identified.