Alpert P., Sholokhman T. (Eds.) Factor Separation in the Atmosphere: Applications and Future Prospects

Cambridge University Press; 2011. – 292 p. ISBN13: 978-0521191739, ISBN10: 0521191734Modeling atmospheric processes in order to forecast the weather or future climate change is an extremely complex and computationally intensive undertaking. One of the main difficulties is that there are a huge number of factors that need to be taken into account, some of which are still poorly understood. The Factor Separation (FS) method is a computational procedure that helps deal with these nonlinear factors. In recent years many scientists have applied FS methodology to a range of modeling problems, including paleoclimatology, limnology, regional climate change, rainfall analysis, cloud modeling, pollution, crop growth, and other forecasting applications. This book is the first to describe the fundamentals of the method, and to bring together its many applications in the atmospheric sciences. The main audience is researchers and graduate students using the FS method, but it is also of interest to advanced students, researchers, and professionals across the atmospheric sciences.ForewordThe FS methodology and the fractional approach)
Investigation of the Factor Separation features for basic mathematical functions
Factor Separation Methodology and paleoclimates
Meso-meteorology: Factor Separation examples in atmospheric meso-scale motions
Using the Alpert-Stein Factor Separation Methodology for land-use land-cover change impacts on weather and climate process with the Regional Atmospheric Modeling System
Application of Factor Separation to heavy rainfall and cyclogenesis: Mediterranean examples
Experience in applying the Alpert-Stein Factor Separation Methodology to assessing urban land-use and aerosol impacts on precipitation
Free and forced thermocline oscillations in Lake Tanganyika
Application of the Factor Separation Methodology to quantify the effect of waste heat, vapor and pollution on cumulus convection
The use of the Alpert-Stein Factor Separation Methodology for climate variable interaction studies in hydrological land surface models and crop yield models
Linear model for the sea breeze
Experience and conclusions from the Alpert-Stein Factor Separation Methodology: Ensemble data assimilation and forecasting applications
Tagging systematic errors arising from different components of dynamics and physics in forecast models
Some difficulties and prospectsAppendix References employing the Alpert-Stein Factor Separation Methodology