Book contents
- Frontmatter
- Contents
- List of contributors
- Foreword
- Preface
- 1 Introduction
- 2 The Factor Separation Methodology and the fractional approach
- 3 Investigation of the Factor Separation features for basic mathematical functions
- 4 Factor Separation Methodology and paleoclimates
- 5 Meso-meteorology: Factor Separation examples in atmospheric meso-scale motions
- 6 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
- 7 Application of Factor Separation to heavy rainfall and cyclogenesis: Mediterranean examples
- 8 Experience in applying the Alpert–Stein Factor Separation Methodology to assessing urban land-use and aerosol impacts on precipitation
- 9 Free and forced thermocline oscillations in Lake Tanganyika
- 10 Application of the Factor Separation Methodology to quantify the effect of waste heat, vapor and pollution on cumulus convection
- 11 The use of the Alpert–Stein Factor Separation Methodology for climate variable interaction studies in hydrological land surface models and crop yield models
- 12 Linear model for the sea breeze
- 13 Experience and conclusions from the Alpert–Stein Factor Separation Methodology
- 14 Tagging systematic errors arising from different components of dynamics and physics in forecast models
- 15 Some difficulties and prospects
- 16 Summary
- Appendix: References employing the Alpert–Stein Factor Separation Methodology
- References
- Index
1 - Introduction
Published online by Cambridge University Press: 03 May 2011
- Frontmatter
- Contents
- List of contributors
- Foreword
- Preface
- 1 Introduction
- 2 The Factor Separation Methodology and the fractional approach
- 3 Investigation of the Factor Separation features for basic mathematical functions
- 4 Factor Separation Methodology and paleoclimates
- 5 Meso-meteorology: Factor Separation examples in atmospheric meso-scale motions
- 6 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
- 7 Application of Factor Separation to heavy rainfall and cyclogenesis: Mediterranean examples
- 8 Experience in applying the Alpert–Stein Factor Separation Methodology to assessing urban land-use and aerosol impacts on precipitation
- 9 Free and forced thermocline oscillations in Lake Tanganyika
- 10 Application of the Factor Separation Methodology to quantify the effect of waste heat, vapor and pollution on cumulus convection
- 11 The use of the Alpert–Stein Factor Separation Methodology for climate variable interaction studies in hydrological land surface models and crop yield models
- 12 Linear model for the sea breeze
- 13 Experience and conclusions from the Alpert–Stein Factor Separation Methodology
- 14 Tagging systematic errors arising from different components of dynamics and physics in forecast models
- 15 Some difficulties and prospects
- 16 Summary
- Appendix: References employing the Alpert–Stein Factor Separation Methodology
- References
- Index
Summary
Background
Numerical models provide a powerful tool for atmospheric research. One of the most common ways of utilizing a model is by performing sensitivity experiments. Their purpose is to isolate the effects of different factors on certain atmospheric fields in one or more case studies. Factors that have been tested in sensitivity studies include, for example, surface sensible and latent heat fluxes, latent heat release, horizontal and vertical resolution, sea surface temperatures, horizontal diffusion, surface stress, initial and boundary conditions, topography, surface moisture, atmospheric stability, and radiation. Sensitivity studies are performed either with real-data case studies or with idealized atmospheric situations.
Sensitivity studies often evaluate the influence of only one factor such as topography (Tibaldi et al., 1980; Dell'Osso, 1984, McGinley and Goerss, 1986), but many investigations test several factors, and try to estimate their relative importance. One common method of evaluating the contribution of a specific factor is by analyzing the difference in fields between a control run and a simulation where this factor is switched off. The difference map is, in general, more illustrative than the presentation of the two individual simulations, and therefore has often been used (e.g., Tibaldi et al., 1980; Mesinger and Strickler, 1982; Lannici et al., 1987; Leslie et al., 1987; Uccellini et al., 1987; Mullen and Baumhafner, 1988; Kuo and Low-Nam, 1990).
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- Information
- Factor Separation in the AtmosphereApplications and Future Prospects, pp. 1 - 4Publisher: Cambridge University PressPrint publication year: 2011