Fuzzy Logic Approach for Evolutionary Modeling of Principal Meteorological Variables
ABSTRACT: The opportunity of fuzzy set approach for study of joint diurnal distribution of principal coupled atmosphere-land variables (temperature of air and soil, humidity of air and soil, atmospheric precipitation, pressure, short-wave radiation, cloudiness) is investigated. Ten years data sets o...
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| Format: | Text |
| Language: | English |
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.292 http://www.erudit.de/erudit/events/esit99/12556_p.pdf |
| Summary: | ABSTRACT: The opportunity of fuzzy set approach for study of joint diurnal distribution of principal coupled atmosphere-land variables (temperature of air and soil, humidity of air and soil, atmospheric precipitation, pressure, short-wave radiation, cloudiness) is investigated. Ten years data sets of one hour temporal resolution for several meteorological sites of Russian north-west region are used. Known and novel interrelationships between various atmospheric and linked soil variables are reviewed. The revealed relationships between solar downward radiation fluxes and soil temperature diurnal patterns allow to simulate all principal elements of surface energy exchange: long-wave outgoing radiation fluxes in the atmosphere, soil heat fluxes, sensible, turbulent and latent heat fluxes. It was found out that the most complicated links take place for fuzzy sets, corresponding to fractional cloudiness diurnal patterns. There is an asymmetrical relationship between solar daily sums of radiance for half cloudy day and mean soil temperature values. That is a main cause for simulation of meteorological and heat balance component diurnal cycles in most ecological models. Introduced stationary and transition modes for main meteorological variable diurnal patterns represent the background for simulation of all known weather phenomena. This modes are used also as a neural network’s nodes for hidden layers. Implementation of neural networks (back propagation algorithm) allows to perform several modeling experiments. Problem of optimum network configuration ( number of nodes in hidden layers) is discussed. For example, it is possible to reconstruct the diurnal cycles of some meteorological |
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