Calculating temperature dependence over long time periods: derivation of methods


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Date

1996

Publication Type

Report

ETH Bibliography

yes

Citations

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Abstract

Rates of ecological processes are usually influenced by temperature. For simplicity and efficiency of ecosystem models it is often necessary to summarise information about temperature dependence from short, e.g. hourly, time intervals over longer, e.g. monthly, time periods, i.e. to calculate long term expected values of dependence functions. This aim can seldom be achieved by applying the temperature function to the mean temperature, because temperature dependencies are in many cases nonlinear. Therefore, we derived newly seven methods for such a temporal aggregation of temperature dependence. The methods determine the expected value interpreting either hourly temperature, daily temperature mean, or daily temperature mean and amplitude as random variables. The dependence function hereby is approximated by a piecewise linear function, the daily temperature course by a triangle and the density function of the normal distribution by a parabola. The resulting methods cover a range of temperature input data resolutions: monthly mean or standard deviation or both of either hourly temperatures, daily temperature extrema, daily temperature means and amplitudes, or only daily tempuature means. The methods can be applied to all types of dependence functions, in particular to nonlinear ones.

Publication status

published

External links

Editor

Book title

Volume

26

Pages / Article No.

Publisher

Terrestrial Systems Ecology, Department of Environmental Systems Science, ETH Zurich

Event

Edition / version

Methods

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Geographic location

Date collected

Date created

Subject

Gap dynamics; Forests; Climatic change; Temperature; Modeling

Organisational unit

02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science

Notes

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