Using the quantile regression method to analyze changes in climate characteristics |
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Authors: | A A Timofeev A M Sterin |
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Institution: | 1.All-Russian Research Institute of Hydrometeorological Information-World Data Center,Obninsk, Kaluga oblast,Russia |
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Abstract: | Possibilities to use the non-parametric regression analysis method, named the quantile regression, for the estimation of changes
in climate characteristics are considered. When analyzing the trends of climatic series, the quantile regression method enables
to get the information on trends along the whole range of quantile values from 0 to 1 of dependent variable distributions,
that is more informative than the use of traditional regression technique, based on the least-squares method (LSM) and enabling
to obtain trend estimations for average values of the dependent variable only. Trend estimation errors for various methods
are analyzed. The computation of quantile regression parameters for real climatic series is executed. Series of meteorological
variables of the diurnal resolution, which characterize the surface climate (minimal, average, and maximal diurnal temperatures)
and free atmosphere climate (temperature of isobaric surfaces up to 30 hPa inclusive) are considered. Seasonal peculiarities
in trend manifestation at different parts of quantile range of these meteorological values are discussed. Concerning the problem
of the analysis of climate trends, the quantile regression method seems to be perspective from the point of view of more detailed
understanding of processes in the climate system, such as the surface and tropospheric warming, stratospheric cooling, long-period
changes in characteristics of climate variability and extremity. |
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