评估希腊气温时间趋势的可变性和可预测性:一种贝叶斯方法

IF 2.8 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Georgios Tsiotas, Athanassios Argiriou, Anna Mamara
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引用次数: 0

摘要

本研究探讨了希腊年平均地表气温时间趋势的变异性和预测能力。利用高斯时间趋势模型,我们首先研究了与时间趋势相关的一些基本统计特征,如平均值和方差。这可以揭示气温的平均值和波动性变化是否与时间相关。为此,我们使用了希腊气象局位于希腊的几个气象站在 1960-2010 年期间观测到的最低和最高气温的平均值。作为第二项实验,我们使用各种高斯时间趋势和无时间趋势模型来研究气温趋势是否可预测。结果非常重要,因为它们揭示了年际趋势优于无趋势的季节、时期和模型类型。此外,它们还显示了统计特征,如不同季节和分时段下时间趋势的平均值和变异性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessing the variability and forecastability of time-trends for air temperatures in Greece: a Bayesian approach

Assessing the variability and forecastability of time-trends for air temperatures in Greece: a Bayesian approach

This study investigates the variability and forecasting ability of time-trend in mean annual surface air temperatures in Greece. Using Gaussian time-trend models, we first investigate some basic statistical characteristics associated with time-trends, such the mean and variance. This can reveal whether temperatures’ mean and volatility changes are associated with time. To do so, we have used mean measures of the minimum and maximum air temperatures observed at several meteorological stations of the Hellenic Meteorological Service located in Greece for the 1960-2010 period. As a second experiment, we investigate whether temperature trends are forecastable or not using various Gaussian time-trend and no-time-trend models. The results are highly significant since they reveal the seasons, the periods and the type of models for which the inter-annual trends out-perform the no-trend ones. Moreover, they also show the statistical characteristics, such as the mean and variability of the time-trend under various seasons and sub-periods.

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来源期刊
Theoretical and Applied Climatology
Theoretical and Applied Climatology 地学-气象与大气科学
CiteScore
6.00
自引率
11.80%
发文量
376
审稿时长
4.3 months
期刊介绍: Theoretical and Applied Climatology covers the following topics: - climate modeling, climatic changes and climate forecasting, micro- to mesoclimate, applied meteorology as in agro- and forestmeteorology, biometeorology, building meteorology and atmospheric radiation problems as they relate to the biosphere - effects of anthropogenic and natural aerosols or gaseous trace constituents - hardware and software elements of meteorological measurements, including techniques of remote sensing
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