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Modelling and forecasting for monthly surface air temperature patterns in India, 1951–2016: Structural time series approach

机译:印度月度表面空气温度模式的建模与预测,1951 - 2016:结构时间序列方法

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Surface air temperature (SAT) is a key meteorological parameter. Modelling and forecasting of the SAT has vital importance to understand the ecological and agricultural changes. We utilized all India monthly mean SAT, which covers a time span of 1951–2016. We used structural time series (STS) analysis to model and forecast the monthly mean SAT. Forecast during 2006–2016 well matched with the observational data. Further, the forecast of monthly mean surface air temperature patterns for 2017–2019 shows a good agreement with climatological behaviour. Note that we observed an increasing trend 0.0009$^{circ}$C per year in monthly mean surface air. Further, we noticed slight chance of rise in temperature about 0.1$^{circ}$C specially for the months of April, May and December in the years 2017–2019. $f{Highlights}$ $ullet$ An increasing trend of 0.0009$^{circ}$C per year is evident in the monthly mean surface air. $ullet$ Raise in temperature of 0.1$^{circ}$C is evident during April, May and December.
机译:表面空气温度(SAT)是一个关键气象参数。饱和的建模与预测对了解生态和农业的变化至关重要。我们利用所有印度月均坐落,涵盖了1951 - 2016年的时间跨度。我们使用结构时间序列(STS)分析来模拟和预测月平均坐。预测2006 - 2016年期间与观察数据良好匹配。此外,2017-2019的月平均表面空气温度模式的预测显示了与气候行为的良好一致性。请注意,我们每月平均地表空气中观察到每年0.0009美元^ { rIC}美元的趋势。此外,我们在2017 - 2019年4月,5月和12月的几个月内,我们注意到了大约0.1美元^ { in $ c的温度略有升高。 $ bf {亮点} $ $ $ bullet $越来越多的趋势为0.0009 $ ^ { rIC}每年在月平均表面空气中是明显的。 $ Bullet $升高在0.1美元^

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