Abstract

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°C per year in monthly mean surface air. Further, we noticed slight chance of rise in temperature about 0.1°C specially for the months of April, May and December in the years 2017–2019.

Highlights

• An increasing trend of 0.0009oC per year is evident in the monthly mean surface air.

• Raise in temperature of 0.1oC is evident during April, May and December.

中文翻译：

---

1951–2016年印度月地面气温模式的建模和预测：结构时间序列方法

摘要

地面气温（SAT）是关键的气象参数。SAT的建模和预测对于了解生态和农业变化至关重要。我们利用了印度所有的月均SAT，涵盖了1951–2016年的时间跨度。我们使用结构时间序列（STS）分析来建模和预测月平均SAT。2006-2016年的预测与观测数据非常吻合。此外，对2017-2019年每月平均地面气温模式的预测显示与气候行为有很好的一致性。请注意，我们观察到每月平均地面空气每年增加0.0009°C的趋势。此外，我们注意到，尤其是在2017-2019年的4月，5月和12月，温度可能会升高约0.1°C。

强调

• 在月平均地面空气中，每年明显增加0.0009oC的趋势。

• 在4月，5月和12月，温度明显升高了0.1oC。