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

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.