Diurnal temperature modelling with sparse data and data integration

Hourly temperature readings play a key role in biological processes, hydrological simulation processes and as inputs to hourly forecasts. However, due to various reasons, most of the climatology stations record only daily maximum and minimum temperatures. Hence, the researchers have to estimate hourly temperature values using the available meteorological measurements. There are many methods proposed in the literature to estimate hourly temperature values, using the available information, and the best method should be chosen by the researcher that suits their application with high accuracies. This paper proposes a novel methodology that can be used to estimate hourly temperatures using only daily maximum and minimum temperature values which is proved to be superior to other stated methodologies in the literature.