A Validation of Temporal Downscaling Models of Estimating Hourly Temperatures Under South African Conditions

High-resolution weather data is essential for studies related to fruit production, building sciences and other mathematical modelling. Most of the historical weather data prior to 1980 was mainly daily. The introduction of automatic weather stations led to the introduction of hourly, minute, and second interval weather data, depending on the period during which the measurement was conducted. In order to conduct studies on climate change and generate the Climate normal, at least 30 years of data is required, and for most of the stations in South Africa, which have long-term data, their normal period was from 1961 to 1990, and the new normal was from 1981 to 2010. It becomes difficult to use daily temperatures only to do analysis for studies that require hourly temperatures, such as the calculation or estimation of chill units or chilling hours. Therefore, there is a need to find a mathematical model or stochastically generating model to derive high temporal resolution temperature data. The temporal downscaling model was used to obtain a full record of hourly temperatures for the period 1981–2010. The validation was based on all winter days within this base period for which observed data were available. A sine curve with input parameters, including daily minimum and maximum temperatures, as well as the day of the year, was more suitable. Other models were also tested, and the results were similar. All the models performed very well under normal weather conditions, while all models failed to simulate the sudden disruption in temperature due to a cold front or any storm activity. Only models for weather forecasting are able to predict sudden changes, but the historical simulators failed, as their inputs were only the daily minimum and maximum, and there was no recording of hourly temperatures available.