In this paper, we describe our efforts to investigate the usefulness of very simple surface temperature modelling, based on a single input parameter, from an operational perspective. A particular infrared sensor would require a minimum temperature difference (contrast) between target (CUBI) and background (sky, for instance) to declare a detection, but it does not ‘care’ if the contrast is larger than that. We use a linear model of the solar irradiance to predict the instantaneous daytime surface temperatures. To operationalize the modelling we calculate rates for true/false positive and negative predictions and show that even simple instantaneous (memory-less) modelling yields good predictions up to 80 % of the time. For modelling of nighttime surface temperatures, we investigate the usefulness of using cloud cover, wind speed, but also out-radiation measurements to predict these temperatures. In this case, we achieve high rates of correct predictions, up to 80 %.
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