Reconstructing Diurnal Cycle of Land Surface Temperature from Daily Max/Min Temperatures

Diurnal cycle (DTC) of land surface temperature (LST) plays a vital role in the study of land-atmosphere interactions, climate change and hydrological cycle. DTC is influenced by solar insolation, wind, and land surface thermal properties, and is indicative of vegetation and soil moisture conditions. Knowledge of diurnal variations are also critical in the study of epidemiology, agriculture, urban heat island effects, and varying demands on energy consumption. There have been several physically-based approaches which use thermal infrared measurements from remote sensing satellites and a combination of harmonic and exponential decay functions to model daytime and night time DTC. But such models are applicable only over clear-sky conditions. In the present study, we employ data on surface-absorbed solar radiation from a companion study and the time series of daily maximum/minimum temperatures to reconstruct the full diurnal cycle. Surface solar absorption is the key driver of LST and in situ observations reveal that the two are correlated linearly in each of the ascending and descending legs of the solar diurnal cycle under almost all sky conditions. This approach will be demonstrated employing in situ data from the NOAA’s Surface Radiation Network (SURFRAD), and US Climate Reference Network (USCRN) sites. This strategy can be applied to the new 5 km gridded daily nClimDiv dataset that is being produced at NOAA.