Reconstruction of the Fine-resolution Apparent Temperature (Humidex)
With the Addition of Aerodynamic Parameters
The “felt temperature” is the preferred measure of hotness or coldness
expressed to depict human sensory. However, to date, our perception of
its spatial pattern with fine spatiotemporal data remains incomplete.
Here, we demonstrated an empirical statistical approach incorporating
atmospheric dynamics theory with aerodynamic parameters capable of
developing hourly datasets at a high spatial resolution (0.01ᵒ x 0.01ᵒ).
This fusion mechanism model, named the Humidex Reconstruction Model
based on Numerical Simulation Data (HRMNSD), employed reanalysis data
and satellite data for both near surface temperature(Tair) and the dew
point temperature(Tdew) to combine their respective advantages in the
correct representation of a turbulent exchange between the surface and
the atmosphere. We showed the good performance of this model in each
season using the Yangtze River Delta, China as an example. The RMSEs of
the Humidex were 2.47°C (in winter), 2.49°C (in spring), 2.80°C (in
summer) and 2.56°C (in autumn), respectively.