Radiative cooling scale method for correcting hourly surface air temperature error in numerical weather prediction models

Globally, a variety of numerical weather prediction (NWP) models are employed by national agencies. However, the derived outputs from these generally inadequate for precise cultivation management due to bias error. This study uses observational data acquired over several months develop an equation correcting surface air temperature (SAT) error in NWP model outputs. With proposed method, converted into potential cancel influence differences between computational elevation and real elevation. The errors corrected using linear regression which radiative cooling scale (RCS) serves as independent variable. RCS is computed observed at nearby meteorological observation station, together with upper-level pressure model. Versions correction developed specific situations: day, night, meteorology, classified six groups. In application root mean square (RMSE) SAT output global spectral operated Japan Meteorological Agency (JMA) was 1.2–1.6 K; RMSE nonhydrostatic JMA 1.2–1.5 K. method level accuracy similar that Kalman filtering technique without requirement constant target site.