Prediction of Cooling of a Nocturnal Environment Using Two Atmospheric Models

Abstract

A surface energy balance model and a boundary layer model were used to predict nocturnal cooling in an agricultural environment. The results from both models were compared with the observed temperatures to determine which model predicted the cooling curve more accurately. Upper air soundings and local characteristics of the nocturnal vegetated environment were processed into boundary layer model (BLM) input files. Ground station measurements were used as input to the surface energy balance model (P-model). The models were run on a real-time basis during the evening of 23 advective and radiative cooling nights. Model output was analyzed for two Florida locations, Gainesville and Ruskin. The 95% confidence intervals from t-tests, run to determine significant difference between predicted minus observed temperature and zero, averaged 3.4°C for the BLM at Gainesville, 5.8°C for the P-model at Gainesville, and 2.8°C for the BLM at Ruskin. A BLM-predicted temperature bias of + 3.4°C at the Gainesville site was attributed to the interpolation procedure that produced a sounding for Gainesville from the Waycross and Ruskin soundings.