Predicting daily mean soil temperature from daily mean air temperature in four northern hardwood forest stands

Soil temperature is very important in regulating ecosystem processes, yet i t is often difficult and costly to measure. Most models that have endeavore d to predict soil temperature have either a long time step or several compl icated independent variables. Daily mean air and soil temperatures were mea sured from 1989-1997 in four northern hardwood sites along a 500 km latitud inal gradient in Michigan. These data were used to derive a simple method t o predict daily mean soil temperature (depth of 15 cm) using the daily mean air temperature from the previous day and a cosine function of Julian date (R-2 = 0.93-0.96; SEM = 0.98-1.40 degreesC). Predicted values were compare d with actual recorded soil temperatures from 1997 at each of the sites, an d the average difference between the observed and predicted values ranged f rom 0.11 to 0.39 degreesC, Different coefficients were estimated for each o f the sites; however, this general method of predicting soil temperature ap pears applicable to any site. Once calibrated for a given site, soil temper ature may be simply estimated, thus reducing the need for extended monitori ng efforts. This method also allows the reconstruction of soil temperature records beyond the monitoring period. Projecting long-term trends in soil t emperature may help to further elucidate several ecosystem processes and al so may provide more information on how a changing global climate will impac t forest ecosystems.