A correlation study of the ground temperatures up to a soil depth of 3m (for lawn condition) with the weather parameters has been performed making use of the observed data in the 4-year period 2006-2009. It is found that within the soil depth of 3m, which belongs to the surface and shallow zones, the ground temperature is strongly correlated to the dry bulb air temperature whereas its dependence on the relative humidity, rainfall, global solar radiation or wind speed is weak. A multivariable nonlinear regression model was then developed based on the soil temperature and weather data within the same four-year period. This model can be utilized to predict soil temperature at various depths underground. The required inputs of the model are the day number of the year, soil depth and dry bulb air temperature. The model has been validated by the data records of the same site in the previous years, as well as the data record from another site in more recent years. This regression model provides a simple, fast and accurate alternative method for the estimation of natural ground temperature. (C) 2011 Elsevier B.V. All rights reserved.