The Influence of Soil Moisture Upon the Geothermal Climate Signal

Estimates of regional climate warming over the past few hundred years are being obtained from profiles of borehole temperature versus depth. The two assumptions in recovering mean annual Surface Air Temperature (SAT) are that the relationship between the Ground Surface Temperature (GST) and the temperature-depth profile is purely conductive, and that SAT is uniquely coupled to GST. While these assumptions have been demonstrated to be approximately valid, they ignore the role of moisture transport in soil and between soil and atmosphere. In this study we examine the influence of climatic changes in precipitation upon mean annual GST with climatic SAT held constant. We use the most recent version of our Prairie SVAT model for a set of 80 year simulations. Our findings are 1) increasing precipitation reduces mean annual GST, 2) phasing maximum precipitation to occur during the warmest months reduces mean annual GST, and 3) increasing the variance of precipitation reduces mean annual GST. The amplitudes of the effects are small but potentially not insignificant fractions of the geothermal climate signal. One of the long-term objectives of this investigation is to use global EOS SAT and remotely sensed soil moisture to link region-specific, geothermal climate signal histories to evolution of regional climate.