Spatial and temporal analyses of geothermal climate signals: Implications for borehole paleoclimatology.

Abstract

Inversions of subsurface temperature profiles to reconstruct ground surface temperature (GST) histories have been widely used as indicators of paleoclimate. These reconstructions assume that heat transport within the subsurface is conductive. Climatic interpretations of GST reconstructions also assume that GST is strongly coupled to surface air temperature (SAT) on timescales of decades and longer. I examine these two assumptions using records of SAT and subsurface temperature time series from Fargo, North Dakota; Prague, Czech Republic; Cape Henlopen State Park, Delaware; and Cape Hatteras National Seashore, North Carolina. These records comprise intra-daily observations that span parts of one or two decades. The characteristics of downward-propagating annual temperature signals at each site clearly indicate that heat transport in the subsurface can be described as one-dimensional conduction in a homogeneous medium. Extrapolations of subsurface observations to the ground surface yield estimates of annual GST signals, and allow comparisons to annual SAT signals. All annual GST signals are modestly attenuated and negligibly phase shifted relative to SAT. Relationships between GST and SAT are further explored on daily, seasonal, and annual timescales to identify and characterize the principal meteorological factors that lead to differences between GST and SAT. I compare subsurface temperature observations to calculations from a conductive subsurface model driven with daily SAT as the surface boundary condition and show daily differences exist between observed and modeled subsurface temperatures. Year-to-year spectral decompositions of daily SAT and subsurface temperature time series are also analyzed. Dissimilarities exist between annual amplitudes of GST and SAT signals. These amplitude differences partition into summer and winter seasons and can lead to mean annual GST that is either cooler or warmer than SAT. Additionally, the differences between mean annual GST and SAT can be estimated using amplitude characterizations of GST and SAT signals. Taken collectively, the results presented here indicate that differences between GST and SAT vary according to site-specific meteorological conditions and can be calculated readily from these conditions. It is therefore possible to conduct large regional studies of GST-SAT differences where long-term meteorological records are available, thus addressing how well GST changes represent SAT changes over large spatial regions on timescales of decades and centuries.