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A Multidisciplinary Approach to Assessing the Causal Components of Climate Change

A Multidisciplinary Approach to Assessing the Causal Components of Climate Change William D. Gosnold, Jr. 1 , Paul Todhunter 1 , Xiquan Dong 1 , Bradley Rundquist 1 , Jacek Majorowicz 1 , and David D. Blackwell 2 1 University of North Dakota, Northern Plains Climate Research Center

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A Multidisciplinary Approach to Assessing the Causal Components of Climate Change

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  1. A Multidisciplinary Approach to Assessing the Causal Components of Climate Change William D. Gosnold, Jr.1, Paul Todhunter1, Xiquan Dong1, Bradley Rundquist1, Jacek Majorowicz1, and David D. Blackwell2 1 University of North Dakota, Northern Plains Climate Research Center 2 Southern Methodist University ABSTRACT. Separation of climate forcing by anthropogenic greenhouse gases from natural radiative climate forcing is difficult because the composite temperature signal in the meteorological and multi-proxy temperature records cannot be resolved directly into radiative forcing components. To address this problem, we have initiated a large-scale, multidisciplinary project to test coherence between ground surface temperatures (GST) reconstructed from borehole T-z profiles, surface air temperatures (SAT), soil temperatures, and solar radiation. Our hypothesis is that radiative heating and heat exchange between the ground and the air directly control the ground surface temperature. Consequently, borehole T-z measurements at multi-year intervals spanning time periods when solar radiation, soil temperatures, and SAT have been recorded should enable comparison of the thermal energy stored in the ground to these quantities. If coherence between energy storage, solar radiation, GST, SAT and multi-proxy temperature data can be discerned for a one or two decade scale, synthesis of GST and multi-proxy data over the past several centuries may enable us to separately determine the anthropogenic and natural forcing of climate change. The data we are acquiring include: (1) New T-z measurements in boreholes previously used in paleoclimate and heat flow research in Canada and the United States from the 1970's to the present. (2) Meteorological data from the US Historical Climatology Network and the Automated Weather Data Network of the High Plains Regional Climate Center, and Environment Canada. (3) Direct and remotely sensed data on land use, environment, and soil properties at selected borehole and meteorological sites for the periods between borehole observations. The project addresses three related questions: What is the coherence between the GST, SAT, soil temperatures and solar radiation? Have microclimate changes at borehole sites and climate stations affected temperature trends? If good coherence is obtained, can the coherence between thermal energy stored in the ground and radiative forcing during the time between T-z measurements be extended several centuries into the past? Fig. 7.Theory The geothermal gradient (Γ) is determined by the ratio of heat flow (Q) to thermal conductivity (κ) and may be expressed by rearranging Fourier’s law of heat conduction as: Γ = Q/κ. On a planetary surface, the controlling quantities in Fourier’s law are thermal conductivity and heat flow from the interior. Thermal conductivity is a physical property of rocks and generally falls within the range of 1.0 W m-1 K-1 to 3.5 W m-1 K-1 depending on rock composition and fabric. Heat flow from the interior is partly heat acquired during formation of the planet and partly heat generated by long-lived radioactive isotopes of potassium, thorium and uranium that are present in trace amounts. Due to the nature of these sources, surface heat flow is constant on time scales of hundreds of millions of years and the background geothermal gradient is linear. Therefore, in the absence of heat transfer by ground water flow, curvature in the near surface T-z profile indicates a recent change in the bounding surface temperature. Cooling trends cause the surface intercept to swing towards cooler temperatures and warming trends cause the surface intercept to swing towards warmer temperatures. Due to the exponential diffusion of the signal with depth and the low thermal diffusivity values for rocks, surface temperature changes occurring 100 years ago affect the T-z profile to about 100 m depths and changes occurring 500 years ago affect the T-z profile to about 500 m depths. Fig. 7, shows the effect on Γ of a 2 degree change persisting for different time periods (red = one year; green = ten years ; blue =100 years.) Fig. 9. The ground-surface temperature history (GSTH) can be calculated from the T-Z profile using a non-linear Bayesian formulation based on the method of least squares called Functional Space Inversion (FSI) (Shen, Pollack and Huang, 1996). In a regional study designed to compare the GSTH with predictions of GCM models of global warming, Gosnold, et a., (1997) used the FSI inversion scheme on a group of specially drilled heat flow boreholes in a 1000 km wide transect in the mid-continent of North America. Their results, shown Table 1 and graphically in Fig. 9 above, indicate a century-long warming trend that increases systematically with latitude as predicted by GCM’s. Fig. 2. Climate forcing components, Intergovernmental Panel on Climate Change, Climate Change 2001: Working Group I: The Scientific Basis. HCN GSTH LATITUDEDeg. C (no.) σDeg. C (no.)σ 41 - 42.9 0.59 (18) 0.55 0.49 (10) 0.31 43 - 44.9 0.72 (13) 0.62 1.03 (10) 0.66 45 - 46.9 1.14 (13) 0.54 2.00 (1) ---- 47 - 49.6 1.34 (7) 0.40 2.44 (8) 0.52 Table 1. Observed warming in the past century from the Historical Climatology Network (HCN) and from borehole data (GSTH). Fig. 3. Global Temperature anomaly 1880 -2002. The anomaly was calculated by removing the mean value of all the data from each monthly data point. Fig. 4. The multi-proxy temperature anomaly is shown in dark blue and the 1σ range is shown in light blue. The observed temperature anomaly is shown in red. Compare scales with Fig. 3. (Modified after Mann et al., 2000.) The goals of this research are to determine the heat flux that caused the warming increases observed in boreholes, e.g. at Minot, Glenburn, and Landa, ND shown above, extract the solar component and thus quantify greenhouse gas forcing of climate change. An example of a heat flux calculation is shown below. A 20 m W m-2 heat flux into the ground accurately matched observed T-Z profiles from 1995 and 2002. Fig. 5. Long wave solar irradiance observed by satellite. Note the 11-year cycle in the data. Fig. 8. T-z profiles from sites in North Dakota, Manitoba, and Saskatchewan showing warming in the upper 100 meters. The profiles are spaced apart on the temperature scale so all may be seen clearly. Fig. 1. Climate stations shown in green and boreholes shown in red. Fig. 6. Subsurface temperature anomaly resulting from the solar signal in shown in Fig. 5.

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