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Paleosols (fossil soils) are abundant in the sedimentary record and reflect, at least in part, regional paleoclimate. Paleopedology thus offers a great potential for elucidating high resolution, deep-time paleoclimate records. However, many fossil soils did not equilibrate with climate prior to burial and instead dominantly express physical and chemical features reflective of other soil forming factors. Current models that use elemental oxides for climate reconstruction bypass the issue of soil-climate equilibration by restricting datasets to narrow ranges of soil properties, soil-forming environments and mean annual precipitation (MAP) and mean annual temperature (MAT). Here we evaluate a data-driven paleosol-paleoclimate model (PPM1.0) that uses subsoil geochemistry to test the ability of soils from wide-ranging environments to predict MAP and MAT as a joint response with few initial assumptions. The PPM1.0 was developed using a combined partial least squares regression (PLSR) and a nonlinear spline on 685 mineral soil B horizons currently forming under MAP ranging from 130 to 6900 mm and MAT ranging from 0 to 27 °C. The PLSR results on 11 major and minor oxides show that four linear combinations of these oxides (Regressors 1-4), akin to classic oxide ratios, have potential for predicting climate. Regressor 1 correlates with increasing MAP and MAT through Fe oxidation, desilication, base loss and residual enrichment. Regressor 2 correlates with MAT through temperature-dependent dissolution of Na- and K-bearing minerals. Regressor 3 correlates with increasing MAP through decalcification and retention of Si. Regressor 4 correlates with increasing MAP through Mg retention in mafic-rich parent material. The nonlinear spline model fit on Regressors 1 to 4 results in a Root Mean Squared Error (RMSEMAP) of 228 mm and RMSEMAT of 2.46 °C. PPM1.0 model simulations result in Root Mean Squared Predictive Error (RMSPEMAP) of 512mm and RMSPEMAT of 3.98 °C. The RMSE values are lower than some preexisting MAT models and show that subsoil weathering processes operating under a wide range of soil forming factors possess climate prediction potential, which agrees with the state-factor model of soil formation. The nonlinear, multivariate model space of PPM1.0 more accurately reflects the complex and nonlinear nature of many weathering processes as climate varies. This approach is still limited as it was built using data primarily from the conterminous USA and does not account for effects of diagenesis. Yet, because it is calibrated over a broader range of climatic variable space than previous work, it should have the widest array of potential applications. Furthermore, because it is not dependent on properties that may be poorly preserved in buried paleosols, the PPM1.0 model is preferable for reconstructing deep time climate transitions. In fact, previous studies may have grossly underestimated paleo-MAP for some paleosols. [ABSTRACT FROM AUTHOR]

The Paleoproterozoic Baraboo paleosol is the most chemically mature Precambrian paleosol in the Lake Superior region, having formed under the influence of a warm, humid climate in a region of subdued topography. We have determined the chemical variability among six samples of granitic protolith and found that such variability is inherited in the weathering profile. To minimize the effect of sample heterogeneity on various geochemical calculations, transformed compositions of saprolite and regolith were generated by obtaining linear least squares fits to the concentrations of SiO 2 , TiO 2 , Al 2 O 3 , and Zr through the weathering profile and summing the totals to 100%. Fortunately, use of measured or transformed compositions makes little difference in calculation of mass fluxes. However, transformed compositions allow for clearer comparisons among paleosols and are essential for determining certain paleosol parameters, such as Chemical Depletion Fraction. Calculations of Total and Reduced Mass Fluxes, Chemical Index of Alteration, Feldspar Index of Weathering, and Chemical Depletion Fraction demonstrate that the Baraboo paleosol is chemically more mature than the Paleoproterozoic Pronto and Cambrian Timna paleosols, but less mature than modern subtropical and tropical soils. Estimates of Mean Annual Temperature (MAT PPM ) and Mean Annual Precipitation (MAP PPM ) for Baraboo are 14.3 19.2 9.4 °C and 1177 1695 658 mm yr −1 , confirming the previous interpretation of a warm, humid climate. Although the level of atmospheric p CO 2 is poorly constrained due to the uncertainty in duration of weathering and possibility of regolith removal by erosion, p CO 2 is calculated to be ≥4.8 × Pre-Industrial Atmospheric Level (280 ppm) for 100,000 years of weathering, which is consistent with the p CO 2 level at 1.7 Ga predicted by the weak sun model. [ABSTRACT FROM AUTHOR]