Triple oxygen and hydrogen isotopes of gypsum hydration water for quantitative paleo-humidity reconstruction

© 2017 Elsevier B.V. Atmospheric relative humidity is an important parameter affecting vegetation yet paleo-humidity proxies are scarce and difficult to calibrate. Here we use triple oxygen (δ17O and δ18O) and hydrogen (δD) isotopes of structurally-bound gypsum hydration water (GHW) extracted from lacustrine gypsum to quantify past changes in atmospheric relative humidity. An evaporation isotope-mass-balance model is used together with Monte Carlo simulations to determine the range of climatological conditions that simultaneously satisfy the stable isotope results of GHW, and with statistically robust estimates of uncertainty. We apply this method to reconstruct the isotopic composition of paleo-waters of Lake Estanya (NE Spain) and changes in normalized atmospheric relative humidity (RHn) over the last glacial termination and Holocene (from ∼15 to 0.6 cal. kyrs BP). The isotopic record indicates the driest conditions occurred during the Younger Dryas (YD; ∼12–13 cal. kyrs BP). We estimate a RHnof ∼40–45% during the YD, which is ∼30–35% lower than today. Because of the southward displacement of the Polar Front to ∼42°N, it was both windier and drier during the YD than the Bølling–Allerød period and Holocene. Mean atmospheric moisture gradually increased from the Preboreal to Early Holocene (∼11 to 8 cal. kyrs BP, 50–60%), reaching 70–75% RHnfrom ∼7.5 cal. kyrs BP until present-day. We demonstrate that combining hydrogen and triple oxygen isotopes in GHW provides a powerful tool for quantitative estimates of past changes in relative humidity

Bayesian Inference for Structural Vector Autoregressions Identified by Markov-Switching Heteroskedasticity

In this study, Bayesian inference is developed for structural vector autoregressive models in which the structural parameters are identified via Markov-switching heteroskedasticity. In such a model, restrictions that are just-identifying in the homoskedastic case, become over-identifying and can be tested. A set of parametric restrictions is derived under which the structural matrix is globally or partially identified and a Savage-Dickey density ratio is used to assess the validity of the identification conditions. The latter is facilitated by analytical derivations that make the computations fast and numerical standard errors small. As an empirical example, monetary models are compared using heteroskedasticity as an additional device for identification. The empirical results support models with money in the interest rate reaction function.Comment: Keywords: Identification Through Heteroskedasticity, Bayesian Hypotheses Assessment, Markov-switching Models, Mixture Models, Regime Chang