Modeling the oxygen 18 concentration in precipitation with ambient climatic and geographic parameters

Abstract

Recent exploratory analysis of a data set from the Austrian Network of Isotopes in Precipitation (ANIP) together with climatic data revealed significant correlations between isotopic compositions in precipitation and climatic conditions (A. Liebminger et al., 2006). Based on these results multivariate models have been developed in order to predict the oxygen 18 concentration from local climatic and geographic parameters. The best two models are applied to 201 new locations for which long term climatic and geographic parameters are available. The resulting modeled oxygen 18 values exhibit good compliance with known correlations of oxygen 18 with temperature and altitude. Isotope distribution charts lead to a reasonable picture of the distribution of oxygen 18 in Austrian precipitation.

Spatially interpolated time series of δ18Ο in Eastern Mediterranean precipitation

“…When data are organized according to climatic type though, latitude and elevation become significant regressors again, and precipitation amount appears to be a significant regressor for desert type areas. This is more or less in line with the findings of Liebminger et al (2006) for Austria, according to which temperature is not among the important regressors, while precipitation and humidity were more dominant during the warmer seasons.…”

“…Most of these data sets were constructed according to the BW method that uses solely geographical and topographical regressors. On a country scale, Dutton et al (2005) produced a 0.5°× 0.5°grid for river and precipitation waters across the USA, while Liebminger et al (2006) showed that on a local scale, the inclusion of longitude as well as meteorological regressors improved the performance of the isotopic models. Including meteorological variables in an attempt to generate gridded isotopic data for the precipitation in Eastern and Central Mediterranean at a 10' × 10' resolution, was not an improvement over the simple BW model (Lykoudis and Argiriou, 2007).…”

Calibrating climate‐δ18O regression models for the interpretation of high‐resolution speleothem δ18O time series

“…The oxygen isotopic ratio ( δ 18 O) in terrestrial archives such as ice cores, speleothems and tree rings, is typically interpreted as a proxy of past rainfall and/or temperature based on a local regression model or “calibration” [e.g., Hendy and Wilson , 1968; Jouzel et al , 1997; Treble et al , 2005a; Danis et al , 2006; Lachniet and Patterson , 2006; Liebminger et al , 2006]. These calibrations, though, are recognized to be problematic because δ 18 O in precipitation also depends on source conditions, water vapor advection and mixing, and storm trajectories [ Noone and Simmonds , 2002; Yoshimura et al , 2003; Treble et al , 2005b; Fischer and Sturm , 2006; Schneider and Noone , 2007], and these factors may be unrelated to the temperature and rainfall at the site of the terrestrial archive.…”

Gridded data set of the stable isotopic composition of precipitation over the eastern and central Mediterranean

“…The finer‐resolution data sets were constructed based on a methodology introduced by Bowen and Wilkinson [2002], involving a regression isotopic model based solely on geographical and topographical regressors and the subsequent interpolation of the residuals. On a country scale, the inclusion of meteorological regressors in the isotopic models, along with the geographical and topographical one, has improved their predictive ability [ Liebminger et al , 2006]. In this work we investigate whether the inclusion in a regression isotopic model of widely available meteorological variables, mainly temperature, precipitation, and vapor pressure, would improve the results of a gridding procedure according to Bowen and Wilkinson [2002].…”