Oxygen isotope ratios (18O/16O) of hemicellulose-derived sugar biomarkers in plants, soils and sediments as paleoclimate proxy II: insight from a climate transect study

The oxygen isotopic composition of precipitation (δ18Oprec) is well known to be a valuable (paleo-)climate proxy. Paleosols and sediments and hemicelluloses therein have the potential to serve as archives recording the isotopic composition of paleoprecipitation. In a companion paper (Zech et al., 2014) we investigated δ18Ohemicellulose values of plants grown under different climatic conditions in a climate chamber experiment. Here we present results of compound-specific δ18O analyses of arabinose, fucose and xylose extracted from modern topsoils (n = 56) along a large humid-arid climate transect in Argentina in order to answer the question whether hemicellulose biomarkers in soils reflect δ18Oprec. The results from the field replications indicate that the homogeneity of topsoils with regard to δ18Ohemicellulose is very high for most of the 20 sampling sites. Standard deviations for the field replications are 1.5‰, 2.2‰ and 1.7‰, for arabinose, fucose and xylose, respectively. Furthermore, all three hemicellulose biomarkers reveal systematic and similar trends along the climate gradient. However, the δ18Ohemicellulose values (mean of the three sugars) do not correlate positively with δ18Oprec (r = −0.54, p < 0.014, n = 20). By using a Péclet-modified Craig-Gordon (PMCG) model it can be shown that the δ18Ohemicellulose values correlate highly significantly with modeled δ18Oleaf water values (r = 0.81, p < 0.001, n = 20). This finding suggests that hemicellulose biomarkers in (paleo-)soils do not simply reflect δ18Oprec but rather δ18Oprec altered by evaporative 18O enrichment of leaf water due to evapotranspiration. According to the modeling results, evaporative 18O enrichment of leaf water is relatively low (∼10‰) in the humid northern part of the Argentinian transect and much higher (up to 19‰) in the arid middle and southern part of the transect. Model sensitivity tests corroborate that changes in relative air humidity exert a dominant control on evaporative 18O enrichment of leaf water and thus δ18Ohemicellulose, whereas the effect of temperature changes is of minor importance. While oxygen exchange and degradation effects seem to be negligible, further factors needing consideration when interpreting δ18Ohemicellulose values obtained from (paleo-)soils are evaporative 18O enrichment of soil water, seasonality effects, wind effects and in case of abundant stem/root-derived organic matter input a partial loss of the evaporative 18O enrichment of leaf water. Overall, our results prove that compound-specific δ18O analyses of hemicellulose biomarkers in soils and sediments are a promising tool for paleoclimate research. However, disentangling the two major factors influencing δ18Ohemicellulose, namely δ18Oprec and relative air humidity controlled evaporative 18O enrichment of leaf water, is challenging based on δ18O analyses alone.

Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain

Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a set-up of the Weather Research and Forecasting Model (WRF) model that minimises system- atic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable set-up: the horizontal resolution, the planetary boundary layer (PBL) parameterisation scheme and the way the WRF is nested to the driving data set. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model set-ups, but sharing the same driving data set. The results show that the lack of representation of the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis nudging, spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model performance is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.