A simple model perturbed physics study of the simulated climate sensitivity uncertainty and its relation to control climate biases

In this study the relationship between climate model biases in the control climate and the simulated climate sensitivity are discussed on the basis of perturbed physics ensemble simulations with a globally resolved energy balance (GREB) model. It is illustrated that the uncertainties in the simulated climate sensitivity (estimated by the transient response to CO₂ forcing scenarios in the twenty first century or idealized 2 × CO₂ forcing experiments) can be conceptually split into two parts: a direct effect of the perturbed physics on the climate sensitivity independent of the control mean climate and an indirect effect of the perturbed physics by changing the control mean climate, which in turn changes the climate sensitivity, as the climate sensitivity itself is depending on the control climate. Biases in the control climate are negatively correlated with the climate sensitivity (colder climates have larger sensitivities), if no physics are perturbed. Perturbed physics that lead to warmer control climate, would in average also lead to larger climate sensitivities, if the control climate is held at the observed reference climate by flux corrections. Thus the effects of control biases and perturbed physics are opposing each other and are partially cancelling each other out. In the GREB model the biases in the control climate are the more important effect for the regional climate sensitivity uncertainties, but for the global mean climate sensitivity both, the biases in the control climate and the perturbed physics, are equally important.     

Plagioclase preferred orientation by TOF neutron diffraction and SEM-EBSD

The lattice preferred orientation (LPO) of an anorthosite (composed of andesine) sampled from a highly deformed anorthositic mylonite (Grenville Province, Quebec) was measured by TOF neutron diffraction and SEM-EBSD. The quantitative texture analysis of neutron data was accomplished by using the Rietveld texture analysis with the WIMV algorithm, implemented in the program package Materials Analysis Using Diffraction (MAUD). The texture calculations of the EBSD data were performed by using the program BEARTEX. Analyses from neutron and electron diffraction data gave similar results if EBSD data are smoothed to account for grain statistics. The principal pole figures show (010) roughly parallel to the rock foliation, (001) poles exhibiting a low angle (25°) to the pole to foliation, and (100) poles close to the Y-direction (perpendicular to the lineation and foliation pole). The [100] crystallographic direction shows a maximum in the lineation direction, [010] directions concentrate near the foliation pole. The geological deformation conditions and the constructed pole figure patterns indicate that the preferred orientation could be attributed to intracrystalline slip dominantly on (010) with [100] as slip direction. Elastic properties, calculated by averaging, document weak anisotropy that has implications for the seismic structure of the lower crust.     

A Dynamic Model to Simulate Arsenic,Lead, and Mercury Contamination in the Terrestrial Environment During Extreme Floods of Rivers

Beside damages of infrastructure in industrial regions, extreme floods can cause contamination with particle‐bound pollutants, e. g., due to erosion of soils and sediments. In order to predict contamination with inorganic pollutants, the transport and fate of arsenic, lead, and mercury during a fictive flood event of River Vereinigte Mulde in the region of Bitterfeld (Germany) with 200 years recurrence time was modeled. The finite element model system Telemac2D, which is subdivided into a hydrodynamic (Telemac‐2D), a transport (Subief‐2D), and a water quality module (wq2subief) was applied. The transport and water quality model models were calibrated using results of sediment trap exposures in the floodplain of River Vereinigte Mulde. Model results exhibited that the spatial patterns of particle‐associated arsenic and lead concentrations significantly changed. Extended, mostly agriculturally used areas showed arsenic and lead concentrations between 150 and 200 mg kg^–1 and 250 and 300 mg kg^–1, respectively, while urban areas were to a great extent spared from high contamination with arsenic and lead. Concentrations of particle‐associated mercury showed a pattern distinct from those of arsenic and lead. Outside of small patches with concentrations up to 63 mg kg^–1, concentrations of particle‐associated mercury remained close to zero. Differences in the spatial patterns of the three pollutants regarded mainly arise from significantly different initial and boundary conditions. Sensitivity analyses of initial and boundary conditions revealed a high sensitivity of particle‐bound pollutant concentrations, whereas the sensitivities of concentrations of suspended sediments and soluble pollutants were mediocre to negligible.     

A Dynamic Model to Simulate Spills of Fuel and Diesel Oil in the Terrestrial Environment during Extreme Fluvial Floods

Extreme fluvial floods may cause severe contamination with fuel oil and diesel, originating from gasoline pipes and tanks in private households and industrial areas, respectively. Geo‐referenced oil spills in the region of Bitterfeld (Germany) after extreme flood events, such as in August 2002, were simulated using the two‐dimensional (2D) Finite Element model system Telemac2D, which is subdivided into a hydrodynamic (Telemac‐2D) and a transport module (Subief2D). Fuel oil settled via adhesion showed a thickness of less than 1.0 mm. Fuel oil concentrations on the flood wave amounted up to 80 g m^–3 in the vicinity of the point sources. At a distance of several hundred meters downstream of the point sources, the fuel oil concentrations were calculated to be zero. Settled areas were only partially contaminated with fuel oil. While one village experienced severe oil contamination, the town of Bitterfeld was almost unaffected by oil spills. It was demonstrated that the 2D transport model applied is capable of simulating fuel oil spills during extreme high waters in the terrestrial environment. Such simulations of fuel oil spills will feed into a GIS‐based decision support system of flood protection.     

An objective analysis of the observed spatial structure of the tropical Indian Ocean SST variability

The observed interannual Indian Ocean sea surface temperature (SST) variability from 1950 to 2008 is analyzed in respect to the spatial structure of the variability. The analysis is based on an objective comparison of the leading empirical orthogonal function modes against the stochastic null hypothesis of spatial red noise (isotropic diffusion). Starting from this red noise assumption, the analysis searches for those structures that are most distinct from the red noise hypothesis. This objective approach will put previously well and less known modes of variability into the context of the multivariate SST variability. The Indian Ocean SST variability is marked by relatively weak SST variability, which is strongly dominated by a basin wide monopole pattern that is caused by different processes. The leading modes of variability are the El Nino Southern Oscillation (ENSO) variability and the warming trend, which both project onto the basin wide monopole structure. Other more characteristic spatial patterns of internal variability are much less dominant in the tropical Indian Ocean, which is quite different from all other ocean basin, where characteristic teleconnection patterns exist. The remaining, ENSO independent, detrended variability is dominated by multi-pole patterns from the southern Indian Ocean reaching into the tropical Indian Ocean, which are probably primarily caused by extra-tropical atmospheric forcings. The large scale tropical Indian Ocean internal variability itself has no dominant structure. The currently often used dipole mode index (DMI) does not appear to present a dominant teleconnection pattern of the Indian Ocean internal SST variability. In the context of the objective analysis presented here, the DMI partly reflects the ENSO variability and is also a representation of the multi-dimensional, chaotic spatial red noise (isotropic diffusion) process. As such the DMI cannot be interpreted as a coherent teleconnection between the two poles.