Climate variability of the mid- and high-latitudes of the Southern Hemisphere in ensemble simulations from 1500 to 2000 AD

To increase the sparse knowledge of long-term Southern Hemisphere (SH) climate variability, we assess an ensemble of 4 transient simulations over the last 500 yr performed with a state-of-the-art atmosphere ocean general circulation model. The model is forced with reconstructions of solar irradiance, greenhouse gas (GHG) and volcanic aerosol concentrations. A 1990 control simulation shows that the model is able to represent the Southern Annular Mode (SAM), and to some extent the South Pacific Dipole (SPD) and the Zonal Wave 3 (ZW3). During the past 500 yr we find that SPD and ZW3 variability remain stable, whereas SAM shows a significant shift towards its positive state during the 20th century. Regional temperatures over South America are strongly influenced by changing both GHG concentrations and volcanic eruptions, whereas precipitation shows no significant response to the varying external forcing. For temperature this stands in contrast to proxy records, suggesting that SH climate is dominated by internal variability rather than external forcing. The underlying dynamics of the temperature changes generally point to a combination of several modes, thus, hampering the possibilities of regional reconstructing the modes from proxy records. The linear imprint of the external forcing is as expected, i.e. a warming for increase in the combined solar and GHG forcing and a cooling after volcanic eruptions. Dynamically, only the increase in SAM with increased combined forcing is simulated.

Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers

The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed.

An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections

An Ensemble Kalman Filter is applied to assimilate observed tracer fields in various combinations in the Bern3D ocean model. Each tracer combination yields a set of optimal transport parameter values that are used in projections with prescribed CO2 stabilization pathways. The assimilation of temperature and salinity fields yields a too vigorous ventilation of the thermocline and the deep ocean, whereas the inclusion of CFC-11 and radiocarbon improves the representation of physical and biogeochemical tracers and of ventilation time scales. Projected peak uptake rates and cumulative uptake of CO2 by the ocean are around 20% lower for the parameters determined with CFC-11 and radiocarbon as additional target compared to those with salinity and temperature only. Higher surface temperature changes are simulated in the Greenland–Norwegian–Iceland Sea and in the Southern Ocean when CFC-11 is included in the Ensemble Kalman model tuning. These findings highlights the importance of ocean transport calibration for the design of near-term and long-term CO2 emission mitigation strategies and for climate projections.

Transient Earth system responses to cumulative carbon dioxide emissions: linearities, uncertainties, and probabilities in an observation-constrained model ensemble

Information on the relationship between cumulative fossil CO2 emissions and multiple climate targets is essential to design emission mitigation and climate adaptation strategies. In this study, the transient response of a climate or environmental variable per trillion tonnes of CO2 emissions, termed TRE, is quantified for a set of impact-relevant climate variables and from a large set of multi-forcing scenarios extended to year 2300 towards stabilization. An  ∼ 1000-member ensemble of the Bern3D-LPJ carbon–climate model is applied and model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte Carlo-type framework. Uncertainties in TRE estimates include both scenario uncertainty and model response uncertainty. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.9 °C (68 % confidence interval (c.i.): 1.3 to 2.7 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and a steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic meridional overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The constrained model ensemble is also applied to determine the response to a pulse-like emission and in idealized CO2-only simulations. The transient climate response is constrained, primarily by long-term ocean heat observations, to 1.7 °C (68 % c.i.: 1.3 to 2.2 °C) and the equilibrium climate sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.

Georges Haenni mit dem Ensemble "Chanson valaisanne", Gruppenbildnis, Ganzfigurbildnis, 1966

Signatur des Originals: S 36/F12069