Validation of surface fluxes in climate simulations of the Arctic with the regional model REMO

To study the variability of the thermohaline circulation in the North Atlantic on decadal time scales, the atmospheric regional model REMO is currently investigated as a component of a fully-coupled atmosphere–ice–ocean model for the Arctic/North Atlantic. A comparison of a 5-year uncoupled simulation of the regional model with a 5-year NCEP/NCAR reanalysis period is carried out in order to assess the performance of the regional model in polar and subpolar regions. The model simulates basic structures realistically. It performs well in middle latitudes but shows some problems in the region of the marginal ice zone and in continental regions with extreme temperature amplitudes. The high elevations of Greenland in the central part of the model domain give rise to problems in the model dynamics, resulting in moderate deviations from NCEP/NCAR reanalysis

Detecting semantic social engineering attacks with the weakest link: Implementation and empirical evaluation of a human-as-a-security-sensor framework

The notion that the human user is the weakest link in information security has been strongly, and, we argue, rightly contested in recent years. Here, we take a step further showing that the human user can in fact be the strongest link for detecting attacks that involve deception, such as application masquerading, spearphishing, WiFi evil twin and other types of semantic social engineering. Towards this direction, we have developed a human-as-a-security-sensor framework and a practical implementation in the form of Cogni-Sense, a Microsoft Windows prototype application, designed to allow and encourage users to actively detect and report semantic social engineering attacks against them. Experimental evaluation with 26 users of different profiles running Cogni-Sense on their personal computers for a period of 45 days has shown that human sensors can consistently outperform technical security systems. Making use of a machine learning based approach, we also show that the reliability of each report, and consequently the performance of each human sensor, can be predicted in a meaningful and practical manner. In an organisation that employs a human-as-a-security-sensor implementation, such as Cogni-Sense, an attack is considered to have been detected if at least one user has reported it. In our evaluation, a small organisation consisting only of the 26 participants of the experiment would have exhibited a missed detection rate below 10%, down from 81% if only technical security systems had been used. The results strongly point towards the need to actively involve the user not only in prevention through cyber hygiene and user-centric security design, but also in active cyber threat detection and reporting

The impact of Greenland's deglaciation on the Arctic circulation

The influence of Greenland's deglaciation on the atmospheric winter and summer circulation of the Arctic have been quantified with the high resolution regional atmospheric model HIRHAM4. Greenland's deglaciation exerts a pronounced influence on the atmospheric winter circulation of the Arctic. The land areas over Siberia and the Canadian archipelago are warmed by up to 5C. Parts of the Atlantic and the Arctic Ocean are cooled by up to 3C. A north-eastward shift of the storm tracks occurs over the North Atlantic as well as an increase of synoptic activity over Alaska. The pronounced P-E changes connected with shifts in the synoptic storm tracks during winter would have important consequences for the atmospheric freshwater input into the Arctic Ocean and the Nordic sea with the potential to cause variability in the Arctic Ocean dynamics on centennial to millennial time scales. The significant differences between simulations with and without Greenland result in a decrease of the geopotential height and a dominant barotropic response of the Arctic atmosphere. These changes correspond to an enhanced winter polar vortex and stratospheric conditions more favorable for large Arctic ozone losses

Intercomparison of Arctic regional climate simulations: Case studies of January and June 1990

Advances in regional climate modelling must be strongly based on analysis of physical processes in comparisonwith data. In a data-poor region such as the Arctic, this procedure may be enhanced by a community-basedapproach, that is, though collaborative analysis by several research groups. To illustrate this approach,simulations were performed with two regional climate models HIRHAM and ARCSyM, over the Arctic basin to65oN, laterally driven at the boundaries by observational analyses. It was found that both models are able toreproduce reasonably the main features of the large-scale flow and the surface parameters in the Arctic. Distinctdifferences in the simulations can be attributed to specific characteristics of the boundary layer and surfaceparameterizations which result in surface flux differences, and to the lateral moisture forcing, both of which affectmoisture availability in the atmosphere. Further disparities are associated with the additional degrees of freedomallowed in the coupled model ARCSyM. Issues of model configuration and experimental design are discussed,including domain size, grid spacing, boundary formulations, model initialization and spinup, and ensemble approaches. In order to reach definitive conclusions in a regional climate model intercomparison, ensemble simulationswith adequate spin-up and equivalent initialization of surface fields will be required