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The increasing concerns of clients, particularly in online commerce, plus the impact of legislations on information security have compelled companies to put more resources in information security. As a result, senior managers in many organizations are now expressing a much greater interest in information security. However, the largest body of research related to preventing breaches is technical, focusing on such issues as encryption and access control. In contrast, research related to the economic aspects of information security is small but rapidly growing. The goal of this technical note is twofold: i) to provide the reader with an structured overview of the economic approaches to information security and ii) to identify potential research directions.

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850–1900, using an observationally based historical warming estimate of 0.8°C between 1850–1900 and 1995–2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above preindustrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections. ; ARC Centre of Excellence for Climate Extremes CE170100023 United States Department of Energy (DOE) Aparece en contenido como:U.S. Department of Energy, Office of Science, research in MultiSector Dynamics, Earth and Environmental System Modeling Program NERC/IIASA Collaborative Research Fellowship NE/T009381/1 Integrated Research Program for Advancing Climate Models (TOUGOU), Grant from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan JPMXD0717935457 U.S. National Aeronautics and Space Administration Climate Indicators and Data Products for Future National Climate Assessments program NX16AG34G European Union's Horizon 2020 research and innovation programme 820829 ; Versión publicada - versión final del editor