Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change

We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal. © 2018 The Author

Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change

We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal

A Feature Model of Coupling Technologies for Earth System Models

Couplers that link together two or more numerical simulations are well-known abstractions in the Earth System Modeling (ESM) community. In the past decade, reusable software assets have emerged to facilitate scientists in implementing couplers. While there is a large amount of overlap in the features supported by software coupling technologies, their implementations differ significantly in terms of both functional and non-functional properties. Using a domain analysis method called feature analysis, we explore the spectrum of features supported by coupling technologies used to build today's production ESMs. The results of the feature analysis will enable automatic code generation of ESM couplers

Towards A Grid Infrastructure For Hydro-Meteorological Research

The Distributed Research Infrastructure for Hydro-Meteorological Study (DRIHMS) is a coordinatedaction co-funded by the European Commission. DRIHMS analyzes the main issuesthat arise when designing and setting up a pan-European Grid-based e-Infrastructure for researchactivities in the hydrologic and meteorological fields. The main outcome of the projectis represented first by a set of Grid usage patterns to support innovative hydro-meteorologicalresearch activities, and second by the implications that such patterns define for a dedicatedGrid infrastructure and the respective Grid architecture

Phenomenological Review on Quark-Gluon Plasma: Concepts vs. Observations

In this review, we present an up-to-date phenomenological summary of research developments in the physics of the Quark--Gluon Plasma (QGP). A short historical perspective and theoretical motivation for this rapidly developing field of contemporary particle physics is provided. In addition, we introduce and discuss the role of the quantum chromodynamics (QCD) ground state, non-perturbative and lattice QCD results on the QGP properties, as well as the transport models used to make a connection between theory and experiment. The experimental part presents the selected results on bulk observables, hard and penetrating probes obtained in the ultra-relativistic heavy-ion experiments carried out at the Brookhaven National Laboratory Relativistic Heavy Ion Collider (BNL RHIC) and CERN Super Proton Synchrotron (SPS) and Large Hadron Collider (LHC) accelerators. We also give a brief overview of new developments related to the ongoing searches of the QCD critical point and to the collectivity in small ($p+p$ and $p+A$) systems.Comment: 64 pages, 29 figures; a new subsection 4.4.2 and a few references have been added; minor changes; published versio

Performance of distributed multiscale simulations

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption

Foundations of distributed multiscale computing: Formalization, specification, and analysis

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Multiscale computing with the multiscale modeling library and runtime environment

We introduce a software tool to simulate multiscale models: The Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We present MUSCLE 2's runtime features, such as its distributed computing capabilities, and its benefits to multiscale modelers. We also describe two multiscale models that use MUSCLE 2 to do distributed multiscale computing: An in-stent restenosis and a canal system model. We conclude that MUSCLE 2 is a notable improvement over the previous version of MUSCLE, and that it allows users to more flexibly deploy simulations of multiscale models, while improving their performance. © 2013 The Authors. Published by Elsevier B.V

Managing uncertainty in integrated environmental modelling:the UncertWeb framework

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks currently offer no support for managing uncertainty. On the other hand, the rich array of modelling frameworks and simulation tools which support uncertainty propagation in complex and chained models typically lack the benefits of web based solutions such as ready publication, discoverability and easy access. In this article we describe the developments within the UncertWeb project which are designed to provide uncertainty support in the context of the proposed ‘Model Web’. We give an overview of uncertainty in modelling, review uncertainty management in existing modelling frameworks and consider the semantic and interoperability issues raised by integrated modelling. We describe the scope and architecture required to support uncertainty management as developed in UncertWeb. This includes tools which support elicitation, aggregation/disaggregation, visualisation and uncertainty/sensitivity analysis. We conclude by highlighting areas that require further research and development in UncertWeb, such as model calibration and inference within complex environmental models