ASA Models, Tools and Software

Consistent algorithm for linking distributed models under asymmetric information

The linkage algorithms solve the problem of linking models, e.g. sectorial and/or regional, into an inter-sectorial inter-regional integrated model. Linkage enables to avoid “hard linking” of models in a single code, which saves the programming time and enables parallel distributed computations of individual models instead of a large scale integrated model. Models linkage preserves the structure of the original models taking into account critically important details, which are usually missing in aggregate models More

Stochastic Quasigradient (SQG) methods: Applications

Stochastic Quasi-Gradient (SQG) methods have been developed for solving general optimization problems without exact calculation of objective function and constraints (let alone of their derivatives). SQG methods enable a sequential revision of approximate solutions towards the optimal using newly acquired information on the system, obtained via either direct on-line observations or(and) simulations.  More

Uncertainty in an Emissions Constrained World: Method Overview and Data Revision

The study by Jonas et al. (2014) “Uncertainty in an Emissions Constrained World” introduces the emissions-temperature-uncertainty (ETU) framework that allows any country to understand its near-term mitigation and adaptation efforts in a globally consistent and long-term context which includes all countries and stipulates global warming to range between 2 and 4 °C. The revised and updated data set supporting the ETU framework is the basis for analyzing greenhouse gas emission targets scaled from global to regional (here EU 27) to national levels (here Austria). More

Probabilistic approach to address temporal verification of changes in global net carbon emissions under the Kyoto Protocol

This study proposes an approach which permits assessing net emission changes under the Kyoto Protocol, in particular with respect to atmospheric CO2 and CO2 emissions from fossil fuel burning, cement manufacture and gas flaring; whereby emission changes are characterized by uncertainty distributions in terms of verification times (VTs).  More

Reconciling information from alternative sources

Studies of complex systems are non-separable from the analysis of partial and imprecise information received from alternative sources. A system analyst deals with a set of ensemble outcomes which needs to be integrated into one estimate in order to install the ensemble into the modelling chain or provide support for the informed decision making. More

Statistical analysis for spatial land use data

A prerequisite to the development of realistic models of land use change is the identification of the most important drivers of change. This tool gives an investigator a possibility to summarize the knowledge about interdependent spatial processes in the GIS lattice. Let alone, such a summary can help to draw substantive conclusions about the region under study. More

Uncertainty in an emissions-constrained world

This web-based database supports the Emissions, Temperature, Uncertainty (ETU) framework described by Jonas et al. (doi 10.1007/s10584-014-1103-6). The ETU framework allows any country to understand its national and near-term mitigation and adaptation efforts in a more realistic context, where uncertainty is taken into account. More

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Impact of Uncertainty on Compliance

This exercise allows a user to get a grip on the uncertainty in the emissions of greenhouse gases and understand its impact at the scale of countries on compliance (Track I: compliance mode) and the amount of emission permits that can be traded (Track II: monitoring mode)  under the Kyoto Protocol. More

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Last edited: 31 January 2019


Elena Rovenskaya

Program Director

Advancing Systems Analysis Program

T +43(0) 2236 807 608

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313