A Critical Evaluation of Post-Normal Science's role in Climate Change Modelling and Political Decision-Making
Cargando...
Fecha
Autores
Título de la revista
Publicado en
Publicado por
Universidad El Bosque
URL de la fuente
Enlace a contenidos multimedia
ISSN de la revista
Título del volumen
Resumen
Descripción
Earth System Modelling is a modern approach for studying the complexity of the world and has become integral to the environmental and climate change discourse. It has enabled the possibility of research into areas previously unreachable and has led to the discovery of some of the most complex phenomena on the planet such as Chaos Theory. The exponential growth of computer capabilities has led to an impressive advance in the recognition of complexity and uncertainty. It has also opened up the path for a new scientific paradigm, post normal science. Decisions increasingly have to be made within this framework. Incomplete or poorly understood information provided by models is, despite modelling uncertainties, increasingly dictating the frontiers and interface of science and politics. Modelling, like any tool, has its advantages and disadvantages. This paper critically evaluates, through a comprehensive literature review, some of the benefits, limitations and controversies that surround models and questions their utilisation in the scientific quest for “truth” within the climate change debate. It also looks into the future of climate modelling and post normal science based decision making for a sustainable world.
Earth System Modelling is a modern approach for studying the complexity of the world and has become integral to the environmental and climate change discourse. It has enabled the possibility of research into areas previously unreachable and has led to the discovery of some of the most complex phenomena on the planet such as Chaos Theory. The exponential growth of computer capabilities has led to an impressive advance in the recognition of complexity and uncertainty. It has also opened up the path for a new scientific paradigm, post normal science. Decisions increasingly have to be made within this framework. Incomplete or poorly understood information provided by models is, despite modelling uncertainties, increasingly dictating the frontiers and interface of science and politics. Modelling, like any tool, has its advantages and disadvantages. This paper critically evaluates, through a comprehensive literature review, some of the benefits, limitations and controversies that surround models and questions their utilisation in the scientific quest for “truth” within the climate change debate. It also looks into the future of climate modelling and post normal science based decision making for a sustainable world.
Earth System Modelling is a modern approach for studying the complexity of the world and has become integral to the environmental and climate change discourse. It has enabled the possibility of research into areas previously unreachable and has led to the discovery of some of the most complex phenomena on the planet such as Chaos Theory. The exponential growth of computer capabilities has led to an impressive advance in the recognition of complexity and uncertainty. It has also opened up the path for a new scientific paradigm, post normal science. Decisions increasingly have to be made within this framework. Incomplete or poorly understood information provided by models is, despite modelling uncertainties, increasingly dictating the frontiers and interface of science and politics. Modelling, like any tool, has its advantages and disadvantages. This paper critically evaluates, through a comprehensive literature review, some of the benefits, limitations and controversies that surround models and questions their utilisation in the scientific quest for “truth” within the climate change debate. It also looks into the future of climate modelling and post normal science based decision making for a sustainable world.
Abstract
Palabras clave
Post-Normal Science, Climate Change, Complexity, Modelling, Policy, Uncertainty
