This workshop brings together natural scientists, social scientists and philosophers to discuss how uncertainties in science can best be communicated both among scientists and to public decision-makers. The main aim for the workshop is to review existing Uncertainty Guidances for treating uncertainties in science and public policy, leading to a new Uncertainty Guidance.
Speakers: Professor Leonard Smith and Dr Gavin Schmidt (NASA GISS)
Chair: Arthur Petersen (UCL)
Video (01:32:56)
The main objective was to help enhance the material already on the CELSIUS Wiki in the area of capital funding of DHC by looking in some detail at research and experience of both DHC itself and other infrastructure projects, as markets open and public-private partnerships become more prevalent. Key issues were the structuring of business models, the risk allocation and flexibility of contracts to make DHC projects attractive for investment, directly or via the creation of special funds and financial instruments. There was a lively discussion, and a summary of some current ideas will be consolidated into a paper which will be added to the Wiki and distributed more widely. The workshop can be thought of as one of a number of initiatives in the area of funding being coordinated as part of CELSIUS 2.
Modelling and simulation are an increasingly important part of modern science, especially in highly policy-relevant disciplines such as ecosystem modelling, natural hazards, and climate projection. Good practice in the use and interpretation of models is therefore vital, both for sound science and for informing evidence-based policy decisions. The workshop will present an overview of model evaluation methods, statistical inference for model output, and the use of models in risk management and decision-making, with the aim of exposing participants to methods and insights available in environmental modelling and encouraging critical evaluation of the approaches and methodologies used in their own research. The workshop will be structured around several themes, with facilitated discussion time and interactive problem-solving exercises, allowing participants to explore and understand the concepts presented by the expert lecturers. Participants will leave with an overview of the key issues of uncertainty in environmental modelling, an understanding of how these affect their own research methods and where to find expert guidance and further information. The course includes a poster session and practical exercises and is held this year in the inspiring surroundings of the Royal Society, in London.
Despite the fact that mathematical simulations are now common place in science, decision making, forward planning, policy, regulation, and litigation, the fundamental connections between a mathematical simulation and the empirical quantities of the world it targets remain vague and wishy-washy. The focus of this meeting is not so much how science and policy draw insights from the general behaviour of complicated simulation modelling, but rather on the mathematical foundation and empirical justification for quantitative interpretation of simulations for use in the real world, the design of computational experiments and model inter-comparisons, the quantitative comparison of simulation and observations under controlled lab conditions, and the end-to-end communication of information between all those involved. The final attendance list will determine the precise selection of topics in the small (~20) intense program, however we expect to include (a) clarifying the relationship between temperature measured by a thermometer or inferred from a satellite, and the variable of the same name in the numerical solution of a set of partial differential equations (on a finite grid), (b) the extent to which ensembles of simulations (whether over sets of initial conditions, parameter values, mathematical model structures, …) can be deployed/interpreted rationally as a probability distribution for the future quantitative measurements, (c) the improvement (specialization) of experimental design for “grand” ensemble experiments and model inter-comparison projects, and how that design might best differ depending on the target of the exercise, and (d) the quantitative contrast of simulation with observations of laboratory experiments under carefully controlled conditions.
This is the sister workshop to Evidence-based Decision Making in a New Climate (February 2016). A group of academics convened to address specifically the challenges raised by business and government participants in the first workshop.
How does your business use the latest scientific information to keep ahead of a changing climate? How do you make decisions based on that information? How could it be better tailored for your purposes? This workshop, based around the example of DECC’s 2050 Global Calculator, is an opportunity both to share best practice and to feedback your experiences, with the aim of improving the relevance of future scientific work for your business needs.
