Climate scenario development

Statistical downscaling and bias correction are becoming standard tools in climate impact studies. This book provides a comprehensive reference to widely-used approaches, and additionally covers the relevant user context and technical background, as well as a synthesis and guidelines for practitioners. It presents the main approaches including statistical downscaling, bias correction and weather generators, along with their underlying assumptions, skill and limitations. Relevant background information on user needs and observational and climate model uncertainties is complemented by concise introductions to the most important concepts in statistical and dynamical modelling. A substantial part is dedicated to the evaluation of regional climate projections and their value in different user contexts. Detailed guidelines for the application of downscaling and the use of downscaled information in practice complete the volume. Its modular approach makes the book accessible for developers and practitioners, graduate students and experienced researchers, as well as impact modellers and decision makers.

Statistical Downscaling and Bias Correction for Climate Research

Integrated environmental assessment is a booming field. Its intellectual challenges, its relevance for real life problems, and its generous financial support have attracted many researchers who either assess the environment in an integrated manner, or purport or pretend to do so. This has led to a wide and diverse range of research and policy activities, all sharing the nominator of integrated environmental assessment. This paper has a twofold objective. Firstly, it discusses the main approaches to Integrated Environmental Assessment (IEA). IEA is meant to deliver usable (scientific) knowledge to environmental policy making. In order to achieve its goal, IEA frequently uses an integrated assessment modelling approach, but it may also use a participatory approach. Modelling and participatory approaches are sometimes considered irreconcilable, since they are different in scope, use different kinds of methods and may even be based on conflicting epistemologies. However, as this paper will argue, they are increasingly recognised as mutual reinforcing approaches. They need each other in order to improve decision making on complex environmental issues by identifying, using and integrating a broad body of knowledge available from different sources. Therefore, the second objective of this paper is to show the mutual interdependence of participatory and modelling approaches in assisting policy-making. It thereby gives special attention to the various goals and functions of IEA. The contributions of IEA to science are beyond the scope of this paper. Section 2 defines the concept of integrated assessment and explores its possible goals and functions in assisting environmental policy-making. Sections 3 and 4 succinctly provide an overview of approaches to integrated assessment. The authors, working in both fields of IEA, have tried not to hide the mutual differences. Especially the strengths and weaknesses of each approach in assisting environmental policy-making are assessed. Section 3 introduces and explains integrated assessment modelling, while section 4 focuses on participatory integrated assessment. Section 5 takes a different angle in assessing the strengths and weaknesses of modelling and participatory approaches. It discusses three examples of what may go wrong if either one of the approaches stands alone. Section 6 presents conclusions as regards possibilities for combining modelling and participation in IEA.

The relevance of participatory approaches in integrated environmental assessment

A b s t r a c t : Regional climate prediction is not an insoluble problem, but it is a pro b l e m characterized by inherent uncertainty. There are two sources of this uncertainty: the unpredictability of the climatic and global systems. The climate system is rendered unpredictable by deterministic chaos; the global system renders climate prediction uncertain through the unpredictability of the external forcings imposed on the climate system. It is commonly inferred from the differences between climate models on regional scales that the models are deficient, but climate system unpredictability is such that this inference is premature; the differences are due to an unresolved combination of climate system unpredictability and model deficiencies. Since model deficiencies are discussed frequently and the two sources of inherent uncertainty are discussed only rarely, this review considers the implications of climatic and global system unpredictability for regional climate prediction. Consequently we regard regional climate prediction as a cascade of uncertainty, rather than as a single result process sullied by model deficiencies. We suggest three complementary methodological approaches: (1) the use of multiple forcing scenarios to cope with global system unpredictability; (2) the use of ensembles to cope with climate system unpredictability; and (3) the consideration of the entire response of the climate system to cope with the nature of climate change. We understand regional climate change in terms of changes in the general circulations of the atmosphere and oceans; so we illustrate the role of uncertainty in the task of regional climate prediction with the behaviour of the North Atlantic thermohaline circulation. In conclusion we discuss the implications of the uncertainties in regional climate prediction for research into the impacts of climate change, and we recognize the role of feedbacks in complicating the relatively simple cascade of uncertainties presented here.

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Predicting regional climate change: living with uncertainty:

The increasing mutual interplay between social, economic, and environmental issues demands integrated policies. Despite an early history of isolated regulatory initiatives related to for instance air, water, and soil over the past two decades, environmental policies have become increasingly integrated. Nevertheless, this is only a first step towards further integration of environmental, social and economic policies. The complexity of the pressing issues, like global climate change, demands an integrated approach to ensure that key interactions, feedbacks and effects are not inadvertently omitted from the analysis. The various pieces of the complex puzzle can no longer be examined in isolation. Integrated Assessment (IA) aims to fit the pieces of the puzzle together, thereby indicating priorities for policy.

Integrated Assessment Modelling

The climatic change “debate” seems to be expanding faster than the available information base. National and international response strategies (mitigation and adaptation) are being discussed in board rooms, governments and the media. Phrases like “the uncertainty in the scenarios” appear to carry meaning but the information seems to be, at best, incomplete and, at worst, totally debased by multiple definitions and usages. “Scenarios” are predictions of possible futures. The “(un)certainty” that characterizes them encompasses prejudices, perspectives, incompleteness of information as well as the differences in completeness, accuracy and sensitivity of different forecasting tools. (Un)certainty is the source of experimentation and learning but excessive (un)certainty is noise and so the search for a signal requires its reduction. This reduction process can both promote planning and co-ordination but also quash unconventional, but ultimately valuable, ideas. Balancing this tension across the modern, multifaceted climatic “divisions” of technology, training, information access, understanding, terminology, economic development, societal flexibility and social and political perceptions is difficult. The current dysfunctioning of the international climatic information “industry” demands improved communication among these diverse communities. This paper discusses some of the difficulties as perceived by a physical scientist turned “gatekeeper” and proposes a twofold strategy for improving the situation: a climatic change information exchange and an explicit recognition of the need for cyclic social co-operation among the participating groups.

A. Henderson-Sellers

Papers

Can we integrate climatic modelling and assessment