Decision support systems for stored water quality: 2. An example application

The components of an environmental decision support system (EDSS) were outlined in Part 1 of this paper. Here, an example application is given using a range of data from the database in order to assess the utility of one specific model chosen from the modelbase: the one-dimensional thermal stratification model, EDD1. The model is applied to a range of lake types worldwide.     

Development and application of “U.S.E.D.”: A hydroclimate lake stratification model

Two model types are currently in use to model the thermal stratification cycle in lakes and reservoirs: the eddy diffusion and the mixed layer (or integral energy) approaches. Here the former is analysed and developments are proposed to remove the empiricisms previously implicit in these models. These discussions permit the reformulation of K_H0 independently of current shear, together with an expression for R_i. The deduced formulae are in good agreement with observations. The newly formulated model (the University of Salford eddy diffusion model, U.S.E.D.) is subsequently used in simulations of lakes and reservoirs at different latitudes which are found to be in good agreement with observations without requiring inter-site calibration.     

Verification of the plume rise/dispersion model USPR: plume rise for single stack emissions

Despite proliferation of the use of air pollution models for regulatory application, major discrepancies still occur between models and also between models and observations, especially when oversimplistic models are used. The problem of predicting plume rise (and subsequently ground level concentrations) from a single source is evaluated here in terms of an integral plume rise and dispersion model (USPR) which encompasses both bouyant rise and turbulent spreading; thus avoiding the problems of the concatenation of separate plume rise and dispersion models. The wide range of validity of the USPR model is demonstrated is terms of plume rise by comparison with the highly buoyant GCOS and Kincaid plumes as well as with dense effluents. It is also shown to be in agreement with Briggs' two-thirds law when the restrictions applicable to the latter model are imposed.     

Can we integrate climatic modelling and assessment?

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.     

Ground based radon-222 observations and their application to atmospheric studies

The aim of this paper is to review recent trends in the application of ground based radon observations to atmospheric research. In spite of over four decades of atmospheric radon monitoring, only in the past decade has the potential of this passive tracer been realised through a series of atmospheric model evaluation studies. Firstly, the key operational requirements for baseline radon detectors are briefly discussed, including lower limit of detection and response time. Then, current radon-related benchmarks for the evaluation of regional and global models are reviewed, with particular consideration given to the implications of data availability, resolution, site location and model spatial/temporal resolution. An 8-year subset of radon observations from the Cape Grim Baseline Air Pollution Station is used to suggest new benchmarks that exploit long-term data sets. Lastly an overview is presented of a technique that uses radon to estimate regional fluxes of climatically sensitive gases, with specific examples for CO2, CH4 and N2O.     

Climate Modelling,Uncertainty and Responses to Predictions of Change

Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by,inter alia, incorporating climate change risk assessment into development planning processes i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (or, better, adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. The urgent issue is the mismatch between the predictions ofglobal climatic change and the need for information onlocal to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. Moreover, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. Unfortunately, climate models cannot yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes.