Extreme events and ecological forecasting

Almost all extreme events lasting less than several weeks that significantly impact ecosystems are weather related. This review examines the response of estuarine systems to intense short-term perturbations caused by major weather events such as hurricanes. Current knowledge concerning these effects is limited to relatively few studies where hurricanes and storms impacted estuaries with established environmental monitoring programs. Freshwater inputs associated with these storms were found to initially result in increased primary productivity. When hydrographic conditions are favorable, bacterial consumption of organic matter produced by the phytoplankton blooms and deposited during the initial runoff event can contribute to significant oxygen deficits during subsequent warmer periods. Salinity stress and habitat destruction associated with freshwater inputs, as well as anoxia, adversely affect benthic populations and fish. In contrast, mobile invertebrate species such as shrimp, which have a short life cycle and the ability to migrate during the runoff event, initially benefit from the increased primary productivity and decreased abundance of fish predators. Events studied so far indicate that estuaries rebound in one to three years following major short-term perturbations. However, repeated storm events without sufficient recovery time may cause a fundamental shift in ecosystem structure (Scavia et al. 2002). This is a scenario consistent with the predicted increase in hurricanes for the east coast of the United States. More work on the response of individual species to these stresses is needed so management of commercial resources can be adjusted to allow sufficient recovery time for affected populations.

The Bayesian view of extreme events

The Bayesian perspective of designing for the consequences of hazard is discussed. Structural engineers should be educated in Bayesian theory and its underlying philosophy, and about the centrality to the prediction problem of the predictive distribution. The primary contribution that Bayesianism can make to the debate about extreme possibilities is its clarification of the language of and thinking about risk. Frequentist methodologies are the wrong approach to the decisions that engineers need to make, decisions that involve assessments of abstract future possibilities based on incomplete and abstract information.

Extreme events and the morphodynamics of gravel-dominated coastal barriers: Strengthening uncertain ground

The long-term morphodynamic ordering of gravel-dominated coastal systems (GDCS), many of which serve as coastal defences in northwest Europe, is dominated by extreme events that generate barrier crest overflow. An understanding of this morphodynamic ordering is fraught with several unresolved difficulties. These are related to the twin problems of the inadequacy of pertinent morphodynamic parameterisation and of obtaining data from modern shores enabling such parameterisation. Major uncertainties concern the timing of over-crest flow in terms of return period of extreme elevation; the intensity and structure of the overflow field; antecedent beachface characteristics in response to storms; the rate of relative sea-level change; tidal stage control; and barrier resistance to forcing, itself determined by a number of unknowns including barrier form and size, sediment size and mosaics, and barrier resilience. While generalised extreme value modelling may provide a means of characterising overwashing return-period and its variability, exceptional tsunami events are outside the scope of such modelling. The characterisation of GDCS morphodynamics in terms of the forcing extreme events will necessitate integrating some or all of these parameters into a single model.

Low temperature conditions in building sandstone: the role of extreme events in temperate environments

Data on rock temperatures has previously been collected to characterise typical diurnal regimes, and more recently to describe short-term variability in extreme locations. However, there is also the case that little is understood concerning the impact of extreme events in otherwise temperate environments. Internal stone temperatures (5?cm) collected during the atypical cold extreme experienced, throughout the UK, in December 2010 show a difference between ambient air temperatures and aspect-related thermal differences, particularly concerning temperature lows and the influence of radiative heating. In this case, debris release was not visible; however, laboratory simulations have shown that under such conditions, surface loss does not necessarily negate the occurrence of internal stone modifications. This preparatory sequence of change demonstrates that surface loss is not the result of one process, but rather many operating over time to sufficiently decrease stone strength to facilitate obvious damage.

Understanding the processes governing climate variability and change, climate predictability and the probability of extreme events

The purpose of Research Theme 4 (RT4) was to advance understanding of the basic science issues at the heart of the ENSEMBLES project, focusing on the key processes that govern climate variability and change, and that determine the predictability of climate. Particular attention was given to understanding linear and non-linear feedbacks that may lead to climate surprises,and to understanding the factors that govern the probability of extreme events. Improved understanding of these issues will contribute significantly to the quantification and reduction of uncertainty in seasonal to decadal predictions and projections of climate change. RT4 exploited the ENSEMBLES integrations (stream 1) performed in RT2A as well as undertaking its own experimentation to explore key processes within the climate system. It was working at the cutting edge of problems related to climate feedbacks, the interaction between climate variability and climate change � especially how climate change pertains to extreme events, and the predictability of the climate system on a range of time-scales. The statisticalmethodologies developed for extreme event analysis are new and state-of-the-art. The RT4-coordinated experiments, which have been conducted with six different atmospheric GCMs forced by common timeinvariant sea surface temperature (SST) and sea-ice fields (removing some sources of inter-model variability), are designed to help to understand model uncertainty (rather than scenario or initial condition uncertainty) in predictions of the response to greenhouse-gas-induced warming. RT4 links strongly with RT5 on the evaluation of the ENSEMBLES prediction system and feeds back its results to RT1 to guide improvements in the Earth system models and, through its research on predictability, to steer the development of methods for initialising the ensembles

Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures

Many different performance measures have been developed to evaluate field predictions in meteorology. However, a researcher or practitioner encountering a new or unfamiliar measure may have difficulty in interpreting its results, which may lead to them avoiding new measures and relying on those that are familiar. In the context of evaluating forecasts of extreme events for hydrological applications, this article aims to promote the use of a range of performance measures. Some of the types of performance measures that are introduced in order to demonstrate a six-step approach to tackle a new measure. Using the example of the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble precipitation predictions for the Danube floods of July and August 2002, to show how to use new performance measures with this approach and the way to choose between different performance measures based on their suitability for the task at hand is shown. Copyright © 2008 Royal Meteorological Society

Migration, immobility and displacement outcomes following extreme events

There is growing international concern at the rise in the severity of impact and frequency of extreme environmental events, potentially as a manifestation of global environmental change. There is a widely held belief that this trend could be linked with a future rise in the migration or displacement of human populations. However, recent approaches to migration influenced by environmental change call into question the notion that migration can be ascribed in a singular way to particular environmental causes or events. This paper undertakes a systematic review of evidence on population movements associated with weather-related extreme events. The paper demonstrates that in the face of extreme environmental events, it is important to distinguish between three outcomes – migration, displacement, and immobility – each of which interact and respond to multiple drivers. It also proposes a further insight: that both those who move, and those who do not move, may find themselves trapped and vulnerable in the face of such extreme events. A review of evidence suggests that short-term displacement that goes hand-in-hand with loss of life, destruction of property and economic disruption poses significant risks not because it is ‘environmental migration’, but because it represents a failure of adaptation to environmental change.

Attribution of climate extreme events

There is a tremendous desire to attribute causes to weather and climate events that is often challenging from a physical standpoint. Headlines attributing an event solely to either human-induced climate change or natural variability can be misleading when both are invariably in play. The conventional attribution framework struggles with dynamically driven extremes because of the small signal-to-noise ratios and often uncertain nature of the forced changes. Here, we suggest that a different framing is desirable, which asks why such extremes unfold the way they do. Specifically, we suggest that it is more useful to regard the extreme circulation regime or weather event as being largely unaffected by climate change, and question whether known changes in the climate system's thermodynamic state affected the impact of the particular event. Some examples briefly illustrated include 'snowmaggedon' in February 2010, superstorm Sandy in October 2012 and supertyphoon Haiyan in November 2013, and, in more detail, the Boulder floods of September 2013, all of which were influenced by high sea surface temperatures that had a discernible human component.

Bayesian analysis of extreme events with threshold estimation

The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds by estimating the GPD parameters based on data beyond it, discarding all the information available be10w the threshold. We introduce a mixture model that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold inc1uded. Prior distribution for the parameters are indirectly obtained through experts quantiles elicitation. Posterior inference is available through Markov Chain Monte Carlo (MCMC) methods. Simulations are carried out in order to analyze the performance of our proposed mode1 under a wide range of scenarios. Those scenarios approximate realistic situations found in the literature. We also apply the proposed model to a real dataset, Nasdaq 100, an index of the financiai market that presents many extreme events. Important issues such as predictive analysis and model selection are considered along with possible modeling extensions.

Analysis of extreme events in the Caribbean 1990-2008

This study presents an analysis of extreme events in the Caribbean subregion for the period 1990 to 2008, and forms part of a similar, wider study focused on the Latin America and the Caribbean region (Central America and South America being the other two subregional components). It explores the economic costs of climate change through an examination of adaptation costs to extreme events. ECLAC, through its Subregional Headquarters for the Caribbean, is pleased to have been able to undertake this study with the financial support of DFID and to have ensured its successful execution in collaboration with technical expertise from the University of the West Indies.