Reducing inconsistencies in point observations of maximum flood inundation level

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.

The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.

Atmospheric electric fields during the Carrington flare

Karen Aplin and Giles Harrison examine international records of the 1859 Carrington flare and consider what they mean for our understanding of space weather today. Space weather is increasingly recognized as a hazard to modern societies, and one way to assess the extent of its possible impact is through analysis of historic space weather events. One such event was the massive solar storm of late August and early September 1859. This is now widely known as the “Carrington flare” or “Carrington event” after the visual solar emissions on 1 September first reported by the Victorian astronomer Richard Carrington from his observatory in Redhill, Surrey (Carrington 1859). The related aurorae and subsequent effects on telegraph networks are well documented (e.g. Clark 2007, Boteler 2006), but use of modern techniques, such as analysis of nitrates produced by solar protons in ice cores to retrospectively assess the nature of the solar flare, has proved problematic (Wolff et al. 2012). This means that there is still very little quantitative information about the flare beyond magnetic observations (e.g. Viljanen et al. 2014).

Global forecasting of thermal health hazards: the skill of probabilistic predictions of the Universal Thermal Climate Index (UTCI)

Although over a hundred thermal indices can be used for assessing thermal health hazards, many ignore the human heat budget, physiology and clothing. The Universal Thermal Climate Index (UTCI) addresses these shortcomings by using an advanced thermo-physiological model. This paper assesses the potential of using the UTCI for forecasting thermal health hazards. Traditionally, such hazard forecasting has had two further limitations: it has been narrowly focused on a particular region or nation and has relied on the use of single ‘deterministic’ forecasts. Here, the UTCI is computed on a global scale,which is essential for international health-hazard warnings and disaster preparedness, and it is provided as a probabilistic forecast. It is shown that probabilistic UTCI forecasts are superior in skill to deterministic forecasts and that despite global variations, the UTCI forecast is skilful for lead times up to 10 days. The paper also demonstrates the utility of probabilistic UTCI forecasts on the example of the 2010 heat wave in Russia.

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

Transport of the smoke plume from Chiado’s fire in Lisbon (Portugal) sensed by atmospheric electric field measurements

The Chiado’s fire that affected the city centre of Lisbon (Portugal) occurred on 25th August 1988 and had a significant human and environmental impact. This fire was considered the most significant hazard to have occurred in Lisbon city centre after the major earthquake of 1755. A clear signature of this fire is found in the atmospheric electric field data recorded at Portela meteorological station about 8 km NE from the site where the fire started at Chiado. Measurements were made using a Benndorf electrograph with a probe at 1 m height. The atmospheric electric field reached 510 V/m when the wind direction was coming from SW to NE, favourable to the transport of the smoke plume from Chiado to Portela. Such observations agree with predictions using Hysplit air mass trajectory modelling and have been used to estimate the smoke concentration to be ~0.4 mg/m3. It is demonstrated that atmospheric electric field measurements were therefore extremely sensitive to Chiado’s fire. This result is of particular current interest in using networks of atmospheric electric field sensors to complement existing optical and meteorological observations for fire monitoring.

Science for Humanitarian Emergencies and Resilience (SHEAR) scoping study: Annex 3 - Early warning system and risk assessment case studies

This report provides case studies of Early Warning Systems (EWSs) and risk assessments encompassing three main hazard types: drought; flood and cyclone. The case studies are taken from ten countries across three continents (focusing on Africa, South Asia and the Caribbean). The case studies have been developed to assist the UK Department for International Development (DFID) to prioritise areas for Early Warning System (EWS) related research under their ‘Science for Humanitarian Emergencies and Resilience’ (SHEAR) programme. The aim of these case studies is to ensure that DFID SHEAR research is informed by the views of Non-Governmental Organisations (NGOs) and communities engaged with Early Warning Systems and risk assessments (including community-based Early Warning Systems). The case studies highlight a number of challenges facing Early Warning Systems (EWSs). These challenges relate to financing; integration; responsibilities; community interpretation; politics; dissemination; accuracy; capacity and focus. The case studies summarise a number of priority areas for EWS related research: • Priority 1: Contextualising and localising early warning information • Priority 2: Climate proofing current EWSs • Priority 3: How best to sustain effective EWSs between hazard events? • Priority 4: Optimising the dissemination of risk and warning information • Priority 5: Governance and financing of EWSs • Priority 6: How to support EWSs under challenging circumstances • Priority 7: Improving EWSs through monitoring and evaluating the impact and effectiveness of those systems

Spatial evaluation of volcanic ash forecasts using satellite observations

The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD)models. In this paper an objectivemetric to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash is presented. The 5 metric is based on the fractions skill score (FSS). Thismeasure of skill provides more information than traditional point-bypoint metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale overwhich skill is being assessed. The FSS determines the scale overwhich a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The 10 idealised scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite retrieved ash data and evaluate VATD forecasts over a long time period.

Precipitation and floodiness

There are a number of factors that lead to non-linearity between precipitation anomalies and flood hazard; this non-linearity is a pertinent issue for applications that use a precipitation forecast as a proxy for imminent flood hazard. We assessed the degree of this non-linearity for the first time using a recently developed global-scale hydrological model driven by the ERA-Interim Land precipitation reanalysis (1980–2010). We introduced new indices to assess large-scale flood hazard, or floodiness, and quantified the link between monthly precipitation, river discharge and floodiness anomalies at the global and regional scales. The results show that monthly floodiness is not well correlated with precipitation, therefore demonstrating the value of hydrometeorological systems for providing floodiness forecasts for decision-makers. A method is described for forecasting floodiness using the Global Flood Awareness System, building a climatology of regional floodiness from which to forecast floodiness anomalies out to two weeks.

The specific role of relationship life events in the onset of depression during pregnancy and the postpartum

Background The precipitating role of life events in the onset of depression is well-established. The present study sought to examine whether life events hypothesised to be personally salient would be more strongly associated with depression than other life events. In a sample of women making the first transition to parenthood, we hypothesised that negative events related to the partner relationship would be particularly salient and thus more strongly predictive of depression than other events. Methods A community-based sample of 316 first-time mothers stratified by psychosocial risk completed interviews at 32 weeks gestation and 29 weeks postpartum to assess dated occurrence of life events and depression onsets from conception to 29 weeks postpartum. Complete data was available from 273 (86.4%). Cox proportional hazards regression was used to examine risk for onset of depression in the 6 months following a relationship event versus other events, after accounting for past history of depression and other potential confounders. Results 52 women (19.0%) experienced an onset of depression between conception and 6 months postpartum. Both relationship events (Hazard Ratio = 2.1, p = .001) and other life events (Hazard Ratio = 1.3, p = .020) were associated with increased risk for depression onset; however, relationship events showed a significantly greater risk for depression than did other life events (p = .044). Conclusions The results are consistent with the hypothesis that personally salient events are more predictive of depression onset than other events. Further, they indicate the clinical significance of events related to the partner relationship during pregnancy and the postpartum.

Continental and global scale flood forecasting systems

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction.

Stigma and risky behaviors among male clients of sex workers in the UK in 2001

This paper builds on existing theoretical work on sex markets (Della Giusta, Di Tommaso, and Strøm, 2009a). Using data from the British Sexual Attitudes Survey, we aim to replicate the analysis of the demand for paid sex previously conducted for the US (Della Giusta, Di Tommaso, Shima and Strøm, 2009b). We want to test formally the effect of attitudes, risky behaviors and personal characteristics on the demand for paid sex. Findings from empirical studies of clients suggest that personal characteristics (personal and family background, self-perception, perceptions of women, sexual preferences etc), economic factors (education, income, work) as well as attitudes towards risk (both health hazard and risk of being caught where sex work is illegal), and attitude towards relationships and sex are all likely to affect demand. Previous theoretical work has argued that stigma plays a fundamental role in determining both demand and risk, and that in particular due to the presence of stigma the demand for sex and for paid sex are not, as has been argued elsewhere, perfect substitutes. We use data from the British Sexual Attitudes Survey of 2001 to test these hypotheses. We find a positive effect of education (proxy for income), negative effects of professional status (proxies for stigma associated with buying sex), positive and significant effects of all risky behavior variables and no significant effects of variables which measure the relative degree of conservatism in morals. We conclude with some policy implications.

Subclinical thyroid dysfunctions are independent risk factors for mortality in a 7.5-year follow-up: the Japanese-Brazilian thyroid study

Objective: The currently available data concerning the influence of subclinical thyroid disease (STD) on morbidity and mortality are conflicting. Our objective was to investigate the relationships between STD and cardiometabolic profile and cardiovascular disease at baseline, as well as with all-cause and cardiovascular mortality in a 7.5-year follow-up. Design: Prospective, observational study. Methods: An overall of 1110 Japanese-Brazilians aged above 30 years, free of thyroid disease, and not taking thyroid medication at baseline were studied. In a cross-sectional analysis, we investigated the prevalence of STD and its relationship with cardiometabolic profile and cardiovascular disease. All-cause and cardiovascular mortality rates were assessed for participants followed for up to 7.5 years. Association between STD and mortality was drawn using multivariate analysis, adjusting for potential confounders. Results: A total of 913 (82.3%) participants had euthyroidism, 99 (8.7%) had subclinical hypothyroidism, and 69 (6.2%) had subclinical hyperthyroidism. At baseline, no association was found between STD and cardiometabolic profile or cardiovascular disease. Multivariate-adjusted hazard ratios (HRs (95% confidence interval)) for all-cause mortality were significantly higher for individuals with both subclinical hyperthyroidism (HR, 3.0 (1.5-5.9); n=14) and subclinical hypothyroidism (HR, 2.3 (1.2-4.4); n=13) than for euthyroid subjects. Cardiovascular mortality was significantly associated with subclinical hyperthyroidism (HR, 3.3 (1.4-7.5); n=8), but not with subclinical hypothyroidism (HR, 1.6 (0.6-4.2); n=5). Conclusion: In the Japanese-Brazilian population, subclinical hyperthyroidism is an independent risk factor for all-cause and cardiovascular mortality, while subclinical hypothyroidism is associated with all-cause mortality.

Sediment-contact fish embryo toxicity assay with Danio rerio to assess particle-bound pollutants in the Tiete River Basin (Sao Paulo, Brazil)

The Tiete River and its tributary Pinheiros River receive a highly complex organic and inorganic pollutants load from sanitary sewage and industrial sources, as well as agricultural and agroindustrial activities. The aim of the present study was to evaluate the embryotoxic and teratogenic effects of sediments from selected locations in the Tiete River Basin by means of the sediment contact embryo toxicity assay with Danio rerio, in order to provide a comprehensive and realistic insight into the bioavailable hazard potential of these sediment samples. Lethal and sub-lethal effects were recorded, and high embryo toxicity could be found in the samples not only in the vicinity of the megacity Sao Paulo (Billings reservoir and Pinheiros River samples), but also downstream (in the reservoirs Barra Bonita, Promissao and Tres Irmaos). Results confirm that most toxicity is due to the discharges of the metropolitan area of Sao Paulo. However, they also indicate additional sources of pollutants along the river course, probably from industrial, agricultural and agroindustrial residues, which contribute to the degradation of each area. The sediment contact fish embryo test showed to be powerful tool to detect embryo toxicity in sediments, not only by being a sensitive method, but also for taking into account bioavailability. This test provides an ecological highly realistic and relevant exposure scenario, and should therefore be added in ecotoxicological sediment quality assessments. (C) 2011 Elsevier Inc. All rights reserved.

Using non-homogeneous Poisson models with multiple change-points to estimate the number of ozone exceedances in Mexico City

In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Poisson process has rate function lambda(t), t >= 0, which depends on some parameters that must be estimated. We take into account two cases of rate functions: the Weibull and the Goel-Okumoto. We consider models with and without change-points. When the presence of change-points is assumed, we may have the presence of either one, two or three change-points, depending of the data set. The parameters of the rate functions are estimated using a Gibbs sampling algorithm. Results are applied to ozone data provided by the Mexico City monitoring network. In a first instance, we assume that there are no change-points present. Depending on the adjustment of the model, we assume the presence of either one, two or three change-points. Copyright (C) 2009 John Wiley & Sons, Ltd.