A Tempered Particle Filter to Enhance the Assimilation of SAR-Derived Flood Extent Maps Into Flood Forecasting Models.

Data assimilation (DA) is a powerful tool to optimally combine uncertain model simulations and observations. Among DA techniques, the particle filter (PF) has gained attention for its capacity to deal with nonlinear systems and for its relaxation of the Gaussian assumption. However, the PF may suffer from degeneracy and sample impoverishment. In this study, we propose an innovative approach, based on a tempered particle filter (TPF), aiming at mitigating PFs issues, thus extending over time the assimilation benefits. Probabilistic flood maps derived from synthetic aperture radar data are assimilated into a flood forecasting model through an iterative process including a particle mutation in order to keep diversity within the ensemble. Results show an improvement of the model forecasts accuracy, with respect to the Open Loop: on average the root mean square error (RMSE) of water levels decrease by 80% at the assimilation time and by 60% 2 days after the assimilation. A comparison with the Sequential Importance Sampling (SIS) is carried out showing that although SIS performances are generally comparable to the TPF ones at the assimilation time, they tend to decrease more quickly. For instance, on average TPF-based RMSE are 20% lower compared to the SIS-based ones 2 days after the assimilation. The application of the TPF determines higher critical success index values compared to the SIS. On average the increase in performances lasts for almost 3 days after the assimilation. Our study provides evidence that the application of the variant of the TPF enables more persistent benefits compared to the SIS.

Ozone short-term exposure and acute coronary events: a multicities study in Tuscany (Italy).

OBJECTIVE: Many studies have investigated the potential role of ozone exposure in cardiovascular mortality and morbidity. The effects on specific cardiovascular outcome and the role of individual susceptibility are less studied. This paper focuses on the short-term effects of ozone on acute coronary events and it investigates comorbidities as indicators of personal susceptibility. SETTING AND PATIENTS: This study was conducted in five urban areas of the Tuscany region (Italy) covering the period January 2002-December 2005. Air quality and meteorological data from urban background monitoring sites were collected. Hospital admissions for acute myocardial infarction and out-of-hospital coronary deaths were extracted from administrative database. DESIGN: Both time series and case-crossover designs were applied. The confounding effects of some time-dependent variables, such as temperature, were taken into account. Some potential susceptibility factors were investigated. Pooled estimates were derived from random-effect meta-analysis. RESULTS: During the warm season 4555 hospitalized acute myocardial infarctions and 1931 out-of-hospital coronary deaths occurred. Authors estimated a 6.3% (95% confidence interval, 1.2%, 11.7%) increase in out-of-hospital coronary deaths for a 10 µg/m3 increase in ozone (lag 0-5). Results also suggested higher risks for females, elderly, and patients previously hospitalized for cerebrovascular and artery diseases. CONCLUSIONS: This study adds further evidence to the relation between cardiovascular diseases and ozone exposure, showing an adverse effect on out-of-hospital coronary deaths, but not on hospitalized acute myocardial infarctions. Some susceptible subgroups, such as females, elderly, and patients affected by some chronic diseases, are likely to be at major risk.

Short-term association between ambient air pollution and risk of hospitalization for acute myocardial infarction: results of the cardiovascular risk and air pollution in Tuscany (RISCAT) study.

Air pollutant levels have been widely associated with increased hospitalizations and mortality from cardiovascular disease. In this study, the authors focused on pollutant levels and triggering of acute myocardial infarction (AMI). Data on AMI hospitalizations, air quality, and meteorologic conditions were collected in 6 urban areas of Tuscany (central Italy) during 2002-2005. Levels of particulate matter with an aerodynamic diameter ≤10 µm (PM(10)) (range of 4-year mean values, 28.15-40.68 µg/m(3)), nitrogen dioxide (range, 28.52-39.72 µg/m(3)), and carbon monoxide (range, 0.86-1.28 mg/m(3)) were considered, and increases of 10 µg/m(3) (0.1 mg/m(3) for carbon monoxide) were analyzed. A time-stratified case-crossover approach was applied. Area-specific conditional regression models were fitted, adjusting for time-dependent variables. Stratified analyses and analyses in bipollutant models were performed. Pooled estimates were derived from random-effects meta-analyses. Among 11,450 AMI hospitalizations, the meta-analytical odds ratio at lag(2) (2-day lag) was 1.013 (95% confidence interval (CI): 1.000, 1.026) for PM(10), 1.022 (95% CI: 1.004, 1.041) for nitrogen dioxide, and 1.007 (95% CI: 1.002, 1.013) for carbon monoxide. More susceptible subgroups were elderly persons (age ≥75 years), females, and older patients with hypertension and chronic obstructive pulmonary disease. This study adds to evidence for a short-term association between air pollutants and AMI onset, also evident at low pollutant levels, suggesting a need to focus on more vulnerable subjects.

Did the September 2010 (Darfield) earthquake trigger the February 2011 (Christchurch) event?

We have investigated the possible cause-and-effect relationship due to stress transfer between two earthquakes that occurred near Christchurch, New Zealand, in September 2010 and in February 2011. The Mw 7.1 Darfield (Canterbury) event took place along a previously unrecognized fault. The Mw 6.3 Christchurch earthquake, generated by a thrust fault, occurred approximately five months later, 6 km south-east of Christchurch's city center. We have first measured the surface displacement field to retrieve the geometries of the two seismic sources and the slip distribution. In order to assess whether the first earthquake increased the likelihood of occurrence of a second earthquake, we compute the Coulomb Failure Function (CFF). We find that the maximum CFF increase over the second fault plane is reached exactly around the hypocenter of the second earthquake. In this respect, we may conclude that the Darfield earthquake contributed to promote the rupture of the Christchurch fault.

Integrating Physical and Topographic Information Into a Fuzzy Scheme to Map Flooded Area by SAR.

A flood mapping procedure based on a fuzzy sets theory has been developed. The method is based on the integration of Synthetic Aperture Radar (SAR) measurements with additional data on the inundated area, such as a land cover map and a digital elevation model (DEM). The information on land cover has allowed us to account for both specular reflection, typical of open water, and double bounce backscattering, typical of forested and urban areas. DEM has been exploited to include simple hydraulic considerations on the dependence of inundation probability on surface characteristics. Contextual information has been taken into account too. The proposed algorithm has been tested on a flood occurred in Italy on November 1994. A pair of ERS-1 images, collected before and after (three days later) the flood, has been used. The results have been compared with the data provided by a ground survey carried out when the flood reached its maximum extension. Despite the temporal mismatch between the survey and the post-inundation SAR image, the comparison has yielded encouraging results, with the 87% of the pixels correctly classified as inundated.