Constructing hope: a multi-agency programme model for young sex offenders living with HIV/AIDS in South Africa

Many young sex offenders in South Africa have HIV/AIDS. This fact both complicates and underlines the importance of delivering effective multi-agency sex offender programmes to these individuals. Reducing reoffending rates is of obvious importance, as stopping these young offenders from offending also means limiting the spread of HIV to new victims. We are proposing an integrative programme that incorporates proven models of sex offender treatment in combination with medical, educational and family support systems to facilitate community reintegration of young sex offenders living with HIV/AIDS. It is our hope to work in partnership with the Department of Correctional Services in South Africa to facilitate such programming in the near future

Mean and extreme climate in Europe under 1.5, 2, and 3°C global warming

Based on high-resolution regional climate models, the change over Europe in mean climate and extremes, including impact-relevant indicators, are investigated under different levels of global warming (1.5°C, 2°C, and 3°C). A suit of indices describing both hot and cold events are employed and, for precipitation, wet and dry conditions; in particular, we examine the evolution of threshold-based indices, such as the number of frost days or tropical nights, which may be relevant for impact assessment on specific sectors.JRC.E.1-Disaster Risk Managemen

Il sistema archivistico italiano

L’articolo descrive il sistema archivistico italiano, che prevede specifici istituti di concentrazione e conservazione per la sezione storica degli archivi prodotti dagli uffici dello Stato e affida agli enti produttori, pubblici o privati, la gestione e la conservazione dei loro documenti. Inoltre illustra iniziative di valorizzazione e di conservazione concentrata di particolari tipologie di archivi a rischio di dispersione. Infine ricorda i principali temi di ricerca che si sono sviluppati negli ultimi anni, indicando le criticità non ancora risolte e i progetti tuttora in corso.The author describes the Italian archival system: in Italy the preservation of historical archives are managed by different institutions. The Archivi di Stato and the Archivio Centrale dello Stato are specific institutions charged of the concentration and the preservation of the historical sections of archives created by State offices, but the archives created by public or private corporate bodies are managed and preserved by their own creators during all phases of archive life. She talks about many initiatives to improve and to preserve, also in concentrated way some typologies of archives that are at-risk. Finally she illustrates the main research subjects and recent studies; she indicates the must important programmes developed in the last years and shows unresolved critical aspects and some projects in progress.L’articolo descrive il sistema archivistico italiano, che prevede specifici istituti di concentrazione e conservazione per la sezione storica degli archivi prodotti dagli uffici dello Stato e affida agli enti produttori, pubblici o privati, la gestione e la conservazione dei loro documenti. Inoltre illustra iniziative di valorizzazione e di conservazione concentrata di particolari tipologie di archivi a rischio di dispersione. Infine ricorda i principali temi di ricerca che si sono sviluppati negli ultimi anni, indicando le criticità non ancora risolte e i progetti tuttora in corso

Projections of indices of daily temperature and precipitation based on bias-adjusted CORDEX-Africa regional climate model simulations

AbstractWe present a dataset of daily, bias-adjusted temperature and precipitation projections for continental Africa based on a large ensemble of regional climate model simulations, which can be useful for climate change impact studies in several sectors. We provide guidance on the benefits and caveats of using the dataset by investigating the effect of bias-adjustment on impact-relevant indices (both their future absolute value and change). Extreme threshold-based temperature indices show large differences between original and bias-adjusted values at the end of the century due to the general underestimation of temperature in the present climate. These results indicate that when biases are accounted for, projected risks of extreme temperature-related hazards are higher than previously found, with possible consequences for the planning of adaptation measures. Bias-adjusted results for precipitation indices are usually consistent with the original results, with the median change preserved for most regions and indices. The interquartile and full range of the original model ensemble is usually well preserved by bias-adjustment, with the exception of maximum daily precipitation, whose range is usually greatly reduced by the bias-adjustment. This is due to the poor simulation and extremely large model range for this index over the reference period; when the bias is reduced, most models converge in projecting a similar change. Finally, we provide a methodology to select a small subset of simulations that preserves the overall uncertainty in the future projections of the large model ensemble. This result can be useful in practical applications when process-based impact models are too expensive to be run with the full ensemble of model simulations

Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations

In this work we asses the benefits of removing bias in climate forcing data used for hydrological climate change impact assessment at pan-European scale, with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 model driven by the SRES-A1B emission scenario are corrected for bias using a histogram equalization method. As target for the bias correction we employ gridded interpolated observations of precipitation, average, minimum, and maximum temperature from the E-OBS data set. Bias removal transfer functions are derived for the control period 1961–1990. These are subsequently used to correct the climate simulations for the control period, and, under the assumption of a stationary error model, for the future time window 2071–2100. Validation against E-OBS climatology in the control period shows that the correction method performs successfully in removing bias in average and extreme statistics relevant for flood simulation over the majority of the European domain in all seasons. This translates into considerably improved simulations with the hydrological model of observed average and extreme river discharges at a majority of 554 validation river stations across Europe. Probabilities of extreme events derived employing extreme value techniques are also more closely reproduced. Results indicate that projections of future flood hazard in Europe based on uncorrected climate simulations, both in terms of their magnitude and recurrence interval, are likely subject to large errors. Notwithstanding the inherent limitations of the large-scale approach used herein, this study strongly advocates the removal of bias in climate simulations prior to their use in hydrological impact assessment

PESETA III – Task1: Climate change projections, bias-adjustment, and selection of model runs

Global warming will greatly affect the climate at regional and local scale through, e.g., the increase of intensity and frequency of extreme weather events (floods, droughts, heat waves, etc.). In order to assess the impact of climate change at such scale (on, e.g., the hydrological cycle or crop production) it is necessary to attain meteorological information with a spatial detail much finer than that provided by global climate models (GCMs). High-resolution climate projections are usually obtained by employing regional climate models (RCMs), which are able to better resolve small-scale features such as topography and heterogeneous land use. When compared to present-day observations, however, the results of climate models can present large biases; in order to be used as an input for process-based impact models (like in PESETA III) outputs from RCMs are usually further post-processed by means of statistical techniques known as bias-correction (or bias-adjustment). Here, we describe the projections of climate change used in PESETA III and the bias-adjustment method applied to them, focusing on the analysis of a series of climate change indices for both the mean climate and extreme events (such as the number of frost days, of the number of consecutive dry days) relevant for impact assessment studies. Results show that, under the RCP8.5 emission scenario, at the end of the Century, maximum temperature is expected to increase, in winter, between about 2.5∘C over the British Isles and 4.8∘C over Scandinavia. In summer, the projected change ranges between 2.5∘C over Britain and 4.7∘C over the Iberian Peninsula. Winter precipitation is projected to increase over most of central and northern Europe in both frequency, and intensity, with a consequent increase of the number of consecutive wet days, and reduction of consecutive dry days. The change in precipitation frequencies distribution is not uniform, though, and a reduction in low precipitation intensity is accompanied by an increase of extreme events, even for the Mediterranean regions where total precipitation is projected to decrease. In summer, a general reduction in precipitation is projected for all regions except Scandinavia and Eastern Europe; as for winter, there is a tendency toward less frequent but more severe precipitation episodes. A set of 12 RCMs’ bias-adjusted climate change projections is provided to the PESETA III impact modellers; the use of such a large ensemble of runs is essential to quantify the uncertainty in climate projections (the so-called inter-model variability). In fact, each model’s run (driven by the same emission scenario) represents an equally plausible projection of the future evolution of the climate. However, due to differences in the models’ formulation and physical parameterization, the climate change signal projected by different models may present significant differences. Due to resource limitations, some impact model groups may not be able to use all the 12 provided runs; in this case, a sub-set of 5 runs is selected to be used by all impact models (compulsory core runs). The sub-set of core runs needs to be able to reproduce, as accurately as possible, the inter-model variability of the entire ensemble. The selection of the sub-set has been performed by means of Principal Component Analysis (PCA) on the bias adjusted climate change indices. Finally, the PESETA III protocol also requires investigating the impacts of a 2ᵒC global warming, compared to the preindustrial period. Here for each RCM run, the timing of reaching 2ᵒC warming is provided following the same procedure used in the FP7 project IMPACT2C, namely: - It is assumed that the climate in a +2ᵒC world is comparable irrespective of when and how fast this warming is reached - An RCM is defined to project a 2ᵒC global warming when the corresponding driving GCM reaches the 2ᵒC threshold, under RCP8.5 emission scenario - For each GCM-RCM run, the +2ᵒC period is defined as the 30 year period centred around the year when the 2ᵒC global warming is first reachedJRC.E.1-Disaster Risk Managemen