The assessment of hydrometeorological risk in small basins requires the availability of skillful, highresolution quantitative precipitation forecasts to predict the probability of occurrence of severe, localized precipitation events. Large-scale ensemble prediction systems (EPS) currently provide forecast scenarios down to a resolution of about 50 km. High-resolution, nonhydrostatic, limited-area ensemble prediction systems provide dynamically based forecasts by extending these scenarios to smaller scales, typically on the order of 10 km. This work explores an alternative approach to the use of limited-area ensemble prediction systems, by directly applying a stochastic downscaling technique to large-scale ensemble forecasts. The performances of these two different approaches for three well-predicted precipitation events in northwestern Italy during 2006 are compared. Ensemble forecasts provided by the ECMWF EPS, downscaled using the Rainfall Filtered Autoregressive Model (RainFARM) stochastic technique, and ensemble forecasts obtained from the Consortium for Small-Scale Modeling Limited-Area Ensemble Prediction System (COSMO-LEPS) are considered. A dense network of rain gauges is used for verification. It is found that the probabilistic forecast skill of stochastically downscaled ensembles may be comparable with that of dynamically downscaled ensembles, using a range of standard forecast skill measures. Stochastic downscaling is suggested as a tool for benchmarking the performance of dynamical ensemble downscaling systems.
T1-weighted Magnetic Resonance images of water in the surroundings of a Nafion surface allowed to identify the presence of a Low Mobility Zone (LMZ), 60 m thick, consisting of water molecules structured in a hydrogen bonding network, promoted by the presence of the acidic protons on the surface of the sulphonated polymer. In parallel, the Exclusion Zone (EZ) was assessed by observing in optical microscopy the distribution of microspheres suspended in the medium in contact with the Nafion membrane. It was found that the LMZ and the EZ do not 2 correspond: in fact, the former is thinner and more stable over time than the latter and they behave differently when ions are present in the medium in which Nafion is immersed.
As manned spaceflights beyond low Earth orbit are in the agenda of Space Agencies, the concerns related to space radiation exposure of the crew are still without conclusive solutions. The risk of long-term detrimental health effects needs to be kept below acceptable limits, and emergency countermeasures must be planned to avoid the short-term consequences of exposure to high particle fluxes during hardly predictable solar events. Space habitat shielding cannot be the ultimate solution: the increasing complexity of future missions will require astronauts to protect themselves in low-shielded areas, e.g. during emergency operations. Personal radiation shielding is promising, particularly if using available resources for multi-functional shielding devices. In this work we report on all steps from the conception, design, manufacturing, to the final test on board the International Space Station (ISS) of the first prototype of a water-filled garment for emergency radiation shielding against solar particle events. The garment has a good shielding potential and comfort level. On-board water is used for filling and then recycled without waste. The successful outcome of this experiment represents an important breakthrough in space radiation shielding, opening to the development of similarly conceived devices and their use in interplanetary missions as the one to Mars.
The use of dense networks of rain gauges to verify the skill of quantitative numerical precipitation forecasts requires bridging the scale gap between the finite resolution of the forecast fields and the point measurements provided by each gauge. This is usually achieved either by interpolating the numerical forecasts to the rain gauge positions, or by upscaling the rain gauge measurements by averaging techniques. Both approaches are affected by uncertainties and sampling errors due to the limited density of most rain gauge networks and to the high spatiotemporal variability of precipitation. For this reason, an estimate of the sampling errors is crucial for obtaining a meaningful comparison. This work presents the application of a stochastic rainfall downscaling technique that allows a quantitative comparison between numerical forecasts and rain gauge measurements, in both downscaling and upscaling approaches, and allows a quantitative assessment of the significance of the results of the verification procedure.
Abstract. The spatial and temporal variability of air temperature, precipitation, actual evapotranspiration (AET) and their related water balance components, as well as their responses to anthropogenic climate change, provide fundamental information for an effective management of water resources and for a proactive involvement of users and stakeholders, in order to develop and apply adaptation and mitigation strategies at the local level. In this study, using an interdisciplinary research approach tailored to water management needs, we evaluate the past, present and future quantity of water potentially available for drinking supply in the water catchments feeding the about 2.3 million inhabitants of the Turin metropolitan area (the former Province of Turin, north-western Italy), considering climatologies at the quarterly and yearly timescales. Observed daily maximum surface air temperature and precipitation data from 1959 to 2017 were analysed to assess historical trends, their significance and the possible cross-correlations between the water balance components. Regional climate model (RCM) simulations from a small ensemble were analysed to provide mid-century projections of the difference between precipitation and AET for the area of interest in the future CMIP5 scenarios RCP4.5 (stabilization) and RCP8.5 (business as usual). Temporal and spatial variations in recharge were approximated with variations of drainage. The impact of irrigation, and of snowpack variability, on the latter was also assessed. The other terms of water balance were disregarded because they are affected by higher uncertainty. The analysis over the historical period indicated that the driest area of the study region displayed significant negative annual (and spring) trends of both precipitation and drainage. Results from field experiments were used to model irrigation, and we found that relatively wetter watersheds in the northern and in the southern parts behave differently, with a significant increase of AET due to irrigation. The analysis of future projections suggested almost stationary conditions for annual data. Regarding quarterly data, a slight decrease in summer drainage was found in three out of five models in both emission scenarios. The RCM ensemble exhibits a large spread in the representation of the future drainage trends. The large interannual variability of precipitation was also quantified and identified as a relevant risk factor for water management, expected to play a major role also in future decades.
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