Search

In Italy, most of the destructive landslides are triggered by rainfall, particularly in central Italy. Therefore, effective monitoring of rainfall is crucial in hazard management and ecosystem assessment. Global precipitation measurement (GPM) is the next-generation satellite mission, which provides the precipitation measurements worldwide. In this research, we employed the available monthly GPM data to estimate the monthly precipitation for the twenty administrative regions of Italy from June 2000 to June 2021. For each region, we applied the non-parametric Mann–Kendall test and its associated Sen's slope to estimate the precipitation trend for each calendar month. In addition, for each region, we estimated a linear trend and the seasonal cycles of precipitation with the antileakage least-squares spectral analysis (ALLSSA) and showed the annual precipitation variations using box plots. Lastly, we compared machine-learning models based on the auto-regressive moving average for monthly precipitation forecasting and showed that ALLSSA outperformed them. The findings of this research provide a significant insight into processing climate data, both in terms of trend-season estimates and forecasting, and can potentially be used in landslide susceptibility analysis. [ABSTRACT FROM AUTHOR]

This study shows how satellite-based passive and active microwave (MW) sensors can be used in conjunction with high-resolution Numerical Weather Prediction (NWP) simulations to provide insights of the precipitation structure of the tropical-like cyclone (TLC) Numa, which occurred on 15–19 November 2017. The goal of the paper is to characterize and monitor the precipitation at the different stages of its evolution from development to TLC phase, throughout the storm transition over the Mediterranean Sea. Observations by the NASA/JAXA Global Precipitation Measurement Core Observatory (GPM-CO) and by the GPM constellation of MW radiometers are used, in conjunction with the Regional Atmospheric Modeling System (RAMS) simulations. The GPM-CO measurements are used to analyze the passive MW radiometric response to the microphysical structure of the storm, while the comparison between successive MW radiometer overpasses shows the evolution of Numa precipitation structure from its early development stage on the Ionian Sea into its TLC phase, as it persists over southern coast of Italy (Apulia region) for several hours. Measurements evidence stronger convective activity at the development phase compared to the TLC phase, when strengthening or weakening phases in the eye development, and the occurrence of warm rain processes in the areas surrounding the eye, are identified. The weak scattering and polarization signal at and above 89 GHz, the lack of scattering signal at 37 GHz, and the absence of electrical activity in correspondence of the rainbands during the TLC phase, indicate weak convection and the presence of supercooled cloud droplets at high levels. RAMS high-resolution simulations support what inferred from the observations, evidencing Numa TLC characteristics (closed circulation around a warm core, low vertical wind shear, intense surface winds, heavy precipitation), persisting for more than 24 h. Moreover, the implementation of DPR 3D reflectivity field in the RAMS data assimilation system shows a small (but non negligible) impact on the precipitation forecast over the sea up to a few hours after the DPR overpass. [ABSTRACT FROM AUTHOR]

The aim of this study was to estimate the determinants of residential water demand for chief towns of every Italian province, in the period 2007-2009, using the linear mixed-effects model estimated with the restricted-maximum-likelihood method. Results confirmed that the applied tariff had a negative effect on residential water consumption and that it was a relevant driver of domestic water consumption. Moreover, income per capita had a positive effect on water consumption. Among measured climatic and geographical features, precipitation and altitude exerted a strongly significant negative effect on water consumption, while temperature did not influence water demand. Further, data show that small towns in terms of population served were characterized by lower levels of consumption. Water utilities ownership itself did not have a significant effect on water consumption but tariffs were significantly lower and residential water consumption was higher in towns where the water service was managed by publicly owned water utilities. However, further research is needed to gain a better understanding of the connection between ownership of water utilities and water prices and water consumption. [ABSTRACT FROM AUTHOR]

An in-depth analysis of historical heavy rainfall fields clearly constitutes an important aspect in many related topics: as examples, mesoscale models for early warning systems and the definition of design event scenarios can be improved, with the consequent upgrading in the prediction of induced phenomena (mainly floods and landslides) into specific areas of interest. With this goal, in this work the authors focused on Calabria region (southern Italy) and classified the main precipitation systems through the analysis of selected heavy rainfall events from high resolution rain gauge network time series. Moreover, the authors investigated the relationships among the selected events and the main synoptic atmospheric patterns derived by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 Reanalysis dataset, in order to assess the possible large-scale scenarios which can induce heavy rainfall events in the study area. The obtained results highlighted: (i) the importance of areal reduction factors, rainfall intensities and amounts in order to discriminate the investigated precipitations systems for the study area; (ii) the crucial role played by the position of the averaged low-pressure areas over the Mediterranean for the synoptic systems, and by low-level temperature for the convective systems. [ABSTRACT FROM AUTHOR]

This study analyzed all characteristics of the error committed in evaluating annual maximum rainfall depth, Hd, associated with a given duration, d, when data with coarse temporal aggregation, ta, were used. It is well known that when ta = 1 min, this error is practically negligible while coarser temporal aggregations can determine underestimation for a single Hd up to 50% and for the average value of sufficiently numerous series of Hd up to 16.67%. By using a mathematical relation between average underestimation error and the ratio ta/d, each Hd value belonging to a specific series could be corrected through deterministic or stochastic approaches. With a deterministic approach, an average correction was identically applied to all Hd values with the same ta and d while, for a stochastic correction, a thorough knowledge of the statistical characteristics of the underestimation error was required. Accordingly, in this work, rainfall data derived from many stations in central Italy were analyzed and it was assessed that single and average errors, which were both assumed as random variables, followed exponential and normal distributions, respectively. Furthermore, the single underestimation error was also found inversely correlated to the corresponding annual maximum rainfall depth. [ABSTRACT FROM AUTHOR]