Reliable secular time series of essential climatic variables are a fundamental element for the assessment of vulnerability, impact and adaptation to climate change. Here, we implement a readily portable procedure for building an upgradable long‐term homogeneous climate dataset using monthly and daily observations of temperature and precipitation over a given area of interest, exemplified here with Abruzzo, a region in Central Italy characterized by complex orography. We process the dataset according to a preliminary ranking of stations based on data quantity and quality, and we exploit the Climatol algorithm for inhomogeneity correction. The corrected time series show trends in broad agreement with external databases (CRU, Berkeley Earth, E‐OBS), and highlight the importance of relying on a local network for a better representation of gradients and variability over the territory. We estimate that maximum (TX) and minimum temperature (TN) increased by ~1.6 and ~2.2°C/century, respectively, over the period 1930–2019, while in the recent decades 1980–2019 we found an accelerated trend of ~5.7 and ~3.9°C/century. Precipitation (RR) decreased by ~10%/century in 1930–2019, while it has been increasing at a rate of ~26%/century in 1980–2019. The Köppen–Geiger climate classification is sensitive to the increase of precipitation in the recent decades, which is attributable to decreased summer precipitation overcompensated by more rain in late spring and early autumn. The cold climate types are retreating upwards along the slopes of the mountain ranges. Over the period 1980–2019, extreme values are also displaying significant trends. Every 2 years, there is one less frost day (TN 25°C) in the Apennines area, while there is one more tropical night (TN >20°C) in the Adriatic coastal area. Precipitation extremes are increasing, especially along the coast, with rain accumulated in the rainiest days increasing at a rate of 1–2%/year.

Large-scale gridded climatic data can be useful for the assessment of climate variability and change as a basis for understanding and monitoring natural hazards, as well as for determining appropriate coping strategies. However, an evaluation of the accuracy of these data products against local observational measurements over the different regions of the globe is always required, as these large-scale data may be affected by systematic errors, which can affect the results of downstream applications. Therefore, this study was carried out to evaluate the performances of two long-term gridded datasets in reproducing station-based precipitation and temperature data over the Apulia region (southern Italy) for the period 1956–2019, with a particular focus on the effect of using the different data sources on the results of trend analyses and aridity classification. The results revealed that the considered gridded data products allow only general indications on the spatial and temporal behavior of climatic variables over the Apulia region, especially in regard to precipitation data.

Climate change poses a major sustainability challenge, with potential far-reaching economic and social impacts, including fluctuations in agricultural yields and subsequent volatility in the availability and prices of essential food resources. In this study, we analyze the changes in climatic variables and agricultural yields for main crops cultivated in the Abruzzo Region (Central Italy), as well as their reciprocal correlation pattern in the time range, 1952–2014. Central Italy exhibits a well-developed agricultural sector and is characterized by a Mediterranean climate; given its proximity to the semi-arid and arid North African climate zone, such a region may be particularly vulnerable to climate change impacts. The analysis reveals an increase in drought intensity and persistence, starting from the 1980s, with a shift towards more temperate conditions in winter months and a transition to a warmer and more arid climate during the summer season. Moreover, the study identifies an overall increase in the correlation magnitude between crop yield fluctuations and climatic variables in the period 1983–2014 compared to that during the previous thirty-year time range. This finding can be interpreted as a change in the resilience (or increased vulnerability) of the agricultural production system to climate change. This work can be thus considered as an interesting case study in the Mediterranean region, offering valuable insights for constructing probabilistic models of fluctuations in agricultural production possibly induced by climate change.

Several studies have demonstrated that in abruptly expanding channels phenomena of flow asymmetry can arise under certain tailwater conditions. These undesired situations are characterized by high-velocity concentrations and backward flows in the tailwater channel. This paper presents some preliminary results of an experimental investigation carried out to study the effects of a system of crossbeams for improving the flow patterns in the tailwater channel. Four different beam spacings, two system orientations and slopes, two locations, and two beam heights were tested in order to define the most adequate geometry of the dissipator. It was found that, for almost all tested configurations, the presence of the crossbeams produced a significant improvement in the flow field in the channel, in terms of velocity distribution and stability under variable downstream conditions.