Given the regional surface network of the Umbria region, a mountainous area located in central Italy, the observed hourly temperature time series from 2010 to 2017 were analysed by applying basic and extended quality control procedures following World Meteorological Organization (WMO) standards. The validation procedure consisted of automatic quality control, producing validated data with metadata subsequently recorded in the NetCDF format. After these controls, data were checked manually and an extended procedure was applied to reconstruct the temperature time series for missing data. The spatiotemporal method used to reconstruct the data was a linear interpolation for 1 hr gaps and the empirical orthogonal function (EOF) algorithm for gaps ≥ 2 hr. The introduction of a complete and homogeneous data set of hourly reanalysis ERA5 (from the European Center for Medium-Range Weather Forecasts-ECMWF) allowed for the reconstruction of the longest gaps with statistical and physical consistency. The final product of the study is a continuous station time series of hourly temperatures that will be available to the public by the end of 2020; a daily version of the original time series is already available on the regional website.

The current evolution of numerical weather prediction models, climate applications, warning and decision support systems needs more information at increasingly finer scales. In this context, mesoscale meteorological networks (mesonets) can provide essential observations for the international community. However, they often suffer from the absence of a national and international coordination, scarce maintenance, inadequate data quality and redundancy. An integrated network design and the implementation of a unified quality management system could reveal the full socio‐economical benefits of mesonet information. This study provides a general procedure to realize an efficient and high‐quality mesonet starting from existing fragmented networks. The process starts by defining a network quality management system (NQMS), which is responsible for the station maintenance and the data quality control (QC) procedures. Stations are first classified based on their primary purpose, their landscape and the instruments siting and exposure in the station enclosure. Then, their quality performances are evaluated by a complex QC system made by numerous QC tests, whose specifications are tailored to the main surface observations. Finally, an integrated network design procedure is provided to identify observational lack and planning site interventions. The design is based on the purpose of the network and all the information gathered by the NQMS. Spatial, meteorological, climate and financial considerations are then used to decide whether to add, remove or modify observations. This procedure is tested in the Umbria region, Central Italy, where its implementation would lead to a considerable advancement in terms of regional weather and climate services.

Radiative-convective equilibrium (RCE) of an ensemble of clouds has been used as an example of a statistical equilibrium state of the atmosphere able to mimic the tropical part of the climate system (K. Emanuel et al., 2014). Indeed, given the crucial importance of the balance between radiative cooling and latent heating due to condensation and surface-sensitive heat flux in the Tropics in the Earth's global balance, the RCE state of the atmosphere has become a proxy to study the link between global circulation and convection (Held et al., 1993;Pauluis & Held, 2002a, 2002bRandall et al., 1994;Yano & Plant, 2012). The implicit assumption in this is that the tropical circulation may be larger than the small-scale convective processes of an ensemble of clouds and that the statistical equilibrium implied by the RCE state is based on processes in near-equilibrium on different space and time scales with the large-scale flow. This point was brought to general attention when the increased computing capability available made it possible to run three-dimensional high-resolution simulations (Bretherton et al., 2005;Tompkins & Craig, 1998) and to study the sensitivity of RCE states using models with enhanced dimensions of the grid reaching the dimensions of mesoscale processes, with explicit moist variables and different physics

Even if the sensitivity of vegetation phenology to climate change has been accepted on global and continental scales, the correlation between global warming and phenotypic variability shows a modulated answer depending on altitude, latitude, and the local seasonal thermal trend. To connect global patterns of change with local effects, we investigated the impact of the observed signal of warming found in Central Italy on two different willow species, Salix acutifolia and Salix smithiana, growing in three phenological gardens of the International Phenological Gardens’ network (IPG) located in different orographic positions. The time series of temperatures and phenological data for the period 2005–2018 were analysed first to find trends over time in the three gardens and then to correlate the recent local warming and the change in the two species phenology. The results confirmed the correlation between phenological trends and local trend of temperatures. In particular: budburst showed a trend of advancement of 1.4 days/year on average in all three gardens; flowering showed a divergent pattern between the gardens of either advancement of 1.0 days/year on average or delay of 1.1 days/year on average; while senescence showed a delay reaching even 3.3 days/year, although significant in only two gardens for both species. These trends were found to be correlated mainly with the temperatures of the months preceding the occurrence of the phase, with a shift in terms of days of the year (DOY) of the two species. Our conclusion is that the observed warming in Central Italy played a key role in controlling the phenophases occurrences of the two willow species, and that the orographic forcing leads to the different shift in DOY of phenophases (from 5 to 20 days) due to the local thermal forcing of the three phenological gardens.

Recent analyses of satellite and surface observations reported a negative annual rainfall trend in central Italy. The complex orography of the Apennines and the strong influence of climate change in the Mediterranean basin complicates the explanation of such trends and their spatial variability. This work aims at describing the link between circulation weather types, orography and precipitation patterns observed in central Italy, as a first step towards the understanding of such climate trends. Using ERA5 reanalysis data from 1951 to 2019, four weather types are identified as most responsible for the spatial variability of rainfall in central Italy. They are associated with cyclonic circulations characterized by high water vapour transport coming from west, southwest, south-east and north-east. The analysis of wind speed and precipitation climatology for the period 1951-2019, as derived from both surface observa-