An extensive analysis of the HISTALP database is presented with the aim of giving a comprehensive picture of secular climate variability and change in the Greater Alpine Region (GAR,(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(43)(44)(45)(46)(47)(48)(49). The HISTALP database encompasses 242 sites and concerns temperature, pressure, precipitation, cloudiness, sunshine duration, vapour pressure and relative humidity. The analyses are based on four regional mean records representing different GAR low-level areas and on an additional mean record representing high-level locations.The first goal of the paper is to give an overview of the seasonal and annual records for the different variables, aiming to highlight both variability on decadal time scale and long-term evolution. Then it focuses on trend and correlation analysis. Trends are presented both for the period of common data availability for all regional average series and for moving windows that permit studying the trends over a wide range of timescales. Correlations among the different variables are presented both for the regional average series and for their high-pass-filtered versions.The analyses, beside highlighting a warming that is about twice as large as the global trend, also show that the different variables have responded in different ways to this warming and that the mutual interactions linking the different variables are often present only at specific temporal scales and only in parts of the GAR and in defined seasons. In spite of this complex behaviour, which may also be due to some residual inhomogeneities still affecting the data, the analyses give evidence that the HISTALP database has an excellent internal consistency and show that the availability of a multi-variable database turns out to be very useful in order to evaluate the reliability of the reconstruction of each variable and to better understand the behaviour and the mutual interactions of the different variables.

High-resolution monthly precipitation climatologies for Italy are presented. They are based on precipitation normals obtained from a quality-controlled dataset of 6134 stations covering the Italian territory and part of the Northern neighbouring regions. The climatologies are computed by means of two interpolation methods modelling the precipitation-elevation relationship at a local level, more precisely a local weighted linear regression (LWLR) and a local regression kriging (RK) are performed. For both methods, local optimisations are also applied in order to improve model performance. Model results are compared with those provided by two other widely used interpolation methods which do not consider elevation in modelling precipitation distribution: ordinary kriging and inverse distance weighting. Even though all the four models produce quite reasonable results, LWLR and RK show the best agreement with the observed station normals and leave-one-out-estimated mean absolute errors ranging from 5.1 mm (July) to 11 mm (November) for both models. Their better performances are even clearer when specific clusters of stations (e.g. high-elevation sites) are considered. Even though LWLR and RK provide very similar results both at station and at grid point level, they show some peculiar features. In particular, LWLR is found to have a better extrapolation ability at high-elevation sites when data density is high enough, while RK is more robust in performing extrapolation over areas with complex orography and scarce data coverage, where LWLR may provide unrealistic precipitation values. However, by means of prediction intervals, LWLR provides a more straightforward approach to quantify the model uncertainty at any point of the study domain, which helps to identify the areas mainly affected by model instability. LWLR and RK high-resolution climatologies exhibit a very heterogeneous and seasonal-dependent precipitation distribution throughout the domain and allow to identify the main climatic zones of Italy.

The International Surface Pressure Databank (ISPD) is the world's largest collection of global surface and sea-level pressure observations. It was developed by extracting observations from established international archives, through international cooperation with data recovery facilitated by the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative, and directly by contributing universities, organizations, and countries. The dataset period is currently 1768-2012 and consists of three data components: observations from land stations, marine observing systems, and tropical cyclone best track pressure reports. Version 2 of the ISPD (ISPDv2) was created to be observational input for the Twentieth Century Reanalysis Project (20CR) and contains the quality control and assimilation feedback metadata from the 20CR. Since then, it has been used for various general climate and weather studies, and an updated version 3 (ISPDv3) has been used in the ERA-20C reanalysis in connection with the European Reanalysis of Global Climate Observations project (ERA-CLIM). The focus of this paper is on the ISPDv2 and the inclusion of the 20CR feedback metadata. The Research Data Archive at the National Center for Atmospheric Research provides data collection and access for the ISPDv2, and will provide access to future versions.

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