Rescue and quality control of sub-daily meteorological data collected at Montevergine Observatory (Southern Apennines), 1884–1963

Abstract

Here we present the rescue of sub-daily meteorological observations collected from 1884 to 1963 at Montevergine Observatory, located in the Southern Apennines in Italy. The recovered dataset consists of 3-daily observations of the following atmospheric variables: dry-bulb temperature, wet-bulb temperature, water vapour pressure, relative humidity, atmospheric pressure, cloud type, cloud cover, rainfall, snowfall and precipitation type. The data, originally available only as paper-based records, have been digitized following the World Meteorological Organization standard practices. After a cross-check, the digitized data went through three different automatic quality control tests: the gross error test, which verifies whether the data are within acceptable range limits; the tolerance test, which flags whether values are above or below monthly climatological limits that are defined in accordance with a probability distribution model specific to each variable; and the temporal coherency test, which checks the rate of change and flags unrealistic jumps in consecutive values. The result of this process is the publication of a new historical dataset that includes, for the first time, digitized and quality-controlled sub-daily meteorological observations collected since the late 19th century in the Mediterranean region north of the 37th parallel. These data are critical to enhancing and complementing previously rescued sub-daily historical datasets – which are currently limited to atmospheric pressure observations only – in the central and northern Mediterranean regions. Furthermore, the Montevergine Observatory (MVOBS) dataset can enrich the understanding of high-altitude weather and climate variability, and it contributes to the improvement of the accuracy of reanalysis products prior the 1950s. Data are available on the NOAA's National Centers for Environmental Information (NCEI) public repository and are associated with a DOI: https://doi.org/10.25921/cx3g-rj98 (Capozzi et al., 2019).