Daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022, are reported. Over this period, the weather station of Padua center underwent many changes, in location or instrument; therefore, some homogeneity tests have been used to identify and remove the effects of these variations and obtain a homogeneous time series. Both absolute and relative tests have been applied and several nearby stations and two reanalysis datasets (ERA5 and MERIDA) have been considered, to enhance the picture of the local situation and provide more robust conclusions. The original observations and the final complete corrected time series with the associated metadata are reported.OB_UNIPD contains daily minimum and maximum temperature collected at the Botanical Garden between 01/01/1980 and 31/12/1993 by the University of Padua;OB_micros_UNIPD contains daily minimum and maximum temperatures collected at the Botanical Garden between 01/10/1993 and 13/12/2001 by the University of Padua using a MICROS weather station;OB_ARPAV contains daily minimum and maximum temperatures collected at the Botanical Garden between 01/05/2000 and 10/03/2019 by ARPAV;CUS_ARPAV contains daily minimum and maximum temperatures collected at the University Sports Center between 11/03/2019 and 30/06/2023 by ARPAV;OB_FINAL_SERIES contains the homogenized daily minimum and maximum temperatures between 01/01/1980 and 30/06/2023, using OB_ARPAV as reference. Metadata are also indicated, reporting the source of each value. The meaning of the metadata codes is reported in OB_FINAL_SERIES_metadata
Abstract. This study explores the grain size seasonal variations on the East Antarctic Plateau, where dry metamorphism occurs, by using microwave radiometer observations from 2000 to 2022. Local meteorological conditions and large scale atmospheric phenomena have been considered in order to explain some peculiar changes of the snow grains. We find that the highest ice divide is the region with the largest grain size in the summer, mainly because the wind speed is low. Moreover, some extreme grain size values with respect to the average (over +3σ) were identified. In these cases, the ERA5 reanalysis revealed a high pressure blocking/ridge situation in the proximity of the onsets of the summer increase of the grain size, conveying the relatively warm and moist air coming from the mid latitudes, often associated with atmospheric rivers. If weak wind and low temperature conditions occur during the following weeks, dry snow metamorphism is facilitated, leading to grain growth. This determines anomalous high maximums of the snow grain size at the end of summer. These phenomena confirm the importance of moisture intrusion events in the East Antarctica and their impact on the physical properties of the ice sheet surface, with a co-occurrence of atmospheric rivers and seasonal changes of the grain size significant over 95 %.
The Padua temperature series is one of the longest in the world, as daily observations started in 1725 and have continued almost unbroken to the present. Previous works recovered readings from the original logs, and digitalized and corrected observations from errors due to instruments, calibrations, sampling times and exposure. However, the series underwent some changes (location, elevation, observing protocols, and different averaging methods) that affected the homogeneity between sub-series. The aim of this work is to produce a homogenized temperature series for Padua, starting from the results of previous works, and connecting all the periods available. The homogenization of the observations has been carried out with respect to the modern era. A newly released paleo-reanalysis dataset, ModE-RA, is exploited to connect the most ancient data to the recent ones. In particular, the following has been carried out: the 1774–2023 daily mean temperature has been homogenized to the modern data; for the first time, the daily values of 1765–1773 have been merged and homogenized; and the daily observations of the 1725–1764 period have been connected and homogenized to the rest of the series. Snowfall observations, extracted from the same logs from which the temperatures were retrieved, help to verify the robustness of the homogenization procedure by looking at the temperature frequency distribution on snowy days, before and after the correction. The possibility of adding new measurements with no need to apply transformations or homogenization procedures makes it very easy to update the time series and make it immediately available for climate change analysis.
Daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022, are reported. Over this period, the weather station of Padua center underwent many changes, in location or instrument; therefore, some homogeneity tests have been used to identify and remove the effects of these variations and obtain a homogeneous time series. Both absolute and relative tests have been applied and several nearby stations and two reanalysis datasets (ERA5 and MERIDA) have been considered, to enhance the picture of the local situation and provide more robust conclusions. The original observations and the final complete corrected time series with the associated metadata are reported.OB_UNIPD contains daily minimum and maximum temperature collected at the Botanical Garden between 01/01/1980 and 31/12/1993 by the University of Padua;OB_micros_UNIPD contains daily minimum and maximum temperatures collected at the Botanical Garden between 01/10/1993 and 13/12/2001 by the University of Padua using a MICROS weather station;OB_ARPAV contains daily minimum and maximum temperatures collected at the Botanical Garden between 01/05/2000 and 10/03/2019 by ARPAV;CUS_ARPAV contains daily minimum and maximum temperatures collected at the University Sports Center between 11/03/2019 and 30/06/2023 by ARPAV;OB_FINAL_SERIES contains the homogenized daily minimum and maximum temperatures between 01/01/1980 and 30/06/2023, using OB_ARPAV as reference. Metadata are also indicated, reporting the source of each value. The meaning of the metadata codes is reported in OB_FINAL_SERIES_metadata
Abstract. This study explores the grain size seasonal variations on the East Antarctic Plateau, where dry metamorphism occurs, by using microwave radiometer observations from 2000 to 2022. Local meteorological conditions and large scale atmospheric phenomena have been considered in order to explain some peculiar changes of the snow grains. We find that the highest ice divide is the region with the largest grain size in the summer, mainly because the wind speed is low. Moreover, some extreme grain size values with respect to the average (over +3σ) were identified. In these cases, the ERA5 reanalysis revealed a high pressure blocking/ridge situation in the proximity of the onsets of the summer increase of the grain size, conveying the relatively warm and moist air coming from the mid latitudes, often associated with atmospheric rivers. If weak wind and low temperature conditions occur during the following weeks, dry snow metamorphism is facilitated, leading to grain growth. This determines anomalous high maximums of the snow grain size at the end of summer. These phenomena confirm the importance of moisture intrusion events in the East Antarctica and their impact on the physical properties of the ice sheet surface, with a co-occurrence of atmospheric rivers and seasonal changes of the grain size significant over 95 %.
The study of long precipitation series constitutes an important issue in climate research and risk assessment. However, long datasets are affected by inhomogeneities that can lead to biased results. A frequent but sometimes underestimated problem is the definition of the climatological day. The choice of different starting times may lead to inhomogeneity within the same station and misalignment with other stations. In this work, the problem of temporal misalignment between precipitation datasets characterized by different starting times of the observation day is analyzed. The most widely used adjustment methods (1 day and uniform shift) and two new methods based on reanalysis (NOAA and ERA5) are evaluated in terms of temporal alignment, precipitation statistics, and percentile distributions. As test series, the hourly precipitation series of Padua and nearby stations in the period of 1993–2022 are selected. The results show that the reanalysis-based methods, in particular ERA5, outperform the others in temporal alignment, regardless of the station. But, for the periods in which reanalysis data are not available, 1-day and uniform shift methods can be considered viable alternatives. On the other hand, the reanalysis-based methods are not always the best option in terms of precipitation statistics, as they increase the precipitation frequency and reduce the mean value over wet days, NOAA much more than ERA5. The use of the series of a station near the target one, which is mandatory in case of missing data, can sometimes give comparable or even better results than any adjustment method. For the Padua series, the analysis is repeated at monthly and seasonal resolutions. In the tested series, the adjustment methods do not provide good results in summer and autumn, the two seasons mainly affected by heavy rains in Padua. Finally, the percentile distribution indicates that any adjustment method underestimates the percentile values, except ERA5, and that only the nearby station most correlated with Padua gives results comparable to ERA5.
Abstract. This study explores the seasonal variations in snow grain size on the East Antarctic Plateau, where dry metamorphism occurs, by using microwave radiometer observations from 2000 to 2022. Local meteorological conditions and large-scale atmospheric phenomena have been considered in order to explain some peculiar changes in the snow grains. We find that the highest ice divide is the region with the largest grain size in the summer, mainly because the wind speed is low. Moreover, some extreme grain size values with respect to the average (over +3σ) were identified. In these cases, the ERA5 reanalysis revealed a high-pressure blocking close to the onsets of the summer increase in the grain size. It channels moisture intrusions from the mid-latitudes, through atmospheric rivers that cause major snowfall events over the plateau. If conditions of weak wind and low temperature occur during the following weeks, dry snow metamorphism is facilitated, leading to grain growth. This determines anomalous high maximums of the snow grain size at the end of summer. These phenomena confirm the importance of moisture intrusion events in East Antarctica and their impact on the physical properties of the ice sheet surface, with a co-occurrence of atmospheric rivers and seasonal changes in the grain size with a significance of over 95 %.
Meteorological observations over the last four decades are of paramount importance to investigate the ongoing climate change. The assessment of the reliability of any climatic time series is thus mandatory to draw correct conclusions. This evaluation involves homogeneity tests to detect artificial discontinuities whose identification is facilitated by metadata availability. In this work, daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022, are examined. Hourly observations began in 1993 and since the aim is to study long term behavior of the temperature, the focus is on daily averages and extremes. Over this period, the weather station of Padua center underwent many changes, in location or instrument; therefore, some tests have been used to identify and remove the effects of these variations and obtain a homogeneous time series. The homogeneity tests applied must be able to identify change-points both in the middle and at the extremes of the series. Some well-known absolute tests have been applied to investigate shift in the mean value: Standard Normal Homogeneity test (SNH), Buishand U and range tests, Pettitt test, F-test, STARS. Some relative tests have been applied too, which are generally more reliable than absolute tests, because they consider the information from neighboring stations. As relative tests rely on the homogeneity and quality of the reference series, several nearby stations and two reanalysis datasets (ERA5 and MERIDA) have been considered, to enhance the picture of the local situation and provide more robust conclusions. The applied tests identify change-points in the years in which a change in instrument or location of the station have occurred, confirming that these changes have compromised the homogeneity of the series. The sub-series obtained splitting the observations in correspondence of these change-points have been homogenized with respect a selected period; corrections must be applied also to future measurements to extend the time series properly.
