This work analyses the precipitation series for 15 meteorological series in Piedmont. The meteorological stations have been chosen because they were meteorological observatories operating continuously for 96 years, from 1913 to 2008. As the first step an historical research over each station has been carried out. In this way, the potential breaks, in the series, either due to changes of location or instruments, have been determined. The Hydrographic Annals, in which the geographical coordinates of each stations (latitude, longitude and elevations) were recorded every years, and the paper registers, where the observers have recorded any changes or malfunctions of the instruments, have been consulted. On the precipitation daily series a quality control have been effectuated by RClimDex program (Zhang et al., 2004). The software allow to identify the outliers caused by an incorrect reading of, or by a wrong transcription from, the original paper. Subsequently the precipitation daily values have been reconstructed, where it was possible, by creating a “complete” dataset, without missing data. Four methods based on different weight averaging techniques (Eischeid et al., 2000) have been chosen: (i) the normal ratio method, (ii) the simple inverse distance weighting, (iii) the multiple regression and (iv) the average of the previous three methods. The selection of the value for filling the gap has been done by choosing the method showing the highest correlation coefficient with the original series. As the last step the SPLIDHOM program (Gruber et al., in press) to homogenize the daily series have been applied. In this way we have obtained the homogeneous series on which trends have been computed and the non-parametric Mann-Kendall test has been used to understand the statistical meaning of the trend. Finally, to illustrate the trend of temperature and precipitation average and extreme values, the indices proposed by “CCL/CLIVAR Working Group on Climate Change Detection” have been calculated. In order to better understand the consequences of climate variations on our environment and society, we have calculated the climate indices (dry and wet days, rainy days, density of precipitation) over the time and also the pluviometric regimes and polygons of Balseinte. The values of precipitation have also allowed to begin the climatic analysis with the aim at defining the principle local climates in Piedmont.
Valuations on historical series of precipitation in Piedmont (NW Italy)
ACQUAOTTA, FIORELLA;FRATIANNI, SIMONA
2009-01-01
Abstract
This work analyses the precipitation series for 15 meteorological series in Piedmont. The meteorological stations have been chosen because they were meteorological observatories operating continuously for 96 years, from 1913 to 2008. As the first step an historical research over each station has been carried out. In this way, the potential breaks, in the series, either due to changes of location or instruments, have been determined. The Hydrographic Annals, in which the geographical coordinates of each stations (latitude, longitude and elevations) were recorded every years, and the paper registers, where the observers have recorded any changes or malfunctions of the instruments, have been consulted. On the precipitation daily series a quality control have been effectuated by RClimDex program (Zhang et al., 2004). The software allow to identify the outliers caused by an incorrect reading of, or by a wrong transcription from, the original paper. Subsequently the precipitation daily values have been reconstructed, where it was possible, by creating a “complete” dataset, without missing data. Four methods based on different weight averaging techniques (Eischeid et al., 2000) have been chosen: (i) the normal ratio method, (ii) the simple inverse distance weighting, (iii) the multiple regression and (iv) the average of the previous three methods. The selection of the value for filling the gap has been done by choosing the method showing the highest correlation coefficient with the original series. As the last step the SPLIDHOM program (Gruber et al., in press) to homogenize the daily series have been applied. In this way we have obtained the homogeneous series on which trends have been computed and the non-parametric Mann-Kendall test has been used to understand the statistical meaning of the trend. Finally, to illustrate the trend of temperature and precipitation average and extreme values, the indices proposed by “CCL/CLIVAR Working Group on Climate Change Detection” have been calculated. In order to better understand the consequences of climate variations on our environment and society, we have calculated the climate indices (dry and wet days, rainy days, density of precipitation) over the time and also the pluviometric regimes and polygons of Balseinte. The values of precipitation have also allowed to begin the climatic analysis with the aim at defining the principle local climates in Piedmont.
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