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Fabbisogno in freddo per le colture arboree nella Regione Abruzzo - Aspetti climatologici
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Evaluation of the similarity between drought indices by correlation analysis and Cohen's Kappa test in a Mediterranean area
No full textIn the literature, numerous papers report comparative analyses of drought indices. In these types of studies, the similarity between drought indices is usually evaluated using the Pearson correlation coefficient, r, calculated between corresponding severity time series. However, it is well known that the correlation does not describe the strength of agreement between two variables. Two drought indices can exhibit a high degree of correlation but can, at the same time, disagree substantially, for example, if one index is consistently higher than the other. From an operational point of view, two indices can be considered in agreement when they indicate the same severity category for a given period (e.g. moderate drought). In this work, we compared six meteorological drought indices based on both correlation analysis and Cohen's Kappa test. This test is typically used in medical or social sciences to obtain a quantitative assessment of the degree of agreement between different methods or analysts. The indices considered are five timescale-dependent indices, i.e. the Percent of Normal Index, the Deciles Index, the Percentile Index, the Rainfall Anomaly Index, and the Standardised Precipitation Index, computed at the 1-, 3-, and 6-month timescales, and the Effective Drought Index, a relatively new index, which has a self-defined timescale. The indices were calculated for 15 stations in the Abruzzo region (central Italy) during 1951–2018. We found that the strength of agreement depends on both the criteria of drought severity classification and the different indices' calculation methods. The Cohen's Kappa test indicates a prevailing moderate or fair agreement among the indices considered, despite the generally very high correlation between the corresponding severity times series. The results demonstrate that the Cohen's Kappa test is more effective than the correlation analysis in discriminating the actual strength of agreement/disagreement between drought indices
Effect of the North Atlantic Oscillation on winter daily rainfall and runoff in the Abruzzo region (Central Italy)
No full textIn this paper a composite analysis was used to assess the influence of the North Atlantic Oscillation (NAO) on the winter daily rainfall and seasonal runoff at 28 stations of the Abruzzo region (Central Italy) during the period 1951–2012. Compositing was based on NAO− and NAO+ phases, identified by mean winter values of the normalized NAO index (NAOI) ≤−0.75 and ≥+0.75, respectively. In accordance with previous studies, it was found that NAO− phases determine, in general, a greater number of wet days (Nw) and (consequently) higher seasonal rainfall amounts in comparison to NAO+ phases. However, the NAO influence is characterized by a certain spatial variability, that can mostly be explained by orographic effects due to the Apennine Mountains. This is particularly evident for the mean rainfall depth per event (Pe) that, during NAO− phases, increases for the stations to the west of the Apennines, while it decreases for most of the stations to the east. The structure of winter daily rainfall of NAO+ and NAO− type, was described by a simple but effective first-order Markov process, determining the transition probabilities P01 (dry to wet) and P10 (wet to dry) and modelling the rainfall depth on wet days by a Weibull distribution. The most significant influence of NAO concerns P01 and the shape parameter of the Weibull distribution that are both higher during the NAO− phase. This means that NAO− phases are characterized by less persistent dry periods and less variable daily rainfall depths, in comparison to NAO+ phases. The effect of these differences on the winter seasonal runoff was explored by applying a Curve Number rainfall-runoff model. Significant increments of the mean seasonal runoff during NAO− phases were observed only for few stations (mainly on the west), characterized by corresponding increments of Nw, Ptot and Pe.). NAO+ phases, instead, are characterized by relevant increments of the seasonal runoff variability, particularly on the eastern areas. In this context, the important regulating function of the watershed conditions was also discussed
Uncertainty in drought monitoring by the Standardized Precipitation Index: the case study of the Abruzzo region (central Italy)
No full textTheoretical and Applied Climatology
5 December 2015, Pages 1-14
Uncertainty in drought monitoring by the Standardized Precipitation Index: the case study of the Abruzzo region (central Italy) ( Articles not published yet, but available online Article in press About articles in press (opens in a new window) )
Vergni, L.a , Di Lena, B.b, Todisco, F.a, Mannocchi, F.a
a Department of Agricultural, Food and Environmental Sciences, University of Perugia, Borgo XX Giugno 74, Perugia, Italy
b Region of Abruzzo, Agricultural Management, Regional Agrometeorological Center, Scerni, CH, Italy
Abstract
As shown by several authors, drought monitoring by the Standardized Precipitation Index (SPI) presents some uncertainties, mainly dependent on the choice of the probability distribution used to describe the cumulative precipitation and on the characteristics (e.g., length and variability) of the dataset. In this paper, the uncertainty related to SPI estimates has been quantified and analyzed with regards to the case study of the Abruzzo region (Central Italy), by using monthly precipitation recorded at 75 stations during the period 1951–2009. First, a set of distributions suitable to describe the cumulative precipitation at the 3-, 6-, and 12-month time scales was identified by using L-moments ratio diagrams. The goodness-of-fit was evaluated by applying the Kolmogorov–Smirnov test, and the Normality test on the derived SPI series. Then the confidence intervals of SPI have been calculated by applying a bootstrap procedure. The size of the confidence intervals has been considered as a measure of uncertainty, and its dependence on several factors such as the distribution type, the time scale, the record length, and the season has been examined. Results show that the distributions Pearson type III (PE3), Weibull (WEI), Generalized Normal (GNO), Generalized Extreme Value (GEV), and Gamma (GA2) are all suitable to describe the cumulative precipitation, with a slightly better performance of the PE3 and GNO distributions. As expected, the uncertainty increases as the record length and time scale decrease. The leading source of uncertainty is the record length while the effects due to seasonality and time scale are negligible. Two-parameter distributions make it possible to obtain confidence intervals of SPI (particularly for extreme values) narrower than those obtained by three-parameter distributions. Nevertheless, due to a poorer goodness of fit, two-parameter distributions can provide less reliable estimates of the precipitation probability. In any event, independently of the type of distribution, the SPI estimates corresponding to extreme precipitation values are always characterized by a relevant uncertainty. This is due to the explosion of the probability variability that occurs when precipitation values approach the tails of the supposed distributio
Monitoraggio delle condizioni di aridità nella Regione Abruzzo mediante l'impiego di un bilancio idrico colturale
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