5 resultados para Rain and rainfall

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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It is well known that the best grape quality can occur only through the achievement of optimal source/sink ratio. Vine balance is in fact a key parameter in controlling berry sugar, acidity and secondary metabolites content (Howell, 2001; Vanden Heuvel et al., 2004). Despite yield reduction and quality improvement are not always strictly related, cluster thinning is considered a technique which could lead to improvement in grape sugar and anthocyanin composition (Dokoozlian and Hirschfelt, 1995; Guidoni et al., 2002). Among several microclimatic variables which may impact grape composition, the effect of cluster light exposure and temperature, which probably act in synergistic and complex way, has been widely explored showing positive even sometimes contradictory results (Spayd et al., 2001; Tarara et al., 2008). Pre-bloom and véraison defoliation are very efficient techniques in inducing cluster microclimatic modification. Furthermore pre-bloom defoliation inducing a lower berry set percentage On these basis the aim of the first experiment of the thesis was to verify in cv Sangiovese the effects on ripening and berry composition of management techniques which may increase source/sink ratio and /or promote light incidence on berries throughout grape ripening. An integrated agronomic, biochemical and microarray approach, aims to understand which mechanisms are involved in berry composition and may be conditioned in the berries during ripening in vines submitted to three treatments. In particular the treatments compared were: a) cluster thinning (increasing in source/sink ratio) b) leaf removal at véraison (increasing cluster light exposure) c) pre-bloom defoliation (increasing source sink ratio and cluster light exposure). Vine response to leaf removal at véraison was further evaluated in the second experiment on three different varieties (Cabernet Sauvignon, Nero d’Avola, Raboso Piave) chosen for their different genetic traits in terms of anthocyanin amount and composition. The integrated agronomic, biochemical and microarray approach, employed in order to understand those mechanisms involved in berry composition of Sangiovese vines submitted to management techniques which may increase source/sink ratio and induce microclimatic changes, bring to interesting results. This research confirmed the main role of source/sink ratio in conditioning sugars metabolism and revealed also that carbohydrates availability is a crucial issue in triggering anthocyanin biosynthesis. More complex is the situation of pre-bloom defoliation, where source/sink and cluster light increase effects are associated to determine final berry composition. It results that the application of pre-bloom defoliation may be risky, as too much dependent on seasonal conditions (rain and temperature) and physiological vine response (leaf area recovery, photosynthetic compensation, laterals regrowth). Early induced stress conditions could bring cluster at véraison in disadvantage to trigger optimal berry ripening processes compared to untreated vines. This conditions could be maintained until harvest, if no previously described physiological recovery occurs. Certainly, light exposure increase linked to defoliation treatments, showed a positive and solid effect on flavonol biosynthesis, as in our conditions temperature was not so different among treatments. Except the last aspects, that could be confirmed also for véraison defoliation, microclimatic changes by themselves seemed not able to induce any modification in berry composition. Further studies are necessary to understand if the peculiar anthocyanic and flavonols composition detected in véraison defoliation could play important role in both color intensity and stability of wines.

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This thesis consists of three self-contained papers. In the first paper I analyze the labor supply behavior of Bologna Pizza Delivery Vendors. Recent influential papers analyze labor supply behavior of taxi drivers (Camerer et al., 1997; and Crawford and Meng, 2011) and suggest that reference-dependence preferences have an important influence on drivers’ labor-supply decisions. Unlike previous papers, I am able to identify an exogenous and transitory change in labor demand. Using high frequency data on orders and rainfall as an exogenous demand shifter, I invariably find that reference-dependent preferences play no role in their labor’ supply decisions and the behavior of pizza vendors is perfectly consistent with the predictions of the standard model of labor’ supply. In the second paper, I investigate how the voting behavior of Members of Parliament is influenced by the Members seating nearby. By exploiting the random seating arrangements in the Icelandic Parliament, I show that being seated next to Members of a different party increases the probability of not being aligned with one’s own party. Using the exact spatial orientation of the peers, I provide evidence that supports the hypothesis that interaction is the main channel that explain these results. In the third paper, I provide an estimate of the trade flows that there would have been between the UK and Europe if the UK had joined the Euro. As an alternative approach to the standard log-linear gravity equation I employ the synthetic control method. I show that the aggregate trade flows between Britain and Europe would have been 13% higher if the UK had adopted the Euro.

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The interaction between atmosphere–land–ocean–biosphere systems plays a prominent role on the atmospheric dynamics and on the convective rainfall distribution over the West Africa monsoon area during the boreal summer. In particular, the initialization of convective systems in the Sub – Sahelian region has been directly linked to soil moisture heterogeneities identified as the major triggering, development and propagation of convective systems. The present study aims at investigating African monsoon large scale convective dynamics and rainfall diurnal cycle through an exploration of the hypothesis behind the mechanisms of a monsoon phenomenon as an emergence of a collective dynamics of many propagating convective systems. Such hypothesis is based on the existence of an internal self – regulation mechanism among the various components. To achieve these results a multiple analysis was performed based on remote sensed rainfall dataset, and global and regional modelling data for a period of 5 seasons: 2004 - 2008. Satellite rainfall data and convective occurrence variability were studied for assessing typical spatio – temporal signatures and characteristics with an emphasis to the diurnal cycle footprint. A global model and regional model simulation datasets, specifically developed for this analysis and based on Regional Atmospheric Modelling System – RAMS, have been analysed. Results from numerical model datasets highlight the evidence of a synchronization between the destabilization of the convective boundary layer and rainfall occurrence due to the solar radiation forcing through the latent heat release. This supports the conclusion that the studied interacting systems are associated with a process of mutual adjustment of rhythms. Furthermore, this rainfall internal coherence was studied in relation to the West African Heat Low pressure system, which has a prominent role in the large scale summer variability over the Mediterranean area since it is acting as one of dynamic link between sub tropical and midlatitudes variability.

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Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

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Extreme weather events related to deep convection are high-impact critical phenomena whose reliable numerical simulation is still challenging. High-resolution (convection-permitting) modeling setups allow to switch off physical parameterizations accountable for substantial errors in convection representation. A new convection-permitting reanalysis over Italy (SPHERA) has been produced at ARPAE to enhance the representation and understanding of extreme weather situations. SPHERA is obtained through a dynamical downscaling of the global reanalysis ERA5 using the non-hydrostatic model COSMO at 2.2 km grid spacing over 1995-2020. This thesis aims to verify the expectations placed on SPHERA by analyzing two weather phenomena that are particularly challenging to simulate: heavy rainfall and hail. A quantitative statistical analysis over Italy during 2003-2017 for daily and hourly precipitation is presented to compare the performance of SPHERA with its driver ERA5 considering the national network of rain gauges as reference. Furthermore, two extreme precipitation events are deeply investigated. SPHERA shows a quantitative added skill over ERA5 for moderate to severe and rapid accumulations in terms of adherence to the observations, higher detailing of the spatial fields, and more precise temporal matching. These results prompted the use of SPHERA for the investigation of hailstorms, for which the combination of multiple information is crucial to reduce the substantial uncertainties permeating their understanding. A proxy for hail is developed by combining hail-favoring environmental numerical predictors with observations of ESWD hail reports and satellite overshooting top detections. The procedure is applied to the extended summer season (April-October) of 2016-2018 over the whole SPHERA spatial domain. The results indicate maximum hail likelihood over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The method demonstrates enhanced performance in case of severe hail occurrences and the ability to separate between ambient signatures depending on hail severity.