L'alluvione di Firenze: la previsione del 1966 con gli strumenti di oggi

<p>Presentation held in Florence (Italy) on 3rd November 2016 to mark the 50-th Anniversary of the "Alluvione di Firenze"</p

A simple assimilation method to ingest satellite soil moisture into a limited-area NWP model

Recently several studies discussed the potential and operational use of satellite soil moisture measurements in new land surface analysis feeding global Numerical Weather Prediction (NWP) models. This work seeks to establish whether a limited-area NWP model might benefit from the assimilation of remotely sensed soil moisture data. The question is important because it is well known that even small errors in the initial conditions could amplify in the future states and lead to erroneous predictions. On the other hand, remotely sensed soil moisture observations are attractive because they offer a synoptic point of view and their reliability with respect to in-situ measurements is demonstrated.The authors used a simple nudging scheme in order to assimilate remotely sensed soil moisture data into a limited-area NWP model. This assimilation method is computationally cheap and simple to implement. Its impact on numerical outputs is evaluated with respect to a control simulation performed without assimilation. Results obtained in both simulations are validated with in-situ soil moisture measurements and with 2-meter temperature observations. Results demonstrate the benefits of the assimilation especially in those remote areas where the coverage of observational instruments is poor and where the irregularity of observations implies interpolation errors when reporting data on a regular grid. As found in bibliography, in well monitored areas the impact of the assimilation is almost neutral

R package rWindrose: 0.2

rWindrose R package Packages to performs data extraction and windrose plot. To install go to https://github.com/alfcrisci/rWindros

Guided Bone Regeneration in the Treatment of a Lateral Periodontal Cyst: 2-Year Clinical and Radiologic Follow-up

Lateral periodontal cysts (LPCs) are rare odontogenic cysts of developmental origin. A 52-year-old man presented with an asymptomatic gingival swelling located between the mandibular left canine and first premolar, both of which were vital. Radiography showed a well-circumscribed radiolucent area and loss of the lamina dura around the tooth socket in contact with the lesion and of the interproximal buccal bone. The lesion was enucleated. The defect was immediately grafted with a 1:1 mixed autologous and heterologous bone graft covered with a collagen membrane. Histology confirmed the diagnosis of LPC. At 12- and 24-month clinical and radiologic follow-up, complete bone and periodontal healing was found, with no sign of recurrence

Guided Bone Regeneration in the Treatment of a Lateral Periodontal Cyst: 2-Year Clinical and Radiologic Follow-up

Lateral periodontal cysts (LPCs) are rare odontogenic cysts of developmental origin. A 52-year-old man presented with an asymptomatic gingival swelling located between the mandibular left canine and first premolar, both of which were vital. Radiography showed a well-circumscribed radiolucent area and loss of the lamina dura around the tooth socket in contact with the lesion and of the interproximal buccal bone. The lesion was enucleated. The defect was immediately grafted with a 1:1 mixed autologous and heterologous bone graft covered with a collagen membrane. Histology confirmed the diagnosis of LPC. At 12- and 24-month clinical and radiologic follow-up, complete bone and periodontal healing was found, with no sign of recurrence

Dynamical Downscaling of ERA5 Data on the North-Western Mediterranean Sea: From Atmosphere to High-Resolution Coastal Wave Climate

A 29-year wind/wave hindcast is produced over the Mediterranean Sea for the period 1990–2018. The dataset is obtained by downscaling the ERA5 global atmospheric reanalyses, which provide the initial and boundary conditions for a numerical chain based on limited-area weather and wave models: the BOLAM, MOLOCH and WaveWatch III (WW3) models. In the WW3 computational domain, an unstructured mesh is used. The variable resolutions reach up to 500 m along the coasts of the Ligurian and Tyrrhenian seas (Italy), the main objects of the study. The wind/wave hindcast is validated using observations from coastal weather stations and buoys. The wind validation provides velocity correlations between 0.45 and 0.76, while significant wave height correlations are much higher—between 0.89 and 0.96. The results are also compared to the original low-resolution ERA5 dataset, based on assimilated models. The comparison shows that the downscaling improves the hindcast reliability, particularly in the coastal regions, and especially with regard to wind and wave directions

Tracking Animals in a Dynamic Environment: Remote Sensing Image Time Series, Spatial Database for GPS Wildlife Tracking Data

This chapter looks into the spatiotemporal dimension of both animal tracking data sets and the dynamic environmental data that can be associated with them. Typically, these geographic layers derive from remote sensing measurements, commonly those collected by sensors deployed on earth-orbiting satellites, which can be updated on a monthly, weekly or even daily basis. The modelling potential for integrating these two levels of ecological complexity (animal movement and environmental variability) is huge and comes from the possibility to investigate processes as they build up, i.e. in a full dynamic framework. This chapter’s exercise will describe howto integrate dynamic environmental data in the spatial database and join to animal locations one of the most used indices for ecological productivity and phenology, the normalised difference vegetation index (NDVI) derived from MODI