Analysis of evening and morning transitions in complex terrain: MATERHORN campaign 2013

A field study of thermal circulation over very gentle slope is described for a specific day characterised by weak synoptic conditions. The emphasis was on morning and evening transitions, but measurements cover the entire day; therefore a brief analysis is performed to represent the general thermal circulation pattern. Both transition periods are characterised by complex dynamic behaviours. During evening transition, the upslope flow has got through a stagnation condition characterised by wind velocity U<0:5 m=s. Only when the stagnating air has become negative buoyant, the flow is allowed to pour downslope like a slab. Some features of front formation has been found during the transition development, such as delay time of downslope flow start up along the slope, and the presence of positive turbulent kinetic energy at the onset of the motion. Eventually the observed evening transition has followed a mixed mechanisms, with features from different models. Therefore the Rayleigh number seems not to be a good criterion by which parametrise evening transition itself. Morning transition is characterised by destruction of nocturnal temperature inversion and the onset of upslope flow. Inversion destruction can be described in terms of CBL growth at surface and inversion decent from the top of the layer. KH has found to be a good indicator of inversion breakup, if used as parameter to study the inversion breakup in terms of temperature reversal. After the inversion breakup, buoyancy and mechanical productions supply the flow with the necessary energy to start the upslope wind. More quantitative analysis are provided by the study of stability parameters and turbulent kinetic energy budgets. Gradient Richardson number has been used in this terms, finding that a mixed SBL-CBL behaviour dominates the most of the observed layers. Tke budget has shown high turbulent behaviour during morning transition while the evening transition has developed entirely in laminar condition, apart from short intermittent turbulent events.

Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data

Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.