The cold frontal depression that affected the area of Cyprus between 28 and 29 January 2008

The baroclinic depression that affected the area of Cyprus during the cold period, between 28 and 29 January 2008 was thoroughly studied and is presented in the present paper. A small perturbation on a northwesterly flow to the north of Cyprus has initiated the generation of the depression and in 24 h this developed into a deep baroclinic system. This depression was associated with intense weather phenomena, such as heavy thunderstorms with hail and near gale force winds. Strong cold advection resulted in a significant temperature decrease; precipitation even in lower altitudes was in the form of snow, while the accumulated rainfall corresponded to the 25% of the monthly normal. January 2008 is considered as a dry month, despite the fact that, on the average, January is considered as the wettest month of the year. In this study, the evolution and development of the depression was investigated from synoptic, dynamic, energetic and thermodynamic perspectives, in order to enhance our knowledge on the life cycle and behaviour of similar depressions over the area with extreme characteristics

A statistical analysis of sounding derived indices and parameters for extreme and non-extreme thunderstorm events over Cyprus

The main purpose of this study is to provide a simple statistical analysis of several stability indices and parameters for extreme and non-extreme thunderstorm events during the period 1997 to 2001 in Cyprus. For this study, radiosonde data from Athalassa station (35°1´ N, 33°4´ E) were analyzed during the aforementioned period. The stability indices and parameters set under study are the K index, the Total Totals (TT) index, the Convective Available Potential Energy related parameters such as Convective Available Potential Energy (CAPE), Downdraft CAPE (DCAPE) and the Convective Inhibition (CIN), the Vorticity Generator Parameter (VGP), the Bulk Richardson Number (BRN), the BRN Shear and the Storm Relative Helicity (SRH). An event is categorized as extreme, if primarily, CAPE was non zero and secondary, if values of both the K and the TotalTotals (TT) indices exceeded 26.9 and 50, respectively. The cases with positive CAPE but lower values of the other indices, were identified as non-extreme. By calculating the median, the lower and upper limits, as well as the lower and upper quartiles of the values of these indices, the main characteristics of their distribution were determined

Synoptic, thermodynamic and agroeconomic aspects of severe hail events in Cyprus

Hail is a hazardous weather element often accompanying a thunderstorm, as a result of either thermal instability or instability associated with baroclinic synoptic-scale systems (i.e. frontal depressions). Nevertheless, instability of any kind and thunderstorm activity does not always lead to the formation of hail of adequate size to reach the ground. The broader the knowledge concerning hail events the better the understanding of the underlying thermodynamic and dynamic mechanisms, as well as the physical processes associated with its formation. <br><br> In the present study, the severe hail events that were recorded in Cyprus during the ten-year period from 1996 until 2005 were examined, first by grouping them into two clusters, namely, the "thermal instability cluster" and the "frontal depression cluster". Subsequently, the spatial and temporal evolution of the synoptic, dynamic and thermodynamic characteristics of these hail events was studied in depth. Also, the impact of hailstorms on the local economy of the island is presented in terms of the compensations paid by the Agricultural Insurance Organization of the country

Preliminary verification results of the DWD limited area model LME and evaluation of its storm forecasting skill over the area of Cyprus

A preliminary verification and evaluation is made of the forecast fields of the non-hydrostatic limited area model LME of the German Weather Service (DWD), for a recent three month period. For this purpose, observations from two synoptic stations in Cyprus are utilized. In addition, days with depressions over the area were selected in order to evaluate the model's forecast skill in storm forecasting

DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.Comment: Accepted at JBI under the new name: "Predicting healthcare trajectories from medical records: A deep learning approach

Do you see what I see? Images of the COVID-19 pandemic through the lens of Google

During times of crisis, information access is crucial. Given the opaque processes behind modern search engines, it is important to understand the extent to which the “picture” of the Covid-19 pandemic accessed by users differs. We explore variations in what users “see” concerning the pandemic through Google image search, using a two-step approach. First, we crowdsource a search task to users in four regions of Europe, asking them to help us create a photo documentary of Covid-19 by providing image search queries. Analysing the queries, we find five common themes describing information needs. Next, we study three sources of variation - users’ information needs, their geo-locations and query languages - and analyse their influences on the similarity of results. We find that users see the pandemic differently depending on where they live, as evidenced by the 46% similarity across results. When users expressed a given query in different languages, there was no overlap for most of the results. Our analysis suggests that localisation plays a major role in the (dis)similarity of results, and provides evidence of the diverse “picture” of the pandemic seen through Google

Preserving the memory of the first wave of COVID-19 pandemic: Crowdsourcing a collection of image search queries

The unprecedented events of the COVID-19 pandemic have generated an enormous amount of information and populated the Web with new content relevant to the pandemic and its implications. Visual information such as images has been shown to be crucial in the context of scientific communication. Images are often interpreted as being closer to the truth as compared to other forms of communication, because of their physical representation of an event such as the COVID-19 pandemic. In this work, we ask crowdworkers across four regions of Europe that were severely affected by the first wave of pandemic, to provide us with image search queries related to COVID-19 pandemic. The goal of this study is to understand the similarities/differences of the aspects that are most important to users across different locations regarding the first wave of COVID-19 pandemic. Through a content analysis of their queries, we discovered five common themes of concern to all, although the frequency of use differed across regions

Report on the CyCAT winter school on fairness, accountability, transparency and ethics (FATE) in AI

The first FATE Winter School, organized by the Cyprus Center for Algorithmic Transparency (CyCAT) provided a forum for both students as well as senior researchers to examine the complex topic of Fairness, Accountability, Transparency and Ethics (FATE). Through a program that included two invited keynotes, as well as sessions led by CyCAT partners across Europe and Israel, participants were exposed to a range of approaches on FATE, in a holistic manner. During the Winter School, the team also organized a hands-on activity to evaluate a tool-based intervention where participants interacted with eight prototypes of bias-aware search engines. Finally, participants were invited to join one of four collaborative projects coordinated by CyCAT, thus furthering common understanding and interdisciplinary collaboration on this emerging topic

Preface "10th EGU Plinius Conference on Mediterranean Storms (2008)"

No abstract available

Tropopause and jetlet characteristics in relation to thunderstorm development over Cyprus

In the present study, the monthly statistical characteristics of jetlet and tropopause in relation to the development of thunderstorms over Cyprus are examined. For the needs of the study the 12:00 UTC radiosonde data obtained from the Athalassa station (33.4° E, 35.1° N) for an 11-year period, from 1997 till 2007, were employed. On the basis of this dataset, the height and the temperature of the tropopause, as well as the height, wind direction and speed of the jetlet were estimated. Additionally, the days in the above period with observed thunderstorms were selected and the aforementioned characteristics of the jetlet and tropopause were noted. The two data sets were subsequently contrasted in an attempt to identify possible relations between thunderstorm development, on the one hand, and tropopause and jetlet characteristics, on the other hand