Scenarios in the development of Mediterranean cyclones

The Mediterranean is one of the most cyclogenetic regions in the world. The cyclones are concentrated along its northern coasts and their tracks are oriented more or less west-east, with several secondary tracks connecting them to Europe and to North Africa. The aim of this study is to examine scenarios in the development of Mediterranean cyclones, based on five selected winter seasons (October–March). We detected the cyclones subjectively using 6-hourly Sea-Level Pressure maps, based on the NCAR/NCEP reanalysis archive. <br><br> HMSO (1962) has shown that most Mediterranean cyclones (58%) enter the Mediterranean from the Atlantic Ocean (through Biscay and Gibraltar), and from the south-west, the Sahara Desert, while the rest are formed in the Mediterranean Basin itself. Our study revealed that only 13% of the cyclones entered the Mediterranean, while 87% were generated in the Mediterranean Basin. The entering cyclones originate in three different regions: the Sahara Desert (6%), the Atlantic Ocean (4%), and Western Europe (3%). <br><br> The cyclones formed within the Mediterranean Basin were found to generate under the influence of external cyclonic systems, i.e. as "daughter cyclones" to "parent cyclones" or troughs. These parent systems are located in three regions: Europe (61%), North Africa and the Red Sea (34.5%) and the Mediterranean Basin itself (4.5%). The study presents scenarios in the development of Mediterranean cyclones during the winter season, emphasizing the cyclogenesis under the influence of various external forcing. <br><br> The large difference with respect to the findings of HMSO (1962) is partly explained by the dominance of spring cyclones generating in the Sahara Desert, especially in April and May that were not included in our study period

Coupled climate model simulations of Mediterranean winter cyclones and large-scale flow patterns

The study aims to evaluate the ability of global, coupled climate models to reproduce the synoptic regime of the Mediterranean Basin. The output of simulations of the 9 models included in the IPCC CMIP3 effort is compared to the NCEP-NCAR reanalyzed data for the period 1961–1990. The study examined the spatial distribution of cyclone occurrence, the mean Mediterranean upper- and lower-level troughs, the inter-annual variation and trend in the occurrence of the Mediterranean cyclones, and the main large-scale circulation patterns, represented by rotated EOFs of 500 hPa and sea level pressure. The models reproduce successfully the two maxima in cyclone density in the Mediterranean and their locations, the location of the average upper- and lower-level troughs, the relative inter-annual variation in cyclone occurrences and the structure of the four leading large scale EOFs. The main discrepancy is the models' underestimation of the cyclone density in the Mediterranean, especially in its western part. The models' skill in reproducing the cyclone distribution is found correlated with their spatial resolution, especially in the vertical. The current improvement in model spatial resolution suggests that their ability to reproduce the Mediterranean cyclones would be improved as well

The spatio-temporal distribution of lightning over Israel and the neighboring area and its relation to regional synoptic systems

The spatio-temporal distribution of lightning flashes over Israel and the neighboring area and its relation to the regional synoptic systems has been studied, based on data obtained from the Israel Lightning Location System (ILLS) operated by the Israel Electric Corporation (IEC). The system detects cloud-to-ground lightning discharges in a range of ~500 km around central Israel (32.5° N, 35° E). The study period was defined for annual activity from August through July, for 5 seasons in the period 2004–2010. <br><br> The spatial distribution of lightning flash density indicates the highest concentration over the Mediterranean Sea, attributed to the contribution of moisture as well as sensible and latent heat fluxes from the sea surface. Other centers of high density appear along the coastal plain, orographic barriers, especially in northern Israel, and downwind from the metropolitan area of Tel Aviv, Israel. The intra-annual distribution shows an absence of lightning during the summer months (JJA) due to the persistent subsidence over the region. The vast majority of lightning activity occurs during 7 months, October to April. Although over 65 % of the rainfall in Israel is obtained during the winter months (DJF), only 35 % of lightning flashes occur in these months. October is the richest month, with 40 % of total annual flashes. This is attributed both to tropical intrusions, i.e., Red Sea Troughs (RST), which are characterized by intense static instability and convection, and to Cyprus Lows (CLs) arriving from the west. <br><br> Based on daily study of the spatial distribution of lightning, three patterns have been defined; "land", "maritime" and "hybrid". CLs cause high flash density over the Mediterranean Sea, whereas some of the RST days are typified by flashes over land. The pattern defined "hybrid" is a combination of the other 2 patterns. On CL days, only the maritime pattern was noted, whereas in RST days all 3 patterns were found, including the maritime pattern. It is suggested that atmospheric processes associated with RST produce the land pattern. Hence, the occurrence of a maritime pattern in days identified as RST reflects an "apparent RST". The hybrid pattern was associated with an RST located east of Israel. This synoptic type produced the typical flash maximum over the land, but the upper-level trough together with the onshore winds it induced over the eastern coast of the Mediterranean resulted in lightning activity over the sea as well, similar to that of CLs. <br><br> It is suggested that the spatial distribution patterns of lightning may better identify the synoptic system responsible, a CL, an "active RST" or an "apparent RST". The electrical activity thus serves as a "fingerprint" for the synoptic situation responsible for its generation

Using social media, machine learning and natural language processing to map multiple recreational beneficiaries

Information and numbers on the use and appreciation of nature are valuable information for protected area (PA) managers. A promising direction is the utilisation of social media, such as the photo-sharing website Flickr. Here we demonstrate a novel approach, borrowing techniques from machine learning (image analysis), natural language processing (Latent Semantic Analysis (LSA)) and self-organising maps (SOM), to collect and interpret >20,000 photos from the Camargue region in Southern France. From the perspective of Cultural Ecosystem Services (CES), we assessed the relationship between the use of the Camargue delta and the presence of natural elements by consulting local managers. Clustering algorithms applied to results of the LSA data revealed six distinct user groups, which included those interested in nature, ornithology, religious pilgrimage, general tourists and aviation enthusiasts. For each group, we produced high-resolution spatial and seasonal maps, which matched known recreational attractions and annual festivals in the Camargue. The accuracy of the group identification, and the spatial and temporal patterns of photo activity, in the Camargue delta were evaluated by local managers of the Camargue regional park. This study demonstrates how PA managers can harness social-media to monitor recreation and improve their management decision making

A statistical method for revealing form-function relations in biological networks

Over the past decade, a number of researchers in systems biology have sought to relate the function of biological systems to their network-level descriptions -- lists of the most important players and the pairwise interactions between them. Both for large networks (in which statistical analysis is often framed in terms of the abundance of repeated small subgraphs) and for small networks which can be analyzed in greater detail (or even synthesized in vivo and subjected to experiment), revealing the relationship between the topology of small subgraphs and their biological function has been a central goal. We here seek to pose this revelation as a statistical task, illustrated using a particular setup which has been constructed experimentally and for which parameterized models of transcriptional regulation have been studied extensively. The question "how does function follow form" is here mathematized by identifying which topological attributes correlate with the diverse possible information-processing tasks which a transcriptional regulatory network can realize. The resulting method reveals one form-function relationship which had earlier been predicted based on analytic results, and reveals a second for which we can provide an analytic interpretation. Resulting source code is distributed via http://formfunction.sourceforge.net.Comment: To appear in Proc. Natl. Acad. Sci. USA. 17 pages, 9 figures, 2 table

Dynamic Fluctuation Phenomena in Double Membrane Films

Dynamics of double membrane films is investigated in the long-wavelength limit including the overdamped squeezing mode. We demonstrate that thermal fluctuations essentially modify the character of the mode due to its nonlinear coupling to the transversal shear hydrodynamic mode. The corresponding Green function acquires as a function of the frequency a cut along the imaginary semi-axis. Fluctuations lead to increasing the attenuation of the squeezing mode it becomes larger than the `bare' value.Comment: 7 pages, Revte

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary variables, demonstrated 93.2 percent correct classifications of DD and NDD. Evaluation of the combined CART-logistic regression scheme in an adjacent geographical region (Gush Dan) demonstrated good results. Using SRS aerosol products for DD and NDD, identification may enable us to distinguish between health, ecological, and environmental effects that result from exposure to these distinct particle populations

Tropical tele-connections to the Mediterranean climate and weather

Some strong natural fluctuations of climate in the Eastern Mediterranean (EM) region are shown to be connected to the major tropical systems. Potential relations between EM rainfall extremes to tropical systems, e.g. El Niño, Indian Monsoon and hurricanes, are demonstrated. For a specific event, high resolution modelling of the severe flood on 3-5 December 2001 in Israel suggests a relation to hurricane Olga. In order to understand the factors governing the EM climate variability in the summer season, the relationship between extreme summer temperatures and the Indian Monsoon was examined. Other tropical factors like the Red-Sea Trough system and the Saharan dust are also likely to contribute to the EM climate variability

Fluid-membrane tethers: minimal surfaces and elastic boundary layers

Thin cylindrical tethers are common lipid bilayer membrane structures, arising in situations ranging from micromanipulation experiments on artificial vesicles to the dynamic structure of the Golgi apparatus. We study the shape and formation of a tether in terms of the classical soap-film problem, which is applied to the case of a membrane disk under tension subject to a point force. A tether forms from the elastic boundary layer near the point of application of the force, for sufficiently large displacement. Analytic results for various aspects of the membrane shape are given.Comment: 12 page

A Roadmap for Building Data Science Capacity for Health Discovery and Innovation in Africa

Technological advances now make it possible to generate diverse, complex and varying sizes of data in a wide range of applications from business to engineering to medicine. In the health sciences, in particular, data are being produced at an unprecedented rate across the full spectrum of scientific inquiry spanning basic biology, clinical medicine, public health and health care systems. Leveraging these data can accelerate scientific advances, health discovery and innovations. However, data are just the raw material required to generate new knowledge, not knowledge on its own, as a pile of bricks would not be mistaken for a building. In order to solve complex scientific problems, appropriate methods, tools and technologies must be integrated with domain knowledge expertise to generate and analyze big data. This integrated interdisciplinary approach is what has become to be widely known as data science. Although the discipline of data science has been rapidly evolving over the past couple of decades in resource-rich countries, the situation is bleak in resource-limited settings such as most countries in Africa primarily due to lack of well-trained data scientists. In this paper, we highlight a roadmap for building capacity in health data science in Africa to help spur health discovery and innovation, and propose a sustainable potential solution consisting of three key activities: a graduate-level training, faculty development, and stakeholder engagement. We also outline potential challenges and mitigating strategies