A review of drought in the Middle East and Southwest Asia

The Middle East and Southwest Asia comprise a region that is water-stressed, societally vulnerable, and prone to severe droughts. Large-scale climate variability, particularly La Niña, appears to play an important role in region-wide drought, including the two most severe of the last fifty years—1999-2001 and 2007-2008—with implications for drought forecasting. Important dynamical factors include orography, thermodynamic influence on vertical motion, storm track changes, and moisture transport. Vegetation in the region is strongly impacted by drought and may provide an important feedback mechanism. In future projections, drying of the eastern Mediterranean is a robust feature, as are temperature increases throughout the region, which will affect evaporation and the timing and intensity of snowmelt. Vegetation feedbacks may become more important in a warming climate. There are a wide range of outstanding issues for understanding, monitoring, and predicting drought in the region, including: dynamics of the regional storm track, the relative importance of the range of dynamical mechanisms related to drought, regional coherence of drought, the relationship between synoptic-scale mechanisms and drought, predictability of vegetation and crop yields, stability of remote influences, data uncertainty, and the role of temperature. Development of a regional framework for cooperative work and dissemination of information and existing forecasts would speed understanding and make better use of available information.

The SPARC Data Initiative: comparisons of CFC-11, CFC-12, HF and SF6 climatologies from international satellite limb sounders

A quality assessment of the CFC-11 (CCl3F), CFC-12 (CCl2F2), HF, and SF6 products from limb-viewing satellite instruments is provided by means of a detailed intercomparison. The climatologies in the form of monthly zonal mean time series are obtained from HALOE, MIPAS, ACE-FTS, and HIRDLS within the time period 1991–2010. The intercomparisons focus on the mean biases of the monthly and annual zonal mean fields and aim to identify their vertical, latitudinal and temporal structure. The CFC evaluations (based on MIPAS, ACE-FTS and HIRDLS) reveal that the uncertainty in our knowledge of the atmospheric CFC-11 and CFC-12 mean state, as given by satellite data sets, is smallest in the tropics and mid-latitudes at altitudes below 50 and 20 hPa, respectively, with a 1σ multi-instrument spread of up to ±5 %. For HF, the situation is reversed. The two available data sets (HALOE and ACE-FTS) agree well above 100 hPa, with a spread in this region of ±5 to ±10 %, while at altitudes below 100 hPa the HF annual mean state is less well known, with a spread ±30 % and larger. The atmospheric SF6 annual mean states derived from two satellite data sets (MIPAS and ACE-FTS) show only very small differences with a spread of less than ±5 % and often below ±2.5 %. While the overall agreement among the climatological data sets is very good for large parts of the upper troposphere and lower stratosphere (CFCs, SF6) or middle stratosphere (HF), individual discrepancies have been identified. Pronounced deviations between the instrument climatologies exist for particular atmospheric regions which differ from gas to gas. Notable features are differently shaped isopleths in the subtropics, deviations in the vertical gradients in the lower stratosphere and in the meridional gradients in the upper troposphere, and inconsistencies in the seasonal cycle. Additionally, long-term drifts between the instruments have been identified for the CFC-11 and CFC-12 time series. The evaluations as a whole provide guidance on what data sets are the most reliable for applications such as studies of atmospheric transport and variability, model–measurement comparisons and detection of long-term trends. The data sets will be publicly available from the SPARC Data Centre and through PANGAEA (doi:10.1594/PANGAEA.849223).

Mitochondrial sequence data and Dipsacales phylogeny: Mixed models, partitioned Bayesian analyses, and model selection

Phylogenetic analyses of chloroplast DNA sequences, morphology, and combined data have provided consistent support for many of the major branches within the angiosperm, clade Dipsacales. Here we use sequences from three mitochondrial loci to test the existing broad scale phylogeny and in an attempt to resolve several relationships that have remained uncertain. Parsimony, maximum likelihood, and Bayesian analyses of a combined mitochondrial data set recover trees broadly consistent with previous studies, although resolution and support are lower than in the largest chloroplast analyses. Combining chloroplast and mitochondrial data results in a generally well-resolved and very strongly supported topology but the previously recognized problem areas remain. To investigate why these relationships have been difficult to resolve we conducted a series of experiments using different data partitions and heterogeneous substitution models. Usually more complex modeling schemes are favored regardless of the partitions recognized but model choice had little effect on topology or support values. In contrast there are consistent but weakly supported differences in the topologies recovered from coding and non-coding matrices. These conflicts directly correspond to relationships that were poorly resolved in analyses of the full combined chloroplast-mitochondrial data set. We suggest incongruent signal has contributed to our inability to confidently resolve these problem areas. (c) 2007 Elsevier Inc. All rights reserved.

Discrepancies in solar irradiation data for Stockholm and Athens

The aim of this study is to evaluate the variation of solar radiation data between different data sources that will be free and available at the Solar Energy Research Center (SERC). The comparison between data sources will be carried out for two locations: Stockholm, Sweden and Athens, Greece. For the desired locations, data is gathered for different tilt angles: 0°, 30°, 45°, 60° facing south. The full dataset is available in two excel files: “Stockholm annual irradiation” and “Athens annual irradiation”. The World Radiation Data Center (WRDC) is defined as a reference for the comparison with other dtaasets, because it has the highest time span recorded for Stockholm (1964–2010) and Athens (1964–1986), in form of average monthly irradiation, expressed in kWh/m2. The indicator defined for the data comparison is the estimated standard deviation. The mean biased error (MBE) and the root mean square error (RMSE) were also used as statistical indicators for the horizontal solar irradiation data. The variation in solar irradiation data is categorized in two categories: natural or inter-annual variability, due to different data sources and lastly due to different calculation models. The inter-annual variation for Stockholm is 140.4kWh/m2 or 14.4% and 124.3kWh/m2 or 8.0% for Athens. The estimated deviation for horizontal solar irradiation is 3.7% for Stockholm and 4.4% Athens. This estimated deviation is respectively equal to 4.5% and 3.6% for Stockholm and Athens at 30° tilt, 5.2% and 4.5% at 45° tilt, 5.9% and 7.0% at 60°. NASA’s SSE, SAM and RETScreen (respectively Satel-light) exhibited the highest deviation from WRDC’s data for Stockholm (respectively Athens). The essential source for variation is notably the difference in horizontal solar irradiation. The variation increases by 1-2% per degree of tilt, using different calculation models, as used in PVSYST and Meteonorm. The location and altitude of the data source did not directly influence the variation with the WRDC data. Further examination is suggested in order to improve the methodology of selecting the location; Examining the functional dependence of ground reflected radiation with ambient temperature; variation of ambient temperature and its impact on different solar energy systems; Im pact of variation in solar irradiation and ambient temperature on system output.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

Integrating geo-referenced multiscale and multidisciplinary data for the management of biodiversity in livestock genetic resources

P>In livestock genetic resource conservation, decision making about conservation priorities is based on the simultaneous analysis of several different criteria that may contribute to long-term sustainable breeding conditions, such as genetic and demographic characteristics, environmental conditions, and role of the breed in the local or regional economy. Here we address methods to integrate different data sets and highlight problems related to interdisciplinary comparisons. Data integration is based on the use of geographic coordinates and Geographic Information Systems (GIS). In addition to technical problems related to projection systems, GIS have to face the challenging issue of the non homogeneous scale of their data sets. We give examples of the successful use of GIS for data integration and examine the risk of obtaining biased results when integrating datasets that have been captured at different scales.

Likelihood approximations and discrete models for tied survival data

Ties among event times are often recorded in survival studies. For example, in a two week laboratory study where event times are measured in days, ties are very likely to occur. The proportional hazards model might be used in this setting using an approximated partial likelihood function. This approximation works well when the number of ties is small. on the other hand, discrete regression models are suggested when the data are heavily tied. However, in many situations it is not clear which approach should be used in practice. In this work, empirical guidelines based on Monte Carlo simulations are provided. These recommendations are based on a measure of the amount of tied data present and the mean square error. An example illustrates the proposed criterion.

Data information system to promote the organization data of collections - modeling considerations by the Unified Modelign Language (UML)

Pode-se afirmar que a evolução tecnológica (desenvolvimento de novos instrumentos de medição como, softwares, satélites e computadores, bem como, o barateamento das mídias de armazenamento) permite às Organizações produzirem e adquirirem grande quantidade de dados em curto espaço de tempo. Devido ao volume de dados, Organizações de pesquisa se tornam potencialmente vulneráveis aos impactos da explosão de informações. Uma solução adotada por algumas Organizações é a utilização de ferramentas de sistemas de informação para auxiliar na documentação, recuperação e análise dos dados. No âmbito científico, essas ferramentas são desenvolvidas para armazenar diferentes padrões de metadados (dados sobre dados). Durante o processo de desenvolvimento destas ferramentas, destaca-se a adoção de padrões como a Linguagem Unificada de Modelagem (UML, do Inglês Unified Modeling Language), cujos diagramas auxiliam na modelagem de diferentes aspectos do software. O objetivo deste estudo é apresentar uma ferramenta de sistemas de informação para auxiliar na documentação dos dados das Organizações por meio de metadados e destacar o processo de modelagem de software, por meio da UML. Será abordado o Padrão de Metadados Digitais Geoespaciais, amplamente utilizado na catalogação de dados por Organizações científicas de todo mundo, e os diagramas dinâmicos e estáticos da UML como casos de uso, sequências e classes. O desenvolvimento das ferramentas de sistemas de informação pode ser uma forma de promover a organização e a divulgação de dados científicos. No entanto, o processo de modelagem requer especial atenção para o desenvolvimento de interfaces que estimularão o uso das ferramentas de sistemas de informação.

The Bauru Group: A continental Cretaceous unit in Brazil - Concepts based on micropaleontological, oxygen isotope and stratigraphical data

The integration of outcrop and subsurface information, including micropaleontological data, facies and sequence stratigraphic studies, and oxygen isotope analysis, allow us to present a new stratigraphic model for the Cretaceous continental deposits of the Bauru Group, Brazil. Thirty-eight fossil taxa were recovered from these deposits, including 29 species of ostracodes and 9 species of charophytes. Seven of these ostracode species and three subspecies are new and formally described here. The associations of Chara barbosai - Ilyocypris cf. riograndensis, found in the Adamantina Formation, and Amblyochara sp. - Neuquenocypris minor mineira nov. subsp., found in the Marília Formation. Ponte Alta Member, represent two distinct groups that are respectively Turonian-Santonian and Maastrichtian (probably Late Maastrichtian) in age. Therefore, a hiatus, encompassing more than 11 Ma, separates those two formations. From bottom to top, four depositional cycles were recognized in the Bauru Group in western São Paulo: cycles 1 and 2 belong to Caiuá Formation (fluvio-lacustrine and lacustrine deposits in the Presidente Prudente region), cycle 3 to the Santo Anastácio and lower Adamantina Formation (respectively fluvial and lacustrine deposits), and cycle 4 to the upper Adamantina Formation (fluvio-lacustrine facies). An erosional unconformity separates the Caiuá and Santo Anastácio Formations (between cycles 2 and 3). The Marília Formation is a distinct unit from the underlying succession; it does not occur in western São Paulo, but is found in restricted areas of São Paulo, Minas Gerais, Mato Grosso do Sul and Goiás States. During the deposition of the Bauru Group (Aptian? to Maastrichtian) the climate was hot and arid-semiarid. Shallow lakes underwent fluctuations in expansion (wet phases) and contraction (dry phases), as well as variations in salinity. During the deposition of the Adamantina Formation (Turonian-Santonian) there were long, dry periods that caused segmentation of large lakes (due to topographic irregularities in the basaltic substrate) and sometimes exposures of the lake floors; when flooded these lake floors were colonized by extensive meadows of single species of charophytes. Small ephemeral ponds, that were hydrochemically unstable and colonized by multiple species of charophytes, were the depositional sites for the marls and mudstones of Ponte Alta Member (Maastrichtian, Late Maastrichtian?). Our micropaleontological age control, combined with the Late Cretaceous ages of volcanic ashes found in the southeastern Brazil coastal basins, and the stratigraphic position of analcimites from the Jaboticabal-SP region, suggest a Late Coniacian-Santonian age for important magmatic events occurred in the interior of Brazil (north-central São Paulo State, Triângulo Mineiro, and southwestern Goiás State).

Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

Engaging environments: Tacit knowledge sharing on the shop floor

Purpose: The purpose of this paper is to identify factors that facilitate tacit knowledge sharing in unstructured work environments, such as those found in automated production lines. Design/methodology/approach: The study is based on a qualitative approach, and it draws data from a four-month field study at a blown-molded glass factory. Data collection techniques included interviews, informal conversations and on-site observations, and data were interpreted using content analysis. Findings: The results indicated that sharing of tacit knowledge is facilitated by an engaging environment. An engaging environment is supported by shared language and knowledge, which are developed through intense communication and a strong sense of collegiality and a social climate that is dominated by openness and trust. Other factors that contribute to the creation of an engaging environment include managerial efforts to provide appropriate work conditions and to communicate company goals, and HRM practices such as the provision of formal training, on-the-job training and incentives. Practical implications: This paper clarifies the scope of managerial actions that impact knowledge creation and sharing among blue-collar workers. Originality/value: Despite the acknowledgement of the importance of blue-collar workers' knowledge, both the knowledge management and operations management literatures have devoted limited attention to it. Studies related to knowledge management in unstructured working environments are also not abundant. © Emerald Group Publishing Limited.

Information, information management and governance

Includes bibliography

Gestão do conhecimento em bibliotecas universitárias: análise de experiências no Brasil e em Portugal

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)