Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3)

The Plant–Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic scheme only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant–Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant–Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

Multi-objective clustering ensemble for gene expression data analysis

In this paper, we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is based on a Pareto-based multi-objective genetic algorithm, with a special crossover operator, which uses clustering validation measures as objective functions. The algorithm proposed can deal with data sets presenting different types of clusters, without the need of expertise in cluster analysis. its result is a concise set of partitions representing alternative trade-offs among the objective functions. We compare the results obtained with our algorithm, in the context of gene expression data sets, to those achieved with multi-objective Clustering with automatic K-determination (MOCK). the algorithm most closely related to ours. (C) 2009 Elsevier B.V. All rights reserved.

A new Home, far from Home : The assimilation process of women involved in intercultural marriages based on Internet meeting

The internet has revolutionized the way we socialize, and as a consequence the way to love. The new communication technologies have facilitated intercultural relationships. Nowadays family relations are one of the major factors in immigration to European countries. Family relations means persons who arrive as family dependents and in accordance with laws regulating family reunification. This thesis aims to apply the classical assimilation theory stated by Milton Gordon (1964), which formulates a series of assimilation stages through which an individual must pass in order to be completely assimilated. In accordance with this theory, marriage is the final phase for a newcomer to fully incorporate into the host society. Thus, based on this presumption and other contemporary theories, the present study has analysed how women who get involved in intercultural marriages based on internet meeting experience these assimilation stages and evaluated the resources used by respondents to incorporate themselves into Swedish society.The main goal of the study was to determine if jumping to the last stage of assimilation does assure the incorporation in the social or/and labour spheres and the findings demonstrate that even though husbands are a valuable resource for assimilation, several cultural issues in Swedish society make it difficult to assure success for the newcomers.On the other hand, Sweden is a country with a strong national sentiment and the assimilation of immigrants still is an important issue to deal with. The Swedish Integration Board has disappeared and major projects for integration have been left in the hands of the municipalities or the Migration Board, institutions that still do not know how to deal with this dilemma.

Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study was applied to the Bacchiglione catchment, located in Italy. The first methodological step was to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model were implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge were generated, as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location were assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that, overall, the assimilation of uncertain observations can improve the hydrologic model performance. In particular, it was found that the model structure is an important factor, of difficult characterization, since can induce different forecasts in terms of outflow discharge. This study is partly supported by the FP7 EU Project WeSenseIt.

Parameterization Of Turbulence Models Using 3DVAR Data Assimilation

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.

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.

CO2 assimilation, photosynthetic light response curves, and water relations of 'Pêra' sweet orange plants infected with Xylella fastidiosa

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Nitrogen assimilation in Citrus based on CitEST data mining

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Influence of diet on assimilation and turnover of C-13 in the tissues of broiler chickens

1. The C-13 turnover rates of the liver and thoracic pectoral muscle of growing broilers were determined by feeding diets with varying C-13 content.2. Male chicks ( 1- d- old) were subjected to treatments based on free choice of 5 different mixes of energy and protein sources from plants with C-3 and C-4 photosynthetic pathways that had differing C-13 content. Rice bran ( R) and soybean meal ( S) were the C-3 sources, while maize ( C) and maize gluten meal ( G) were the C-4 sources. Choices were R + S, C + G, R + G, C + S or R + C +G + S. The 6th treatment was a complete feed ( CF) that was similar to a commercial broiler feed.3. The isotopic composition of the birds' tissues was representative of the isotopic composition of the diets. The assimilation was faster for C-3, in both liver and muscle, than for C-4 diets, and give the delta per mil difference between the diet and tissues.4. The liver is the most active metabolic tissue and gave more rapid isotope turnover than in muscle.

Deformed Gaussian orthogonal ensemble and the statistical fluctuations in the spectra of the quartic oscillator

The nearest-neighbor spacing distributions proposed by four models, namely, the Berry-Robnik, Caurier-Grammaticos-Ramani, Lenz-Haake, and the deformed Gaussian orthogonal ensemble, as well as the ansatz by Brody, are applied to the transition between chaos and order that occurs in the isotropic quartic oscillator. The advantages and disadvantages of these five descriptions are discussed. In addition, the results of a simple extension of the expression for the Dyson-Mehta statistic Δ3 are compared with those of a more popular one, usually associated with the Berry-Robnik formalism. ©1999 The American Physical Society.

Agir ensemble pour une gestion plus efficace des services de l'eau potable et l'assainissement en Haïti

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Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data

We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.

Analysis of ensemble models in the medium term hydropower scheduling

The medium term hydropower scheduling (MTHS) problem involves an attempt to determine, for each time stage of the planning period, the amount of generation at each hydro plant which will maximize the expected future benefits throughout the planning period, while respecting plant operational constraints. Besides, it is important to emphasize that this decision-making has been done based mainly on inflow earliness knowledge. To perform the forecast of a determinate basin, it is possible to use some intelligent computational approaches. In this paper one considers the Dynamic Programming (DP) with the inflows given by their average values, thus turning the problem into a deterministic one which the solution can be obtained by deterministic DP (DDP). The performance of the DDP technique in the MTHS problem was assessed by simulation using the ensemble prediction models. Features and sensitivities of these models are discussed. © 2012 IEEE.

Condiciones para asimilar la inmigración en el Brasil urbano = Conditions of immigrant assimilation in urban Brazil

Los documentos del Seminario fueron publicados por UNESCO en 1961 con el título: La urbanización en América Latina/Urbanization in Latin America