Parallel implementation of a simplified semi-physical wildland re spread model using OpenMP

[EN]We present a parallel 2D version of a simplified semi-physical wildland fire spread model based on conservation equations, with convection and radiation as the main heat transfer mechanisms. This version includes some 3D effects. The OpenMP framework allows distributing the prediction operations among the available threads in a multicore architecture, thereby reducing the computational time and obtaining the prediction results much more quickly. The results from the experiments using data from a real fire in Galicia (Spain) confirm the benefits of using the parallel version.Junta of Castilla y Leó

Simulación paramétrica paralela. Aplicación a modelos de predicción de inundaciones.

El modelado y la simulación de inundaciones provocadas por el desborde de ríos brinda sistemas computacionales para el estudio y la predicción de estos fenómenos naturales, con el objetivo de pronosticar su comportamiento. Estos sistemas necesitan tomar gran cantidad de datos de entrada para aumentar su precisión, como también deben generar múltiples escenarios para cubrir todas las situaciones de riesgo. Por esto, son de cómputo intensivo y pueden tomar días de procesamiento hasta lograr resultados. A este problema se le suma la falta de certeza en los valores de los datos de entrada del proceso. Mediante la programación paralela y los avances en cómputo de alto rendimiento en clusters de computadoras, se pretende atenuar el problema de la incertidumbre de los datos de entrada y optimizar el proceso de predicción mediante la simulación de múltiples escenarios. Con este trabajo se pretende desarrollar una metodología para optimizar la predicción de inundaciones provocadas por el desborde de ríos, en principio de llanuras o planicies, y en particular en la Cuenca del Río Salado o en el Paraná Medio.Eje: Procesamiento Concurrente, Paralelo y DistribuidoRed de Universidades con Carreras en Informática (RedUNCI

Simulación paramétrica paralela. Aplicación a modelos de predicción de inundaciones.

El modelado y la simulación de inundaciones provocadas por el desborde de ríos brinda sistemas computacionales para el estudio y la predicción de estos fenómenos naturales, con el objetivo de pronosticar su comportamiento. Estos sistemas necesitan tomar gran cantidad de datos de entrada para aumentar su precisión, como también deben generar múltiples escenarios para cubrir todas las situaciones de riesgo. Por esto, son de cómputo intensivo y pueden tomar días de procesamiento hasta lograr resultados. A este problema se le suma la falta de certeza en los valores de los datos de entrada del proceso. Mediante la programación paralela y los avances en cómputo de alto rendimiento en clusters de computadoras, se pretende atenuar el problema de la incertidumbre de los datos de entrada y optimizar el proceso de predicción mediante la simulación de múltiples escenarios. Con este trabajo se pretende desarrollar una metodología para optimizar la predicción de inundaciones provocadas por el desborde de ríos, en principio de llanuras o planicies, y en particular en la Cuenca del Río Salado o en el Paraná Medio.Eje: Procesamiento Concurrente, Paralelo y DistribuidoRed de Universidades con Carreras en Informática (RedUNCI

The Brazilian Developments on the Regional Atmospheric Modeling System (BRAMS 5.2): An Integrated Environmental Model Tuned for Tropical Areas

We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System where different previous versions for weather, chemistry and carbon cycle were unified in a single integrated software system. The new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. Together with the description of the main features are examples of the quality of the transport scheme for scalars, radiative fluxes on surface and model simulation of rainfall systems over South America in different spatial resolutions using a scale-aware convective parameterization. Besides, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America are shown. Atmospheric chemistry examples present model performance in simulating near-surface carbon monoxide and ozone in Amazon Basin and Rio de Janeiro megacity. For tracer transport and dispersion, it is demonstrated the model capabilities to simulate the volcanic ash 3-d redistribution associated with the eruption of a Chilean volcano. Then, the gain of computational efficiency is described with some details. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5 km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding on its functionalities and skills are discussed. At last, we highlight the relevant contribution of this work on the building up of a South American community of model developers

The Brazilian Developments On The Regional Atmospheric Modeling System (brams 5.2): An Integrated Environmental Model Tuned For Tropical Areas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS), in which different previous versions for weather, chemistry, and carbon cycle were unified in a single integrated modeling system software. This new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. The description of the main model features includes several examples illustrating the quality of the transport scheme for scalars, radiative fluxes on surface, and model simulation of rainfall systems over South America at different spatial resolutions using a scale aware convective parameterization. Additionally, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America, are shown. Atmospheric chemistry examples show the model performance in simulating near-surface carbon monoxide and ozone in the Amazon Basin and the megacity of Rio de Janeiro. For tracer transport and dispersion, the model capabilities to simulate the volcanic ash 3-D redistribution associated with the eruption of a Chilean volcano are demonstrated. The gain of computational efficiency is described in some detail. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near-surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding both its functionalities and skills are discussed. Finally, we highlight the relevant contribution of this work to building a South American community of model developers. © Author(s) 2017.1011892222014/01563-1, FAPESP, Fundação de Amparo à Pesquisa do Estado de São Paulo2014/01564-8, FAPESP, Fundação de Amparo à Pesquisa do Estado de São Paulo2015/10206-0, FAPESP, Fundação de Amparo à Pesquisa do Estado de São Paulo306340/2011-9, Conselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas

We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS), in which different previous versions for weather, chemistry, and carbon cycle were unified in a single integrated modeling system software. This new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. The description of the main model features includes several examples illustrating the quality of the transport scheme for scalars, radiative fluxes on surface, and model simulation of rainfall systems over South America at different spatial resolutions using a scale aware convective parameterization. Additionally, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America, are shown. Atmospheric chemistry examples show the model performance in simulating near-surface carbon monoxide and ozone in the Amazon Basin and the megacity of Rio de Janeiro. For tracer transport and dispersion, the model capabilities to simulate the volcanic ash 3-D redistribution associated with the eruption of a Chilean volcano are demonstrated. The gain of computational efficiency is described in some detail. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5 km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near-surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding both its functionalities and skills are discussed. Finally, we highlight the relevant contribution of this work to building a South American community of model developers.CNPqFAPESPEarth System Research Laboratory at the National Oceanic and Atmospheric Administration (ESRL/NOAA), Boulder, USAInst Nacl Pesquisas Espaciais, Ctr Previsao Tempo & Estudos Climat, Cachoeira Paulista, SP, BrazilDiv Ciência da Computação, Instituto Tecnológico de Aeronáutica, São José dos Campos, SP, BrazilUniv Estadual Paulista Unesp, Fac Ciencias, Bauru, SP, BrazilCtr Meteorol Bauru IPMet, Bauru, SP, BrazilUniv Fed Sao Paulo, Dept Ciencias Ambientais, Diadema, SP, BrazilUniv Sao Paulo, Inst Astron Geofis & Ciencias Atmosfer, Sao Paulo, SP, BrazilUniv Fed Campina Grande, Dept Ciencias Atmosfer, Campina Grande, PB, BrazilEmbrapa Informat Agr, Campinas, SP, BrazilUniv Fed Sao Paulo, Inst Ciencia & Tecnol, Sao Jose Dos Campos, SP, BrazilUniv Fed Rio Grande do Norte, Dept Ciencias Atmosfer & Climat, Programa Pos Grad Ciencias Climat, Natal, RN, BrazilInst Nacl Pesquisas Espaciais, Ctr Ciencias Sistema, Sao Jose Dos Campos, SP, BrazilUniv Fed Sao Joao Del Rei, Dept Geociencias, Sao Joao Del Rei, MG, BrazilInst Nacl Pesquisas Espaciais, Lab Associado Computacao & Matemat Aplica, Sao Jose Dos Campos, BrazilUniv Evora, Inst Ciencias Agr & Ambientais Mediterr, Evora, PortugalUniv Lusofona Humanidades & Tecnol, Ctr Interdisciplinar Desenvolvimento Ambient Gest, Lisbon, PortugalUniv Fed Pelotas, Fac Meteorol, Pelotas, RS, BrazilUnive Tecnol Fed Parana, Londrina, PR, BrazilNASA, Goddard Space Flight Ctr, Univ Space Res Assoc, Goddard Earth Sci Technol & Res Global Modeling &, Greenbelt, MD USAUniv Fed Sao Paulo, Inst Ciencia & Tecnol, Sao Jose Dos Campos, SP, BrazilUniv Fed Sao Paulo, Inst Ciencia & Tecnol, Sao Jose Dos Campos, SP, BrazilCNPq: 306340/2011-9FAPESP: 2014/01563-1FAPESP: 2015/10206-0FAPESP: 2014/01564-8Web of Scienc

Método de reducción de incertidumbre basado en algoritmos evolutivos y paralelismo orientado a la predicción y prevención de desastres naturales : Doctorado en Ciencias de la Computación, Facultad de Ciencias Físico Matemáticas y Naturales de la Universidad Nacional de San Luis

La presente tesis doctoral aborda la problemática de la incertidumbre existente en todo sistema de predicción, focalizando en el desarrollo de métodos de reducción de incertidumbre aplicados a la predicción de fenómenos naturales. Debido a que estos fenómenos suelen causar gran impacto en las comunidades, la flora y la fauna, el ecosistema, entre otros, los sistemas de predicción deben proporcionar respuesta en el menor tiempo posible. Por estos motivos, los métodos propuestos han sido desarrollados utilizando capacidades de alto rendimiento. El primer método desarrollado en esta tesis (ESS-IM), comenzó con el objetivo de lograr una mejora a una metodología previamente desarrollada denominada ESS (Sistema Estadístico Evolutivo). Específicamente se trabajó en el incremento del paralelismo de la metaheurística interna, incorporando una arquitectura basada en modelo de islas bajo un esquema de migración. Este desarrollo logró incrementar la capacidad de búsqueda de la metaheurística interna, impactando de forma directa en un incremento en la calidad de predicción del método. En la validación, ESS-IM fue aplicado en una serie de casos de quemas controladas e incendios forestales. Es importante destacar que, en forma conjunta al desarrollo de la tesis, se llevaron a cabo diferentes investigaciones complementarias, tales como: estudios de sintonización de parámetros, desarrollo de un sistema de generación de mapas de incendios forestales a partir de imágenes satelitales, diseño de una red inalámbrica de sensores como sistema de alerta temprana, entre otros. Finalmente, en la última etapa de la tesis, se implementó una versión híbrida basada en metaheurísticas evolutivas bajo una estrategia colaborativa basada en islas. El método HESS-IM, se implementó de forma heterogénea (a nivel de hardware), logrando que los resultados obtenidos incrementen la calidad de predicción y eficiencia del método.Eje: Tesis de Doctorado.Red de Universidades con Carreras en Informátic

Parallel Implementation of the Algorithm to Compute Forest Fire Impact on Infrastructure Facilities of JSC Russian Railways

Forest fires have a negative impact on the economy in a number of regions, especially in Wildland Urban Interface (WUI) areas. An important link in the fight against fires in WUI areas is the development of information and computer systems for predicting the fire safety of infrastructural facilities of Russian Railways. In this work, a numerical study of heat transfer processes in the enclosing structure of a wooden building near the forest fire front was carried out using the technology of parallel computing. The novelty of the development is explained by the creation of its own program code, which is planned to be put into operation either in the Information System for Remote Monitoring of Forest Fires ISDM-Rosleskhoz, or in the information and computing system of JSC Russian Railways. In the Russian Federation, it is forbidden to use foreign systems in the security services of industrial facilities. The implementation of the deterministic model of heat transfer in the enclosing structure with the complexity of the algorithm O (2N2 + 2K) is presented. The program is implemented in Python 3.x using the NumPy and Concurrent libraries. Calculations were carried out on a multiprocessor cluster in the Sirius University of Science and Technology. The results of calculations and the acceleration coefficient for operating modes for 1, 2, 4, 8, 16, 32, 48 and 64 processes are presented. The developed algorithm can be applied to assess the fire safety of infrastructure facilities of Russian Railways. The main merit of the new development should be noted, which is explained by the ability to use large computational domains with a large number of computational grid nodes in space and time. The use of caching intermediate data in files made it possible to distribute a large number of computational nodes among the processors of a computing multiprocessor system. However, one should also note a drawback; namely, a decrease in the acceleration of computational operations with a large number of involved nodes of a multiprocessor computing system, which is explained by the write and read cycles in cache files

Forest fire danger extremes in Europe under climate change: variability and uncertainty

Forests cover over a third of the total land area of Europe. In recent years, large forest fires have repeatedly affected Europe, in particular the Mediterranean countries. Fire danger is influenced by weather in the short term, and by climate when considering longer time intervals. In this work, the emphasis is on the direct influence on fire danger of weather and climate. For climate analysis at the continental scale, a daily high-emission scenario (RCP 8.5) was considered up to the end of the century, and a mitigation scenario that limits global warming to 2 °C was also assessed. To estimate fire danger, the Canadian Fire Weather Index (FWI) system was used. FWI provides a uniform numerical rating of relative fire potential, by combining the information from daily local temperature, wind speed, relative humidity, and precipitation values. The FWI is standardised to consider a reference fuel behaviour irrespective of other factors. It is thus well suited to support harmonised comparisons, to highlight the role of the varying climate in the component of fire danger that is driven by weather. RESULTS. Around the Mediterranean region, climate change will reduce fuel moisture levels from present values, increasing the weather-driven danger of forest fires. Furthermore, areas exhibiting low moisture will extend further northwards from the Mediterranean, and the current area of high fuel moisture surrounding the Alps will decrease in size. Projected declines in moisture for Mediterranean countries are smaller with mitigation that limits global warming to 2 °C, but a worsening is still predicted compared with present. There is a clear north-south pattern of deep fuel moisture variability across Europe in both climate change scenarios. Areas at moderate danger from forest fires are pushed north to central Europe by climate change. Relatively little change is expected in weather-driven fire danger across northern Europe. However, mountain systems show a fast pace of change. ADAPTATION OPTIONS. Key strategies to be considered may include vegetation management to reduce the likelihood of severe fires, as well as fuel treatments to mitigate fire hazard in dry forests. These measures should be adapted to the different forest ecosystems and conditions. Limited, preliminary knowledge covers specific but essential aspects. Evidence suggests that some areas protected for biodiversity conservation may be affected less by forest fires than unprotected areas, despite containing more combustible material. Specific typologies of old-growth forests may be associated with lower fire severity than densely stocked even-aged young stands, and some tree plantations might be more subject to severe fire compared with multi-aged forests. Particular ecosystems and vegetation associations may be better adapted for post-fire recovery, as long as the interval between fires is not too short. Therefore, deepening the understanding of resistance, resilience and habitat suitability of mixtures of forest tree species is recommended. Human activity (accidental, negligent or deliberate) is one of the most common causes of fire. For this reason, the main causes of fire should be minimized, which includes analysing the social and economic factors that lead people to start fires, increasing awareness of the danger, encouraging good behaviour and sanctioning offenders. LIMITATIONS. Bias correction of climate projections is known to be a potential noticeable source of uncertainty in the predicted bioclimatic anomalies to which vegetation is sensitive. In particular, the analysis of fire danger under climate change scenarios may be critically affected by climatic modelling uncertainty. This work did not explicitly model adaptation scenarios for forest fire danger because ecosystem resilience to fire is uneven and its assessment relies on factors that are difficult to model numerically. Furthermore, a component of the proposed climate-based characterization of future wildfire potential impacts may be linked to the current distribution of population, land cover and use in Europe. The future distribution of these factors is likely to be different from now.JRC.E.1-Disaster Risk Managemen