Relevant bibliographies by topics / Fine weather

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fine weather'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Fine weather"

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Toth, Zoltan, Steve Albers, and Yuanfu Xie. "Analysis of Fine-Scale Weather Phenomena." Bulletin of the American Meteorological Society 93, no. 3 (March 1, 2012): ES35—ES38. http://dx.doi.org/10.1175/bams-d-11-00148.1.

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Fernández-Caldas, Enrique. "In the Summertime When the Weather Is Fine." International Archives of Allergy and Immunology 161, no. 2 (2013): 97–98. http://dx.doi.org/10.1159/000345993.

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KAWAHARA, Yoshihisa, Noriyuki IKEDA, and Kenichiro KASHIWAGI. "Heat and Moisture Transfer in Tokyo under Fine Weather." ENVIRONMENTAL SYSTEMS RESEARCH 25 (1997): 469–74. http://dx.doi.org/10.2208/proer1988.25.469.

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Duval, Tim P., and J. M. Waddington. "Landscape and weather controls on fine-scale calcareous fen hydrodynamics." Hydrology Research 43, no. 6 (January 27, 2012): 780–97. http://dx.doi.org/10.2166/nh.2011.127.

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Calcareous fens are species-rich peatlands thought to form at discrete alkaline groundwater discharge points. Here the spatial and temporal variability in the peat pore-water hydrodynamics at a fine (plot) scale of three calcareous fens in southern Ontario was investigated over three growing seasons to evaluate the sensitivity of these wetlands to weather fluctuation and landscape position. Only a small area of the fens demonstrated patterns of groundwater upwelling, and positive vertical hydraulic gradients (VHG) were low, peaking at 0.1. Local decreases in saturated hydraulic conductivity generated areas of pore-water over-pressuring in the peat profile through much of the fens. Several areas were subjected to large negative VHG (max = −0.2), causing sustained groundwater recharge. In this study the strength of the connection to the principal source area of water (alkaline stream) determined the pattern and variability of calcareous fen peat hydrodynamics amongst three growing seasons differing markedly in precipitation. The range of pore-water hydrodynamics evident in this study provides evidence for the processes controlling the sensitivity of calcareous fens to climate and land-use change. A conceptual model linking calcareous fen landscape position to weather- and climate-induced hydrodynamic variability is presented to guide management of these biodiverse ecosystems.
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Elkins, Norman. "A POSSIBLE RELATIONSHIP BETWEEN FINE-WEATHER INVERSIONS AND FEEDING SWIFTS." Weather 45, no. 7 (July 1990): 262–65. http://dx.doi.org/10.1002/j.1477-8696.1990.tb05636.x.

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Neumann, J. "Forecasts of Fine Weather in the Literature of Classical Antiquity." Bulletin of the American Meteorological Society 70, no. 1 (January 1989): 46–49. http://dx.doi.org/10.1175/1520-0477-70.1.46.

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Lovas, Róbert, Péter Kardos, András Zénó Gyöngyösi, and Zsolt Bottyán. "Weather model fine-tuning with software container-based simulation platform." Időjárás 123, no. 2 (2019): 165–81. http://dx.doi.org/10.28974/idojaras.2019.2.3.

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Hobiger, Thomas, Seiichi Shimada, Shingo Shimizu, Ryuichi Ichikawa, Yasuhiro Koyama, and Tetsuro Kondo. "Improving GPS positioning estimates during extreme weather situations by the help of fine-mesh numerical weather models." Journal of Atmospheric and Solar-Terrestrial Physics 72, no. 2-3 (February 2010): 262–70. http://dx.doi.org/10.1016/j.jastp.2009.11.018.

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Wodrich, J. V., T. Winkler, B. Leaf, S. F. Clark, and B. Youker. "WET WEATHER IMPACTS ON INFLUENT FINE SCREENING SYSTEM DESIGN AND OPERATION." Proceedings of the Water Environment Federation 2005, no. 11 (January 1, 2005): 4395–411. http://dx.doi.org/10.2175/193864705783866649.

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Jiang, Zhihong, Yuguo Ding, Chunyu Zheng, and Weilin Chen. "An improved, downscaled, fine model for simulation of daily weather states." Advances in Atmospheric Sciences 28, no. 6 (October 18, 2011): 1357–66. http://dx.doi.org/10.1007/s00376-011-0086-8.

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Dissertations / Theses on the topic "Fine weather"

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Jessee, Sharon A. "A monotony of fine weather imagined worlds in contemporary American fiction /." Access abstract and link to full text, 1986. http://0-wwwlib.umi.com.library.utulsa.edu/dissertations/fullcit/8616607.

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Tai, Pui Kuen Amos P. K. "Impact of Climate Change on Fine Particulate Matter \((PM_{2.5})\) Air Quality." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10576.

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This dissertation investigates the impact of 2000-2050 climate change on fine particulate matter \((PM_{2.5})\) air quality. We first applied a multiple linear regression model to study the correlations of total \(PM_{2.5}\) and its components with meteorological variables using the past decadal \(PM_{2.5}\) observations over the contiguous US. We find that daily variation in meteorology can explain up to 50% of \(PM_{2.5}\) variability. Temperature is positively correlated with sulfate and organic carbon (OC) almost everywhere. The correlation of nitrate with temperature is negative in the Southeast but positive in California and the Great Plains. Relative humidity (RH) is positively correlated with sulfate and nitrate, but negatively with OC. Precipitation is strongly negatively correlated with all \(PM_{2.5}\) components. We then compared the observed correlations of \(PM_{2.5}\) with meteorological variables with results from the GEOS-Chem chemical transport model. The results indicate that most of the correlations of \(PM_{2.5}\) with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling \(PM_{2.5}\) variability, and showed that 20-40% of the observed \(PM_{2.5}\) daily variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. From 1999-2010 observations we further showed that interannual variability of annual mean \(PM_{2.5}\) in most of the US is strongly correlated with the synoptic period T of the dominant meteorological mode as diagnosed from a spectral-autoregressive analysis. We then used the observed local \(PM_{2.5}\)-to-period sensitivity to project \(PM_{2.5}\) changes from the 2000-2050 changes in T simulated by fifteen IPCC AR4 GCMs following the SRES A1B scenario. We project a likely increase of \(\sim 0.1 \mu g m^{-3}\) in annual mean \(PM_{2.5}\) in the eastern US arising from less frequent frontal ventilation, and a likely decrease of \(\sim 0.3 \mu g m^{-3}\) in the northwestern US due to more frequent maritime inflows. These circulation-driven changes are relatively small, representing only a minor climate penalty or benefit for \(PM_{2.5}\) regulatory purpose.
Engineering and Applied Sciences
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David, Telse. "Studying the contribution of urban areas to fine sediment and associated element contents in a river bed." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113554.

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Urban wet weather discharge impairs the receiving water and sediment quality. Among other factors, particulate matter plays a role. It increases the suspended sediment load of the receiving water and may thus enhance the clogging of the bed sediment which serves as an important river habitat. This thesis investigates how much urban areas may contribute to the fine sediment and associated element load which is retarded by the bed sediment. It is based on an extensive field study. The study area was the Bode River, a mid-sized stream in Central Germany. About 10 km upstream of the river mouth, the sampling campaign took place close to Staßfurt, a town of 20’000. During the sampling campaign, the intrusion of fine sediment into the bed sediment was captured by sediment traps. Furthermore three possible sources of this fine sediment were sampled. Within the Town of Staßfurt, we sampled urban wet weather discharge at three sites to capture urban areas. As second source naturally occurring fine sediment was considered. Therefore we took sediment cores upstream of the Town of Staßfurt. As third source, the impact of the upstream catchment was captured by taking suspended sediment samples. For all sample types, particle-bound element contents were determined to establish element patterns of the receptor and the source sites. The rationale thereby is that the element pattern at the receptor sites results from the element patterns of the sources. Consequently the contribution of the sources can be calculated by mixing models. In the study area, particulate matter from urban areas is distinct from river borne fine sediment due to elevated copper, zinc, nitrogen and phosphorus contents. We conducted an in-depth analysis of this element pattern by a cluster analysis. It revealed that the particle-bound element pattern is source specific whereby nitrogen, phosphorus and carbon are related to sewage and behave differently than most metals such as copper which mainly originate from surface runoff. The degree to which element patterns agree from site to site is limited by the variability encountered within sample sets from individual sites. Thereby the variability of the element pattern depends on the complexity of the catchment. The contribution of urban areas to fine sediment and associated elements which were captured by sediment traps was calculated by a mixing model. Based on this mixing model, about 10% of the fine sediment originate from urban areas. Thereby the impact of the Town of Staßfurt could not be detected leading to the conclusion that upstream urban areas contribute most. Because of the elevated content of e.g. copper and zinc, urban areas contribute up to 40% and thus disproportionally high to particle-associated copper and zinc load. The source apportionment of the fine sediment is little influenced by the elements considered in the mixing model. Different element patterns showed that the median contribution of urban areas ranges from 0 – 20%. This lies within the interquartile range of the initial mixing model. Another result of the measurement campaign ist that sediment traps over-estimated the anthropogenic impact because they did not resemble the surrounding bed sediment. When they were exposed, they were completely free from fine sediment and hence served as sink of suspended sediment. During the sampling campaign, one source was not directly taken into account. It was possible, though, to delineate this source by nonnegative matrix factorization. Within the Town of Staßfurt, a soda ash production site discharges into the Bode River. The nonnegative matrix factorization uncovered that the soda ash production site is a major source of particulate matter and contributes up to 30% of the fine sediment captured by the traps downstream of the Town of Staßfurt. This source dilutes most element contents as it mainly consists of carbonates. This was revealed by studying the element binding according to the BCR extraction scheme. This thesis shows that urban areas may be a major source of particulate matter and especially associated elements retarded by the bed sediment. It shows that the element contents form a viable pattern to calculate how much urban areas contribute to fine sediment by mixing models. The thesis further shows that nonnegative matrix factorization is a viable tool to delineate such a distinct source as soda ash production site
Misch- und Regenwasserentlastungen beeinträchtigen die Qualität von Vorflutgewässern. Unter anderem gelangt Feinsediment während Entlastungsereignissen in Vorflutgewässer. Dieses erhöht die Fracht an suspendiertem Sediment und verstärkt die Kolmatierung der Gewässersohle. Damit ist das hyporheische Interstitial, das ein wichtiges Fließgewässerhabitat ist, vom Eintrag von Feinsediment betroffen. Diese Arbeit untersucht, wie sehr urbane Flächen zur Feinsedimentfracht und zur Fracht von partikulär gebundenen Elementen beitragen können, die im Bettsediment zurückgehalten werden. Sie beruht auf einer umfangreichen Messkampagne. Das Untersuchungsgebiet dafür war die Bode, ein mittelgroßer Fluss in Mitteldeutschland. Etwa 10 km flussaufwärts der Mündung fand die Messkampagne nahe der Kleinstadt Staßfurt statt. Im Rahmen dieser Messkampagne haben wir den Eintrag von Feinsediment in das Bettsediment durch Sedimentkörbe erfasst. Drei Quellen dieses Feinsediments haben wir berücksichtigt. In Staßfurt wurden eine Regen- und zwei Mischwassereinleitungen beprobt, um urbane Flächen zu erfassen. Als zweite Quelle wurde natürlich vorkommendes Feinsediment berücksichtigt. Dafür haben wir Sedimentkerne flussaufwärts von Staßfurt genommen. Als dritte Quelle haben wir das stromaufwärts liegende Einzugsgebiet erfasst, indem wir das suspendierte Sediment beprobt haben. Für alle Proben wurde der Elementgehalt bestimmt, um das Elementmuster des Feinsediments, das ins Bettsediment eingetragen wurde, und der Quellen zu ermitteln. Der Grund für diese Messstrategie war, dass das Elementmuster des Feinsediments in den Körben aus den Elementmustern der Quellen, Regen- bzw. Mischwassereinleitungen, natürlich vorkommendes Feinsediment und suspendiertes Sediment aus dem Einzugsgebiet, resultieren sollte. Damit ist es möglich, den Beitrag über Mischungsmodelle zu berechnen. Im Untersuchungsgebiet unterscheidet sich das Feinsediment, das von urbanen Flächen stammt, von dem flussbürtigen Feinsediment aufgrund erhöhter Kupfer-, Zink-, Stickstoff- und Phosphorgehalte. Wir haben das Elementmuster der urbanen Flächen mit einer Clusteranalyse genauer untersucht. Dies ergab, dass das partikulär gebundene Elementmuster quellenspezifisch ist, wobei sich Stickstoff, Phosphor und Kohlenstoff Abwasser zuordnen lassen, während die meisten Metalle wie Kupfer und Zink hauptsächlich aus dem Oberflächenabfluss stammen. Das Maß, zu dem die Muster von Messpunkt zu Messpunkt übereinstimmen, wird durch die Variabilität beschränkt, die die Proben eines Messpunktes aufweisen. Diese Variabilität hängt dabei von der Komplexität des Einzugsgebiets ab. Über eine Mischungsrechnung konnten wir berechnen, wie viel urbane Flächen zur Fracht von Feinsediment und daran gebundenen Elementen in den Sedimentkörben beitrugen. Im Untersuchungsgebiet stammen etwa 10 % des Feinsediments, das durch die Sedimentkörbe aufgefangen wurde, von urbanen Flächen. Der Beitrag der Stadt Staßfurt konnte dabei aber nicht von dem Beitrag weiter flussaufwärts gelegener urbaner Gebiete getrennt werden. Daraus folgt, dass weiter stromaufwärts liegende Gebiete mehr beitragen als Staßfurt. Wegen des erhöhten Gehalts an z.B. Kupfer und Zink tragen urbane Flächen ca. 40 % und damit überproportional hoch zur partikulär gebundenen Kupfer- und Zinkfracht bei. Für die Berechung des Quellenbeitrags zum Feinsediment spielt es keine große Rolle, welche Elemente in der Mischungsrechnung berücksichtigt werden. Verschiedene Elementmuster ergeben, dass der Medianbeitrag urbaner Flächen zwischen 0 und 20 % liegt. Dies entspricht dem Interquartilsabstand der ursprünglichen Mischungsrechnung. Ein weiteres Resultat der Untersuchungen ist, dass die Sedimentkörbe den anthropogenen Einfluss überschätzten, weil sie das umgebende Bettsediment nicht exakt abbildeten und als Falle funktionierten. Innerhalb Staßfurts gibt es ein Sodawerk, das seine Produktionsabwässer in die Bode einleitet. Während der Messkampagne wurde diese Quelle nicht direkt erfasst. Es war trotzdem möglich, diese Quelle durch nicht-negative Matrix-Faktorisierung zu identifizieren. Die nicht-negative Matrix-Faktorisierung ergab, dass das Abwasser des Sodawerks eine Hauptquelle des Feinsediments der Bode ist. Bis zu 30 % des Feinsediments in den Sedimentkörben flussabwärts von Staßfurt lassen sich dem Sodawerk zuordnen. Dieses Feinsediment besteht hauptsächlich aus Karbonaten und verdünnt die meisten Elementgehalte. Dies wurde deutlich, indem die Elementbindungen nach dem BCR Extraktionsschema untersucht wurden. Diese Arbeit zeigt die Relevanz, die urbane Flächen als Quelle von Feinsediment und daran gebundener Elementfracht haben, die ins Interstitial eingetragen werden. Sie zeigt, dass die Elementgehalte ein Muster bilden, mit dem es möglich ist, über eine Mischungsrechnung zu klären, wie viel urbane Flächen zum Feinsediment beitragen. Die Arbeit zeigt ferner, dass nicht-negative Matrix-Faktorisierung ermöglicht, eine so charakteristische Quelle wie ein Sodawerk zu identifizieren
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Smith, Jennifer Lauren. "Every Night at 8pm." VCU Scholars Compass, 2011. http://scholarscompass.vcu.edu/etd/2496.

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An experiential thesis, this document begins at dawn, travels through storms and calm air and ends at night in Argentina. It details the circumstances and influences leading to my thesis exhibition at the Anderson Gallery, including an artist’s statement told through a creative reading of Ray Bradbury’s “All Summer in a Day” and the excitement I found in an out-of-print text on scuba diving.
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Lecoeur, Eve. "Influence de l'évolution climatique sur la qualité de l'air en Europe." Thesis, Paris Est, 2013. http://www.theses.fr/2013PEST1176/document.

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La pollution atmosphérique est le produit de fortes émissions de polluants (et de leurs précurseurs) et de conditions météorologiques défavorables. Les particules fines (PM2.5) sont l'un des polluants les plus dangereux pour la santé publique. L'exposition répétée ou prolongée à ces particules entraîne chaque année des maladies respiratoires et cardio-vasculaires chez les personnes exposées ainsi que des morts prématurées. L'évolution du climat dans les années à venir aura un impact sur des variables météorologiques (température, vents, précipitations, ...). Ces variables influencent à leur tour divers facteurs, qui affectent la qualité de l'air (émissions, lessivage par les précipitations, équilibre gaz/particule, ...). Si de nombreuses études ont déjà projeté l'effet du changement climatique sur les concentrations d'ozone, peu se sont intéressées à son effet sur les concentrations de particules fines, en particulier à l'échelle du continent européen. C'est ce que cette thèse se propose d'étudier. La circulation atmosphérique de grande échelle est étroitement liée aux variables météorologiques de surface. Par conséquent, il est attendu qu'elle ait également un impact sur les concentrations de PM2.5. Nous utilisons dans cette thèse une approche statistique pour estimer les concentrations futures de PM2.5 à partir d'observations présentes de PM2.5, de quelques variables météorologiques pertinentes et d'outils permettant de représenter cette circulation atmosphérique (régimes et types de temps). Le faible nombre d'observations journalières de PM2.5 et de ses composants en Europe nous a conduit à créer un jeu de données pseudo-observées à l'aide du modèle de qualité de l'air Polyphemus/Polair3D, puis à l'évaluer de façons opérationnelle et dynamique, afin de s'assurer que l'influence des variables météorologiques sur les concentrations de PM2.5 est reproduite de manière satisfaisante par le modèle. Cette évaluation dynamique d'un modèle de qualité de l'air est, à notre connaissance, la première menée à ce jour.Les projections de PM2.5 sur les périodes futures montrent une augmentation systématique des concentrations de PM2.5 au Royaume-Uni, dans le nord de la France, au Benelux et dans les Balkans, et une diminution dans le nord, l'est et le sud-est de l'Europe, en Italie et en Pologne. L'évolution de la fréquence des types de temps ne suffit pas toujours à expliquer l'évolution de ces concentrations entre les périodes historique et futures, car les relations entre circulation atmosphérique de grande échelle et types de temps, entre types de temps et variables météorologiques, et entre variables météorologiques et concentrations de PM2.5 sont amenées à évoluer dans le futur et contribuent à l'évolution des concentrations de PM2.5. L'approche statistique développée dans cette thèse est nouvelle pour l'estimation de l'impact du climat et du changement climatique sur les concentrations de PM2.5 en Europe. Malgré les incertitudes qui y sont associées, cette approche est facilement adaptable à différents modèles et scénarios, ainsi qu'à d'autres régions du monde et d'autres polluants. En utilisant des observations pour définir la relation polluant-météorologie, cette approche serait d'autant plus robuste
Air pollution is the result of high emissions of pollutants (and pollutant precursors) and unfavorable meteorological conditions. Fine particulate matter (PM2.5) is one of the pollutants of great concern for human health. Every year, a repeated or continuous exposure to such particles is responsible for respiratory and cardiovascular diseases among the concerned populations and leads to premature deaths. Climate change is expected to impact meteorological variables (temperature, wind, precipitation,...). Those variables will influence numerous factors, which will affect air quality (emissions, precipitation scavenging, gas/particle equilibrium,...). A large body of studies have already investigated the effects of climate change on ozone, whereas only a few have addressed its effects on PM2.5 concentrations, especially over Europe. This is the subject we investigate in this thesis. Large-scale circulation is closely linked to surface meteorological variables. Therefore, it is expected that it will impact PM2.5 concentrations too. In this thesis, we develop a statistical algorithm to estimate future PM2.5 concentrations from present PM2.5 observations, selected meteorological variables and tools to represent this circulation (weather regimes and weather types). The lack of daily observations of PM2.5 and its components over Europe prevents us to used observations. Consequently, we have created a pseudo-observed PM2.5 data set, by using the Polyphemus/Polair3D air quality Chemical-Transport Model. Both operational and dynamic evaluations were conducted against EMEP measurements, to ensure that the influence of meteorological variables on PM2.5 concentrations is correctly reproduced by the model. As far as we know, this dynamic evaluation of an air quality model with respect to meteorology is the first conducted to date.Future PM2.5 concentrations display an increase over the U.K., northern France, Benelux, and in the Balkans, and a decrease over northern, eastern, and southeastern Europe, Italy, and Poland compared to the historical period. The evolution of weather type frequencies is not sufficient to explain the PM2.5 changes. The relationships between the large-scale circulation and the weather types, between the weather types and meteorological variables, and between meteorological variables and PM2.5 concentrations evolve with future meteorological conditions and also contribute to PM2.5 changes. The statistical method developed in this thesis is a new approach to estimate the impact of climate and climate change on PM2.5 concentrations over Europe. Despite some uncertainties, this approach is easily applicable to different models and scenarios, as well as other geographical regions and other pollutants. Using observations to establish the pollutant-meteorology relationship would make this approach more robust
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Weiler, Michael. "Weathered." Thesis, Rensselaer Polytechnic Institute, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10267249.

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WEATHERED is a means to give back and say thanks to all who have helped me through life and offer similar aid to anyone willing to listen. Presented within the CRAIVE Lab at the Rensselaer Polytechnic Institute's Technology Park on March 4th, 4pm to 8pm, it depicts an allegorical journey of survival, change, and rediscovery as people are reunited with their identity after separating themselves from it as a means of survival.

In the Thesis, the autobiographical forces behind WEATHERED are defogged, revealing a personal past of birth, growth, abuse, survival, and healing. It will further unravel and look deeper into the artwork's use of allegory, its development process, and conceptual decisions and symbolism, all in conjunction with the artist's creative growth and metamorphosis.

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Pope, Ellis Abel. "Integrating technology into a grade five resource-based weather unit." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0029/MQ47468.pdf.

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Power, Mitchell J. "Recent and Holocene fire, climate, and vegetation linkages in the northern Rocky Mountains, USA /." view abstract or download file of text, 2006. http://proquest.umi.com/pqdweb?index=0&did=1232403871&SrchMode=1&sid=1&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1180996482&clientId=11238.

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Thesis (Ph. D.)--University of Oregon, 2006.
Typescript. Includes vita and abstract. Includes appendices with Foy Lake pollen and charcoal data and fire atlas metadata. Includes bibliographical references (leaves 233-244). Also available for download via the World Wide Web; free to University of Oregon users.
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Simpson, Colin Campbell. "Numerical Modelling of Atmospheric Interactions with Wildland Fire." Thesis, University of Canterbury. Geography, 2013. http://hdl.handle.net/10092/7800.

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Wildland fires are a type of vegetation fire that burn in a rural or wild landscape and affect many countries worldwide. They are an important mechanism in ecosystem maintenance, although in certain cases wildland fires can adversely affect both people and the environment. A wildland fire can interact with the surrounding topography, vegetation and weather in a complex manner, which makes microscale prediction of wildland fire behaviour difficult in many situations. This thesis focused on the application of the Weather Research and Forecast (WRF) numerical weather prediction (NWP) and WRF-Fire coupled atmosphere-fire models to investigating aspects of atmospheric interactions with wildland fire. The research covered a wide range of atmospheric scales, from a seasonal mesoscale analysis of fire weather conditions across New Zealand to a microscale analysis of complex atmosphere-fire interactions over idealised terrain. The first study investigated the suitability of WRF modelling of fire weather conditions for the 2009/10 wildland fire season in New Zealand. The WRF model horizontal grid spacing was 8 km and the model output was directly compared with near-surface fire weather conditions meaured and derived at 23 weather stations located throughout New Zealand. The analysis considered the air temperature, relative humidity, wind conditions, rainfall and the New Zealand Fire Weather Index (FWI) and Continuous Haines Index (CHI) on observed high-end fire weather days. WRF typically underpredicted the air temperatures and relative humidities, whereas it typically overpredicted the wind speeds, CHI and the number of high-end fire weather days. WRF was assessed to be unsuitable for accurately modelling particular aspects of fire weather, such as the wind speed and direction, in mountainous terrain and near complex coastlines. Further research is needed to investigate how varying the horizontal resolution in WRF affects the assessed accuracy of modelled fire weather conditions. The second study investigated the behaviour of the Haines Index (HI), CHI and FWI, and their associated atmospheric properties for the 2009/10 wildland fire season in New Zealand. The analysis demonstrated that there was a large degree of spatial variability in fire weather conditions throughout New Zealand, particularly in or near mountainous terrain. The fire weather severity was highest in the eastern South Island and appeared to be closely associated with mesoscale atmospheric processes over mountainous terrain, although the relationship between these atmospheric processes and fire weather condi- tions requires further investigation. The HI and CHI were both limited in their utility at measuring aloft fire weather conditions in high altitude regions. Finally, the fire weather conditions associated with the 36 largest wildland fires of the fire season were evaluated, although no statistical relationships were found between the wildland fire size and either the CHI or FWI. The third study investigated the fire weather conditions across the South Island associated with an extreme foehn event on 6 February 2011. Mountain waves developed in the northwesterly synoptic flow over the Southern Alps and were found to directly influence the fire weather conditions near the surface and aloft in the lee of the mountains. A hydraulic jump along the foothills of the Canterbury Plains resulted in a downslope windstorm with wind speeds exceeding 80 km/h. Further south, large amplitude mountain lee waves directly influenced the near-surface wind speeds and atmospheric stability aloft. The foehn winds were associated with peak air temperatures over 35˚C in the eastern South Island, which are significantly higher than the climatological average. The FWI indicated widespread extreme near-surface fire weather conditions in the lee of the mountains. The subsequent passge of a cold front on 7 February brought a marked reduction in fire weather severity across the South Island. The fourth study investigated atypical wildland fire behaviour on steep leeward slopes through a series of idealised WRF-Fire simulations. The analysis considered both the leeward flow characteristics over a triangular ridge line and the fire spread from an ignition point at the base of the leeward slope. The fire spread was modelled for two different fuel types and with two-way atmosphere-fire coupling both enabled and disabled. The modelled fire spread in the heavy fuel type with coupling enabled closely resembled the fire channelling wildland fire behaviour phenomenon. The initial fire spread was initially dominated by upslope fire spread to the mountain ridge line at an average rate of around 2.0 km/h. This was followed by a phase of intermittent rapid lateral fire spread close to the ridge line at a maximum rate of around 3.6 km/h. The intermittent rapid lateral fire spread was driven by strongly circulating horizontal near-surface winds that were associated with updraft-downdraft interfaces. These updraft-downdraft interfaces formed due to an interaction between the strong pyro-convection and terrain-modified winds. The presented research collectively demonstrated the versatility and effectiveness of NWP and coupled atmosphere-fire modelling for studying various aspects of atmospheric interactions with wildland fire. The research further highlighted the effects of atmospheric processes over complex terrain on fire weather conditions and wildland fire behaviour. Although three of the studies in the thesis had a regional focus on New Zealand, the research outcomes should benefit end users in fire management worldwide.
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Viegas, de Barros Ana Lúcia. "Impact of climatic variability on the fire behaviour of different land ecosystems." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/4874.

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Wildfires are a natural phenomenon that strongly impacts the environment. Many terrestrial ecosystems depend on fire to maintain their ecological equilibrium and biodiversity, but new destructive fire patterns, often associated with land management practices and rapid climate change, have been degrading soil and water resources, increasing erosion by wind, precipitation and floods, decreasing biodiversity and contributing to desertification. Furthermore, pyrogenic emissions from biomass burning are an important source of atmospheric pollution and they impact the radiative balance of the troposphere, strongly contributing to the greenhouse effect. The objective of this research was to investigate the impact of climate variability on geographic, ecological, seasonal and inter-annual distributions of fires and correspondent pyrogenic emissions, across a variety of ecosystems. With this purpose, 10 years of world, monthly, 1°x1° gridded data, from the Global Fire Emissions Database, were compared with land-cover data, from the Goddard Institute of Space Studies, and with weather data, from the European Centre for Medium Range Weather Forecasting, the Global Precipitation Climatology Centre and the Global Hydrology Resource Centre. Overall, the climate parameters significantly correlated with carbon emissions were air and soil temperature, air and soil humidity, rainfall, wind speed and lightning density during the fire season, and also precipitation and snow cover up to 6 months before the fire season. Good statistical quantitative models of carbon emissions (correlations above 70%, and up to 95%, between estimated and predicted values, with residuals normally distributed) using humidity, temperature or lagged rainfall as predictors, were found almost exclusively in tropical grasslands, shrublands and woodlands, especially in Africa, where fire behaviour was more regular. In boreal and temperate forests and woodlands, where fire patterns were irregular and fire returning periods were larger, there were not enough fires, in 10 years of data, to obtain useful predictive statistical models. The fire models presented here, together with the quantitative statistical relationships found between climate and fire patterns, in different land ecosystems, are apt to be used in predictive climate models, land management, fire risk assessment and mitigation of climate change.
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Books on the topic "Fine weather"

1

Scott, Jack S. A time of fine weather. New York: St. Martin's Press, 1985.

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Lawson, Bruce D. Diurnal variation in the fine fuel moisture code: Tables and computer source code. Victoria, B.C: Canada-British Columbia Partnership Agreement on Forest Resource Development, 1996.

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Let's find out about the weather. Tunbridge Wells: Ticktock, 2009.

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Cheney, Phil. Grassfires: Fuel, weather and fire behaviour. 2nd ed. Collingwood, Vic: CSIRO Publishing, 2008.

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Cheney, Phil. Grassfires: Fuel, weather, and fire behaviour. Collingwood, Australia: CSIRO Pub., 1997.

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Péch, Gyula. Automatic reporting fire weather network at Petawawa, Ontario. Chalk River, Ont: Petawawa National Forestry Institute, 1995.

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Haines, Donald A. Fire-weather stations in northeastern United States. [St. Paul, Minn.]: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station, 1988.

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Haines, Donald A. Fire-weather stations in northeastern United States. [St. Paul, Minn.?]: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station, 1988.

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Haines, Donald A. Fire-weather stations in northeastern United States. [St. Paul, Minn.]: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station, 1988.

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Haines, Donald A. Fire-weather stations in northeastern United States. [St. Paul, Minn.?]: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station, 1988.

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Book chapters on the topic "Fine weather"

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Gygax, H. A., and B. Broder. "Diurnal Variation of Ozone in Fine Weather Situations Over Hilly Terrain." In Atmospheric Ozone, 765–69. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5313-0_150.

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Cox, Louis Anthony. "Do Cold Weather and Fine Particulate Matter Air Pollution Cause Early Deaths in the Elderly?" In Improving Risk Analysis, 353–72. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-6058-9_13.

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Llaguno-Munitxa, Maider, and Elie Bou-Zeid. "Sensing the Environmental Neighborhoods." In Proceedings of the 2020 DigitalFUTURES, 124–33. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_12.

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AbstractGiven the benefits of fine mapping of large urban areas affordably, mobile environmental sensing technologies are becoming increasingly popular to complement the traditional stationary weather and air quality sensing stations. However the reliability and accuracy of low-cost mobile urban technologies is often questioned. This paper presents the design of a fast-response, autonomous and affordable Mobile Urban Sensing Technology (MUST) for the acquisition of high spatial resolution environmental data. Only when accurate neighborhood scale environmental data is affordable and accessible for architects, urban planners and policy makers, can design strategies to enhance urban health be effectively implemented. The results of an experimental air quality sensing campaign developed within Princeton University Campus is presented.
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Wills, Rosalie, James A. Milke, Sara Royle, and Kristin Steranka. "Weather-Related Maintenance Considerations." In SpringerBriefs in Fire, 57–58. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2883-5_10.

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Carvalho, Ana C., Anabela Carvalho, Ana I. Miranda, Carlos Borrego, and Alfredo Rocha. "Climate Change and Fire Weather Risk." In Detecting and Modelling Regional Climate Change, 555–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04313-4_47.

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Stocks, B. J., and T. J. Lynham. "Fire Weather Climatology in Canada and Russia." In Fire in Ecosystems of Boreal Eurasia, 481–94. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8737-2_44.

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Schweizer, Donald, Tom Nichols, Ricardo Cisneros, Kathleen Navarro, and Trent Procter. "Wildland Fire, Extreme Weather and Society: Implications of a History of Fire Suppression in California, USA." In Extreme Weather Events and Human Health, 41–57. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23773-8_4.

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Bird, Isabella L. "Fine Weather—Cremation in Japan—The Governor of Tôkiyô—An Awkward Question—An Insignificant Building—Economy in Funeral Expenses—Simplicity of the Cremation Process—The Last of Japan." In Unbeaten Tracks in Japan, 325–28. (Isabella Lucy), 1831–1904-Correspondence 3.Japan- Description and travel 4.Japan-: Routledge, 2019. http://dx.doi.org/10.4324/9781315788715-57.

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Camia, Andrea, and Giuseppe Amatulli. "Weather Factors and Fire Danger in the Mediterranean." In Earth Observation of Wildland Fires in Mediterranean Ecosystems, 71–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01754-4_6.

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Roads, John, Shyn-Chin Chen, Jack Ritchie, F. Fujioka, H. Juang, and M. Kanamitsu. "ECPC’s Global to Regional Fire Weather Forecast System." In Early Warning Systems for Natural Disaster Reduction, 609–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55903-7_82.

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Conference papers on the topic "Fine weather"

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Zhu, Ziqi, Jiafeng Li, Li Zhuo, and Jing Zhang. "Extreme Weather Recognition Using a Novel Fine-Tuning Strategy and Optimized GoogLeNet." In 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2017. http://dx.doi.org/10.1109/dicta.2017.8227431.

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Choe, Do-Eun, Gary Talor, and Changkyu Kim. "Prediction of Wind Speed, Potential Wind Power, and the Associated Uncertainties for Offshore Wind Farm Using Deep Learning." In ASME 2020 Power Conference collocated with the 2020 International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/power2020-16557.

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Abstract Floating offshore wind turbines hold great potential for future solutions to the growing demand for renewable energy production. Thereafter, the prediction of the offshore wind power generation became critical in locating and designing wind farms and turbines. The purpose of this research is to improve the prediction of the offshore wind power generation by the prediction of local wind speed using a Deep Learning technique. In this paper, the future local wind speed is predicted based on the historical weather data collected from National Oceanic and Atmospheric Administration. Then, the prediction of the wind power generation is performed using the traditional methods using the future wind speed data predicted using Deep Learning. The network layers are designed using both Long Short-Term Memory (LSTM) and Bi-directional LSTM (BLSTM), known to be effective on capturing long-term time-dependency. The selected networks are fine-tuned, trained using a part of the weather data, and tested using the other part of the data. To evaluate the performance of the networks, a parameter study has been performed to find the relationships among: length of the training data, prediction accuracy, and length of the future prediction that is reliable given desired prediction accuracy and the training size.
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Wang, Shu, Ju Hu, Chen Lv, Zongpeng Song, and Zhouyang Ren. "Fine resolution 30-year climatic wind energy dataset over China for renewable energy assessment and operation via Weather Research and Forecasting model hindcast." In 2019 IEEE 3rd International Electrical and Energy Conference (CIEEC). IEEE, 2019. http://dx.doi.org/10.1109/cieec47146.2019.cieec-2019645.

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Ramesh, Vishal, Shashank Terala, Sandip Mazumder, Gurpreet Matharu, Dhaval Vaishnav, and Syed Ali. "A Reduced Model for Efficient Simulation of Freezing of Water in Large Tanks." In ASME 2020 Heat Transfer Summer Conference collocated with the ASME 2020 Fluids Engineering Division Summer Meeting and the ASME 2020 18th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/ht2020-8940.

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Abstract Water-urea mixtures are used in diesel vehicles for exhaust aftertreatment. The liquid mixture, stored in a tank, is susceptible to freezing in cold weather. Depending on weather conditions, the tank size and the liquid fill level, the freezing of the entire liquid may span over a day. Mitigation strategies require understanding of the freezing history. Traditional computational fluid dynamics and heat transfer (CFD/CHT) methodologies are impractical for modeling such freezing processes because of restrictions in the time-step size — typically milliseconds — posed by numerical stability and physical time-scale considerations. The primary constraint for using small time-step sizes is the fine-scale motion generated by natural convection in both the liquid and the gas (unoccupied space). A new model is proposed and demonstrated for efficient prediction of the propagation of the solidification front. In this model, heat transfer due to natural convection is modeled as a diffusive process analogous to how turbulent transport is modeled using an eddy diffusivity and a gradient diffusion model. The model enables use of large time-steps since the fine-scale motions due to natural convection are no longer resolved. The model was validated against experimental data, which were also collected as part of the study. Each experiment collected data at intervals of 6 seconds for a total duration of about 24 hours. Several different tank fill levels were considered, and good agreement with experimental data was noted, especially for shallow fill levels. Large-scale parallel three-dimensional calculations were conducted in a few days of computational time using the proposed model as opposed to a year (projected) of computational time using traditional CFD/CHT models and the same computational resources.
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Haupt, Sue Ellen, Gerry Wiener, Yubao Liu, Bill Myers, Juanzhen Sun, David Johnson, and William Mahoney. "A Wind Power Forecasting System to Optimize Power Integration." In ASME 2011 5th International Conference on Energy Sustainability. ASMEDC, 2011. http://dx.doi.org/10.1115/es2011-54773.

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The National Center for Atmospheric Research (NCAR) has developed a wind prediction system for Xcel Energy, the power company with the largest wind capacity in the United States. The wind power forecasting system includes advanced modeling capabilities, data assimilation, nowcasting, and statistical post-processing technologies. The system ingests both external model data and observations. NCAR produces a deterministic mesoscale wind forecast of hub height winds on a very fine resolution grid using the Weather Research and Forecasting (WRF) model, run using the Real Time Four Dimensional Data Assimilation (RTFDDA) system. In addition, a 30 member ensemble system is run to both improve forecast accuracy and provide an indication of forecast uncertainty. The deterministic and ensemble model output plus data from various global and regional models are ingested by NCAR’s Dynamic, Integrated, Forecast System (DICast®), a statistical learning algorithm. DICast® produces forecasts of wind speed for each wind turbine. These wind forecasts are then fed into a power conversion algorithm that has been empirically derived for each Xcel power connection node. In addition, a ramp forecasting technology fine-tunes the capability to accurately predict the time, magnitude, and duration of a ramping event. This basic system has consistently improved Xcel’s ability to optimize the economics of incorporating wind energy into their power system.
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"Victorian fire weather trends and variability." In 23rd International Congress on Modelling and Simulation (MODSIM2019). Modelling and Simulation Society of Australia and New Zealand, 2019. http://dx.doi.org/10.36334/modsim.2019.h7.harris.

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del Rio, V. Santalla, R. Nocelo-Lopez, M. Vera-Isasa, M. Garcia-Sanchez, I. Cuinas, A. Vazquez-Alejos, P. Torio, and E. de Lorenzo. "Forest Fire Detection with Weather Radars." In 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC). IEEE, 2018. http://dx.doi.org/10.23919/ursi-at-rasc.2018.8471621.

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Satoh, Kohyu, Shiro Kitamura, Kunio Kuwahara, and K. T. Yang. "An Analysis to Predict Forest Fire Danger and Fire Spread." In ASME 2003 Heat Transfer Summer Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/ht2003-47357.

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Forest fires are of common occurrence all over the world, causing severe damages to valuable natural environment and loss of human lives. In order to reduce the damages by forest fires, it is useful to utilize a system, which can predict the occurrence of forest fires and the spread of fires. Well known is a system in USA, called NFDRS to predict forest fire occurrence and FARSITE to predict fire growth, based on the fire weather information taken from a network, combined with forest fuel conditions and land topography data, and processed by an algorithm to generate the various fire danger indices. In Japan the number of forest fires is roughly 3,000 per year, which is 1/30 times compared with USA, and there are very few fires exceeding 1000 ha burnt area, hence there has existed scant demand for this type of intelligent system. Although recently there is an increasing demand for such a system in Japan, the US system for forest-fire prediction is however not applicable to Japan, since the forest topology and weather conditions between Japan and USA are far different. Moreover, many fire weather stations have been installed in the US forests, but in Japan no such fire weather stations are installed in forests. Thus, as a first step to develop an intelligent system for Japan, we have analyzed the fundamentals of forest fire danger rating and the fire spread, based on the weather data and other information on forest fires. The objective of this study is to examine how the fundamentals, based on analyzing the past fire occurrences and CFD simulations particularly on “Katunuma Fire”, can predict the occurrence of forest fires and the spread of forest fires.
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Pu, Junfu, Wengang Zhou, and Houqiang Li. "Dilated Convolutional Network with Iterative Optimization for Continuous Sign Language Recognition." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/123.

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This paper presents a novel deep neural architecture with iterative optimization strategy for real-world continuous sign language recognition. Generally, a continuous sign language recognition system consists of visual input encoder for feature extraction and a sequence learning model to learn the correspondence between the input sequence and the output sentence-level labels. We use a 3D residual convolutional network (3D-ResNet) to extract visual features. After that, a stacked dilated convolutional network with Connectionist Temporal Classification (CTC) is applied for learning the mapping between the sequential features and the text sentence. The deep network is hard to train since the CTC loss has limited contribution to early CNN parameters. To alleviate this problem, we design an iterative optimization strategy to train our architecture. We generate pseudo-labels for video clips from sequence learning model with CTC, and fine-tune the 3D-ResNet with the supervision of pseudo-labels for a better feature representation. We alternately optimize feature extractor and sequence learning model with iterative steps. Experimental results on RWTH-PHOENIX-Weather, a large real-world continuous sign language recognition benchmark, demonstrate the advantages and effectiveness of our proposed method.
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Roe, Kevin, Duane Stevens, and Carol McCord. "High resolution weather modeling for improved fire management." In the 2001 ACM/IEEE conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/582034.582082.

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Reports on the topic "Fine weather"

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LeGrand, Sandra, Christopher Polashenski, Theodore Letcher, Glenn Creighton, Steven Peckham, and Jeffrey Cetola. The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41560.

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Airborne particles of mineral dust play a key role in Earth’s climate system and affect human activities around the globe. The numerical weather modeling community has undertaken considerable efforts to accurately forecast these dust emissions. Here, for the first time in the literature, we thoroughly describe and document the Air Force Weather Agency (AFWA) dust emission scheme for the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosol model within the Weather Research and Forecasting model with chemistry (WRF-Chem) and compare it to the other dust emission schemes available in WRF-Chem. The AFWA dust emission scheme addresses some shortcomings experienced by the earlier GOCART-WRF scheme. Improved model physics are designed to better handle emission of fine dust particles by representing saltation bombardment. WRF-Chem model performance with the AFWA scheme is evaluated against observations of dust emission in southwest Asia and compared to emissions predicted by the other schemes built into the WRF-Chem GOCART model. Results highlight the relative strengths of the available schemes, indicate the reasons for disagreement, and demonstrate the need for improved soil source data.
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Haines, Donald A., and John S. Frost. Fire-Weather Stations in the Northeastern United States. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station, 1988. http://dx.doi.org/10.2737/nc-rn-346.

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Chen, Shyh-Chin, John Benoit, Jack Ritchie, Yunfei Zhang, Hann Ming Henry Juang, Ying-Ju Chen, and Tom Rolinski. FireBuster—a web application for high-resolution fire weather modeling. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, 2019. http://dx.doi.org/10.2737/psw-gtr-264.

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Chen, Shyh-Chin, John Benoit, Jack Ritchie, Yunfei Zhang, Hann Ming Henry Juang, Ying-Ju Chen, and Tom Rolinski. FireBuster—a web application for high-resolution fire weather modeling. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, 2019. http://dx.doi.org/10.2737/psw-gtr-264.

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Agee, James K. Fire and weather disturbances in terrestrial ecosystems of the eastern Cascades. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1994. http://dx.doi.org/10.2737/pnw-gtr-320.

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Mason, Lisa. SPSS Data File - Data from Mental Health, Weather Extremes, and Race study. University of Tennessee, Knoxville Libraries, August 2016. http://dx.doi.org/10.7290/uxbqktg.

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Siirila-Woodburn, Erica, Cynthia Gerlein-Safdi, Juliane Mueller, P. Dennedy-Frank, and Robinson Negron-Juarez. AI predicted shifts in watershed hydrodynamics driven by extreme weather and fire. Office of Scientific and Technical Information (OSTI), April 2021. http://dx.doi.org/10.2172/1769660.

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Flint, A. L., and W. J. Davies. Meteorological data for water years 1988-94 from five weather stations at Yucca Mountain, Nevada. Office of Scientific and Technical Information (OSTI), November 1997. http://dx.doi.org/10.2172/548893.

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Aalto, Juha, and Ari Venäläinen, eds. Climate change and forest management affect forest fire risk in Fennoscandia. Finnish Meteorological Institute, June 2021. http://dx.doi.org/10.35614/isbn.9789523361355.

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Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.
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Reyes, Julian, Jeb Williamson, and Emile Elias. Spatio-temporal analysis of Federal crop insurance cause of loss data: A roadmap for research and outreach effort. U.S. Department of Agriculture, April 2018. http://dx.doi.org/10.32747/2018.7202608.ch.

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Federal crop insurance provides a financial safety net for farmers against insured perils such as drought, heat, and freeze. In 2016 over $100 billion dollars of crops were insured through the Federal crop insurance program administered by the U.S. Department of Agriculture Risk Management Agency. In this white paper, we analyze publicly-available Federal crop insurance data to understand how weather and climate-related perils, or causes of loss (COL), change over time and spatial areas. We find that over 75% of all weather/climate-related indemnities (i.e., crop losses) from 2001 to 2016 are due to three COL: drought, excess moisture, and hail. However, the extent to which these top COL and others impact indemnities is highly dependent on the time period, temporal scale, and spatial scale of analysis. Moreover, we identify what COL are region- or season-specific, and visualize COL trends over time. Finally, we offer a road map of research applications to quantify such trends in indemnities, as well as outreach and extension efforts that include an online data portal.
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