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Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 1: Overview and Observing Component of the Research Project RENOVRISK-CYCLONE ArchiMer
Bousquet, Olivier; Barruol, Guilhem; Cordier, Emmanuel; Barthe, Christelle; Bielli, Soline; Calmer, Radiance; Rindraharisaona, Elisa; Roberts, Gregory; Tulet, Pierre; Amelie, Vincent; Fleischer-dogley, Frauke; Mavume, Alberto; Zucule, Jonas; Zakariasy, Lova; Razafindradina, Bruno; Bonnardot, François; Singh, Manvendra; Lees, Edouard; Durand, Jonathan; Mekies, Dominique; Claeys, Marine; Pianezze, Joris; Thompson, Callum; Tsai, Chia-lun; Husson, Romain; Mouche, Alexis; Ciccione, Stephane; Cattiaux, Julien; Chauvin, Fabrice; Marquestaut, Nicolas.
The international research program “ReNovRisk-CYCLONE” (RNR-CYC, 2017–2021) directly involves 20 partners from 5 countries of the south-west Indian-Ocean. It aims at improving the observation and modelling of tropical cyclones in the south-west Indian Ocean, as well as to foster regional cooperation and improve public policies adapted to present and future tropical cyclones risk in this cyclonic basin. This paper describes the structure and main objectives of this ambitious research project, with emphasis on its observing components, which allowed integrating numbers of innovative atmospheric and oceanic observations (sea-turtle borne and seismic data, unmanned airborne system, ocean gliders), as well as combining standard and original methods...
Tipo: Text Palavras-chave: Tropical cyclone; South-west Indian Ocean; Gliders; Unmanned airborne system; Biologging; Sea turtles; Global satellite navigation system; ReNovRisk; Numerical modelling; Climate modelling; Austral and cyclonic swells; Seismic data.
Ano: 2021 URL: https://archimer.ifremer.fr/doc/00691/80281/83366.pdf
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Modelling air temperature for the state of São Paulo, Brazil Scientia Agricola
Rodríguez-Lado,Luis; Sparovek,Gerd; Vidal-Torrado,Pablo; Dourado-Neto,Durval; Macías-Vázquez,Felipe.
Spatial modelling of air temperature (maximum, mean and minimum) of the State of São Paulo (Brazil) was calculated by multiple regression analysis and ordinary kriging. Climatic data (mean values of five or more years) were obtained from 256 meteorological stations distributed uniformly over the State. The correlation between the climatic dependent variables, with latitude and altitude as independent variables was significant and could explain most of the spatial variability. The coefficients of determination (P < 0.05) varied in the range of 0.924 and 0.953, showing that multiple regression analysis is an accurate method for the modelling of air temperature for the State of São Paulo. Finally, these regression equations were used together with the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: DEM; GIS; Multiple regression analysis; Kriging; Climate modelling.
Ano: 2007 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162007000500002
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