Study of Extreme Brazilian Meteorological Events

H. M. Ruivo (), F. M. Ramos (), H. F. de Campos Velho () and G. Sampaio ()
Additional contact information
H. M. Ruivo: National Institute for Space Research
F. M. Ramos: National Institute for Space Research
H. F. de Campos Velho: National Institute for Space Research
G. Sampaio: National Institute for Space Research

Chapter Chapter 45 in Integral Methods in Science and Engineering, 2015, pp 539-550 from Springer

Abstract: Abstract Today, there is increasing scientific evidence that extreme climate and weather phenomena could become more frequent under a warmer planet (IPCC: Cambio climático 2007: Informe de síntesis. Grupo Intergobernamental de Expertos sobre el Cambio Climático [Equipo de redacción principal: Pachauri,R.K. y Reisinger, A. (directores de la publicacion)] Ginebra, Suiza 104, 2007). This picture has been gradually emerging, since the first IPCC Assessment report in 1990, from a series of studies based on an increasing amount of data, which comprehensively covers the relevant atmospheric, land, ice and ocean variables, computed or measured at different time intervals and spatial resolutions. These data sets come from remote instruments in satellites and in situ sensor networks, or are the outputs of computer simulations and reanalyzes (Overpeck et al., Science 331:700–702, 2011). Among the challenges generated by this deluge of data is the development of better technologies to store, distribute, analyze, and visualize their information content (Hey et al., The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research. Available: http://research.microsoft.com/en-us/collaboration/fourthparadigm/ . Accessed 04 Nov 2011 (2010); Foster, Nature. 440:419, 2006). Here we present an innovative data mining approach to investigate the climatic causes of extreme events.

Keywords: extreme climate; data mining (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-16727-5_45

Ordering information: This item can be ordered from
http://www.springer.com/9783319167275

DOI: 10.1007/978-3-319-16727-5_45

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().