Data/hora: 21/09/2024 12:11:52

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	03/12/2015	
Data da última atualização: 	08/03/2016	
Autoria: 	LACERDA, F. F.; NOBRE, P.; SOBRAL, M. C.; LOPES, G. M. B.; CHOU, S. C.; ASSAD, E. D.; BRITO, E.	
Afiliação: 	IPA; Inpe; UFPE; IPA; Inpe; EDUARDO DELGADO ASSAD, CNPTIA; National Meteorology and Geophysics Institute, Cape Verde.	
Título: 	Long-term temperature and rainfall trends over northeast Brazil and Cape Verde.	
Ano de publicação: 	2015	
Fonte/Imprenta: 	Journal of Earth Science & Climatic Change, v. 6, n. 8, 2015.	
Páginas: 	8 p.	
Idioma: 	Inglês	
Conteúdo: 	This study investigates long-term climate trends in Pernambuco, Northeast Brazil (Nordeste), and in the Tropical Atlantic islands of Fernando de Noronha and Cape Verde. The study is based on meteorological station time series and model simulations of present and future climates. Past trends are compared with numerical simulations of present and future climate scenarios for the periods of 1960-2000 and 2010-2050. Both the station data analyses and numerical simulations revealed trends of increasing temperature maxima and diminishing precipitation. While station data analyses showed modest warming in Fernando de Noronha they revealed strong warming and drying trends in Cape Verde similar to the trends detected over the semiarid Nordeste. The water-balance calculations for the study sites showed reduced soil moisture availability and total rainfall in all areas. The observed temperature and precipitation trends are indicative that aridification processes are underway in Pernambuco and Cape Verde. The atmospheric model simulations were consistent with the station data regarding the present warming; the climate change scenarios for 2010-2050 indicated a faster increase of daily temperature maxima over Nordeste compared to that simulated for the recent past.	
Palavras-Chave: 	Anthropogenic origin; Dados meteorológicos; Séries temporais.	
Thesagro: 	Temperatura.	
Thesaurus Nal: 	Meteorological data; Temperature; Time series analysis.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/134702/1/longterm-Lacerda.pdf	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
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