干旱区生态环境知识资源中心(Arid): Rainfall Prediction in the State of Paraiba, Northeastern Brazil Using Generalized Additive Models

Arid

DOI	10.3390/w12092478
	Rainfall Prediction in the State of Paraiba, Northeastern Brazil Using Generalized Additive Models
	Dantas, Leydson G.; dos Santos, Carlos A. C.; de Olinda, Ricardo A.; de Brito, Jose I. B.; Santos, Celso A. G.; Martins, Eduardo S. P. R.; de Oliveira, Gabriel; Brunsell, Nathaniel A.
通讯作者	dos Santos, CAC
来源期刊	WATER
EISSN	2073-4441
出版年	2020
卷号	12 期号:9
英文摘要	The state of Paraiba is part of the semi-arid region of Brazil, where severe droughts have occurred in recent years, resulting in significant socio-economic losses associated with climate variability. Thus, understanding to what extent precipitation can be influenced by sea surface temperature (SST) patterns in the tropical region can help, along with a monitoring system, to set up an early warning system, the first pillar in drought management. In this study, Generalized Additive Models for Location, Scale and Shape (GAMLSS) were used to filter climatic indices with higher predictive efficiency and, as a result, to perform rainfall predictions. The results show the persistent influence of tropical SST patterns in Paraiba rainfall, the tropical Atlantic Ocean impacting the rainfall distribution more effectively than the tropical Pacific Ocean. The GAMLSS model showed predictive capability during summer and southern autumn in Paraiba, highlighting the JFM (January, February and March), FMA (February, March and April), MAM (March, April and May), and AMJ (April, May and June) trimesters as those with the highest predictive potential. The methodology demonstrates the ability to be integrated with regional forecasting models (ensemble). Such information has the potential to inform decisions in multiple sectors, such as agriculture and water resources, aiming at the sustainable management of water resources and resilience to climate risk.
英文关键词	non-stationary water resources SST indices Northeast of Brazil zero adjusted Gamma distribution (ZAGA)
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000580705800001
WOS关键词	SEASONAL DROUGHT PREDICTION ; FLOOD FREQUENCY-ANALYSIS ; MANN-KENDALL TEST ; ARTIFICIAL-INTELLIGENCE ; EXTREME PRECIPITATION ; SERIAL-CORRELATION ; RESERVOIR INDEXES ; ATLANTIC SST ; CLIMATE ; STREAMFLOW
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/326993
作者单位	[Dantas, Leydson G.] Natl Inst Space Res, Ctr Weather Forecasting & Climate Studies, BR-12630000 Cachoeira Paulista, SP, Brazil; [dos Santos, Carlos A. C.; de Brito, Jose I. B.] Univ Fed Campina Grande, Acad Unit Atmospher Sci, Ctr Technol & Nat Resources, BR-58109970 Campina Grande, Paraiba, Brazil; [de Olinda, Ricardo A.] Paraiba State Univ, Dept Stat, BR-58429500 Campina Grande, Paraiba, Brazil; [Santos, Celso A. G.] Univ Fed Paraiba, Dept Civil & Environm Engn, BR-58051900 Joao Pessoa, Paraiba, Brazil; [Martins, Eduardo S. P. R.] Res Inst Meteorol & Water Resources, BR-60115221 Fortaleza, Ceara, Brazil; [de Oliveira, Gabriel] Univ Toronto, Dept Geog & Planning, Toronto, ON M5S 3G3, Canada; [Brunsell, Nathaniel A.] Univ Kansas, Dept Geog & Atmospher Sci, Lawrence, KS 66045 USA
推荐引用方式 GB/T 7714	Dantas, Leydson G.,dos Santos, Carlos A. C.,de Olinda, Ricardo A.,et al. Rainfall Prediction in the State of Paraiba, Northeastern Brazil Using Generalized Additive Models[J],2020,12(9).
APA	Dantas, Leydson G..,dos Santos, Carlos A. C..,de Olinda, Ricardo A..,de Brito, Jose I. B..,Santos, Celso A. G..,...&Brunsell, Nathaniel A..(2020).Rainfall Prediction in the State of Paraiba, Northeastern Brazil Using Generalized Additive Models.WATER,12(9).
MLA	Dantas, Leydson G.,et al."Rainfall Prediction in the State of Paraiba, Northeastern Brazil Using Generalized Additive Models".WATER 12.9(2020).