SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling
This study aims at predicting the Standard Precipitation Index (SPI) drought class transitions in Portugal, considering the influence of the North Atlantic Oscillation (NAO) as one of the main large-scale atmospheric drivers of precipitation and drought fields across the Western European and Mediter...
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ftdoajarticles:oai:doaj.org/article:b4871257a7f2498fb1fa348c4642c895 2023-05-15T17:32:05+02:00 SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling Elsa E. Moreira Carlos L. Pires Luís S. Pereira 2016-01-01T00:00:00Z https://doi.org/10.3390/w8020043 https://doaj.org/article/b4871257a7f2498fb1fa348c4642c895 EN eng MDPI AG http://www.mdpi.com/2073-4441/8/2/43 https://doaj.org/toc/2073-4441 2073-4441 doi:10.3390/w8020043 https://doaj.org/article/b4871257a7f2498fb1fa348c4642c895 Water, Vol 8, Iss 2, p 43 (2016) 3-dimensional log-linear models drought class transitions odds confidence intervals Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 article 2016 ftdoajarticles https://doi.org/10.3390/w8020043 2022-12-31T15:25:22Z This study aims at predicting the Standard Precipitation Index (SPI) drought class transitions in Portugal, considering the influence of the North Atlantic Oscillation (NAO) as one of the main large-scale atmospheric drivers of precipitation and drought fields across the Western European and Mediterranean areas. Log-linear modeling of the drought class transition probabilities on three temporal steps (dimensions) was used in an SPI time series of six- and 12-month time scales (SPI6 and SPI12) obtained from Global Precipitation Climatology Centre (GPCC) precipitation datasets with 1.0 degree of spatial resolution for 10 grid points over Portugal and a length of 112 years (1902–2014). The aim was to model two monthly transitions of SPI drought classes under the influence of the NAO index in its negative and positive phase in order to obtain improvements in the predictions relative to the modeling not including the NAO index. The ratios (odds ratio) between transitional probabilities and their confidence intervals were computed in order to estimate the probability of one drought class transition over another. The prediction results produced by the model with the forcing of NAO were compared with the results produced by the same model without that forcing, using skill scores computed for the entire time series length. Overall results have shown good prediction performance, ranging from 73% to 76% in the percentage of corrects (PC) and 56%–62% in the Heidke skill score (HSS) regarding the SPI6 application and ranging from 82% to 85% in the PC and 72%–76% in the HSS for the SPI12 application. The model with the NAO forcing led to improvements in predictions of about 1%–6% (PC) and 1%–8% (HSS), when applied to SPI6, but regarding SPI12 only seven of the locations presented slight improvements of about 0.4%–1.8% (PC) and 0.7%–3% (HSS). Article in Journal/Newspaper North Atlantic North Atlantic oscillation Directory of Open Access Journals: DOAJ Articles Water 8 2 43 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
3-dimensional log-linear models drought class transitions odds confidence intervals Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 |
spellingShingle |
3-dimensional log-linear models drought class transitions odds confidence intervals Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Elsa E. Moreira Carlos L. Pires Luís S. Pereira SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling |
topic_facet |
3-dimensional log-linear models drought class transitions odds confidence intervals Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 |
description |
This study aims at predicting the Standard Precipitation Index (SPI) drought class transitions in Portugal, considering the influence of the North Atlantic Oscillation (NAO) as one of the main large-scale atmospheric drivers of precipitation and drought fields across the Western European and Mediterranean areas. Log-linear modeling of the drought class transition probabilities on three temporal steps (dimensions) was used in an SPI time series of six- and 12-month time scales (SPI6 and SPI12) obtained from Global Precipitation Climatology Centre (GPCC) precipitation datasets with 1.0 degree of spatial resolution for 10 grid points over Portugal and a length of 112 years (1902–2014). The aim was to model two monthly transitions of SPI drought classes under the influence of the NAO index in its negative and positive phase in order to obtain improvements in the predictions relative to the modeling not including the NAO index. The ratios (odds ratio) between transitional probabilities and their confidence intervals were computed in order to estimate the probability of one drought class transition over another. The prediction results produced by the model with the forcing of NAO were compared with the results produced by the same model without that forcing, using skill scores computed for the entire time series length. Overall results have shown good prediction performance, ranging from 73% to 76% in the percentage of corrects (PC) and 56%–62% in the Heidke skill score (HSS) regarding the SPI6 application and ranging from 82% to 85% in the PC and 72%–76% in the HSS for the SPI12 application. The model with the NAO forcing led to improvements in predictions of about 1%–6% (PC) and 1%–8% (HSS), when applied to SPI6, but regarding SPI12 only seven of the locations presented slight improvements of about 0.4%–1.8% (PC) and 0.7%–3% (HSS). |
format |
Article in Journal/Newspaper |
author |
Elsa E. Moreira Carlos L. Pires Luís S. Pereira |
author_facet |
Elsa E. Moreira Carlos L. Pires Luís S. Pereira |
author_sort |
Elsa E. Moreira |
title |
SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling |
title_short |
SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling |
title_full |
SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling |
title_fullStr |
SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling |
title_full_unstemmed |
SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling |
title_sort |
spi drought class predictions driven by the north atlantic oscillation index using log-linear modeling |
publisher |
MDPI AG |
publishDate |
2016 |
url |
https://doi.org/10.3390/w8020043 https://doaj.org/article/b4871257a7f2498fb1fa348c4642c895 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Water, Vol 8, Iss 2, p 43 (2016) |
op_relation |
http://www.mdpi.com/2073-4441/8/2/43 https://doaj.org/toc/2073-4441 2073-4441 doi:10.3390/w8020043 https://doaj.org/article/b4871257a7f2498fb1fa348c4642c895 |
op_doi |
https://doi.org/10.3390/w8020043 |
container_title |
Water |
container_volume |
8 |
container_issue |
2 |
container_start_page |
43 |
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1766130018972336128 |