SPI Drought Class Predictions Driven by the North Atlantic Oscillation Index Using Log-Linear Modeling

Elsa Moreira,Luís Pereira,Carlos Pires

doi:10.3390/w8020043

Elsa Moreira, Luís Pereira + Show 1 more

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https://doi.org/10.3390/w8020043

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Journal: Water	Publication Date: Jan 30, 2016
Citations: 57	License type: CC BY 4.0

Affiliation: University of Lisbon, Universidade Nova de Lisboa

Abstract

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).

Highlights

Drought is a natural temporary imbalance of water availability, consisting of a persistent lower-than-average precipitation, of uncertain frequency, duration and severity, and of unpredictable or difficult-to-predict occurrence, resulting in diminished water resource availability and carrying capacity of ecosystems [1]
Both contingency tables for NAOand North Atlantic Oscillation (NAO)+, either relative to the SPI6 (Table 2) or the SPI12 (Table 3), present higher frequency values for the transitions that imply the maintenance of the precedent drought classes and smaller frequencies for the transitions that imply the increase/decrease of the drought classes, when changing by two or three values
That is because the sensitivity of precipitation to the NAO index is generally stronger in the wetter regimes, in accordance with the asymmetric correlations between NAO and Standard Precipitation Index (SPI) presented by Pires and Perdigão [16]

Summary

Introduction

Drought is a natural temporary imbalance of water availability, consisting of a persistent lower-than-average precipitation, of uncertain frequency, duration and severity, and of unpredictable or difficult-to-predict occurrence, resulting in diminished water resource availability and carrying capacity of ecosystems [1]. The importance of early warning to water users for timely implementation of preparedness and mitigation measures is well known and has been widely addressed by several authors [1,2,3]. Drought prediction is a major concern for water managers, farmers and other water end-users because it constrains their decisions. Water 2016, 8, 43 measures and policies can be taken in order to mitigate the effects of the drought [3,4]. Short-term drought predictions, from one to three months, may be used to alert farmers and water managers about the initiation, continuation or end of a drought and about the need for preparedness measures before a drought is effectively installed or for a post-drought period. Forecasting when a drought is likely initiating or to coming to an end is a difficult task

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