Monthly Prediction of Drought Classes Using Log-Linear Models under the Influence of NAO for Early-Warning of Drought and Water Management

Elsa Moreira,Ricardo Trigo,Ana Russo

doi:10.3390/w10010065

Elsa Moreira, Ricardo Trigo + Show 1 more

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https://doi.org/10.3390/w10010065

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Journal: Water	Publication Date: Jan 12, 2018
Citations: 11	License type: CC BY 4.0

Affiliation: University of Lisbon, Universidade Nova de Lisboa

Abstract

Drought class transitions over a sector of Eastern Europe were modeled using log-linear models. These drought class transitions were computed from time series of two widely used multiscale drought indices, the Standardized Preipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI), with temporal scales of 6 and 12 months for 15 points selected from a grid over the Prut basin in Romania over a period of 112 years (1902–2014). The modeling also took into account the impact of North Atlantic Oscillation (NAO), exploring the potential influence of this large-scale atmospheric driver on the climate of the Prut region. To assess the probability of transition among different drought classes we computed their odds and the corresponding confidence intervals. To evaluate the predictive capabilities of the modeling, skill scores were computed and used for comparison against benchmark models, namely using persistence forecasts or modeling without the influence of the NAO index. The main results indicate that the log-linear modeling performs consistently better than the persistence forecast, and the highest improvements obtained in the skill scores with the introduction of the NAO predictor in the modeling are obtained when modeling the extended winter months of the SPEI6 and SPI12. The improvements are however not impressive, ranging between 4.7 and 6.8 for the SPEI6 and between 4.1 and 10.1 for the SPI12, in terms of the Heidke skill score.

Highlights

The social, environmental and economic impacts of drought, as well as its features, have been studied in numerous studies [1,2,3,4,5,6,7]
The temporal evolution of the original drought and wetness classes for the study period is shown in Figure 2 (SPEI6) and Figure 3 (SPEI12), considering the classification proposed by McKee et al [39]
Predictability of the Standardized Preipitation Evapotranspiration Index (SPEI) and SPI drought classes under the influence of North Atlantic Oscillation (NAO) was studied for the Prut basin using three-dimensional log-linear models, which are probabilistic models that learn from the preceding two months with the aim of predicting the drought class in the following month

Summary

Introduction

The social, environmental and economic impacts of drought, as well as its features, have been studied in numerous studies [1,2,3,4,5,6,7]. Since 1950, a positive tendency of drought patterns has been observed over some regions of the globe [8,9,10], in part due to global warming [11]. Within the European context, the positive drought trends seem to be acute in the Mediterranean area [10,12,13], where increased dryness [14,15,16] and temperature is more notorious [6,17]. In a paper by Spinoni et al [19], the drought events in the last five decades in the Carpathian region (ranging from the Czech Republic to Serbia, encompassing Slovakia, Poland, Hungary, Ukraine, and Romania) were analyzed. The most intense droughts took place in 1990, 2000, and 2003, followed

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