Monthly prediction of drought classes using log-linear models under the influence of NAO for early-warning of drought and water management

Elsa Moreira, Ana Russo, Ricardo M. Trigo

Research output: Contribution to journalArticle

4 Citations (Scopus)
5 Downloads (Pure)

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.

Original languageEnglish
Article number65
JournalWater (Switzerland)
Volume10
Issue number1
DOIs
Publication statusPublished - 12 Jan 2018

Fingerprint

Drought
Droughts
Water management
North Atlantic Oscillation
linear model
drought
water management
Linear Models
linear models
prediction
Water
modeling
persistence
Benchmarking
Eastern Europe
Romania
Evapotranspiration
Climate
time series
Time series

Keywords

  • Drought classes
  • Log-linear modeling
  • North Atlantic Oscillation (NAO)
  • Persistence
  • Standardized Precipitation and Evapotranspiration Index (SPEI)
  • Standardized Precipitation Index (SPI)

Cite this

@article{7703a3b0b30245e19125a2b2da62c429,
title = "Monthly prediction of drought classes using log-linear models under the influence of NAO for early-warning of drought and water management",
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.",
keywords = "Drought classes, Log-linear modeling, North Atlantic Oscillation (NAO), Persistence, Standardized Precipitation and Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI)",
author = "Elsa Moreira and Ana Russo and Trigo, {Ricardo M.}",
note = "info:eu-repo/grantAgreement/FCT/3599-PPCDT/147467/PT# info:eu-repo/grantAgreement/FCT/5876/147204/PT# SFRH/BPD/99757/2014 This work was partially supported by the projects IMDROFLOOD-Improving Drought and Flood Early Warning, Forecasting and Mitigation using real-time hydroclimatic indicators (WaterJPI/0004/2014) and project UID/MAT/00297/2013 (Centro de Matematica e Aplicacoes), both funded by funded by Fundacao para a Ciencia e a Tecnologia, Portugal (FCT). Ana Russo thanks also FCT by the Post-Doc research grant SFRH/BPD/99757/2014.",
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Monthly prediction of drought classes using log-linear models under the influence of NAO for early-warning of drought and water management. / Moreira, Elsa; Russo, Ana; Trigo, Ricardo M.

In: Water (Switzerland), Vol. 10, No. 1, 65, 12.01.2018.

Research output: Contribution to journalArticle

TY - JOUR

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AU - Moreira, Elsa

AU - Russo, Ana

AU - Trigo, Ricardo M.

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KW - Standardized Precipitation Index (SPI)

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