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SPI Modes of Drought Spatial and Temporal Variability in Portugal: Comparing Observations, PT02 and GPCC Gridded Datasets

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  • Tayeb Raziei
  • Diogo Martins
  • Isabella Bordi
  • João Santos
  • Maria Portela
  • Luis Pereira
  • Alfonso Sutera

Abstract

Regional drought modes in Portugal are identified applying the Principal Component Analysis (PCA) and Varimax rotation to the Standardized Precipitation Index (SPI) computed on various time scales using the three precipitation datasets covering the period 1950–2003: (i) The observation dataset composed of 193 rain-gauges distributed almost uniformly over the country, (ii) the PT02 high-resolution gridded dataset provided by the Portuguese Meteorological Institute, and (iii) the GPCC dataset with 0.5° spatial resolution. Results suggest that the three datasets well agree in identifying the principal drought modes, i.e. two sub-regions in northern and southern Portugal with independent climate variability. The two sub-regions appear stable when the SPI time scale is varied from 3- to 24-month, and the associated rotated principal component scores (RPCs) do not show any statistically significant linear trend. The degree of similarity between the rotated loadings or REOFs of different SPI time scales for the three used datasets was examined through the congruence coefficients, whose results show a good agreement between the three datasets in capturing the main Portuguese sub-regions. A third spatial mode in central-eastern Portugal was identified for SPI-24 in PT02, with the associated RPC characterized by a statistically significant downward trend. The stability of the identified sub-regions as a function of studied time period was also evaluated applying the same methodologies to a set of three different time windows and it was found that the southern sub-region is very stable but the northern and central-eastern sub-regions are very sensitive to the selected time window. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Tayeb Raziei & Diogo Martins & Isabella Bordi & João Santos & Maria Portela & Luis Pereira & Alfonso Sutera, 2015. "SPI Modes of Drought Spatial and Temporal Variability in Portugal: Comparing Observations, PT02 and GPCC Gridded Datasets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(2), pages 487-504, January.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:2:p:487-504
    DOI: 10.1007/s11269-014-0690-3
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    References listed on IDEAS

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    1. B. Bonaccorso & I. Bordi & A. Cancelliere & G. Rossi & A. Sutera, 2003. "Spatial Variability of Drought: An Analysis of the SPI in Sicily," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 17(4), pages 273-296, August.
    2. Tayeb Raziei & Isabella Bordi & Luis Pereira, 2011. "An Application of GPCC and NCEP/NCAR Datasets for Drought Variability Analysis in Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(4), pages 1075-1086, March.
    3. Brunella Bonaccorso & David Peres & Antonino Cancelliere & Giuseppe Rossi, 2013. "Large Scale Probabilistic Drought Characterization Over Europe," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(6), pages 1675-1692, April.
    4. Donald Wilhite & Mark Svoboda & Michael Hayes, 2007. "Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 763-774, May.
    5. Paulo, A.A. & Ferreira, E. & Coelho, C. & Pereira, L.S., 2005. "Drought class transition analysis through Markov and Loglinear models, an approach to early warning," Agricultural Water Management, Elsevier, vol. 77(1-3), pages 59-81, August.
    6. Tayeb Raziei & Isabella Bordi & Luis Pereira, 2013. "Regional Drought Modes in Iran Using the SPI: The Effect of Time Scale and Spatial Resolution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(6), pages 1661-1674, April.
    7. repec:ucp:bkecon:9780226316529 is not listed on IDEAS
    8. Sergio Vicente-Serrano, 2006. "Differences in Spatial Patterns of Drought on Different Time Scales: An Analysis of the Iberian Peninsula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 37-60, February.
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    Cited by:

    1. Ana Paulo & Diogo Martins & Luís Santos Pereira, 2016. "Influence of Precipitation Changes on the SPI and Related Drought Severity. An Analysis Using Long-Term Data Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5737-5757, December.
    2. Abdelaaziz Merabti & Diogo S. Martins & Mohamed Meddi & Luis S. Pereira, 2018. "Spatial and Time Variability of Drought Based on SPI and RDI with Various Time Scales," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(3), pages 1087-1100, February.
    3. Jin Huang & Yadong Lei & Fangmin Zhang & Zhenghua Hu, 2017. "Spatio-temporal analysis of meteorological disasters affecting rice, using multi-indices, in Jiangsu province, Southeast China," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(4), pages 661-672, August.

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