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| Titel |
Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets |
| VerfasserIn |
T. Raziei, I. Bordi, L. S. Pereira, A. Sutera |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 14, no. 10 ; Nr. 14, no. 10 (2010-10-12), S.1919-1930 |
| Datensatznummer |
250012444
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| Publikation (Nr.) |
 copernicus.org/hess-14-1919-2010.pdf |
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| Zusammenfassung |
Space-time variability of hydrological drought and wetness over Iran is
investigated using the National Centers for Environmental
Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis
and the Global Precipitation Climatology Centre (GPCC) dataset for the
common period 1948–2007. The aim is to complement previous studies on the
detection of long-term trends in drought/wetness time series and on the
applicability of reanalysis data for drought monitoring in Iran. Climate
conditions of the area are assessed through the Standardized Precipitation
Index (SPI) on 24-month time scale, while Principal Component Analysis (PCA)
and Varimax rotation are used for investigating drought/wetness variability,
and drought regionalization, respectively. Singular Spectrum Analysis (SSA)
is applied to the time series of interest to extract the leading nonlinear
components and compare them with linear fittings.
Differences in drought and wetness area coverage resulting from the two
datasets are discussed also in relation to the change occurred in recent
years. NCEP/NCAR and GPCC are in good agreement in identifying four
sub-regions as principal spatial modes of drought variability. However, the
climate variability in each area is not univocally represented by the two
datasets: a good agreement is found for south-eastern and north-western
regions, while noticeable discrepancies occur for central and Caspian sea
regions. A comparison with NCEP Reanalysis II for the period 1979–2007,
seems to exclude that the discrepancies are merely due to the introduction
of satellite data into the reanalysis assimilation scheme. |
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