An Application of GPCC and NCEP/NCAR Datasets for Drought Variability Analysis in Iran

The lack of reliable and updated precipitation datasets is the most important limitation that hinders establishing a drought monitoring and early warning system in Iran. To overcome this obstacle, we have evaluated the applicability of GPCC and NCEP/NCAR precipitation datasets for drought analysis in Iran. For this purpose, drought variability across the country has been analyzed through the standardized precipitation index (SPI) on 12-month time scale based on the common period 1951–2005. For each dataset, by applying the principal component analysis (PCA) to the SPI field and Varimax rotation, the studied area has been regionalized into a few distinctive sub-regions characterized by independent climatic variability. Results have been checked against observations at 32 rain gauge stations having reliable data for the study period. Both GPCC and NCEP/NCAR datasets identify the same sub-regions of drought variability and they are in good agreement with observations. However, the NCEP rotated principal component scores associated with the sub-regions show different time variability with respect to the behaviours captured by GPCC, on one hand, and observations, on the other hand. It seems that, in central Iran such differences concern mainly the period before the seventies. Thus, the results suggest that GPCC dataset is a useful tool for drought monitoring in Iran and it can be used to complement the information provided by rain gauge observations. The NCEP/NCAR reanalysis dataset shows a better agreement with observations for the period 1970–2005 than for 1951–2005, and its discrepancies in the regional time variability of drought with respect to GPCC and observations should be taken into account when periods before the seventies are considered. Copyright Springer Science+Business Media B.V. 2011