Article

Analyzing spatial patterns of meteorological drought using standardized precipitation index

Meteorological Applications (Impact Factor: 1.32). 10/2007; 14(4):329 - 336. DOI:10.1002/met.33

ABSTRACT Drought is a slow-onset, creeping natural hazard and a recurrent phenomenon in the arid and semi-arid regions of Gujarat (India). In Asia, the standardized precipitation index (SPI) has gained wider acceptance in the detection and the estimation of the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI, in comparison with other indices, is that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. This index captures the accumulated deficit (SPI < 0) or surplus (SPI > 0) of precipitation over a specified period, and provides a normalized measure (i.e. spatially invariant Z score) of relative precipitation anomalies at multiple time scales. In the present study, monthly time series of rainfall data (1981–2003) from 160 stations were used to derive SPI, particularly at 3-month time scales. This 3-month SPI was interpolated to depict spatial patterns of meteorological drought and its severity during typical drought and wet years. Correlation analysis was also done to evaluate usefulness of SPI to quantify effects of drought on food grain productivity. Further, time series of SPI were exploited to assess the drought risk in Gujarat. Copyright © 2007 Royal Meteorological Society

0 0
 · 
1 Bookmark
 · 
119 Views
  • Source
    International Journal of Climatology 01/2013; · 2.89 Impact Factor
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: Drought is one of the most costly natural disasters in the world. Understanding the drought characteristics in space and time will help deepen our apprehension of the drought formation and evolution mechanisms. It can also contribute to design monitoring system for drought warning and mitigation. In this study, we analyzed meteorological droughts, using the Standardized Precipitation Index, for Lancang River Basin, Southwest China. The 46-year (1960–2005) daily precipitation observations from 35 meteorological stations in the basin were used to derive the drought index. Spatial patterns and temporal patterns of the drought characteristics at multiple scales were investigated. The results utilizing the Principal Component Analysis and K-means clustering methods suggest that the study area can be divided into four sub-regions geographically with each sub-region having its own distinctive temporal evolution patterns of droughts. The temporal variability of droughts was investigated using the Empirical Mode Decomposition (EMD) analysis and the wavelet method. The EMD analysis showed that more than 60 % of the variance of the drought is associated with intra-decadal fluctuations in precipitation, except for one sub region, represented by the Changdu station. The wavelet transform showed an evolution of the main cycle near 3–7 years for most parts of the study area.
    Theoretical and Applied Climatology 12/2013; · 1.76 Impact Factor
  • [show abstract] [hide abstract]
    ABSTRACT: A large ensemble of 24 bias-corrected and uncorrected regional climate model (RCM) simulations is used to investigate climate change impacts on water supply patterns over Germany using the seasonal winter and summer Standardized Precipitation Index (SPI) based on 6-month precipitation sums. The climate change signal is studied comparing SPI characteristics for the reference period 1971-2000 with those of the "near" (2036-2065) and the "far" (2071-2100) future. The spread of the climate change signal within the simulation ensemble of bias-corrected versus non-corrected data is discussed. Ensemble scenarios are evaluated against available observation-based data over the reference period 1971-2000. After correcting the model biases, the model ensemble underestimates the variability of the precipitation climatology in the reference period, but replicates the mean characteristics. Projections of water supply patterns based on the SPI for the time periods 2036-2065 and 2071-2100 show wetter winter months during both future time periods. As a result soil drying may be delayed to late spring extending into the summer period, which could have an important effect on sensible heat fluxes. While projections indicate wetting in summer during 2036-2065, drier summers are estimated towards the south-west of Germany for the end of the 21st century. The use of the bias correction intensifies the signal to wetter conditions for both seasons and time periods. The spread in the projection of future water supply patterns between the ensemble members is explored, resulting in high spatial differences that suggest a higher uncertainty of the climate change signal in the southern part of Germany. It is shown that the spread of the climate change signals between SPIs based on single ensemble members is twice as large as the difference between the mean climate change signal of SPIs based on bias-corrected and uncorrected precipitation. This implies that the sensitivity of the SPI to the modelled precipitation bias is small compared to the range of the climate change signals within our ensemble. Therefore, the SPI is a very useful tool for climate change studies allowing us to avoid the additional uncertainties caused by bias corrections.
    Biogeosciences 05/2013; 10(5):2959-2972. · 3.75 Impact Factor