Spatial and temporal variations in the accuracy of meteorological drought indices

Meteorological drought indices are commonly calculated using data from weather stations and then interpolated to create a map of moisture conditions. These maps are used to communicate drought information to decision makers and the general public. This study analyzes five of the factors (drought index, interpolation method, seasonality, climate region, and station density) that influence the accuracy of these maps. This study compared the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) using data from the Cooperative Observer Network (COOP) and United States Historical Climatology Network (USHCN). The accuracy of the drought maps varied significantly over time and space. The most significant factor affecting the accuracy of the meteorological drought maps was seasonality. Errors were higher in regions (e.g., southeastern U.S.), and months (e.g., summer), dominated by convective precipitation. The choice of interpolation method also had an influence. We found that Ordinary Kriging (OK) performed better than Inverse Distance Weighting (IDW) in all cases and therefore it was recommended for interpolating drought indices. Not surprisingly, maps that were created using more stations (COOP) were more accurate. The normalized errors of SPI and SPEI were very similar and so the choice of drought index had little impact on the accuracy of the drought maps.

Abstract licence: CC BY

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