Abstract

Abstract. Drought is a phenomenon which can cause large economical impact even in Europe. To assess the magnitude and the spatial extension of drought events, it is important to have a standardized drought index which is applicable for a large climatically heterogeneous region like Europe or the WMO RA VI Region (Europe and the Middle East). Such an index should describe the drought phenomenon adequately, but it should also be derivable from meteorological quantities which are easily and timely available in whole Europe. In a first investigation, some candidates for drought indices were chosen, compared and assessed for applicability in whole Europe. The most appropriate one seems to be the widely known Standardized Precipitation Index (SPI) which is a standardized and handy measurement of drought for any location and requires nothing but precipitation data. However, it has turned out that for some places in the RA VI Region, notably in arid regions in summer, the SPI does not always provide reasonable or easily interpretable results. For that reason, some modifications of the SPI have been tried out and tested statistically. It seems that the gamma distribution of precipitation which is used for computation of the SPI is in fact the most appropriate one and other distributions have not improved the results substantially. On the other hand a so called zero correction, which sets very small precipitation totals to dry values, only dependent on the precipitation distribution, but independent on the individual location delivers more reasonable results. Maps of the new modified drought index and its anomalies from the climate normal are produced quasi-operationally and distributed via the Internet each month. The drought monitoring is part of the monitoring programme of the WMO RA VI Pilot Regional Climate Centre on Climate Monitoring (RCC-CM) hosted by the German Meteorological Service (Deutscher Wetterdienst, DWD), and the maps can be found on its present RCC-CM platform (http://www.dwd.de/rcc-cm).

Highlights

  • Drought is a phenomenon which can appear in many parts of the globe (Wilhite, 2000) and can cause large economic impacts even in Europe

  • Some modifications of the Standardized Precipitation Index (SPI) have been tried out and tested statistically. It seems that the gamma distribution of precipitation which is used for computation of the SPI is the most appropriate one and other distributions have not improved the results substantially

  • In a first investigation (Pietzsch, 2009), three drought indices were chosen, compared and assessed for applicability to the whole of Europe. These were the Aridity Index according to de Martonne (1950) (Precipitation/[Temperature + 10]), the Climatic Water Balance (Muller-Westermeier, 2005) (Precipitation Evaporation according to Wendling, 1995) and the Standardized Precipitation Index (McKee et al, 1993)

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Summary

Introduction

Drought is a phenomenon which can appear in many parts of the globe (Wilhite, 2000) and can cause large economic impacts even in Europe. The aim of the investigation is to produce an operational system to monitor drought conditions, showing their variability in time and space It should be an index which is easy to calculate and apply to the whole region so that individual sub-regions can be compared to each other. The approach is to create a drought index by choosing an already existing and widely used index which is applicable for most of the WMO RA VI Region, and by introducing modifications for those parts of the Region where improvement of the index is needed due to their special climatic characteristics Such an index can provide an overview of drought conditions and its variability in space and time operationally. Another reason for having chosen that time scale is that the aim of this paper is the construction of a drought index for monthly climate monitoring, to enable a comparison with other monthly climate monitoring products such as temperature and precipitation anomalies

Comparison of drought indices
SPI modifications
Production of time series and operational maps
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