Articles | Volume 4, issue 2
Geosci. Instrum. Method. Data Syst., 4, 189–196, 2015
Geosci. Instrum. Method. Data Syst., 4, 189–196, 2015

Research article 12 Oct 2015

Research article | 12 Oct 2015

Global trend analysis of the MODIS drought severity index

P. I. Orvos1,2, V. Homonnai2, A. Várai3, Z. Bozóki4, and I. M. Jánosi2,3 P. I. Orvos et al.
  • 1Department of Optics and Quantum Electronics, University of Szeged, Szeged, Hungary
  • 2Regional Research Center, Eötvös Loránd University, Székesfehérvár, Hungary
  • 3Department of Physics of Complex Systems, Eötvös Loránd University, Budapest, Hungary
  • 4MTA-SZTE Research Group on Photoacoustic Spectroscopy, University of Szeged, Szeged, Hungary

Abstract. Recently, Mu et al. (2013) compiled an open access database of a remotely sensed global drought severity index (DSI) based on MODIS (Moderate Resolution Imaging Spectroradiometer) satellite measurements covering a continuous period of 12 years. The highest spatial resolution is 0.05° × 0.05° in the geographic band between 60° S and 80° N latitudes (more than 4.9 million locations over land). Here we present a global trend analysis of these satellite-based DSI time series in order to identify geographic locations where either positive or negative trends are statistically significant. Our main result is that 17.34 % of land areas exhibit significant trends of drying or wetting, and these sites constitute geographically connected regions. Since a DSI value conveys local characterization at a given site, we argue that usual field significance tests cannot provide more information about the observations than the presented analysis. The relatively short period of 12 years hinders linking the trends to global climate change; however, we think that the observations might be related to slow (decadal) modes of natural climate variability or anthropogenic impacts.

Short summary
The remotely sensed drought severity index (DSI) records compiled by Mu et al. (2013) exhibit significant local trends in several geographic areas. Since the interpretation of DSI values and trends depend on several local factors, standard field significance tests cannot provide more reliable results than the presented local trend survey. The observed continent-wide trends might be related to a slow (decadal) mode of climate variability, a link to global climate change cannot be established.