Global trend analysis of the MODIS drought severity index

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...

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Main Authors: P. I. Orvos, V. Homonnai, A. Várai, Z. Bozóki, I. M. Jánosi
Format: Article
Language:English
Published: Copernicus Publications 2015-10-01
Series:Geoscientific Instrumentation, Methods and Data Systems
Online Access:http://www.geosci-instrum-method-data-syst.net/4/189/2015/gi-4-189-2015.pdf
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spelling doaj-f5a3e3b948ed4a3ab8b0934dc62c6cfb2020-11-25T01:57:11ZengCopernicus PublicationsGeoscientific Instrumentation, Methods and Data Systems2193-08562193-08642015-10-014218919610.5194/gi-4-189-2015Global trend analysis of the MODIS drought severity indexP. I. Orvos0V. Homonnai1A. Várai2Z. Bozóki3I. M. Jánosi4Department of Optics and Quantum Electronics, University of Szeged, Szeged, HungaryRegional Research Center, Eötvös Loránd University, Székesfehérvár, HungaryDepartment of Physics of Complex Systems, Eötvös Loránd University, Budapest, HungaryMTA-SZTE Research Group on Photoacoustic Spectroscopy, University of Szeged, Szeged, HungaryRegional Research Center, Eötvös Loránd University, Székesfehérvár, HungaryRecently, 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.http://www.geosci-instrum-method-data-syst.net/4/189/2015/gi-4-189-2015.pdf
collection DOAJ
language English
format Article
sources DOAJ
author P. I. Orvos
V. Homonnai
A. Várai
Z. Bozóki
I. M. Jánosi
spellingShingle P. I. Orvos
V. Homonnai
A. Várai
Z. Bozóki
I. M. Jánosi
Global trend analysis of the MODIS drought severity index
Geoscientific Instrumentation, Methods and Data Systems
author_facet P. I. Orvos
V. Homonnai
A. Várai
Z. Bozóki
I. M. Jánosi
author_sort P. I. Orvos
title Global trend analysis of the MODIS drought severity index
title_short Global trend analysis of the MODIS drought severity index
title_full Global trend analysis of the MODIS drought severity index
title_fullStr Global trend analysis of the MODIS drought severity index
title_full_unstemmed Global trend analysis of the MODIS drought severity index
title_sort global trend analysis of the modis drought severity index
publisher Copernicus Publications
series Geoscientific Instrumentation, Methods and Data Systems
issn 2193-0856
2193-0864
publishDate 2015-10-01
description 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.
url http://www.geosci-instrum-method-data-syst.net/4/189/2015/gi-4-189-2015.pdf
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