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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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 |
work_keys_str_mv |
AT piorvos globaltrendanalysisofthemodisdroughtseverityindex AT vhomonnai globaltrendanalysisofthemodisdroughtseverityindex AT avarai globaltrendanalysisofthemodisdroughtseverityindex AT zbozoki globaltrendanalysisofthemodisdroughtseverityindex AT imjanosi globaltrendanalysisofthemodisdroughtseverityindex |
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1724975786106028032 |