Understanding the global hydrological droughts of 2003-2016 and their relationships with teleconnections.

Canonical Correlation Analysis (CCA) Drought hot spots GRACE Terrestrial Water Storage (TWS) Global droughts Sea Surface Temperature (SST) Teleconnections

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
10 Feb 2019
Historique:
received: 13 07 2018
revised: 31 08 2018
accepted: 17 09 2018
pubmed: 8 10 2018
medline: 8 10 2018
entrez: 8 10 2018
Statut: ppublish

Résumé

Droughts often evolve gradually and cover large areas, and therefore, affect many people and activities. This motivates developing techniques to integrate different satellite observations, to cover large areas, and understand spatial and temporal variability of droughts. In this study, we apply probabilistic techniques to generate satellite derived meteorological, hydrological, and hydro-meteorological drought indices for the world's 156 major river basins covering 2003-2016. The data includes Terrestrial Water Storage (TWS) estimates from the Gravity Recovery And Climate Experiment (GRACE) mission, along with soil moisture, precipitation, and evapotranspiration reanalysis. Different drought characteristics of trends, occurrences, areal-extent, and frequencies corresponding to 3-, 6-, 12-, and 24-month timescales are extracted from these indices. Drought evolution within selected basins of Africa, America, and Asia is interpreted. Canonical Correlation Analysis (CCA) is then applied to find the relationship between global hydro-meteorological droughts and satellite derived Sea Surface Temperature (SST) changes. This relationship is then used to extract regions, where droughts and teleconnections are strongly interrelated. Our numerical results indicate that the 3- to 6-month hydrological droughts occur more frequently than the other timescales. Longer memory of water storage changes (than water fluxes) has found to be the reason of detecting extended hydrological droughts in regions such as the Middle East and Northern Africa. Through CCA, we show that the El Niño Southern Oscillation (ENSO) has major impact on the magnitude and evolution of hydrological droughts in regions such as the northern parts of Asia and most parts of the Australian continent between 2006 and 2011, as well as droughts in the Amazon basin, South Asia, and North Africa between 2010 and 2012. The Indian ocean Dipole (IOD) and North Atlantic Oscillation (NAO) are found to have regional influence on the evolution of hydrological droughts.

Identifiants

DOI: 10.1016/j.scitotenv.2018.09.231 PMID: 30293010
pubmed: 30293010
pii: S0048-9697(18)33675-1
doi: 10.1016/j.scitotenv.2018.09.231
pii:
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2587-2604

Informations de copyright

Copyright © 2018 Elsevier B.V. All rights reserved.

Auteurs

E Forootan (E)

School of Earth and Ocean Sciences, Cardiff University, United Kingdom; Institute of Physics and Meteorology (IPM), University of Hohenheim, Stuttgart, Germany. Electronic address: ForootanE@cardiff.ac.uk.

M Khaki (M)

School of Earth and Planetary Sciences, Discipline of Spatial Sciences, Curtin University, Perth, Australia; School of Engineering, University of Newcastle, Callaghan, New South Wales, Australia.

M Schumacher (M)

Institute of Physics and Meteorology (IPM), University of Hohenheim, Stuttgart, Germany.

V Wulfmeyer (V)

Institute of Physics and Meteorology (IPM), University of Hohenheim, Stuttgart, Germany.

N Mehrnegar (N)

School of Earth and Ocean Sciences, Cardiff University, United Kingdom.

A I J M van Dijk (AIJM)

Fenner School of Environment and Society, The Australian National University, Canberra, Australia.

L Brocca (L)

National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy.

S Farzaneh (S)

School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran.

F Akinluyi (F)

Department of Remote Sensing and Geo-science Information System, School of Earth and Mineral Sciences, Federal University of Technology, Akure, Nigeria.

G Ramillien (G)

Centre National de la Recherche Scientifique (CNRS), France.

C K Shum (CK)

Division of Geodetic Science, School of Earth Sciences, Ohio State University, Columbus, OH, USA; State Key Laboratory of Geodesy and Earth's Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China.

J Awange (J)

School of Earth and Planetary Sciences, Discipline of Spatial Sciences, Curtin University, Perth, Australia.

A Mostafaie (A)

Surveying Department, Faculty of Engineering, University of Zabol, Iran.

Classifications MeSH