Joseph L. Awange

Prof. Joseph L. Awange

School of Earth and Planetary Sciences, Curtin University, Perth, Australia
orcid

Research Focus & Metrics

Academic Career Length

28Years (1999-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 October 2013 in Journal of Climate
Verified
Journal Article
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HEHussen Seid Endris
Hussen Seid Endris
POPhilip Omondi
Philip Omondi
SJSuman Jain
Suman Jain
CLChristopher Lennard
Christopher Lennard
BHBruce Hewitson
Bruce Hewitson
LTLukiya Tazalika
Lukiya Tazalika
This study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models. In general, the analysis herein demonstrates that the multimodel ensemble mean simulates eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region.

26 June 2013 in International Journal of Climatology
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POPhilip Aming'O Omondi
Philip Aming'O Omondi
Joseph L. AwangeJoseph L. Awange
Joseph L. Awange
Ehsan ForootanEhsan Forootan
Ehsan Forootan
LOLaban Ayieko Ogallo
Laban Ayieko Ogallo
RBRuben Barakiza
Ruben Barakiza
EKEverline Komutunga
Everline Komutunga
Recent special reports on climate extremes have shown evidences of changes in the patterns of climate extremes at global, regional and local scales. Understanding the characteristics of climate extremes at regional and local levels is critical not only for the development of preparedness and early warning systems, but is also fundamental in the development of any adaptation strategies. There is still very limited knowledge regarding the past, present and future patterns of climate extremes in the Greater Horn of Africa (GHA). This study, which was supported by the World Bank Global Facility for Disaster Reduction and Recovery (WB‐GFDRR) and implemented by the World Meteorological Organization, was organized in terms of three workshops with three main objectives; (1) analysis of daily rainfall and temperature extremes for ten countries in the GHA region using observed in situ data running from 1971 to 2006, (2) assessing whether the United Kingdom Met‐office and Hadley centre Providing REgional Climates for Impact Studies (UK‐PRECIS) modelling system can provide realistic representation of the past and present climate extremes as observed by available in situ data, and (3) studying the future regional climate extremes under different scenarios to further assess the expected changes in climate extremes. This paper, therefore, uses the outputs of these workshops and also includes post‐workshop analyses to assess the changes of climate extremes within the GHA. The results showed a significant decrease in total precipitation in wet days greater than 1 mm and increasing warm extremes, particularly at night, while cold extremes are decreasing. Considering a combination of geophysical models and satellite gravimetry observations from the Gravity Recovery and Climate Experiment (GRACE) mission in the frame of GRACE daily Kalman‐smoothing models, for the years 2002 to 2010, we explored a decline in total water storage variations over the GHA.

1 February 2019 in Science of The Total Environment
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Journal Article
Closed access
Ehsan ForootanEhsan Forootan
Ehsan Forootan
Mehdi KhakiMehdi Khaki
Mehdi Khaki
MSM. Schumacher
M. Schumacher
VWV. Wulfmeyer
V. Wulfmeyer
NMNooshin Mehrnegar
Nooshin Mehrnegar
AMA. Mostafaie
A. Mostafaie

21 April 2015 in International Journal of Climatology
Verified
Journal Article
Open access
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Joseph L. AwangeJoseph L. Awange
Joseph L. Awange
Vagner FerreiraVagner Ferreira
Vagner Ferreira
Ehsan ForootanEhsan Forootan
Ehsan Forootan
KHKhandu
Khandu
SASamuel Andam-Akorful
Samuel Andam-Akorful
XHX.F. He
X.F. He
Quantifying the amount of precipitation and its uncertainty is a challenging task all over the world, particularly over the African continent, where rain gauge (RG) networks are poorly distributed. In recent decades, several satellite remote sensing (SRS)‐based precipitation products have become available with reasonable spatial and temporal resolutions to be applied in hydrological and climate studies. However, uncertainties of these products over Africa are largely unknown. In this study, the generalized ‘three‐cornered‐hat’ (TCH) method is applied to estimate uncertainties of gridded precipitation products over the entire African continent, without being dependent to the choice of a reference dataset. Six widely used SRS‐based precipitation products (at monthly scales) were evaluated over the entire continent during the period of 2003–2010. The TCH results are further compared to those of the classical evaluation using the Global Precipitation Climatology Centre (GPCC) over entire Africa, as well as to the RG observations over the Greater Horn of Africa (GHA). Overall, for the study period (2003–2010), the TCH results indicate that the RG‐merged products contain smaller error amplitudes compared to the satellite‐only products, consistent with the GPCC‐based evaluation. A multiple comparison procedure ranking, which was applied based on signal‐to‐noise ratios (SNRs), indicated that PERSIANN contains the highest SNR and thus suitable over most of Africa, followed by ARCv2, TRMM, CMORPH, TAMSAT, and GSMaP. To extract the main spatio‐temporal variability of rainfall over Africa, complex empirical orthogonal function technique was applied, from which the extracted patterns of GPCC, TRMM, PERSIANN, and ARCv2 were found to be similar but different from those of TAMSAT, CMORPH, and GSMaP. Finally, the TCH and RG‐based validation methods were found to provide similar evaluations for the SRS‐only products (CMORPH and GSMaP) over GHA, with CMORPH emerging to be the most suitable product, consistent with previous studies.

1 January 2014 in Remote Sensing of Environment
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Journal Article
Closed access
Ehsan ForootanEhsan Forootan
Ehsan Forootan
RRR. Rietbroek
R. Rietbroek
JKJ. Kusche
J. Kusche
MSM.A. Sharifi
M.A. Sharifi
Joseph L. AwangeJoseph L. Awange
Joseph L. Awange
JFJames Famiglietti
James Famiglietti

7 July 2007 in Water Resources Management
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Journal Article
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Joseph L. AwangeJoseph L. Awange
Joseph L. Awange
MSMohammad A. Sharifi
Mohammad A. Sharifi
GOGodfrey Ogonda
Godfrey Ogonda
JWJens Wickert
Jens Wickert
EGErik W. Grafarend
Erik W. Grafarend
MOMonica A. Omulo
Monica A. Omulo