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AIMS Environmental Science

2017, Volume 4, Issue 4: 596-620. doi: 10.3934/environsci.2017.4.596
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Evaluation of ERA-Interim, MERRA, NCEP-DOE R2 and CFSR Reanalysis precipitation Data using Gauge Observation over Ethiopia for a period of 33 years

  • Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India.
  • Received: 01 April 2017 Accepted: 28 August 2017 Published: 13 September 2017

  • The vital demand of reliable climatic and hydrologic data of fine spatial and temporal resolution triggered the employment of reanalysis datasets as a surrogate in most of the hydrological modelling exercises. This study examines the performance of four widely used reanalysis datasets: ERA-Interim, NCEP-DOE R2, MERRA and CFSR, in reproducing the spatio-temporal characteristics of observed daily precipitation of different stations spread across Ethiopia, East Africa. The appropriateness of relying on reanalysis datasets for hydrologic modelling, climate change impact assessment and regional modelling studies is assessed using various statistical and non-parametric techniques. ERA-Interim is found to exhibit higher correlation and least root mean square error values with observed daily rainfall, which is followed by CFSR and MERRA in most of the stations. The variability of daily precipitation is better captured by ERA, CFSR and MERRA, while NCEP-DOE R2 overestimated the spread of the precipitation data. While ERA overestimates the probability of moderate rainfall, it is seemingly better in capturing the probability of low rainfall. CFSR captures the overall distribution reasonable well. NCEP-DOE R2 appears to be outperforming others in capturing the probabilities of higher magnitude rainfall. Climatological seasonal cycle and the characteristics of wet and dry spells are compared further, where ERA seemingly replicates the pattern more effectively. However, observed rainfall exhibits higher frequency of short wet spells when compared to that of any reanalysis datasets. MERRA relatively underperforms in simulating the wet spell characteristics of observed daily rainfall. CFSR overestimates the mean wet spell length and mean dry spell length. Spatial trend analysis indicates that the northern and central western Ethiopia show increasing trends, whereas the Central and Eastern Ethiopia as well as the Southern Ethiopia stations show either no trend or decreasing trend. Overall, ERA-Interim and CFSR are better in depicting various characteristics of daily rainfall in Ethiopian region.

    Citation: Tewodros Woldemariam Tesfaye, C.T. Dhanya, A.K. Gosain. Evaluation of ERA-Interim, MERRA, NCEP-DOE R2 and CFSR Reanalysis precipitation Data using Gauge Observation over Ethiopia for a period of 33 years[J]. AIMS Environmental Science, 2017, 4(4): 596-620. doi: 10.3934/environsci.2017.4.596

    Related Papers:

  • The vital demand of reliable climatic and hydrologic data of fine spatial and temporal resolution triggered the employment of reanalysis datasets as a surrogate in most of the hydrological modelling exercises. This study examines the performance of four widely used reanalysis datasets: ERA-Interim, NCEP-DOE R2, MERRA and CFSR, in reproducing the spatio-temporal characteristics of observed daily precipitation of different stations spread across Ethiopia, East Africa. The appropriateness of relying on reanalysis datasets for hydrologic modelling, climate change impact assessment and regional modelling studies is assessed using various statistical and non-parametric techniques. ERA-Interim is found to exhibit higher correlation and least root mean square error values with observed daily rainfall, which is followed by CFSR and MERRA in most of the stations. The variability of daily precipitation is better captured by ERA, CFSR and MERRA, while NCEP-DOE R2 overestimated the spread of the precipitation data. While ERA overestimates the probability of moderate rainfall, it is seemingly better in capturing the probability of low rainfall. CFSR captures the overall distribution reasonable well. NCEP-DOE R2 appears to be outperforming others in capturing the probabilities of higher magnitude rainfall. Climatological seasonal cycle and the characteristics of wet and dry spells are compared further, where ERA seemingly replicates the pattern more effectively. However, observed rainfall exhibits higher frequency of short wet spells when compared to that of any reanalysis datasets. MERRA relatively underperforms in simulating the wet spell characteristics of observed daily rainfall. CFSR overestimates the mean wet spell length and mean dry spell length. Spatial trend analysis indicates that the northern and central western Ethiopia show increasing trends, whereas the Central and Eastern Ethiopia as well as the Southern Ethiopia stations show either no trend or decreasing trend. Overall, ERA-Interim and CFSR are better in depicting various characteristics of daily rainfall in Ethiopian region.


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