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Climatic Change

, Volume 124, Issue 4, pp 805–819 | Cite as

Precipitation variability and trends in Ghana: An intercomparison of observational and reanalysis products

  • R. ManzanasEmail author
  • L. K. Amekudzi
  • K. Preko
  • S. Herrera
  • J. M. Gutiérrez
Article

Abstract

Inter-annual variability and trends of annual/seasonal precipitation totals in Ghana are analyzed considering different gridded observational (gauge- and/or satellite-based) and reanalysis products. A quality-controlled dataset formed by fourteen gauges from the Ghana Meteorological Agency (GMet) is used as reference for the period 1961–2010. Firstly, a good agreement is found between GMet and all the observational products in terms of variability, with better results for the gauge-based products—correlations in the range of 0.7–1.0 and nearly null biases—than for the satellite-gauge merged and satellite-derived products. In contrast, reanalyses exhibit a very poor performance, with correlations below 0.4 and large biases in most of the cases. Secondly, a Mann-Kendall trend analysis is carried out. In most cases, GMet data reveal the existence of predominant decreasing (increasing) trends for the first (second) half of the period of study, 1961–1985 (1986–2010). Again, observational products are shown to reproduce well the observed trends—with worst results for purely satellite-derived data—whereas reanalyses lead in general to unrealistic stronger than observed trends, with contradictory results (opposite signs for different reanalyses) in some cases. Similar inconsistencies are also found when analyzing trends of extreme precipitation indicators. Therefore, this study provides a warning concerning the use of reanalysis data as pseudo-observations in Ghana.

Keywords

Rainfall Regime Reanalysis Product Gridded Product Observational Product Rain Gauge Observation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This study was supported by the EU project QWeCI (Quantifying Weather and Climate Impacts on health in developing countries), funded by the European Commission Seventh Framework Research Programme under the grant agreement 243964. Additionally, the authors are very thankful to GMet (especially to Mr. Charles Yorke) for providing the gauge data. L. K. Amekudzi is also grateful to the Abdus Salam International Centre for Theoretical Physics (ICTP) for granting a sixty-six days research fellow visit including the use of its facilities. Finally, the authors want to thank the three anonymous reviewers for their detailed comments which have greatly helped to improve the manuscript.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • R. Manzanas
    • 1
    Email author
  • L. K. Amekudzi
    • 2
  • K. Preko
    • 2
  • S. Herrera
    • 3
  • J. M. Gutiérrez
    • 1
  1. 1.Grupo de MeteorologíaInstituto de Física de Cantabria, CSIC-Univ. de CantabriaSantanderSpain
  2. 2.Meteorology and Climate Science Unit, Department of PhysicsKwame Nkrumah University of Science and Technology (KNUST)KumasiGhana
  3. 3.Grupo de Meteorología, Departamento de Matemática Aplicada y Ciencias de la ComputaciónUniv. de Cantabria, Avda. de los Castros s/nSantanderSpain

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