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

Inter-annual variability and trends of annual/seasonal precipitation totals in Ghana are analyzed considering different gridded observational (gaugeand/or satellite-based) and reanalysis products. A qualitycontrolled 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 satellitegauge 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 R. Manzanas ( ) · J. M. Gutiérrez Grupo de Meteoroloǵıa. Instituto de F́ısica de Cantabria, CSIC-Univ. de Cantabria. Avda. de los Castros, s/n, 39005 Santander, Spain E-mail: [email protected] L. K. Amekudzi · K. Preko Meteorology and Climate Science Unit. Dept. of Physics, Kwame Nkrumah Univ. of Science and Technology (KNUST., Kumasi, Ghana S. Herrera Grupo de Meteoroloǵıa. Dpto. Matemática Aplicada y Ciencias de la Computación, Univ. de Cantabria. Avda. de los Castros, s/n, 39005 Santander, Spain 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.