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 (gauge- and/or satellite-based) and reanalysis products. A quality-controlled dataset formed by fourteen gauges from the Ghana Meteorological Agency (GMet) is...
| Authors: | , , , , |
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| Format: | article |
| Status: | Versión aceptada para publicación |
| Publication Date: | 2014 |
| Country: | España |
| Institution: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repository: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/93817 |
| Online Access: | http://hdl.handle.net/10261/93817 |
| Access Level: | Open access |
| Keyword: | Precipitation Ghana Gridded observations Reanalysis Variability Trends |
| Summary: | 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 ones. Contrarily, 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. GMet data reveals 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 warns on the use of reanalysis data as pseudo-observations in Ghana. |
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