Evaluation of daily gridded meteorological datasets over the Niger Delta region of Nigeria and implication to water resources management

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Abstract

Hydro-climatological study is difficult in most of the developing countries due to the paucity of monitoring stations. Gridded climatological data provides an opportunity to extrapolate climate to areas without monitoring stations based on their ability to repli-cate the Spatio-temporal distribution and variability of observed datasets. Simple cor-relation and error analyses are not enough to predict the variability and distribution of precipitation and temperature. In this study, the coefficient of correlation (R2), Root mean square error (RMSE), mean bias error (MBE) and mean wet and dry spell lengths were used to evaluate the performance of three widely used daily gridded precipitation, maximum and minimum temperature datasets from the Climatic Research Unit (CRU), Princeton University Global Meteorological Forcing (PGF) and Climate Fore-cast System Reanalysis (CFSR) datasets available over the Niger Delta part of Nigeria. The Standardised Precipitation Index was used to assess the confidence of using grid-ded precipitation products on water resource management. Results of correlation, er-ror, and spell length analysis revealed that the CRU and PGF datasets performed much better than the CFSR datasets. SPI values also indicate a good association between station and CRU precipitation products. The CFSR datasets in comparison with the other data products in many years overestimated and underestimated the SPI. This indicates weak accuracy in predictability, hence not reliable for water resource man-agement in the study area. However, CRU data products were found to perform much better in most of the statistical assessments conducted. This makes the methods used in this study to be useful for the assessment of various gridded datasets in various hy-drological and climatic applications.
Original languageEnglish
Article number1
Pages (from-to)21-39
Number of pages19
JournalAtmospheric and Climate Sciences
Volume10
Issue number1
Early online date23 Dec 2019
DOIs
Publication statusPublished - 1 Jan 2020

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Keywords

  • standardised precipitation index SPI
  • climate forecast system reanalysis
  • climate research
  • Niger Delta
  • Hydro-climatology

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