In situ data in West Africa are scarce,and reanalysis datasets could be an alternative source to alleviate the problem of data availability.Nevertheless,because of uncertainties in numerical prediction models and assi...In situ data in West Africa are scarce,and reanalysis datasets could be an alternative source to alleviate the problem of data availability.Nevertheless,because of uncertainties in numerical prediction models and assimilation methods,among other things,existing reanalysis datasets can perform with various degrees of quality and accuracy.Therefore,a proper assessment of their shortcomings and strengths should be performed prior to their usage.In this study,we examine the performance of ERA5 and ERA-interim(ERAI)products in representing the mean and extreme climates over West Africa for the period 1981-2018 using observations from CRU and CHIRPS.The major conclusion is that ERA5 showed a considerable decrease in precipitation and temperature biases and an improved representation of inter-annual variability in much of western Africa.Also,the annual cycle is better captured by ERA5 in three of the region’s climatic zones;specifically,precipitation is well-reproduced in the Savannah and Guinea Coast,and temperature in the Sahel.In terms of extremes,the ERA5 performance is superior.Still,both reanalyses underestimate the intensity and frequency of heavy precipitations and overestimate the number of wet days,as the numerical models used in reanalyses tend to produce drizzle more often.While ERA5 performs better than ERAI,both datasets are less successful in capturing the observed long-term trends.Although ERA5 has achieved considerable progress compared to its predecessor,improved datasets with better resolution and accuracy continue to be needed in sectors like agriculture and water resources to enable climate impact assessment.展开更多
文摘In situ data in West Africa are scarce,and reanalysis datasets could be an alternative source to alleviate the problem of data availability.Nevertheless,because of uncertainties in numerical prediction models and assimilation methods,among other things,existing reanalysis datasets can perform with various degrees of quality and accuracy.Therefore,a proper assessment of their shortcomings and strengths should be performed prior to their usage.In this study,we examine the performance of ERA5 and ERA-interim(ERAI)products in representing the mean and extreme climates over West Africa for the period 1981-2018 using observations from CRU and CHIRPS.The major conclusion is that ERA5 showed a considerable decrease in precipitation and temperature biases and an improved representation of inter-annual variability in much of western Africa.Also,the annual cycle is better captured by ERA5 in three of the region’s climatic zones;specifically,precipitation is well-reproduced in the Savannah and Guinea Coast,and temperature in the Sahel.In terms of extremes,the ERA5 performance is superior.Still,both reanalyses underestimate the intensity and frequency of heavy precipitations and overestimate the number of wet days,as the numerical models used in reanalyses tend to produce drizzle more often.While ERA5 performs better than ERAI,both datasets are less successful in capturing the observed long-term trends.Although ERA5 has achieved considerable progress compared to its predecessor,improved datasets with better resolution and accuracy continue to be needed in sectors like agriculture and water resources to enable climate impact assessment.
