West African Summer Monsoon Precipitation Variability as Represented by Reanalysis Datasets

Kwesi Akumenyi Quagraine,Kwesi Twentwewa Quagraine,Cornelia Klein,Nana Ama Browne Klutse,Francis Nkrumah

doi:10.3390/cli8100111

Abstract

Focusing on West Africa, a region riddled with in situ data scarcity, we evaluate the summer monsoon monthly rainfall characteristics of five global reanalysis datasets: ERA5, ERA-Interim, JRA-55, MERRA2, and NCEP-R2. Their performance in reproducing the West African monsoon (WAM) climatology, interannual variability, and long-term trends for the main monsoon months are compared to gauge-only and satellite products. We further examine their ability to reproduce teleconnections between sea surface temperatures and monsoon rainfall. All reanalyses are able to represent the average rainfall patterns and seasonal cycle; however, regional biases can be marked. ERA5, ERA-Interim, and NCEP-R2 underestimate rainfall over areas of peak rainfall, with ERA5 showing the strongest underestimation, particularly over the Guinea Highlands. The meridional northward extent of the monsoon rainband is well captured by JRA-55 and MERRA2 but is too narrow in ERA-Interim, for which rainfall stays close to the Guinea Coast. Differences in rainband displacement become particularly evident when comparing strong El Niño Southern Oscillation (ENSO) years, where all reanalyses except ERA-Interim reproduce wetter Sahelian conditions for La Niña, while overestimating dry conditions at the coast except for NCEP-R2. Precipitation trends are not coherent across reanalyses and magnitudes are generally overestimated compared to observations, with only JRA-55 and NCEP-R2 displaying the expected positive trend in the Sahel. ERA5 generally outperforms ERA-Interim, highlighting clear improvements over its predecessor. Ultimately, we find the strengths of reanalyses to strongly vary across the region.

Highlights

Understanding precipitation variability over West Africa is important to the population as their economies rely heavily on agriculture to supplement livelihoods, food security, and water availability [1,2]
We used Climatic Research Unit (CRU)-TS4.03 as a reference dataset for comparison with the other observations and the reanalysis datasets for the study period
We examined precipitation characteristics in the monsoon rainfall season (JJAS) for West Africa (Figure 2)

Summary

Introduction

Understanding precipitation variability over West Africa is important to the population as their economies rely heavily on agriculture to supplement livelihoods, food security, and water availability [1,2]. A likely alternative approach to tackling this challenge is to resort to reanalysis datasets In this context, reanalysis datasets represent a global, model-based solution to reconstruct continuous atmospheric fields [8]. Reanalyses are an important source of climate information [9], providing a physically consistent approximation of the state of the atmosphere that allows process-based analyses of rainfall variability and associated atmospheric drivers. It is useful when we want to evaluate rainfall changes but drivers of extreme variability. Even the boundary conditions crucial for a skilful rainfall representation were found to be comparably ill-constrained [7,11,12,13]

Methods

Results

Conclusion