Assessing reanalysis data for understanding rainfall climatology and variability over Central Equatorial Africa

Wenjian Hua,Minhua Qin,Liming Zhou,Sharon E Nicholson,Haishan Chen

doi:10.1007/s00382-018-04604-0

Abstract

Understanding the rainfall climatology and variability over Central Equatorial Africa (CEA) has largely been hampered by the lack of adequate in situ observations and meteorological stations for the last three decades. Large differences and uncertainties among several observational and reanalysis data sets and various climate model simulations present another big challenge. This study comprehensively assesses the currently widely used reanalysis products based on quality-controlled radiosonde observations and a new gauge-based rainfall data set, NIC131, in order to identify the “best” reanalysis products available over CEA. Among the seven reanalysis data sets (i.e., 20CR, CFSR, ERA-Interim, JRA-55, MERRA2, NCEP-1 and NCEP-2), MERRA2 is closest to NIC131 in reproducing the mean climatology and interannual variability and has the smallest biases and root-mean-square error (RMSE) in describing the observed wind fields in the lower- and middle-troposphere, and the two NCEP reanalyses can better capture geopotential height fields than the other reanalyses. Overall, the reanalyses capture the major features of the rainfall seasonal cycle and the seasonal evolution in the reference data but demonstrate an evident spread of spatiotemporal characteristics. By examining the moisture transport, we find that the differences in the lower- and middle-tropospheric circulation can reasonably explain the differences in the rainfall climatology among the reanalyses. Considering the large differences in horizontal and vertical wind fields among the seven reanalyses, we need to use the best reanalysis wind and moisture fields to explain the observed rainfall and associated circulation changes over CEA.

Highlights

Tropical rainforests influence the transfers of energy, moisture and trace gases with the overlying atmosphere, the hydrologic cycle and carbon storage via various biogeophysical, biogeochemical and biological processes, and have the potential to modulate regional and global climate and carbon sequestration (e.g., Bonan 2008; Humphrey et al 2018)
As the Integrated Global Radiosonde Archive (IGRA) data have many missing records for the period 1980–2014 and include few stations over the Congo Basin, we examine a region over western equatorial Africa with adequate upper air coverage
There are only eleven observation sites to cover the equatorial Africa, the results suggest that National Centers for Environmental Prediction (NCEP)-2 and MERRA2 are better able to capture the HGT and wind fields in the lower troposphere, respectively, than the other reanalyses

Summary

Introduction

Tropical rainforests influence the transfers of energy, moisture and trace gases with the overlying atmosphere, the hydrologic cycle and carbon storage via various biogeophysical, biogeochemical and biological processes, and have the potential to modulate regional and global climate and carbon sequestration (e.g., Bonan 2008; Humphrey et al 2018). As rainfall is the major climatic control on rainforest dynamics and an important component of the hydrological cycle, several studies probed the CEA rainfall patterns and variability using available precipitation data sets and identified large uncertainties among these data sets (Malhi and Wright 2004; Samba et al 2008; Diem et al 2014; Zhou et al 2014). Multiple coupled models disagreed on the locations of maximum rainfall over the Congo Basin and multi-model ensemble means were unable to reproduce the observed rainfall state (Creese and Washington 2016). These observational and modeling studies all point to large uncertainties and difficulties in understanding and modeling the rainfall climatology, patterns and variability over CEA

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