Abstract
Abstract. Evapotranspiration (ET) from tropical forests serves as a critical moisture source for regional and global climate cycles. However, the magnitude, seasonality, and interannual variability of ET in the Congo Basin remain poorly constrained due to a scarcity of direct observations, despite the Congo being the second-largest river basin in the world and containing a vast region of tropical forest. In this study, we applied a water balance model to an array of remotely sensed and in situ datasets to produce monthly, basin-wide ET estimates spanning April 2002 to November 2016. Data sources include water storage changes estimated from the Gravity Recovery and Climate Experiment (GRACE) satellites, in situ measurements of river discharge, and precipitation from several remotely sensed and gauge-based sources. An optimal precipitation dataset was determined as a weighted average of interpolated data by Nicholson et al. (2018), Climate Hazards InfraRed Precipitation with Station data version 2 (CHIRPS2) , and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record product (PERSIANN-CDR), with the relative weights based on the error magnitudes of each dataset as determined by triple collocation. The resulting water-balance-derived ET (ETwb) features a long-term average that is consistent with previous studies (117.2±3.5 cm yr−1) but displays greater seasonal and interannual variability than seven global ET products. The seasonal cycle of ETwb generally tracks that of precipitation over the basin, with the exception that ETwb is greater in March–April–May (MAM) than in the relatively wetter September–October–November (SON) periods. This pattern appears to be driven by seasonal variations in the diffuse photosynthetically active radiation (PAR) fraction, net radiation (Rn), and soil water availability. From 2002 to 2016, Rn, PAR, and vapor-pressure deficit (VPD) all increased significantly within the Congo Basin; however, no corresponding trend occurred in ETwb. We hypothesize that the stability of ETwb over the study period despite sunnier and less humid conditions may be due to increasing atmospheric CO2 concentrations that offset the impacts of rising VPD and irradiance on stomatal water use efficiency (WUE).
Highlights
The Congo Basin in central Africa is the second-largest river basin in the world and supports one of Earth’s three major humid tropical forest regions (Alsdorf et al, 2016)
The triple collocation (TC) results indicate that NIC131-gridded, a Congo-specific gauge-based dataset designed using meteorological stations absent from the Global Precipitation Climatology Centre (GPCC) network and a principal-component-based statistical approach, is the best currently available P dataset for the Congo Basin after 2002 (Nicholson et al, 2018)
This study leverages several remotely sensed and gaugebased precipitation datasets, river gauge data, and terrestrialwater-storage anomalies from Gravity Recovery and Climate Experiment (GRACE) to produce ET estimates for the Congo Basin in central Africa at the monthly timescale. This technique has been successfully applied to the Amazon Basin in recent years, but to the authors’ knowledge it has not yet been used in the Congo Basin except as part of global-scale reviews of major river basins
Summary
The Congo Basin in central Africa is the second-largest river basin in the world and supports one of Earth’s three major humid tropical forest regions (Alsdorf et al, 2016). 24 % to 39 % of evapotranspiration (ET) from the Congo Basin is recycled as local rainfall (Dyer et al, 2017), and model simulations indicate changes in ET within the basin affect moisture cycling across the African continent (Van Der Ent and Savenije, 2011; Bell et al, 2015; Sorí et al, 2017). Understanding the magnitude, variability, and drivers of ET in the Congo Basin is crucial for studying the climate systems of central Africa and the global tropics, especially because significant environmental shifts have already been reported within the basin. Burnett et al.: Data-driven estimates of evapotranspiration and its controls in the Congo Basin
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