Characterizing Land Cover Impacts on the Responses of Land Surface Phenology to the Rainy Season in the Congo Basin

Knowledge of how rainfall seasonality affects land surface phenology has important implications on understanding ecosystem resilience to future climate change in the Congo Basin. We studied the impacts of land cover on the response of the canopy greenness cycle (CGC) to the rainy season in the Congo Basin on a yearly basis during 2006–2013. Specifically, we retrieved CGC from the time series of two-band enhanced vegetation index (EVI2) acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI). We then detected yearly onset (ORS) and end (ERS) of the rainy season using a modified Climatological Anomalous Accumulation (CAA) method based on the daily rainfall time series provided by the Tropical Rainfall Measurement Mission. We further examined the timing differences between CGC and the rainy season across different types of land cover, and investigated the relationship between spatial variations in CGC and rainy season timing. Results show that the rainy season in the equatorial Congo Basin was regulated by a distinct bimodal rainfall regime. The spatial variation in the rainy season timing presented distinct latitudinal gradients whereas the variation in CGC timing was relatively small. Moreover, the inter-annual variation in the rainy season timing could exceed 40 days whereas it was predominantly less than 20 days for CGC timing. The response of CGC to the rainy season varied with land cover. The lead time of CGC onset prior to ORS was longer in tropical woodlands and forests, whereas it became relatively short in grasslands and shrublands. Further, the spatial variation in CGC onset had a stronger correlation with that of ORS in grasslands and shrublands than in tropical woodlands and forests. In contrast, the lag of CGC end behind ERS was widespread across the Congo Basin, which was longer in grasslands and shrublands than that in tropical woodlands and forests. However, no significant relationship was identified between spatial variations in ERS and CGC end.