Seasonal Variation of Congo Rainforests from DSCOVR/EPIC and MISR Observations

Abstract:

Knowledge of seasonal variation of tropical rainforests are essential for understanding its response to the climate change. The equatorial Congo rainforest, the second-largest on Earth, however is still lacking of systematic analyses of seasonal variation in forest greenness with strong observational evidences. This poster investigates the seasonality of the Congo rainforest with Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) and Multi-angle Imaging SpectroRadiometer (MISR) datasets. The monthly mean near-infrared (NIR) bidirectional reflectance factor (BRF) from EPIC of 2016-2019 exhibits a bimodal pattern over the Congo forest, which is consistent with the seasonality of leaf area from MODIS LAI (Collection 6) and precipitation from TRMM. Analyses of NIR BRF angular signatures from MISR and EPIC further confirms that more green leaves appear during the wet season compared to the dry season. Variation in the canopy scattering coefficient (CSC) suggests a higher leaf absorption in wet season than in dry season, which is attributed to a higher concentration of chlorophyll and/or dry matter in leaves. This research also demonstrates the complementarity and consistency between DSCOVR/EPIC records and existing data from polar-orbiting satellites in tropical rainforest monitoring, and the CSC will be provided in the upcoming version of DSCOVR/EPIC Vegetation Earth System Data Record (VESDR) science product.