Climate Seasonality of Tropical Evergreen Forest Region

Abstract

Climatic seasonality has lacked research attention in terms of global tropical forests, where it impacts vegetation productivity, biodiversity, and hydrological cycles. This study employs two methods—climatological anomalous accumulation (CAA) and potential evapotranspiration (PET) threshold—to detect the climatic seasonality of global tropical forests, including the onset and duration of wet seasons. Spatial clustering based on the length of the wet season is used to delineate smaller regions within the tropical forest areas to observe their precipitation patterns. The results show that these methods effectively reveal more homogeneous regions and their respective rainfall patterns. In particular, we found that the wet season in Amazon forests detected by the CAA method is more uniform in space than the PET threshold, but the global tropical forest regions divided by the CAA method on average contain more complex climates than the PET threshold. Moreover, the year-round abundant precipitation in Southeast Asia, which is strongly influenced by monsoons, presents challenges for wet season detection. Overall, this work provides an objective perspective for understanding the climatic seasonality changes in tropical forests and lays a scientific foundation for future forest management and the development of adaptation strategies to global climate change.