Identification of extreme climatic events using SMOS

Soil moisture (SM) is a crucial parameter in the hydrological cycle. SM wet and dry trends help to identify extreme weather events, with a rapid increase in SM suggesting heavy rainfall or flood events and a significant or prolonged decrease in SM representing drought events. SMOS and SMAP remote sensing satellites provide surface SM data globally. The surface SM is highly variable in terms of space and time. In contrast, root zone soil moisture (RZSM) is stable and retains long-term information, making it a better indicator of prolonged drought/wet conditions. In this context, SMOS RZSM is computed from the SMOS surface SM using a simple physical model to integrate surface SM information to a root zone. The study benefits from the availability of long-term series data of the SMOS RZSM on a global scale from 2010 to 2023 (approximately 14 years). Then, the SM index is developed using long-time series data of the SMOS RZSM for a better understanding of the distribution of wet and dry SM and its link to extreme events. The study primarily focuses on Australia and Europe. The results show that the developed SMOS SM index captures heavy rainfall/flood and drought conditions. The analysis determines the occurrence of floods due to La Niña and El Niño effects over Australia and the existence of drought in Europe due to the North Atlantic oscillation. This study can help to understand the interconnected factors that influence extreme climatic conditions, ranging from natural climatic phenomena to human-induced activities.