Soil Moisture as an Indicator for Thunderstorm Prediction
A new study revealed how soil moisture can serve as an early warning signal for thunderstorms that lead to flash floods and landslides. This is particularly relevant in regions like India, West and Central Africa, South America, and parts of the United States and China.
What are Mesoscale Convective Systems?
Mesoscale convective systems (MCS) are large clusters of thunderstorms. They can cover areas larger than England and travel hundreds of kilometres. MCSs are responsible for rainfall, accounting for 50 to 90 per cent of total precipitation in tropical regions. These storms can cause extensive damage to life, livestock, and infrastructure.
Soil Moisture as a Predictive Tool
Traditionally, storm forecasting has focused on atmospheric data. However, this study shifts the focus to land surface conditions, especially soil moisture levels. The researchers found that changes in soil moisture could be detected two to five days before storm formation. This advance notice can provide critical lead time for early warnings in vulnerable areas.
Impact of Soil Moisture on Storm Intensity
The research indicates that contrasting soil moisture levels over large distances can affect storm dynamics. Variations in moisture can increase rainfall by 10 to 30 per cent, depending on the storm’s size and location. Larger contrasts in moisture content lead to changes in wind direction and speed, which can enhance storm power and rainfall distribution.
Regional Hotspots for MCS Activity
The study identified specific regions as hotspots for MCS activity. These include West and Central Africa, northern India, Argentina, China, and the United States Great Plains. A notable example is the March 2024 thunderstorm in West Bengal, which resulted in substantial damage and loss of life.
Early Warning Systems
An early warning system integrates hazard monitoring, forecasting, and disaster risk assessment. According to the United Nations Office for Disaster Risk Reduction, such systems enable communities and governments to act promptly, reducing risks associated with severe weather events. The study puts stress on the need for improved forecasting methods that include land surface conditions.
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