Stanford scientists have warned of significant changes in the patterns of extreme wet and dry events during monsoon that are increasing the risk of drought and flood in central India.
Researchers, including two Indian origin-scientists, show that the intensity of extremely wet spells and extremely dry spells during the South Asian Monsoon season have both been increasing in recent decades.
“We are looking at rainfall extremes that only occur at most a few times a year, but can have very large impact,” said senior author Noah Diffenbaugh, senior fellow at the Stanford Woods Institute for the Environment.
The South Asian Monsoon is an annual wind-driven weather pattern that is responsible for 85 per cent of India’s annual precipitation and is vital for the country’s agricultural sector.
Deepti Singh, lead author of the study, said that rainfall extremes during the months of the monsoon season can be as important as how much total water is received.
For example, during critical crop growth stages, too many days without rain can reduce yields or lead to crop failure, which can reverberate through India’s agriculture-dependent economy.
At the same time, short periods of very heavy rainfall can create humanitarian disasters, such as in 2005, said researchers.
Dr. Diffenbaugh and his team wanted to test whether the pattern of extreme wet and dry “spells” during the monsoon season had changed in recent decades.
Wet and dry spells were defined as three or more consecutive days of extremely high or low rainfall, respectively.
The team compared rainfall data gathered by the Indian Meteorological Department and other sources over a 60-year period.
They used rigorous statistical methods to compare peak monsoon rainfall patterns during two time periods: from 1951 to 1980, and from 1981 to 2011.
The team looked specifically at rainfall during the months of July and August, which is the peak of the South Asian summer monsoon.
The analysis focused on central India, which is the core of the monsoon region and has extremely high population densities.
The team analysed the Indian monsoon data using statistical tools that account for so-called spatial and temporal relationships, which are typically ignored in “classical” or “off-the-shelf” statistical tools that were originally designed for use in the fields of biology, medicine and agriculture.
Such “spatial-temporal dependencies” are particularly important when studying temperature, rainfall and other geophysical phenomena that can change over a daily scale, said Bala Rajaratnam, assistant professor of statistics and of environmental Earth system science.
For example, if it rains today, there’s a higher chance that it will rain tomorrow because a storm system is already in place.
When the team members analysed the Indian monsoon data using their statistical methods, they discovered that although the average total rainfall during the monsoon season has declined, the variability of rainfall during the peak monsoon months has increased.
In particular, the researchers observed increases in the intensity of wet spells and in the frequency of dry spells.
“The statistical techniques show that the changes in these characteristics are robust and that these changes are unlikely to happen purely by chance,” Ms. Singh added.
The finding was published in the journal Nature Climate Change .
