Seventy-five years of weather observations in India, when plotted on a graph, resemble the cardiogram of a vast organism. Instead of a single steady pulse, there are fifteen different lines, each with its own rhythm. Somewhere the heartbeat is as steady as a sleeping person's, while elsewhere it falters, as if after a quick run. The scientists decided not just to measure the average temperature at these points, but to understand how the very nature of the pulse changes: whether it becomes more predictable or, conversely, more chaotic.
To do this, they took temperature and humidity data from 1948 to 2022 at 15 locations covering all of India's climate zones, from the cold deserts of Ladakh to the humid tropics of Kochi. Each data point was transformed into a state in an abstract space where nearby states mean similar weather. Then, moving through time with a window of about seven years, they watched how often the weather returned to previously seen states. If it returns frequently and regularly, the dynamics are predictable, like a pendulum. If rarely and erratically, like Brownian motion.
The results were unexpected. Nearly all 15 locations experienced a shift toward more chaotic dynamics between 1972 and 1979. During those years, there were strong El Niño events in 1972–73 and La Niña in 1973–76, warm and cold currents off the coast of Peru that affect weather worldwide. India's climate, like a sensitive orchestra, fell out of rhythm under the influence of these distant events. After 2000, the dynamics became more regular again, as if the orchestra had found its former tempo. For humidity, however, the picture is different: before 1970, regularity prevailed, then scattered shifts began, and clusters formed differently.
The work shows that climate shifts are not just changes in temperature or humidity, but a restructuring of the very nature of variability. Understanding climate risks requires considering not only geography but also the nonlinear links between the atmosphere, ocean, and land. Although the application of the results is still limited, they provide a methodological guide for analyzing climate dynamics in other countries with monsoon circulation.
Let's return to the cardiogram. Now it is clear that India's climate does not have a single pulse but a whole network of rhythms that occasionally synchronize or diverge. And if we want to know when to expect arrhythmia, we need to listen not to average values but to the rhythm itself.
The analysis window of 5000 time steps corresponds to about 7 years—comparable to the typical period of El Niño. This choice allowed capturing an entire ENSO cycle within one window and seeing its influence on dynamics.