Forget modern weather prediction models, horoscopes are taking over. Weathermen are blending their meterological data with astrological kundalis to predict rainfall. Indian Meteorological Department (IMD) and Central Research Institute for Dryland Agriculture (CRIDA), Hyderabad, have kick-started a pilot project that will blend well-proven scientific meteorological data, backed by mathematical calculations, with astronomical data for weather prediction.
Visibly excited about this new field called astro-meteorology, CRIDA director YS Ramakrishna says, “Agricultural practices are largely weather-sensitive. So far, the relationship between weather events across the world had to be correlated with the local weather conditions over the past century that led to a scientific way of weather forecasting. Closer home, since 1990s, scientists have been making medium range weather predictions with moderate success. However, with the annual monsoon phenomenon beginning to behave abnormally during the past few years, their predictions have been going haywire.” This, despite the fact that improved methods have been generated and a 16 parameter model been used by IMD for predicting long-range rainfall .
So far, modern science has been at crossroads when it comes to weather prediction. Moreover, a major problem arises when prediction has to be made for smaller regions, especially to understand the local weather conditions, mainly the rainfall, thermal and humidity, etc. Keeping in mind the systematic changes taking place in the tropical circulation pattern, new parameters have been added and a new prediction model developed by IMD.
The new methodology is interesting as scientists attempt to arrive at the rainfall prediction based on star positions. Surprised, but let’s look at our traditional astronomical knowledge wherein, astronomical data plays a major decision maker. Can this data, derived based on the star positions, used for predicting rainfall? “There is accuracy rate of 60-70% and there is always a relevance of ancient wisdom for weather forecasting for improving agro-advisories,’’ Ramakrishna points out.
A peep into the past throws up interesting reading too. During the Vedic age, when sage Varahamihira wrote two important works — Panchasiddhantika and Brihat Samhita — it goes without saying that there existed a traditional wisdom for weather prediction. In fact, the prediction of sunrise and sunset is followed till date.
Unraveling the intricacies of astronomy further, Gayatri astronomy expert Devi Vasudev says, when the Sun traverses star Krittika, the summer heat gets intensified as this star is associated with Sun, the fire god in Vedic texts. And this is precisely the time, when the mercury shoots up. The stars are ruled by natural elements and it is believed that movement of Sun and Saturn in conjunction imply that winter is ahead. Similarly, dry weather will prevail if Sun and Jupiter conjoin, while with Venus rainfall is round the corner, and so on.
IMD scientists inform that a pilot project has been initiated by the Gujarat government to blend the astronomical data with scientifical data for better rainfall prediction. “The potential for Jyotisha to forecast monsoons, if explored, can help to a large extent in improving accuracy based on modern methods,” Vasudev says in a theme paper presented in a recent meeting at CRIDA. The paper highlights that Sun’s entry into a constellation changes the weather pattern and solar ingress into Scorpio has a bearing on monsoon.
Mr Ramakrishna says that these studies point out towards the long-term prediction of rainfall based on astrological parameters that are generated by careful and systematic observation and experience. “These are in no manner inferior to the research models used by modern scientists,” he adds. In no uncertain terms, the next move by IMD and CRIDA is to work together to see how far the data can be blended to draw on the strengths of each segment.
A working group has been formed along with IMD and state agricultural universities and CRIDA is the nodal agency to bring out a medium range prediction model and blend it with latest techniques. Its time to trust the weatherman, at least for the time being.