A newly devised algorithm powered by Artificial Intelligence can help increase the predictability of the Indian Summer Monsoons (ISMR) 18 months ahead of the season.
- The algorithm called predictor discovery algorithm (PDA) made using a single ocean-related variable could facilitate skillful forecast of the ISMR in time for making effective agricultural and other economic plans for the country.
- While researchers have well established the scientific basis for ISMR predictability and made significant advances over the past century in understanding the variability and predictability of ISMR, the skillful prediction of ISMR even one month in advance has remained a major challenge.
- Neither the potential (theoretically possible) skill (correlation between the predicted and observed ISMR) and the actual skill of ISMR forecast are available at longer lead times–6, 12, 18, 24- months ahead of the season.
- Traditionally, researchers select a predictor of ISMR based on the maximum correlation of an atmospheric or oceanic variable with ISMR over a region of the globe. Such technique restricts in the realization of the true potential predictability of ISMR as it accounts for one predictor over a particular region at a time.
- Scientists at the Institute of Advanced Study in Science and Technology (IASST) along with their collaborators have found that the widely used sea surface temperature (SST) is inadequate for calculation of long-lead prediction of ISMR.
- They devised a predictor discovery algorithm (PDA) that generates predictor at any lead month by projecting the ocean thermocline depth (D20) over the entire tropical belt between 1871 and 2010 onto the correlation map between ISMR and D20 over the same period.
