IMD Forecasts La Niña But Warns Of Unusually Weak Impact This Winter
Northern India has now come under the influence of the westerlies, winds that bring the winter cold to the northern part of the subcontinent, and noticeable weather shifts across the region can now be felt. As per the Indian Meteorological Department (IMD), the northern Indian subcontinent, which consists of Jammu & Kashmir, Punjab, Himachal Pradesh, and Delhi, is under the influence of fog that can be seen evidently in the mornings, and the average maximum and minimum temperature ranges have also started to decline.
The winter season in the current cycle has been delayed, and the IMD reports that neutral El Niño-Southern Oscillation (ENSO) conditions prevail in the equatorial Pacific, with surface sea temperatures falling below average in the eastern equatorial region. The data also suggest the formation of La Niña in the post-monsoon season.
La Niña is typically known to bring cooler-than-average sea surface temperatures in the equatorial Pacific, which results in more severe winters. The phenomenon usually gains strength between October and February, which in turn leads to much harsher winters and torrential rain, adversely impacting winter agriculture, especially for areas that depend on farming during this season.
This year, though, La Niña is predicted to be unusually feeble. OP Sreejith, head of climate monitoring at IMD, said that because of climate change, the anomaly has not been able to linger with high temperatures. So, this implies that due to the dwindling intensity, it is likely to be warmer than usual over this winter season, especially in the north.
La Niña can only be declared if the Oceanic Niño Index persistently falls into at least -0.5°C, which has not occurred this season so far. Although the US National Oceanic and Atmospheric Administration (NOAA) predicted earlier that mid-year would clearly usher in the La Niña phase, such expectations have been found to be incorrect. According to the latest blog from NOAA, this “spooky weather” actually only brings out the increasing difficulty of predicting ENSO patterns against changing climate dynamics.
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