The Fine Margins of Thunderstorm Inferences

During thunderstorm season a common feedback received often especially from those who do not follow weather regularly is “Weather Bloggers just give stories and it never rains as they say”  Their ire at times is also directed towards IMD too with some practical jokes like when ever IMD says it will rain we can be assured of  no rains that day.

Weather Models typically work on equations with a lot of observational data fed into super computers to estimate weather patterns based on how various factors like Wind / Clouding / Sunshine etc  are expected to behave.  Sometimes in the absence of real time observational data estimates are used in these equations, a small variance here could mean a variance that will progressively become larger as the time frame increases  leading to larger errors.

While its too easy to say the common people do not understand the difficulties of weather inferences and just complain about no rains without giving thoughts to the background work being put in. To an extent the weather bloggers of Chennai like Pradeep John aka Tamil Nadu Weather Man have made a lot of efforts to provide simple explanations to various weather phenomenons for the common people to relate better.  It is a long journey and possibly going to be slow learning but the efforts will surely create a more weather aware community.

If one were to look at yesterday’s context many models estimated thunderstorms to happen over South Interior Karnataka, South AP & parts of North TN.  The models estimated the turbulent zone to be at the latitudes south of Bengaluru while in reality instability happened North of Bengaluru, a shift of about 100 – 150 kms, meant the entire band of thunderstorms climbed North by the same distance leading to a complete change in rainfall pattern compared to what model estimated.  This pattern was though picked up by models that were available on public domain late evening yesterday while the COMK post was made about 12 hours before based on available resources then by which time the events were actually unfolding in front of our eyes.

Just like all of you Weather Bloggers are also on a constant learning curve may be slightly ahead of you due to our passion for weather.