AIML based Nowcasting of thunderstorm and lightning using atmospheric observation including multiple radars, satellite, lightning and model data.

The receipts 🧾

Every red flag on this statement, in full. These are the four places it bites.

1. Exhibit A

   Bulk lightning location data for India is not openly distributed, so the lightning half of the statement cannot be trained or verified properly and you will be inferring it from convective proxies — say so rather than implying you predicted lightning

2. It gets worse

   Advection of the current radar or satellite field is a surprisingly strong nowcasting baseline at short lead times, and a model that merely matches it has added nothing

3. Still reading?

   Convective events are rare in a grid-and-time sense, so a model optimised on accuracy will learn to predict no storm and score well — use categorical scores that penalise misses, not accuracy

4. And the finisher

   The description contains nothing but the title, so two teams could build entirely different systems and both be responsive, which puts the burden of defining success on you

The damage report 📉

Every score this statement earned, and what each one actually costs you.

• Feasibility

  3/5

  Buildable. Not comfortably. There is a week in here you have not planned for yet.

  Geostationary satellite infrared and water-vapour imagery over India is freely available at high cadence and is enough to nowcast convective development on its own, but the radar products are only selectively public and bulk lightning location data for India is not openly distributed, so the lightning half of the statement rests on observations you probably cannot obtain.

• Innovation scope

  4/5

  There is something genuinely new here. Do not bury it under another dashboard.

  The description is the title repeated, prescribing no architecture, region, grid, lead time or output format, so the entire formulation of the nowcasting problem is yours.

• Clarity

  1/5

  Nobody is sure what is being asked, quite possibly including the people who asked it.

  A verbatim repetition of the title with no background, no requirement, no lead time, no resolution, no data source and no accuracy criterion — the statement provides no information about the deliverable beyond naming the task.

• Acceptance potential

  3/5

  Middle of the pack. This statement will not win the room for you — you will have to.

  Nowcasting is genuinely doable from free satellite imagery, the verification methodology is well established so you can prove skill against a fair baseline, and the safety case for lightning warning in India is unarguable — but the lightning observations the statement names are not openly available, so you will be nowcasting convection and inferring lightning rather than doing what was asked.

• Effort

  Heavy

  Heavy. Somebody on this team is not sleeping in week three. Pick who, on purpose.

  Building an aligned multi-source image sequence archive, training a spatiotemporal model, implementing meaningful baselines and constructing a proper categorical verification harness is four pieces, with the data alignment across sources being the slowest.

• Demo-ability

  Medium

  Demoable, if you rehearse it. Nobody rehearses it.

  A forecast loop playing beside the observed sequence is a good and honest visual, but convective nowcasting output is a probability field rather than a crisp answer, and its quality is only apparent to someone who understands what the baseline would have produced.

• Data

  None supplied

  No dataset comes with this one, so every accuracy figure you quote is a number about labels you invented.

  Nothing is provided with the statement. You are sourcing, cleaning and labelling it yourself, and that work is invisible in the demo but very visible in the questions.

The demo they will have already seen 🪞

Somewhere around 140–330 teams are heading here, and the description is doing the choosing for most of them. They will read the same brief, reach the same architecture, and build a version of the same demo you are planning. Being correct is the floor. If your five minutes could be swapped with the team before you and nobody in the room would notice, you have not picked badly — you have built predictably, which costs exactly the same and hurts more.

What survives 🛡️

The ground worth standing on when the questions start.

• Geostationary satellite imagery over India is free and frequent enough to nowcast convection on its own, so the project is viable even without radar or lightning access
• Nowcasting has a well-established verification methodology with standard categorical scores, so you can demonstrate skill rigorously rather than showing a plausible-looking animation
• Optical flow advection is a genuinely strong and fair baseline, and beating it convincingly is a real result that a meteorological panel will recognise immediately