Air PollutionWeather Coupled Forecasting System (Delhi NCR Focus)
Ministry of Earth Sciences (MoES) · Disaster Management · Software
The science is correct and the coupled model at the centre of it is a research-group undertaking, so you will either not run it or run it once — if you fall back to a statistical forecast, be honest that you did the thing the statement rejected.
What it actually is
Delhi's winter smog is not just a pollution problem or a weather problem but both feeding each other — a temperature inversion traps the particulates near the ground, and the trapped particulates block sunlight and change the weather that would otherwise clear them. Forecasts that treat the two separately get it wrong. The ask is a coupled system that simulates both together and predicts air quality three days out.
What to build
A coupled meteorology-chemistry forecast over the National Capital Region running to seventy-two hours, with two-way feedback between the meteorological state the statement names — temperature, wind and planetary boundary layer height — and the chemical state of particulate matter, ozone and nitrogen oxides, so aerosol loading feeds back into the radiation budget and boundary layer development rather than being carried passively; an emissions treatment representing both the local baseline and the seasonal external contribution from regional crop residue burning; explicit diagnosis of inversion strength as a forecast product in its own right since it is the mechanism that determines whether a spike traps or disperses; and a dashboard presenting the air quality outlook alongside the inversion and plume dispersion picture that explains it.
Smallest thing that wins the room
Run a documented severe smog episode and show the forecast reproducing the observed spike, with the inversion strength diagnostic rising ahead of it and the plume trajectory explaining where the particulate load came from.
How crowded this one gets
A guess, projected from the 2025 statements — the last year where both the submission counts and the winners were published.
Quieter than 41% of the 226 · #134 of 226 by expected field
A normal-sized field. Your idea has to be good, not miraculous.
Why: central ministry statements sat below the average.
This is a guess, not a fact
Nobody has published 2026’s numbers yet. This is an analysed estimate from last year’s pattern, so please do not take it as the truth — check the live counter on the SIH portal before you decide anything. The range covers the middle half of likely outcomes, so one statement in two lands outside it. Entry closes at 500 ideas per statement, so no range goes past that — a statement that reaches the cap fills and shuts rather than drawing an unlimited crowd. The model reads only three things a team can see before choosing — software or hardware, the theme, and what kind of body posted it — and those explain about a quarter of the variation in last year’s field sizes (R² 0.25 on held-out statements). Trust the band more than the number, and the ordering more than either. It cannot see how good your idea is, which is the part that actually decides it.
The scores
The number is the shorthand. The line under it is the reason.
Acceptance potential
2/5The two-way coupled chemistry-meteorology model is the statement's explicit and central requirement and is beyond student compute, so most teams will substitute a statistical air quality forecast trained on station data — which is entirely achievable but is exactly the uncoupled approach the statement opens by rejecting.
Feasibility
2/5The statement explicitly requires a coupled weather-chemistry model with two-way feedback, and running one is a research-group undertaking — it needs an emissions inventory the coupled model can consume, expert configuration, and core-hours well beyond a student allocation for even a single seventy-two-hour forecast over a fine domain.
Innovation scope
2/5The coupled modelling framework is named, the feedback requirement is mandated, the species are listed, the horizon is fixed and the deliverable is specified, so the approach is dictated and what remains is configuration rather than design.
Clarity
4/5The physical mechanism is explained well and correctly, the species to model and the meteorological variables to couple are named individually, and the horizon and deliverables are explicit — though nothing states what forecast accuracy would count as success.
Effort
MassiveConfiguring and running a coupled chemistry-transport model over a nested urban domain, assembling emissions inputs, validating against monitoring stations and building an operational dashboard is a research programme with a computational cost that dominates everything else.
Demo-ability
MediumReproducing a documented smog episode with the inversion diagnostic rising ahead of it is a persuasive and honest result, but you will be showing one hindcast run rather than an operating system, because each run is expensive.
In its favour
- Green flag: The physical argument in the statement is correct and well explained, so the scientific framing of your pitch is already written and defensible
- Green flag: Ground monitoring data for the region is publicly available and dense, so validation against observed concentrations is straightforward and honest
- Green flag: Inversion strength as a standalone forecast diagnostic is genuinely useful, cheap to compute from meteorological fields alone, and is the one deliverable here that a small team can definitely produce well
- Green flag: Air quality in this region is a subject a panel will engage with immediately, so the impact case needs no argument
Against it
- Red flag: Two-way coupled chemistry-meteorology modelling is the stated core and is computationally out of reach — substituting a statistical model trained on station data answers a question the statement explicitly opens by rejecting, so if you do that, say so rather than implying coupling
- Red flag: Emissions inventories are the largest source of error in any air quality model and reliable local inventories for this region are not openly available, so even a correctly configured coupled run inherits that uncertainty
- Red flag: A single seventy-two-hour coupled forecast can consume more compute than a whole hackathon allows, so you will demonstrate one hindcast rather than an operational system and should frame it that way
- Red flag: No accuracy target is stated, so a forecast that looks broadly right during a smog episode can be presented as a success without any real verification — build the station comparison properly instead
What you will be writing
- WRF-Chem or equivalent coupled meteorology-chemistry model
- aerosol-radiation feedback configuration
- emissions inventory preparation for the model domain
- planetary boundary layer and inversion strength diagnostics
- CPCB station validation of PM2.5 and ozone
- HYSPLIT-style plume trajectory analysis
- Atmospheric chemistry
- Air quality forecasting
- Urban environmental modelling
Prior art to read before you start
coupled weather-chemistry forecasting · inversion-driven pollution trapping · crop residue plume transport modelling
Analysed by Claude Opus. Every score above is a judgment call with its reasoning attached — kindly cross-check this against the official statement on the SIH portal before your team commits to it.