Right Now Predictions About

About MausamNow

Multi-model weather comparison for India. Five models (including AI), one chart, plain-English interpretation.

The models

Why multiple models? No single model is always right. When 3–5 models agree on rain, confidence is high. When only one model shows rain, treat it as a possibility, not a certainty. Indian models (MausamGram, IMD Rain) are better for short-term local predictions. Global models (GFS, ECMWF) are more useful for extended outlooks beyond 2 days. GraphCast AI offers an alternative perspective using machine learning — it sometimes catches patterns traditional models miss, but can also overpredict rain.

IMD MausamGram

IMD's official multi-model ensemble forecast on a 12.5km grid. Best for short-term (1–2 day) hyperlocal predictions across India. Updated daily from the 00Z model run.

12.5 km grid Up to ~5.5 days mausamgram.imd.gov.in

IMD IMD Rain Model (via MOSDAC)

Heavy rainfall forecast from India's NWP (Numerical Weather Prediction) model, hosted on ISRO's Meteorological & Oceanographic Satellite Data Archival Centre. Catches trace rainfall that global models often miss. Also provides Lightning Potential Index (LPI) for thunderstorm risk assessment.

~12 km grid Up to 72 hours MOSDAC weather portal

Global GFS (NOAA, USA)

Global Forecast System by NOAA. A strong general-purpose model, updated every 6 hours, though not specifically tuned for Indian monsoon dynamics. Accessed via the open-source Open-Meteo API.

~13 km resolution Up to 16 days NOAA/NCEP

Global ECMWF IFS (Europe)

European Centre for Medium-Range Weather Forecasts. Widely regarded as the world's most accurate global weather model. Updated every 6 hours. Accessed via Open-Meteo.

~9 km resolution Up to 15 days ecmwf.int

AI GraphCast (Google DeepMind)

An AI/machine learning weather model developed by Google DeepMind and run operationally by NOAA. Instead of solving physics equations like traditional models, GraphCast learns weather patterns from 40 years of historical data (ERA5 reanalysis). Research shows it outperforms ECMWF on many metrics for 2–3 day forecasts. However, it runs at 6-hourly timesteps (interpolated to hourly by Open-Meteo) and can overpredict precipitation in dry periods. Supports temperature, rain, wind, and cloud cover but not humidity. Enabled via checkbox — off by default.

~25 km resolution Up to 16 days DeepMind blog

About the author

Abhijit Vaidya

Software engineer based in Pune. I write about AI experiments, distributed systems, and whatever else I can't stop thinking about.

MausamNow is open source. View on GitHub. All weather data comes from freely available government and open-source APIs.