How the GFS Model Forecasts Rainfall in India – Accuracy, Limitations & How to Read the Maps
The Global Forecast System (GFS) is the backbone of VayuMet's short-range weather maps. Understanding how it works — and where it falls short — will help you interpret rainfall forecasts for India with the right level of confidence.
What is the GFS Model?
The Global Forecast System (GFS) is a numerical weather prediction (NWP) model developed and operated by NOAA's National Centers for Environmental Prediction (NCEP). It runs four times daily — at 00Z, 06Z, 12Z, and 18Z UTC — producing forecasts out to 16 days at global coverage.
VayuMet uses GFS for all short-range weather products: rainfall accumulation, 6-hourly precipitation, surface and upper-level wind, temperature, humidity, and cloud cover.
GFS at a Glance
How GFS Generates a Rainfall Forecast
GFS begins each run by ingesting observations from radiosondes, weather satellites, surface stations, aircraft, and ocean buoys — a process called data assimilation. These observations are blended with the previous model state to produce an "analysis" — the model's best estimate of the current atmosphere.
From this analysis, GFS solves the fundamental equations of atmospheric dynamics (conservation of mass, momentum, energy, and moisture) forward in time. Rainfall in GFS comes from two parameterised physical processes:
- Grid-scale precipitation — large-scale lifting and saturation that the model resolves directly (e.g., frontal systems, monsoonal troughs).
- Convective parameterisation — sub-grid convection (thunderstorms, squall lines) represented by the Simplified Arakawa–Schubert (SAS) scheme. This is where GFS accuracy drops significantly for isolated convective events.
Key insight: GFS at 0.25° resolution cannot explicitly resolve a thunderstorm cell (~5–10 km in diameter). It estimates the aggregate effect of convection on the grid box — which is why its point-location rainfall forecasts have high uncertainty, especially for convective events.
How VayuMet Processes GFS Data
VayuMet downloads raw GFS GRIB2 files directly from NOAA's NOMADS server within minutes of each model run completing. The processing pipeline:
- Subset the global GRIB2 to the India domain (65°E–100°E, 5°N–40°N)
- Extract APCP (accumulated precipitation) and PRATE (precipitation rate) fields at each forecast hour
- Convert to GeoTIFF with a WGS-84 projection using GDAL
- Apply a colour ramp (blue–green–yellow–orange–red) calibrated to Indian monsoon rainfall intensities
- Serve the GeoTIFF directly to the browser where a WebGL renderer overlays it on the Leaflet map
No smoothing, bias correction, or post-processing is applied to the underlying GFS precipitation fields. What you see on VayuMet is the raw model output.
Accuracy: Where GFS Performs Well in India
Large-Scale Monsoon Systems
GFS excels at tracking synoptic-scale systems that drive the Indian monsoon: the monsoon trough position, low-pressure systems and depressions in the Bay of Bengal, and broad widespread rainfall episodes over the Indo-Gangetic Plain. At the 1–4 day forecast range, GFS rainfall placement for these systems typically has a positional error of under 150–200 km.
Cyclone Track Forecasting
GFS performs comparably to ECMWF in cyclone track forecasting in the North Indian Ocean at the 3–5 day range. Intensity forecasts are less reliable due to the same convective parameterisation limitations.
Day 1–2 Forecasts
Within the first 48 hours, GFS rainfall forecasts for large-scale events are generally reliable for situational awareness and planning. Beyond 5 days, skill drops significantly for precipitation — use extended range forecasts as broad guidance only.
Limitations: Where to be Cautious
| Scenario | GFS Limitation | Practical Impact |
|---|---|---|
| Western Ghats orographic rainfall | 25 km grid cannot resolve steep orography; actual windward rainfall is 3–5× higher than GFS suggests | Significantly underestimates coastal Karnataka/Kerala/Maharashtra rainfall during active monsoon |
| Himalayan foothills (Uttarakhand, HP, NE) | Same terrain resolution issue; flash-flood triggering rainfall missed | High false-alarm or miss rates for extreme events |
| Isolated thunderstorms (pre-monsoon) | Convective parameterisation produces smoother, lower-intensity rainfall than observed | Hail/lightning events poorly captured; underestimates peak intensities |
| Beyond Day 5 | Chaotic error growth in tropics; monsoon break/active transitions become unpredictable | Extended forecasts should be treated as climatological guidance, not day-specific predictions |
| Arid zones (Rajasthan, Kutch) | Small errors in moisture flux produce large percentage errors in low rainfall amounts | Occasional spurious rainfall blobs in dry zones |
How to Read VayuMet GFS Rainfall Maps
Choosing the Right Accumulation Window
VayuMet offers both 6-hourly accumulation and cumulative (total from run start) rainfall views. For identifying peak rainfall events, use the 6-hourly view — it shows when the heaviest rain falls within a day. Cumulative is better for assessing total event rainfall over several days.
Interpreting the Colour Ramp
The rainfall colour scale on VayuMet uses an asymmetric ramp designed for Indian conditions:
- Light blue (0–5 mm): Trace to light rainfall — generally not impactful.
- Green–teal (5–25 mm): Light to moderate rainfall — agricultural significance.
- Yellow–orange (25–75 mm): Moderate to heavy — possible localised flooding in urban areas.
- Red–maroon (75–150 mm+): Very heavy to extremely heavy — IMD alert threshold territory. Use with caution given GFS orographic limitations.
Using the Time Slider
Step through forecast hours using the time slider at the bottom of the map. A useful technique is to compare the Day 1 forecast from the current run against the Day 1 forecast from the previous run (6 hours earlier) — if the two runs show significant differences, confidence in the forecast is low.
Safety note: VayuMet GFS maps are intended for situational awareness only. For official flood, cyclone, or weather warnings, always consult the India Meteorological Department (IMD) at imd.gov.in.
GFS vs ECMWF for Indian Rainfall
ECMWF's IFS model consistently outperforms GFS for medium-range (3–7 day) precipitation forecasting in the tropics, including India. However, ECMWF's high-resolution output is not freely available. GFS is the best freely available global NWP model and performs well enough for most situational awareness applications at the 0–4 day range. VayuMet uses GFS precisely because its data is open, updated frequently, and covers all required variables including wind, aerosols, and aviation products.
Further Reading
- NOAA GFS Model Description & Products
- NCEI – Global Forecast System Overview
- India Monsoon 2026 – State-by-State Onset Dates
- VayuMet Data Sources & Methodology