Observation from above
Satellite observations provide a wide view of cloud systems and their movement. Radar adds a local precipitation picture. Neither product directly measures every flight hazard, so both must be used with their limits in mind.
What each system sees
A satellite senses radiation from cloud, land and sea. Radar detects returned energy from precipitation targets. Satellite is valuable over ocean and remote areas; radar is strongest within useful range of its network.
A bright radar echo does not by itself prove severe turbulence, and a cloud image cannot give a cloud base. The crew must add reports, soundings and forecasts.
Limit before interpretation
Check image time, projection, coverage and channel before identifying a feature. A single frame gives location, while a sequence gives movement and development.
Use the product to ask a question, then use another observation or forecast to answer it.
Polar orbiting satellites
A polar-orbiting satellite passes over different parts of the Earth on successive tracks. Its orbit gives useful high-latitude coverage and detailed swaths, but a particular point is not watched continuously.
Swath, repeat pass and resolution
A swath is the strip observed as the satellite passes. Repeat-pass time and viewing geometry determine how frequently the same place is seen. A detailed polar image can still be old by the time it reaches the briefing.
The value of a polar image is high spatial detail and coverage away from the equator. The limitation is temporal continuity. Use a geostationary sequence when rapid evolution is the main concern.
Flight use
For an oceanic or remote route, compare the latest polar pass with surface observations and forecast charts. Do not assume its cloud edge remains current without a time sequence.
If a feature is near the edge of the swath, consider the location uncertainty before plotting it against the route.
Geostationary satellites and Indian systems
A geostationary satellite remains over the same equatorial position and gives a continuous view of a large region. This makes it especially useful for following tropical convection, monsoon cloud and cyclone structure.
Continuous view, not equal detail
The viewing angle becomes less favourable far from the sub-satellite point. Resolution and feature location must therefore be treated with care near the edge of the image. A continuous sequence is the main strength.
Joshi uses Indian meteorological satellite systems as the regional example. Their visible, infrared and water-vapour channels support cloud and moisture monitoring over the Indian Ocean region.
Operational use
Use the animation to see whether cloud is growing, decaying or translating. Then compare with radar where available, current reports and the SIGWX forecast.
A satellite spiral pattern can support a tropical-cyclone assessment, but the advisory remains the authoritative flight-planning product.
Visible, infrared and water vapour
Each image channel answers a different question. Visible imagery shows reflected sunlight. Infrared imagery relates brightness to temperature. Water-vapour imagery is a moisture product and is included here as Joshi support.
Day and night logic
Visible imagery has cloud texture and contrast in daylight but is not a night product. Infrared imagery works day and night. High cold cloud usually appears brighter on standard infrared displays because its cloud-top temperature is lower.
Infrared brightness is not cloud thickness, cloud base or icing severity. A low warm cloud can be dark while still limiting an approach. Use cloud reports and forecasts for the lower atmosphere.
Cloud-top temperature
A grey scale or false colour scale converts temperature ranges into display values. Compare cloud-top temperature with the environmental temperature profile only when the product and sounding time make that comparison meaningful.
Deep convection often has cold tops, but the route decision must still include its movement, embedded character and reported tops.
Locate and interpret the feature
Image interpretation begins with location. Coastlines, graticules, map projection and time labels prevent a cloud band, dust plume or tropical system being placed in the wrong airspace.
False colour and feature clues
False colour assigns colours to brightness or temperature ranges so boundaries are easier to see. It changes the display, not the underlying observation. Dust, haze, smoke, snow and volcanic plumes require channel knowledge and synoptic context.
A pale feature in a false-colour image is not automatically high cloud. Check the legend, channel, surrounding terrain and previous frames.
Cross-check the interpretation
Compare a satellite feature with METAR, radar, upper-air data and charted fronts. If the products disagree, investigate time, height, range and sensor limitations rather than forcing a conclusion.
A reliable interpretation says both what is likely and what remains uncertain.
Turn images into a flight decision
Satellite and radar are most useful when they are part of a sequence of evidence. They show the shape and motion of weather, while reports and forecasts add the conditions needed for an operational decision.
A practical sequence
First identify the feature and its time. Then assess its movement from successive images. Compare with radar for precipitation, METARs for surface effects, SIGWX for significant weather and the wind-temperature chart for the flight level.
This sequence avoids the two common errors: treating a picture as a complete forecast, or ignoring a large developing system because it is not yet at the aerodrome.
What to record
Record the feature location, movement, expected route crossing time, vertical or precipitation evidence, alternatives and uncertainty. The next update time is part of the plan.
A change in route or level should be traceable to an observed or forecast consequence, not simply to the appearance of an image.
Radar and satellite limits used together
Joshi's radar material adds the local precipitation view. A PPI displays echoes by range and azimuth; an RHI shows a vertical slice. Beam height increases with range, drizzle can be missed and the bright band can exaggerate echo strength. Doppler radar estimates radial motion, but no radar return alone measures turbulence. Use the time stamp and radar range before treating an echo as route-critical.
Image interpretation
A polar satellite gives a swath with repeat-pass gaps; a geostationary satellite gives continuous coverage but a poorer viewing angle away from its sub-satellite point. In an IR image, cold high cloud normally maps to brighter shades. False colour remaps those brightness values to colours. Locate every feature with coastlines and graticules, then compare a sequence with radar, surface observations, a front analysis and the forecast chart before calling dust, smoke, haze or volcanic plume.
Operational recognition examples
- Dust plume follows the low-level wind and often has a diffuse edge. Confirm it with surface visibility reports because an image cannot give the runway value.
- Smoke may be carried far from a source and can resemble thin cloud in some displays. Check daylight visible imagery, reports and the synoptic wind.
- Volcanic plume requires advisory information and a time sequence; do not identify ash solely from one enhanced image.
INSAT imagery is especially useful for watching monsoon cloud and tropical systems over the Indian Ocean. Resolution differs by channel, so do not compare a visible fine-scale boundary directly with a coarser water-vapour feature without allowing for the sampling difference.
Channel selection in practice
Use visible imagery to separate low stratus texture from land only in daylight. Use infrared after dark to monitor cold convective tops and broad frontal cloud. Use water-vapour imagery to identify dry slots and moist upper flow, but do not describe it as a direct cloud or precipitation measurement. A cloud-top temperature estimate is meaningful only when the image calibration and the temperature profile are current.
Satellite briefing checklist
- Time read the image time and the observation interval between frames.
- Channel identify visible, infrared or water vapour before interpreting brightness.
- Location use coastline, graticule and projection to place the feature.
- Motion compare successive frames, then use radar for precipitation where coverage exists.
- Forecast cross-check with fronts, SIGWX and upper-air data before assigning cloud, icing or turbulence risk.
Weather radar wavelengths and siting affect detection. The Indian network's coastal and airport radars provide strong local support, but their useful resolution reduces with range. Terrain blocks the beam and Earth curvature raises it above low precipitation at distance. These limitations explain why a radar image and a low-visibility METAR can sometimes appear inconsistent.