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Introduction

Combining satellite images from different channels goes far back in the history of satellite meteorology. The idea behind it can be summarized as follows:

Different channels give different information, and the combinations of channels reveal more information and features of the Earth's surface and atmosphere than single channels alone.

There are two ways of making better use of satellite images:

  • Enhanced satellite images
  • RGB presentation (Red Green Blue)

Looking back at the history of satellite meteorology, the first enhanced images were generated for severe convection like MCS (Mesoscale Convective Systems) to reveal the coldest cloud tops and the growing rate of these cold tops. The first RGB combinations were developed for the USA's polar orbiting satellites and the first application was discriminating low clouds from middle and high clouds.

As time passed, a large number of different RGB products were developed by various institutes and weather services. The usefulness of some combinations was sometimes questionable and comparison between different RGBs became difficult.

With the creation of the MSG and its 12 channels, each with its own unique qualities, a series of standardized RGBs were developed. These RGBs will be described according to their significance and usefulness.


EuMeTrain has developed an easy to use RGB analysing tool. It will help you with analysing the images and understanding the physics behind it. The tool is streight forward, but if you have any question, here is a little guide. You might get a false positive for a virus. Please ignore it, here is a short explanation why this happens.

The Tool is made for Windows platform. To be able to use it you will need .Net Framework 4.0 or higher.

Basic ideas behind enhanced satellite images

This application typically uses IR images that represent cloud top temperatures. Different colors are assigned to specific temperature ranges.

The following example presents the same case as the one that was already used for the basic channels - a winter case. The coldest temperatures can be found in the cloud tops of a warm front shield; the high cloud fibers at the rear of the cold frontal cloud band are also enhanced by the corresponding colors.

However, enhanced IR images are especially useful for convective cloud systems; a summertime example with an unstable situation is shown in the case below. Beyond simply coloring the coldest clouds, enhanced IR images reveal structures typical for convective cells and systems like cold rings, warm cores, U/V structures and overshooting tops much more easily than basic channels alone would.

Basic idea behind RGBs

The three colors red, green and blue are allocated for three MSG channels or, if appropriate, channel differences. All other colors are generated as a combination of these three basic colors. The choice between channels and channel differences depends on the features that are being looked for.

This shall be demonstrated with the so-called Natural Color RGB, which is composed from the channels 03 (R), 02 (G) and 01 (B). Each of these three visible channels contains information about reflected sunlight (and consequently the optical thickness of clouds), but each channel also adds its own physical specialty:

Ch 03 (1.6 µm): particle phase and size (water, small and bigger ice droplets)
Ch 02 (0.8 µm): "greenness" of vegetation
Ch 01 (0.6 µm): optical thickness

The next figure shows the resulting colors for four typical features in the "Natural Color RGB"

Maximum signal from Ch 2: cloud-free; surface and vegetation dominates; resulting color: green
Medium values from all channels but Ch 3 dominates; no clouds or vegetation; resulting color: reddish
Medium values from all three channels; medium albedo - thick water cloud; resulting color: grayish
High values from ch 1 and 2 : high albedo; low counts from Ch 3: typical for ice cloud and/or snow; resulting color: cyan

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When using RGBs, it is important to understand which qualities the individual channels or channel differences provide.

The Natural Color RGB

Information received from the three channels that contribute to the RGB combination

NIR IR Optical thickness and particle phase and size - information about water droplets as well as small and large ice droplets
VIS 02 Optical thickness and differences in vegetation - "greenness" of vegetation
VIS 01 Optical thickness: albedo - information about cloud thickness

Resulting colors for typical features

Gray Thick water clouds
Cyan Ice clouds, snow
Green Vegetation
Red vegetation free land, desert
Black Ocean

Typical application areas

  • First impression of the large scale weather
  • Differentiation of water and ice clouds

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The High Resolution VIS (HRVis) RGB

Information received from the three channels that contribute to the RGB combination

HRV Optical thickness - High resolution (pixel: 1 km at Nadir)
HRV Optical thickness - High resolution (pixel: 1 km at Nadir)
The HRV channel is used in both red and green components to retain the high resolution information
10.8 (Classical IR Window channel) - Information about cloud top temperature

Resulting colors for typical features

White Thick convective cells
Blue Cold cloud tops, especially thin cirrus
Yellow Fog and low cloud

Typical application areas

  • Discrimination of cloud systems of different vertical extent
  • Recognition of small-scale structures, especially in convective and low clouds/fog

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This RGB is very useful for convective systems, as it lets us tell the thick Cb kernel apart from the thin high Cirrus anvil, as well as recognizing the overshooting tops. A convective summer case is presented below:

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The Airmass RGB

Information received from the three channels that contribute to the RGB combination

WV6.2 - WV 7.3 (difference of the two WV channels) Information about moisture content in middle/upper layers of the troposphere
IR 9.7 - IR 10.8 (ozone channel - IR window channel) Information about ozone concentration, which differentiates cold (polar) and warm (mid-level, subtropical) air masses
Cold air mass: high ozone concentration and low tropopause; warm air mass: low ozone concentration and high tropopause
WV 6.2 (Water Vapor channel 05) Information about humidity in upper layers of the troposphere

Resulting colors for typical features

White Thick clouds
Green Warm air masses
Blue Cold air masses
Dark red/brown Dry upper air, PV anomalies

Typical application areas

  • Differentiation between cold and warm air masses (blue - green)
  • Recognition of very dry air that has descended from the stratosphere (dark brown)
  • Dynamical features: tropopause folding; high PV values

Due to the incorporation of water vapor and ozone channels, the Airmass RGB's usage at high satellite viewing angels is limited.

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The Dust RGB

Information received from the three channels that contribute to the RGB combination

IR 12 - 10.8 (difference of the two IR window channels. Split window) Information about dust, which gives a high contribution of red component
10.8 - 8.7 (difference of two IR window channels) Differentiation between water and ice clouds (channel 07 identifies ice clouds better)
10.8 (IR Window channel) Information about cloud top temperatures

Resulting colors for typical features

Pink Dust
Red Thick ice cloud
Black Cirrus
Orange/yellowish/green Low cloud

Typical application areas

  • Detection of synoptic, mesoscale and local cloud systems
  • Discrimination of different cloud systems and cloud thicknesses (thick - high thin - low cloud)
  • Detection of sand storms
  • Detection of SO2 plumes from volcanoes

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The Day Microphysics RGB

Information received from the three channels that contribute to the RGB combination

VIS 0.8 (visible channel 02) Surface reflectance (sand, snow), Cloud albedo
MIR 3.9 (mixed channel, but only solar part is included) Detection of ice clouds by the differences in particle size and reflectance properties between water and ice clouds, Fire detection
IR 10.8 (IR window channel) Temperature of surface/cloud top temperatures

Resulting colors for typical features

Red Thick precipitating cloud
Black brown Cirrus with thick crystals
Green Small ice crystals (often lee cloud)
Pink Snow and ice

Typical application areas

  • Convection
  • Fog and low cloud
  • Fire (contribution from channel 04)

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The 24-Hour Microphysics RGB

Information received from the three channels that contribute to the RGB combination

IR 12 - 10.8 Information about dust, which gives a high value of the red component
IR 10.8 - 3.9/8.7 Differentiation between water and ice cloud; better ability to tell the difference between low clouds and fog than the Dust RGB
IR 10.8 - 3.9 is only useful during the night; replacing channel 3.9 with 8.7 is necessary for the 24-Hour Microphysics RGB. It is similar to the Dust RGB, but has a different temperature range.
From IR 10.8 Information about cloud top temperatures

Resulting colors for typical features

Red Thick ice cloud
Black Cirrus
Ocher/yellowish/green Low cloud

Typical application areas

  • Synoptic scale and mesoscale cloud systems: convection
  • Similar to Dust RGB

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The Severe Storm RGB

Information received from the three channels that contribute to the RGB combination

WV6.2 - WV 7.3 (difference of the two WV channels) Information about moisture content in middle/upper layers of the troposphere
IR3.9 - IR10.8 High values of the green component for cold cloud tops, high reflectivity (small ice particles) for very cold cloud tops, and lower reflectivity (normal updraft)
NIR1.6 - VIS.0.6 Information about ice and/or water clouds

Resulting colors for typical features

Blue Ocean/land
Red Convective cloud: large ice particles
Yellow Convective cloud: small ice particles

Typical application areas

  • Convective cells
  • Detection of severe storm centers

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