Fog in satellite images

Winter last year i stumbled over a satellite image product at I don’t know how the cloud mask on this site is created but it seemed to have a problem with fog. Looking at this image only one gets the impression that there are absolutely no clouds over Germany. Looking into the sky proves that it is foggy. So this cloud mask could be a little bit misleading when used for example for estimating temperatures.

But how can this difference of observation and product be explained?

There are different factors influencing the detection of fog via satellites. To understand the problems with remote sensing of fog at night one needs to know the basics of satellite remote sensing.

Thermal and visible spectra

The law of Stefan-Boltzmann says that every body sends out radiation defined by it’s temperature. According to Wien’s law the maximum of suns radiation can be found between 400 and 700nm. So most of the radiance enery falls in the visible range (colors: red, green, blue).


(Figure from

The visible spectrum is followed by the thermal spectrum. The radiation that is send out by earth falls into this range. Ideally every body sends out radiation with the maximal possible emessivity of one. Bodys with emessivity of one are called black bodies. Lower emessivity means lower radiation will be sent out.

Considering a stratified atmosphere (cooling in the troposphere layer with height until one reaches the tropopause) it is clear that the warm surface has got a higher brightness temperature than the colder clouds in higher layers.

Satellites measure either the reflected solar radiation or the emitted infrared radiation. The latter is observable day and night while the first one can not be measured at night. Satellites normally observe the radiation in the infrared spectrum in different channels, considering a narrow wavelength spectrum. On most satellite images in the internet one can see the informations from the 10.8 micrometre channel, which is a window channel. That means that (nearly) no radiation is absorbed by water vapour in the atmosphere at this wavelength. For this reason the channel measures either the surface brightness temperature or cloud top temperatures.

Let’s have a look at the situation considered at the beginning of this post:

* Some areas show clear conditions so that the surface cools steadily

* There are other areas were it is foggy. Through to re-radiation of absorbed radiation from the fog to the earth’s surface these areas are much warmer.

* Some areas are covered by clouds.

In normal Infrared satellite images the foggy areas can not be detected that easily as the measured brightness temperatures are too similar in both areas.

If there is only the 10.8 micrometre channel the situation would look rather bleak. Using the combination of different channels one can obtain the desired information about foggy areas.

On one finds the “Night Microphysics RGB” product. What does it mean?

The product combines 4 infrared channels in the following way:

The 10.8 micrometre channel is colored blue.
The 10.8 – 3.9 micrometre difference is colored green.
The 10.8 – 12.0 channel difference is colored red.

Fog and stratus clouds in general are composed of small water droplets. These show a different behaviour in the 3.9 micrometre channel. And can be distinguished from higher ice clouds.

If you are interested in more physical details you can find excellent information on

Let’s have a look at today’s image of the Night Microphysics RGB:


The foggy areas are observable by the greenish color.

Even on the first glimpse very boring weather situations can be very interesting when viewed from the right perspective. And moreover the measured negative temperature values are very impressive.

The following 2m temperature values were observed at east Bavaria and southern Saxony at 20 UTC.

Mähring: -22,3°C ( )
Tirschenreuth-Lodermühl: -20,5°C ( )
Morgenröthe-Rautenkranz: -20,4°C ( )
Dippoldiswalde-Reinberg: -19,8°C ( )

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  1. Daniel, September 23, 2014:

    I totally agree how a certain weather can affect while capturing an aerial view using satellite imagery. Thus, there’s some other tools that might somehow prevent this from happening. Yet, it is also a big help to those who are monitoring the weather that may help them to gather data/information regarding to the climate.

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