Chapter III: Satellite data - tools for better assessment
Introduction
The main advantage of satellite data is their broad spatial and temporal coverage which enables the detection of severe weather events prior to other sources. Observing volcanic ash clouds, it might seem obvious that the closer you get, the better your chance to detect them.
Therefore polar orbiting weather satellites like MetOp seem to be beneficial, since they offer excellent spatial coverage as a result of their lower flight level (820 km).
As a further consequence of the lower flight level, polar orbiting satellites like MetOp can only provide a restricted number of images per day. Therefore at lower latitudes constant monitoring of weather conditions or ash clouds is not possible. For operational weather forecasting it is essential to monitor the ever changing weather conditions.
Therefore MSG images which operate on a high temporal resolution will be preferred. The core instrument on Meteosat 9 is SEVIRI (Spinning Enhanced Visible and Infrared Imager) and provides the information of 12 different spectral bands.
One way to deal with these different images is to compare them and filter information. Apparently this task demands a lot of time and can be very challenging.
Here is an animation of the single satellite imageries for 15 April 2010 1200UTC. Navigate though the different channels and try to identify the Ash Cloud.
Figure 3.1: Different channels of Meteosat 9 for 15 April 2010 1200UTC
Single satellite images
HRV
Monitoring small scale events the high resolution visible imagery can provide excellent information.
The MSG HRV channel operates on a horizontal resolution of 1 km (sub satellite area) and its ability to discriminate small scale features can also be beneficial when observing volcanic ash clouds. However it should be noted that it can be difficult to monitor very thin ash clouds with HRV imageries. The detection depends on the reflectivity of the underlying surface and is easier over oceans. Moreover the sun angle plays an important rule, whereas during the morning hours there is a better chance to detect ash clouds due to strong forward scattering of the solar radiation on the ash particles. Thus, the detection of volcanic ash cloud with HRV images is only possible under certain conditions and should be considered as an addition tool.
Figure 3.2: HRV loop 20100415 09UTC-15UTC
As you can see the high resolution visible images cannot provide a clear discrimination of the ash cloud. Of course the viewer gets a vague impression about its location, but for preciser information different products should be consulted.
IR3.9 - Reflected Component
The IR3.9 channel consists of 2 different parts: a solar component (during day) and a thermal component (both during day and night). For the detection of volcanic ash the reflected part of the solar component can be very useful, since is particularly sensitive to cloud phase and particle size. This characteristic is based on a notably different emissivity of the IR3.9 channel compared to other channels such as the IR10.8 channel. Considering the detection of volcanic ash there will be differences in the reflection of ash particles and cloud particles. This difference can finally be seen in the image. However using the IR3.9r images one should be aware of limb cooling. Thus, for larger viewing angles the optical path through the atmosphere is greater. As a consequence features at higher latitudes appear a little blurred.
Figure 3.3: IR3.9r loop 20100415 10UTC-16UTC
The analysis of this case shows that the detection of the ash cloud with the IR3.9 reflected component did not work well. It only gives a hint where the ash cloud could be found. One of the reason might be the fact, that Iceland is situated in higher latitudes and limb cooling has a blurring effect on the satellite images.
Brightness Temperature Differences
IR12.0 - IR10.8
Volcanic ash clouds consist of silicate particles, aluminium dioxide, ferrous sulphates and other trace elements. After the eruption of Eyjafjallajökull the Nordic Volcanological Center performed a comprehensive analysis of the components of the volcanic ash cloud. Results showed a remarkable high concentration of silicate particles of about 58 per cent (Nordic Volcanological Center). Therefore channels sensitive to this characteristic should be used for tracking the ash cloud. Volcanic ash clouds which contain a high concentration of silicate particles can be detected using the brightness temperature difference between IR12.0 and IR10.8. This difference arises as an effect of the lower emissivity of silicate particles at 10.8 μm than at 12.0 μm. In consequence the resulting brightness temperature difference of volcanic ash clouds will be positive. In contrast the brightness temperature difference for ice clouds will be negative due to the lower emissivity at 12.0 μm. Therefore this method enables the discrimination among volcanic ash clouds and ice clouds.
IR10.8 - IR8.7
Apart from producing ash clouds volcanic eruptions release enormous amounts of gases. Volcanic plumes with high concentration of sulfur dioxide can be detected using the IR8.7 channel. Generally S02 clouds are more transparent at IR10.8 than at IR8.7 due to the higher absorption at spectral ranges about 8.7μm. As a consequence the brightness temperature difference IR10.8-IR8.7 for SO2-clouds is positive. In contrast ice clouds are more transparent at IR8.7 than at IR10.8. As a result observing ice clouds the brightness temperature difference will be negative. This fact enables a clear discrimination between S02 and iceclouds, and this information is finally also used in the RGB-composites. Be careful in case of temperature inversions, since brightness temperature differences can be negative then.
Figure 3.4: loop 20100414 21UTC - 20100415 18UTC
As the analysis of the eruption of Eyjafjallajökull demonstrates, this information is only useful if you know the exact location where the eruption took place. On this basis the corresponding ash plumes can be analysed in regard to positive brightness temperature differences. Since positive brightness temperature differences can also arise due to different reasons (for example you can detect positive brightness temperatures in the loop over Norway) one has to be careful with further assumptions. This method again only gives a hint where SO2 signals can be found. Neither single satellite images nor one specific brigthness temperature difference enable the clear discrimination of ash clouds. This highly recommends to use combined products (see next section 3.3).
RGB Imagery
Since operational weather forecasts are bound to a time limit, efficient tools for filtering information are required. For this purpose the so called RGB (red green blue) composites have been designed. RGBs have been designed to highlight information that would not been clearly visible, if only one channel was being used. RGB composites can be very useful for the tracking of volcanic ash clouds, since selected features can be emphasized in these pictures. The concept of RGB is to implement the information of 3 different channels or combined channels and mark each part in one colour. As the name already indicates the 3 different colours available are red, green and blue, whereas the resulting image will then be a colourful satellite image. When all three colours are present in full intensity the resulting image is white. Following this method a broad range of composites with particular properties can be created. For example the Dust RGB and Ash RGB enable the discrimination of ice clouds and dust/ash signals.
Dust RGB
The Dust RGB implements the information provided by 3 different window channels of MSG, namely IR12.0, IR10.8 and IR8.7. Since the IR12.0 and IR10.8 are clean window channels, they are able to discriminate among land surface temperatures and cloud temperatures. In addition the IR8.7 channel provides information about trace gases and aerosols. As a result the whole range of information can be included, that would not be available if only one single channel was being used.
The dust-RGB is built upon these 3 parts of information:
Red = IR12.0-IR10.8 (-4°C to+2°C)
Green = IR10.8-IR8.7 (0°C to 15°C)
Blue = IR10.8 (12°C to 16°C)
Dust RGBs offers the possibility to depict plumes over land and sea both during day and night. Depending on the brightness temperature difference between IR12.0 and IR10.8 dust or cirrus clouds can be observed. Based on this difference the red color fraction of the RGB composite is determined. Since the IR12.0 channel is particularly suitable to observe cirrus clouds (lower emissivity) the resulting brightness temperature difference will be negative in case of these clouds.
Thin cirrus clouds will be marked in black in the Dust RGB. In contrast for dust plumes the brightness temperature difference will be positive. This will lead to a higher red fraction in the imagery.
Figure 3.5: Meteosat 9 Dust RGB - 23 February 2006 1200UTC
Dust RGBs are not only suitable to detect Saharan dust storms, but can also help to detect volcanic ash clouds. In Dust RGBs volcanic ash clouds are represented in an orange colour.
Figure 3.6: Meteosat 9 Dust RGB - 15 April 2010 1100UTC
An orange composite consists of full intensity of the red fraction, medium intensity of the green fraction and low intensity of the blue fraction. Like in the Dust RGB the positive brightness temperature difference IR12.0-IR10.8 will lead to a high intensity of the red colour fraction. However it is the green fraction which plays the important role here. The IR8.7 channel is able to detect aerosols like ash particles (lower emissivity). In consequence the brightness temperature difference IR10.8-IR8.7 will be positively orientated, leading to medium intensity of the green fraction.
Using this information take a look at the Dust RGB loop of Europe.
Figure 3.7: Meteosat 9 Dust RGB - 15 April 2010 from 000UTC to 1330UTC.
Outline of the weather event from 14 - 17 April
In the beginning there were only mid- and low-level clouds present near Iceland. Within the next few hours the colour changes from green to dark green and finally black. As already explained black indicates thin cirrus clouds. These ice clouds resulted from the enormous amount of water vapour which was produced when the melting water from the glacier entered the volcanic chimney. The resulting ice clouds masked the ash signal in the beginning -> have a look at the loop! Moreover the clouds present in the south-east of Iceland were affected by a warm front band reaching over Iceland. Additionally there could be lee waves detected in the east of Iceland (see also single IR10.8 image, 15 April 00 UTC).
During the next few hours the ice sublimated, whereas the ash particles remained. Looking at the Dust RGB loop, the first ash signals can be detected around 06 UTC. The ash particles appeared in a slight orange colour. Monitoring the ash clouds during the morning hours, it comes clear that the volcano is still emitting ash particles. This new ash clouds then undercut the track of the ice clouds coming from the north of Iceland.
At 12 UTC the older part of the ash clouds reached Norway, whereas the newer part was heading south-eastwards. As already mentioned in the introduction it should be noted, that ash clouds are only visible in the satellite imagery at a certain concentration. Therefore neighboring regions should be considered when issuing warnings.
Ash RGB
The main principle about Ash RGB is the same as in the Dust RGB. There are 3 parts of information combined, each marked with one own colour. Like in the dust-RGB, the channels being implemented are the following ones:
Red = IR12.0-IR10.8 (-4°C to +°2C)
Green = IR10.8-IR8.7 (-4°C to +°5C)
Blue = IR10.8 (-30°C to 30°C)
In contrast to the Dust RGB the temperature ranges linked to certain cloud features are slightly different. As a result the final composite experiences a shift into the green colour fraction.
Colour interpretation:
- Sulphur dioxide clouds are green
- Depending on the height, temperature and particle size, ash goes from being red (when it is very cold) to magenta (when it is warm) to yellow (when it is composed of small ash particles)
- Thin cirrus is black
- High clouds and thunderstorms are brown
- Near-surface temperatures are in shades of blue and green
In the following Ash RGB ash clouds appears in a yellowish colour. The main benefit of the Ash RGB is that it shows the three major volcanic effluents (ash, sulphur dioxide and ice crystals) in distinct colours, enabling users to observe effluents drifting from the site of an eruption. But it should be noted that it cannot detect ash or sulphur dioxide embedded in ice (mixed volcanic cloud). Take a look at the Ash RBG and compare it to the Dust RGB: (shifting mouse -> RGB changes):
Figure 3.8: Meteosat 9 Ash RGB - 15 April 2010 1200UTC. Hover your mouse over the image to bring up the corresponding Dust RGB.
MetOp Analysis - Getting closer to the surface
The key characteristic about polar orbiting satellites is their high spatial resolution, since they operate on a lower flighting level (820km). However they can only provide a restricted number of imageries depending on the selected latitude. Their main mission is to provide additional high quality product to the MSG imageries. The present operating polar orbiting satellite MetOp-A carries several instruments such as IASI, GOME2 and AVHRR. These instruments operate on different spectral ranges. The products derived from these instruments will be briefly introduced.
IASI (Infrared Atmospheric Sounding Interferometer)
IASI has been developed for operational meteorological soundings with a very high level of accuracy. Based on the atmospheric emission spectra measured in the thermal infrared range temperature and humidity profiles can be derived. Therefore a Michelson interferometer which enables the spectral decomposition is being used. Moreover the information collected by IASI can be used for tracking SO2-signals or other trace gases. Below one sees a loop showing the SO2-tracking in April 2010: The x-axes denote the longitudes and the y-axis the latitudes. The grey shade in the upper left corner indicates the position of Iceland. The time lapse shows the track of the SO2 signal, whereas on 18 April a further eruption takes place.
Figure 3.9: IASI SO2 Product for 15 to 18 April 2010.
The output generated by IASI-measurements enables the discrimination among SO2-signals, ice and ash-particles. Here is brief time table showing the track of the volcanic ash cloud from the 14th of April 2010 to the 15th of April 2010.
Figure 3.10: IASI SO2, Ice and Ash product for 14 and 15 April 2010.
GOME2 (Global Ozone Monitoring Experiment-2)
GOME is an optical spectrometer which senses the Earths backscattered radiance and solar irradiance in the ultraviolet and visible part of the spectrum (240 - 790 nm) at a high spectral resolution of 0.2 - 0.4 nm. Based on this data the atmospheric ozone content as well as information about sulfur dioxide, water vapour, bromine oxide and other trace gases can be derived.
GOME-2 near-real-time products are available up to two hours after sensing (see GOME2-products).
Figure 3.11: Metop-A Gome-2 SO2 product for 15 and 16 April 2010, Ice and Ash product for 14 and 15 April 2010. Source: DLR
AVHRR(Advanced Very High Resolution Radiometer)
The Advanced Very High Resolution Radiometer (AVHRR) operates at 5 different channels simultaneously in the visible and infrared bands. As a high-resolution imager (about 1.1 km near nadir) its main purpose is to provide cloud and surface information such as cloud coverage, cloud top temperature, surface temperature over land and sea, and vegetation or snow/ice. The ability to discriminate small scale features is particularly suitable concerning the detection of volcanic ash clouds. According to Prata (see references) measurements of infrared emission in the 10-12 micrometer window can be used to detect volcanic ash during an eruption and in the days and weeks following. The major effects on the emission due to the cloud are a decrease in signal from the 11 micrometer channel with respect to the 12 micrometer channel and it is presumed that this is due to the reverse absorption effect found for liquid H2SO4 aerosols and observed for volcanic dust. This effect allows ready discrimination of volcanic cloud from water-ice clouds. In an operational environment where AVHRR imagery is available on real time, a volcanic signature can be recognized by computing an image of the IR11.0-IR12.0 temperature differences. Regions of negative IR11.0-IR12.0 are indicative of volcanic ash. It is therefore possible to use this as an operational tool to assist in the forecast of volcanic cloud hazards to air traffic. The picture below, the orange-red colors represent negative brightness temperature differences which are indicators for ash clouds. In contrast positive brightness temperature differences show water-/ice clouds.
Figure 3.12: Metop-A AVHRR 15 April 2010 1046UTC.