Suman Goyal Scientist-E
Satellite Application Unit India Meteorological Department
Satellite meteorology is a branch of meteorological sciences which deals with the study of earth’s atmosphere
and oceans by using the data obtained from remote sensing devices flown onboard satellites orbiting the earth.
Any object having temperature above absolute zero degree emits energy in the form of electromagnetic
radiation. Therefore all objects on the earth surface (land, sea surface clouds, vegetation etc) emits radiations in
different wave lengths depending upon their temperatures. Most of these radiation absorbed by the gases like
carbon-di-oxide, water vapour and ozone in the atmosphere. However radiations of wave length that of visible
range and few band of near infrared, thermal infrared and microwave are not absorbed and escape to the outer
space. The sensor (radiometer) fitted with the meteorological satellites detects these radiation and transmit the
data to the earth receiving stations. These data is then analyzed to identify the different objects like cloud sea
1.1 Meteorological satellite system:
There are two types of satellites viz., Geostationary Satellite and Polar orbiting Satellite observing the earth for
(a) Geostationary Satellites:
Geostationary satellites orbit around the earth over the equator at a height 35800 km. They complete one orbit
in every 24 hours so that their period is synchronized with that of the Earth’s rotation about its own axis. They
remain over same location on the equator. Geostationary satellite images are built up by scanning with a mirror
that is tilted in steps from pole to pole at such a rate that on each rotation of the satellite an adjacent strip of
the Earth is scanned.
(b) Polar orbiting satellite:
Polar orbiting satellites orbits pass approximately over the poles usually at a height of about 850 km. The whole
surface of the Earth can be observed by these satellites which follow orbits nearly fixed in space while the Earth
rotates beneath them. The areas scanned on each pass called swath are nearly adjacent at the equator on
consecutive passes but it overlaps on polewards.
1.2 Indian Satellites
INSAT -3A, a multipurpose satellite for providing telecommunication broadcasting, meteorological and search &
rescue services was launched by European Ariane-5 Launch Vehicle on April 10, 2003. It is located at 93.5° E
longitude in the geostationary orbit. For meteorological observations, INSAT- 3A carries a Very High Resolution
Radiometer (VHRR) with imaging capacity in Visible (0.55-0.75 µm ), Thermal infrared (10.5-12.5 µm) and Water
Vapour (5.7 – 7.1 µm) channels, providing 2x2 km, 8x8 km and 8x8 km ground resolutions respectively. In
addition, INSAT-3A carries a Charge Coupled Device (CCD) camera providing 1x1 km ground resolution in the
Visible (0.63 – 0.69 µm), Near infrared (0.77 – 0.86 µm) and Short wave infrared (1.55 – 1.70 µm) bands.
KALPANA -1 (formerly Metsat 1) is an exclusive meteorological satellite which was launched by Polar Satellite
launch vehicle (PSLV) on September 12, 2002. It is located at 74°E longitude. Metsat 1 satellite was renamed to
KALPANA 1 in honour of Kalpana Chawla, born in Karnal (1961), India, who died as a NASA astronaut on Feb 1,
2003 in Space Shuttle Colombia accident. KALPANA -1 comprise a VHRR and a Data Relay Transponder (DRT)
payload to provide meteorological services. The VHRR observes in Visible (0.55-0.75 µm), Thermal infrared
(10.5-12.5 µm ) and Water Vapour (5.7 – 7.1 µm ) channels, providing 2x2 km, 8x8 km and 8x8 km ground
The OCEANSAT –2, a polar orbiting satellite launched on 23rd September 2009 into a near polar sun-synchronous
orbit of 720 km with equatorial crossing time of 12 noon. The repetitively achievable will be two days. It is ISRO’s
second in the series of Indian Remote Sensing Satellite (IRS) dedicated for ocean research. OCEANSAT - 2 carries
two payloads for ocean related studies, namely Ocean Colour Monitor (OCM) and Ku-Band pencil Beam
scatterometer. OCM-2 is an 8-band multi-spectral camera operating in the Visible – Near IR spectral range. This
camera provides an instantaneous geometric field of view of 360 meter and a swath of 1400 km. The Ku-band
pencil beam scatterometer is active microwave radar operating at 13.515 GHz providing a ground resolution cell
of size 25 x 25 km.
It is a polar orbiting satellite launched on 12 October 2011 having following payloads. a) Microwave Analysis and Detection of Rain and Atmospheric Structures (MADRAS), with five channels of microwave for estimation of atmospheric water parameters in the equatorial belt. b) SAPHIR microwave humidity sounder and radiometer of 6 channels for humidity profile. c) SCARAB-broadband radiation measurement for measurement of Radiation fluxes.
1.3 Other Satellites
In addition to two Indian satellites, another geostationary satellite namely Meteosat -7 (location 57.5° E)
operated by EUMETSAT is operational to contribute Global observing system for eastern portions of Europe,
Africa, the Middle East, Asia and the Indian Ocean region. India Meteorological department uses the products of
Meteosat-7 for weather services. The payloads of METEOSAT-7 include Multi-Spectral Radiometer including
the channels VIS, IR and WV with spatial resolution of 5km at nadir for IR & WV channels and 2.5km for VIS
2. Interpretation of Satellite imageries
2.1 Visible Imagery:
Visible imagery is derived from reflected or scattered solar radiation towards the satellite from the Earth-
atmosphere system. The brightness (shade) of the visible image depends upon the reflectivity or albedo of the
underlying surface, intensity of the solar beam and relative position of sun & satellite with respect to the Earth.
So, visible imagery is not available during night.
The Cumulonimbus clouds have highest (90%) albedo followed by fresh snow, other thick clouds (Cu, Ac, As, Sc,
St, Cs), old snow, Shallow, broken clouds (St, Ci, Cs, Cc, Cu), sea ice, land surface whereas, water surfaces have
lowest (8%) albedo. Therefore, visible imagery is very useful for distinguishing between clouds, land, and
sea/ocean, i.e. contrast between these three are best in this imagery. In general, land appears brighter than sea
but darker than clouds. Cloud structure may also be identified by viewing shadow and highlights in visible
imagery when sun shine falls obliquely onto clouds.
Some problems may arise while interpreting a visible imagery which is mentioned as follows:
(a) Distinguishing clouds over a snow-covered area: Distinction between snow and clouds is very difficult as
in visible image both have almost same brightness (large albedo). Animation of visible image can reveal
clouds moving over the stationary snow/ice.
(b) Thin clouds: Thin cloud coverage having low albedo over a dark surface area may be underestimated as it
does not show up very brightly in VIS imagery. On the other hand sometimes thin clouds over a high
albedo desert surface may be seen misleadingly bright because of scattering light from lower surfaces
reaching to the satellite.
(c) Small clouds: Detection of Small clouds, such as fair weather cumulus may be difficult in visible imagery
because of lower spatial resolution of satellite radiometer.
(d) Variation in brightness of different land surfaces: Brightness of land varies with the type of surface like, a
desert appears very bright and forests & vegetated land appear darker which may misleads the
(e) Distinction between fog and stratus cloud: On visible images, fog is relatively featureless and difficult to
distinguish from higher stratus clouds.
Fig-1 Kalpana-1 visible image showing different features.
2.2 Infrared (IR) Imagery
IR imagery is derived from emitted terrestrial radiation at thermal – infrared wavelength (10-12µm). It provides
quantitative measurements of temperature of the underlying surface or clouds. The greatest advantage of IR
images is it’s round the clock (day & night) availability. In black and white IR imagery, white shades i.e. high
brightness represents cold areas (higher cloud heights) whereas black shades (low brightness) indicates warm
surfaces or low cloud height. Therefore height estimation of different layers of clouds is easier by analysing IR
imagery in comparison to other imagery. Thin cirrus, which is often transparent in VIS imagery, can show up
Cloud free Sea
Coast line A
A: Low Clouds (Cu) over Sea, B: Low/medium clouds over land, C: Cumulonimbus clouds.
clearly in IR imagery, especially when it lies over a much warmer surface. Some problems related to
interpretation of IR imagery can be summarized as follows:
(a) Detection of fog and low clouds: During night time fog and low clouds can not be differentiated from
other land surface features because of negligible temperature contrast among them.
(b) Land sea contrast: In IR imagery coast line can be seen clearly only when there is large difference between
land and sea surface temperatures. For example, the most prominent temperature difference between land and
sea is normally found in summer and winter and is least in spring and autumn.
Fig-2 Kalpana-1 IR image showing different features.
Thin cirus line
2.3 WV Imagery
Water vapour absorbs and reradiates electromagnetic radiation in the absorption band 6 -7 µm and is used for
detecting presence of moisture in the middle and upper levels (600 -300 hPa) of the atmosphere. However if air
is dry some radiations may come from layers as low as 800hPa. Like IR imagery it is also available at all times of
the day and night. In WV image, each pixel is assigned a gray shade according to the measured brightness
temperature where white indicates a very cold brightness temperature (radiation from a moist layer or cloud in
the upper troposphere), and black indicates a warm brightness temperature (radiation from the Earth or a dry
layer in the middle troposphere). But there is no such simple relationship between moisture and brightness of
WV image as some clouds (high & deep clouds and Cb anvils) also emits some radiation in WV band. Simply dark
region or black portion in WV imagery indicates an area of high temperature and the dryness of upper and
middle atmosphere and bright region or white portion in WV imagery depicts an area of low temperature and
moist upper and middle atmosphere or presence of tall/high cloud. One of most important feature of WV image
is presence of extensive & continuous structures of atmosphere so that cloud patterns which may appear
distinct from each other in the VIS & IR can be recognized in WV image as being a part of the same air mass. In
addition this characteristic of WV image also provides information about the swirling middle tropospheric wind
patterns and jet streams. The "moist" and "dry" features seen on WV imagery are resulting from various
combinations of vertical motion, horizontal deformation and moisture advection within the middle and upper
troposphere. WV image is therefore can be used to represent three-dimensional atmospheric motions on the
meso and synoptic scale. The boundaries between dark and light image gray shades in WV image indicate
transition zones between different moisture regime or cloud regime, which have important role in recognition of
various meteorological phenomenon. The greatest disadvantage of WV imagery is moist air or cloud in the lower
tropospheric level (near surface) is not depicted well in WV imagery.
Fig-3 Kalpana-1 Water vapour image.
2.4 Basic principles of satellite imagery interpretation
Six basic characteristics to identify clouds in satellite image are as follows:
(a) Brightness: - The brightness of a cloud in satellite imagery is one of the best indicators to determine the
thickness, composition and height of the cloud. In visible imagery higher (lower) brightness are associated with
thick (thin) clouds due to high (low) reflectivity. In IR imagery high (low) brightness represents cold (warm) cloud
top temperature. Higher brightness in water vapour imagery corresponds to high content of moisture in middle
and upper troposphere.
(b) Texture: - Texture of an image is the spatial arrangement of the elements which reveal the degree of
smoothness viz., smooth, fibrous, opaque, or mottled, of the image. It can only be seen in VIS imagery.
(c) Shape or Form of elements: – Individual Clouds element can assume a variety of shapes like round, straight,
scattered, diffuse or curved, whether regular or irregular.
(d) Pattern: - Cloud systems on satellite imagery can form recognizable patterns like linear, cellular, circular,
banded, comma, etc. The individual cloud elements can also be organized into identifiable patterns like squall
lines bands of med & high clouds and convective clouds in case of cyclones and wave pattern (in association with
trough and ridge). Cloud patterns may be, in general, associated with topography, air flow, vertical and
horizontal wind shear.
(e) Size: - The size of cloud pattern and individual element are useful indicator of the scale of weather system.
(f) Vertical Structure: - The information regarding the vertical structure of clouds can be obtained through
satellite imagery. In a visible image, shadow of taller clouds falls on lower surface. Cloud top temperature (CTT)
obtained from IR imagery is valuable parameter to asses the height of the cloud.
2.5 Some more important points to be remembered as mentioned below while
interpreting satellite imagery:
(a) Continuity in time has to be maintained.
(b) The pictures should not be viewed in isolation but must be interpreted with reference to past weather
and earlier imageries.
(c) It is necessary to keep in mind the time of the day, season and local peculiarities/topography while
interpreting satellite imageries.
(d) Similarly in different seasons (e.g. summer and winter) the image disc of the northern and southern
hemisphere will have different brightness.
(e) Local features like mountains and valleys introduce their own effects.
2.6 Different products derived from Kalpana-1 Imageries
Outgoing Longwave Radiation (OLR) Cloud Top Temperature (CTT)
Sea Surface Temperature (SST) Quantitative Precepitation Estimation (QPE)
Cloud Motion Vector (CMV) Water Vapour Wind (WVW)
2.7 Products of other satellites (Meteosat-7)
Vertical Wind shear
Vertical wind shear is calculated by subtracting the low-level layer-averaged flow (925-700mb) from the upper-level layer-averaged flow (150-300mb). The brown streamline contours indicate the direction of the shear. The yellow contours show the magnitude of the shear (kt).
Shear tendency over past 24 hours White solid lines for increasing trend. Blue dotted lines for decreasing trend. Black lines for no change in shear.
Lower level convergence Upper level divergence
Lower level winds Upper level winds
850 hPa vorticity Microwave Imagery (Available in http://www.nrlmry.navy.mil/TC.html)
3. Cloud Identification in Satellite Imagery
Unlike ground observation, which visually observes the cloud forms from the earth’s surface, the satellites
observe the behavior of the cloud tops far from above the earth. Also the resolution of sensors on board the
satellites are coarser than the human eye, and so the cloud form classification as detailed as surface observation
is impossible. Thus, we must understand that the cloud types identified by the satellites are basically different
from the cloud forms identified by surface observation. The complete interpretation of cloud structure must
make use of both satellite imagery and other available observational data.
3.1 Classification of Clouds
Using the different types of satellite imageries in combination the clouds can be divided into mainly three
categories viz., low, medium, and high, on the basis of their height/vertical development. Also the three types of
cloud genera viz, cumuliform, stratiform and cirriform of different height categories can be identified in satellite
imageries. Brightness of clouds in satellite imagery is a most important feature for distinction of different cloud
types viz., high clouds (Cirrus (Ci), Cirrostratus, Cirrocumulus, Anvil Cirrus), middle level clouds(Cm) and low
clouds(Cumulus(Cu), Stratus(St), Stratocumulus(Sc), Cumulonimbus(Cb), Cumulus Congestus (Cg)). So a
qualitative idea of cloud type identification by visible and infrared imagery on the basis of brightness is
illustrated in Fig-4
3.1.1 Low Clouds
The base height of low clouds can be less than 1km height above the earth surface. Cumulus, cumulonimbus,
towering cumulus, stratus/fog, and stratocumulus are the most commonly observed low clouds.
(a) Cumulus (Cu) clouds
Cumulus clouds usually formed as a result of atmospheric instability (mainly convective type due to land surface
heating. Cumulus clouds in satellite imagery can appear as a puffy or popcorn shape or ‘lumpy’ or detached
cauliflower with sharp outlines. These clouds can be rather isolated or they can be grouped together in clusters
better known as “open-cell” cumuli. Cumulus clouds can cause showers and thunder shower especially in lower
VIS Imagery: – Cumulus clouds are easily seen in visible picture if there are no other clouds above them. Large
individual elements and group of broken/scattered cumulus appear as bright white blobs of clouds. On the other
hand, the small individual elements of cumulus clouds are seen as gray areas.
IR Imagery: – Cumulus clouds covering a large area can only be seen as a dark gray shade.
WV Imagery: – Cumulus clouds can not normally be detected.
Fig-4 Qualitative idea of cloud type identification by visible and infrared imagery based
on brightness on the imagery.
(b) Cumulonimbus (Cb) clouds
Cumulonimbus clouds are multi-layer clouds with very strong vertical development, Cb clouds are tallest of all
clouds and in general they are associated with severe weather causing lightning, thunder, heavy rainfall and hail.
The top of the Cb may be flat, anvil-shaped and as high as 20km and base as low as 1-2km. The anvil-shaped
tops are formed because of the stronger winds at those higher levels of the atmosphere. Whenever, the vertical
wind shear is large a distinct edge of Cb on the windward side and fibrous indistinct edge of cirrus anvil on
leeward side can be seen.
VIS imagery: – appears as very white cloud with very bright top.
IR Imagery: – appears as very bright white tones with well defined boundaries (till anvil top is not fully
WV Imagery: - Cb is easily identified as bright white shades.
(c) Stratus Clouds (St) or Fog:
The main characteristics of Stratiform or layered clouds are: (i) they are lowest layer clouds (base height less
than 1 km); (ii) appear very flat or layered i.e., very little vertical development; and (iii) formed in a stable
atmosphere. This type of cloud causes no precipitation but can reduce the visibility drastically. In satellite
imagery, these clouds can be distinguished from other clouds by smooth, flat top and sharp boundaries. But,
stratus and fog are undistinguishable in satellite imagery.
Visible Imagery:- thick stratus and/or dense fog appear to have a uniform bright tone, smooth texture with
sharp boundaries. Shade becomes darker with decrease in density or thickness of clouds.
IR imagery:- stratus and fog are difficult to detect in IR imagery because of low temperature contrast between
these (very low) clouds/fog and surrounding surfaces. However, during daytime the contrast may be sufficiently
large especially over land areas and the stratus/fog may appear as uniform dull gray shade in IR image.
WV Imagery: - stratus and fog can not be detected in WV imagery.
(d) Stratocumulus (Sc) clouds
Stratocumulus is widely scattered cumulus clouds with very little vertical development or formed by the
convective development of stratus clouds along the low level flow. Only drizzle can be expected with
stratocumulus. These types of clouds can be seen throughout the tropics. In satellite imagery the stratocumulus
appears as a cluster or extensive cloud band formed by small cloud elements. Whereas the individual cloud
elements of stratocumulus are similar to small & medium cumulus except irregular shape.
Visible Imagery:- stratocumulus appears as cloud sheet or parallel bands and the shades varies from white to
light gray depending on the thickness/ density of the cloud.
IR Imagery: – medium to dark gray shades.
WV Imagery: – can not be detected.
3.1.2 Middle level Clouds
Middle clouds usually developed in between 2 and 5 km height and are composed of supercooled water
droplets and/or ice crystals. The main middle level clouds viz. Altocumulus, altostratus and Nimbostratus may be
observed independently and/or in combination of two or three in satellite imagery. Therefore they are difficult
to distinguish from each other. These clouds may occasionally be associated with some light precipitation.
(a) Altocumulus (Ac) clouds
These clouds have cellular appearance and the elements of clouds are often occurs in patches or sheets. Theses
clouds are usually accompanied /associated with large scale synoptic scale systems like tropical cyclones in
tropics. A well developed altocumulus can be seen in a satellite image in the absence of cirrus clouds above it.
Visible imagery: − appears as very bright white patches or sheets. If the size of the individual element of
altocumulus clouds is smaller than pixel resolution (as observed in most of the cases) than the gap between the
patches are lost and Ac will be very difficult to distinguish from altostratus. Altocumulus is also very difficult to
distinguish from stratocumulus because of almost same brightness and texture in visible imagery.
IR imagery: – appears as light gray shade. So, in IR imagery Ac (light gray) and Sc (medium to dark gray) can be
differentiated from each other, unlike visible imagery (both white).
WV Imagery: - Ac can be seen as light gray tones if there is no cirrus.
(b) Altostratus (As) clouds
Altostratus appears as a more uniform surface of clouds and individual elements are difficult to detect. These
clouds are often organised into bands or extensive sheets. Some light rain may experienced in association with
Visible imagery: − In most simplest case As can be identified as a uniform cloud surface in light gray shade in a
VIS imagery depending on the thickness of the layer.
IR imagery: – If As is thick a uniform medium gray will appear otherwise light gray shades only.
WV Imagery:- uniform light gray shades for thick As.
(c) Nimbostratus (Ns) clouds
Like cumulonimbus clouds these clouds are also called multi-layer clouds because sometimes their base height
may be as low as 1km and top at around 5km. These clouds are rain bearing clouds at lower altitude and have
great ability to cause severe weather - lightning, thunder, heavy rainfall etc.
Visible imagery: − a uniform clouds surface in white tone as in case of As.
IR imagery: – will appear white shade.
WV Imagery: - white but slightly lighter than IR imagery shades.
3.1.3 High Clouds
The clouds which developed at higher altitude, generally above 6km and maximum around 18km where
temperatures are very low, known as cirriform clouds (“cirro” means high). Cirriform clouds are composed of ice
crystals and have fibrous look. These wispy clouds appear very thin because of lower availability of moisture at
(a) Cirrus (Ci) clouds
In general the shape of Ci clouds look as thin hook, strands and filaments or dense tuff. These clouds often form
a very thin, long, fibrous, band structure, which may vary in width from few kilometer to 100-200km and length
may go beyond thousand of kilometer range.
Visible Imagery: – The shade of Ci clouds depends upon the underlying surface because of their thin structure. If
background is dark (ocean, forest etc) Ci will be have light gray shade and if the background is very bright (like
desert) it will disappear/invisible.
IR Imagery: – Thin Ci appears as light gray subject to considerable contamination. However, its appearance will
be brighter with the increase in thickness.
WV Imagery: - Cirrus usually appears white on water vapor images because their high-altitude ice crystals emit
"cold" 6.7 micron radiation.
(b) Cirrostratus (Cs) Clouds
In satellite imagery cirrostratus clouds form a smooth & uniform structure over a long broad band covering an
VIS Imagery: - Brightness of Cs clouds increases with thickness of the cloud layer. Thin Cs has light gray shades
and thick Cs layer may have white tone in VIS imagery. Thick Cs associated with tropical cyclone generally
appears white, smooth and organized pattern. Occasionally thick Cs may cast shadow on underlying surfaces.
IR Imagery: – In IR imagery Cs can have white or light gray tone depending on the thickness and small variation
in temperatures. Thick Cs will be difficult to separate from middle level clouds.
WV Imagery: – Cs will appear white to light gray shade although fibrous edges will not be seen.
(c) Cirrocumulus (Cc) clouds
Cirrocumulus clouds are formed by the vertical motion in upper troposphere. The size of the individual elements
of cirrocumulus is often below the radiometric resolution of geostationary satellite. So, Cc are difficult to
distinguish from Cs and thus it gives almost similar look as cirrostratus in all three (VIS, IR, WV) satellite
Anvil Cirrus clouds
Anvil cirrus is highest layer clouds at the top of the mature cumulonimbus cloud. They have sharp edge on the
upwind/windward side and very thin filmy, fibrous and indistinct edge on the downwind/leeward side of the
parent Cb clouds. In general anvil Ci has smooth texture; usually irregular shaped and aligned parallel to upper
VIS Imagery:– bright white tone just over the parent Cb clouds and brightness will reduce as the thickness and
distance from Cb clouds increases.
IR Imagery: – Anvil Ci will appear very bright over most active part of Cb clouds and as it moves away from active
convective cell its brightness will decrease due to spreading over large area and hence low density.
WV Imagery: – looks very bright over Cb clouds like in IR imagery.
Fig-5 Identification of different cloud types - Kalpana-1 (a) Visible and
(b) Infrared image of 17th August 2008 (0600UTC).
Fig-6 Identification of different cloud types - Insat-3A (a) Visible and (b) Infrared
Image of 4th January 2006 (0300UTC).
Fig-7 Kalpana-1 (a)VIS and (b)IR image of 19th September 2008(0600 UTC).
4. Weather systems as observed in Satellite images
In this chapter satellite observed features and identification of various weather systems, mainly emphasizing on
the weather events observed over Indian region in different season has been discussed. Also this chapter
includes some surface features which are identified with the help of satellite imageries.
4.1 Western Disturbances
A Western Disturbance (WD) is a synoptic scale weather system mainly during winter months which originate
over Mediterranean Sea, Black Sea and Caspian Sea and moves from west to east across Iran, Iraq, Afghanistan,
Pakistan and North India. Generally it can be seen as low pressure area, Cyclonic Circulation (Cycir) or trough in
lower tropospheric levels over North Pakistan. Also the WD’s are often associated with a trough in the middle
and upper troposphere which tilts westward with height. Geo stationary Satellite images are valuable source of
information for tracking such migratory disturbances due to its shallowness nature in case of weak systems.
The Kalpana-1 Visible image suggesting low level circulation over central Pakistan and neighbourhood and IR
image showing Comma shaped with organised banded structure convective clouds over northwest India in
association with an intense WD on 10th February 2007 are depicted in Fig-8(a) & (b). Well organized shape also
can be seen in water vapour imagery in Fig- 8 (c).
Fig-8 (a) Kalpana-1 VIS image of 10th February (0600UTC), 2007 indicating circulation over central Pakistan (b)
Kalpana -1 IR image of same time shows comma shaped banded structure in association WD over the area. (c)
Kalpana-1 WV imagery of same time shows circulation over central Pakistan and neighbourhood in
association with the WD.
A vortex in association with a typical WD over Afghanistan and neighbourhood are shown in Fig-9 (a) & (b)
Fig-9 Kalpana-1 (a) IR image of 0900UTC 25th March 2008 and (b) Water vapour winds showing a typical WD
over Afghanistan and neighbourhood.
The movement of WD’s can be observed through the animation of the satellite imageries
4.2 . Induced Systems
Occasionally under influence of intense WD’s lows or cycir’s develop in the lower troposphere over Rajasthan
and adj. West Madhya Pradesh (South of Lat 30˚N). Such disturbances are known as Induced Systems. These
systems can be recognized as low level circulation in organised low clouds in visible imagery. An example of
induced system is shown in Fig-10.
Fig-10 INSAT-1 composite image of 11th February 2002(0600 UTC) indicating an induced system over
Generally fog is a localized weather phenomenon. It is suspension of very small water droplets in the
atmosphere near surface level reducing the horizontal visibility to less than 1 km with relative humidity 75% or
more. On the basis of formation mechanism fog is classified into four types viz., Radiation fog, Advection fog,
Steaming fog and Frontal fog. Radiation and advection fog occur mostly over north India during winter. Fog
occurs over large areas mainly in its rear sector and sometimes ahead of it in association with western
disturbances. Recognition of fog is an important aspect in satellite meteorology. Simply fog is stratus clouds
which formed at ground level. In visible imagery fog appears with a smooth flat texture and sharp boundaries
(Fig-11 a & 12 a). Fog appears as dull gray shade or can not be seen at all in IR imagery. It is nearly impossible to
detect fog in IR imagery if land surface temperature almost equals to the temperature of the top of the fog as
seen in IR imageries of Fig 11 (b) & 12 (b). Normally to identify fog, both visible and IR imagery are used
simultaneously. Also good thumb rule may be followed is that if a smooth white cloud does not move in
animation of shorter period images, it is usually fog. Also, as fog evaporates, it usually from its outside, thinner
edge and works it way inwards. During day time fog can be easily detected from morning (0200UTC) onwards to
evening (1100UTC) in visible imageries.
Fig-11 (a) Visible image of 18th December 2008(0600 UTC) indicating fog over East India and
(b) corresponding IR image of the same time.
(a) (b) VIS IR
Fig-12 (a) Visible image of 30th December 2008(0500 UTC) indicating fog over Northwest India and (b)
corresponding IR image of the same time.
4.4 Sub-Tropical Jet Stream
Bands of strong westerly winds develop at high altitudes in the middle latitudes mainly due to large scale
temperature gradient between tropics and poles. Two bands of westerly winds in the upper atmosphere around
30° and 50 -60° latitude are usually present in each hemisphere. The poleward band referred as Polar jet stream
and the southern branch is called the Sub-Tropical westerly Jet (STWJ).
The STWJ is generally observed over North India from October to May and is strongest during the winter and its
mean location roughly along 27°N at 200 hPa level (12km) with mean wind speed at the jet core about 100 kts.
The jet stream axis is the area of highest velocity winds in a jet stream. An arbitrary lower limit 60 kts/hr is
assigned to the wind speed along the axis of the jet stream. A variety of common patterns can be used to
identify the jet stream axis through satellite imageries.
One most common indicator of position of jet stream axis is the cirrus clouds that tend to form on the southern
side of axis with well defined boarder on their pole ward edge. This border usually has a flattened ‘S’ shape and
jet stream axis locates just beyond the northern edge of the cirrus shield nearly parallel to this boarder. How the
cirrus shield formed in association with a Jet Stream is graphically shown in Fig-13.
When there is not enough moisture in the atmosphere to allow formation of a cirrus shield, cirrus streaks can be
observed parallel to the jet stream flow and to the right of the jet stream axis. Generally Cirrus streak can form
only with stronger wind speed 60 knots or more. The INSAT IR and WV images showing these features are
presented in Fig-14(a) & (b). However it could not be prominently observed in visible image (Fig-14 c).
If no cirrus clouds are present but other high and middle –level cloud exist the jet stream can still be identified.
Where the jet crosses a cloud formation the cloud bands will be most advanced downstream. The upstream
boarders will also be more advanced than the surrounding clouds making these clouds a ‘U’ or a ‘V’ shape. This
feature illustrated in Fig-15. Finally, as upper level airflow is often associated with a pronounced drying of the
upper atmosphere water vapour imagery has significant role for locating jet streams. The dryness appears in
water vapour imagery as a dark dry band is associated with the position of jet stream.
Fig-13 Cirrus shield in association with a STWJ.
Fig-14 (a ) IR and (b)WV image of 6th March, 2002 (0500 UTC) showing STWJ.
Fig-14 (c) Visible image of 6th March, 2002 (0500UTC) of 6th March 2002.
Fig-15(a) Advancement associated with a jet stream along a cloud band. (b) Kalpana-1 IR
image of 28th January 2006 showing Jet stream axis crossing the low/medium clouds.
Since Subtropical Westerly jet is an upper level phenomenon, it is observed clearly in IR and WV imageries but
not in VIS imagery
4.5 Easterly waves:
Easterly waves are waves/trough in the equatorial trade wind belts with a wavelength about 2000 – 2500 km.
They are observed in some parts of the tropics between 5°N to 15°N namely over North Atlantic, Mid Pacific and
in the Indian seas during November to March. These are weak waves and can be detected in the wind field than
in the pressure field and it is best seen at 700 -600hPa level. Easterly wave can be tracked with geostationary
satellite images. The convection and cloud formation associated with easterly wave is often observed in the
satellite imagery as an inverted ‘V’ pattern in clouds. Maximum cloudiness with convection can be seen on the
rare side of an easterly wave and medium/high level clouds can be seen on the ahead of the trough axis.
Kalpana-1 visible image of 20th December 2007 (0800 UTC) depicting the associated cloud pattern in association
with an easterly wave in Fig-16.
Fig-16 Kalpana-1 Visible image of 20th December 2007 (0800 UTC) showing the
associated cloud pattern in association with an easterly wave.
4.6 Inter Tropical Convergence Zone (ITCZ)
Maximum solar heating occurs at latitudes near the equator, warming the sea surface and causing the surface
air to rise. As the air ascends high into the atmosphere, it is replenished at the surface by the northeast trade
winds from the north and the southeast trade winds from the south. A narrow zone of convergence of trade
winds from both summer and winter hemispheres is known as ITCZ. The mean position of ITCZ for year as a
whole is 5°N and it is also called as the meteorological equator or the heat equator. It is associated with deep
atmospheric convection, heavy precipitation, and weak mean wind speeds. In Satellite imageries ITCZ is
observed as a complex cloud band encircling the earth. The cloud band characteristic of the ITCZ does not
always appear permanently around the equator, nor does is it take form of a continuous belt. Sometimes it is
seen in satellite images as a series of cloud clusters interspersed with clear areas due to presence of easterly
waves and mesoscale circulations.
The location of ITCZ varies depending upon the season and physiography. Seasonal northward migration of ITCZ
over Indian continent in the summer period brings monsoon and ITCZ shifted towards southward upto 5°S
during winter months. The cloud pattern in association with ITCZ and location of ITCZ at different season as can
be seen through satellite imageries is presented in Fig-17(a-d). However it may be remembered that there are
intra-seasonal variation in position of ITCZ as seen in Fig-17(e-g).
(a) VIS 10-02-2009 0300UTC 0300UTC
(b) VIS 18-05-2006 0500UTC
(c) VIS 30-06-2005 0900UTC (d) VIS 29-10-2008 0400UTC
Fig-17 (a-d) INSAT images showing the cloudiness in association with ITCZ in different season and indicating
the seasonal variation of location of the ITCZ. Rest three imageries (e-g) images showing the cloudiness in
association with ITCZ during October, November, and December 2009.
4.7 Convective activity
One of the most important weather phenomena during pre-monsoon season in India is mesoscale
convective systems viz., thunderstorms, squall lines, hailstorms, tornadoes etc.
A thunderstorm is a cumulonimbus storm that produces lightning and thunder. There are
different types of thunderstorms, some of which produce more severe weather than others. Lightning
is potentially deadly. Tornadoes, floods, and hail can be extremely destructive, dangerous severe
weather conditions. Satellite observations can play an important role in identifying the location of
The basic building block of thunderstorms is the thunderstorm cells. Life cycle of a thunderstorm cell has
three stages viz., Growing stage, mature stage and dissipating stage. A cumulus cloud begins to grow vertically
as a form of a tower (known as towering cumulus) to a height upto 6 km in the growing stage. In the mature
stage of the thunderstorm the clouds attains to its maximum height often upto 12 km or above. A mature
thunderstorm appears as bright white in all three channels VIS, IR and WV images because of the strong
(g) IR 29-12-2009 0600UTC
(e) IR 20-10-2009 1200UTC (f) IR 11-11-2009 1800UTC
reflection from Cb tops, low cloud top temperature and high moisture content respectively. In VIS images the
tall clouds may sometimes cast a shadow on the lower level clouds. The height of the Cb cells can be estimated
from the Cloud Top Temperature (CTT).
The upper portion of a thunderstorm cell which is extending upto upper tropospheric level can blown
away at a distance from parent cloud mass under influence of strong upper tropospheric winds. This distant
cloud masses is known as thunderstorm anvil. An IR image with CTT contour analysis showing an intense
thunderstorm cell with anvil is depicted in Fig-18. The direction and speed of movement of the anvil away from
its parent thunderstorm depends upon winds at the anvil level. The thunderstorm anvils can be seen in IR
images as bright white oval-shaped cloud masses. Sometimes a domed- structure of a thunderstorm that
extends above the anvil, often into the stratosphere may be observed is known as the Overshooting top. It can
be seen in VIS images as the cauliflower cloud structure extending above the anvil like a dome.
Most of the severe thunderstorms are of multi-cell or super-cell type. In case of super cell type of
thunderstorm the entire storm behaves as if it is a single cell and it may persist for many hours. Super cell
thunderstorm produces tornados or hailstorms. A super cell thunderstorm may evolve into a rotation circulating
called a meso-cyclone which can generate a tornado. A squall line is composed of individual intense Cb cells
arranged in a line (150-250 km long), or band. They occur along a boundary of unstable air, which gives them a
East and North Eastern region of India is highly prone to violent thunderstorm activity known as Nor’wester
(moving from NW direction) particularly during premonsoon season. Convective dust storms over northwest
India, particularly Rajasthan, occur during March to June which is locally called Aandhi’s. Development of
premonsoon afternoon thunderstorm cells as observed in satellite imageries over east India manifested as
squally weather over different parts of west Bengal on 25th April 2007 is shown in Fig-19. A satellite image
showing duststorm over northwest India is presented in Fig-20.
Fig-18 IR image with CTT contour analysis of 15th April 2007(1500 UTC) indicating intense premonsoon
thunderstorm cell over East India.
Fig-19 Kalpana –IR imageries of different hours of 25th April 2007 showing the development of
premonsoon thunderstorm cells over East India.
Fig-20 Satellite image view of a dust storm over Northwest India.
Different aspects of monsoon like (a) onset of monsoon (b) advance of monsoon (c) low level jet (d)
tropical easterly jet (e) monsoon depression (f) Off-shore trough and off- shore vortex (g) Tibetan High (h)
Mascarine High (i) active monsoon (j) Break Monsoon (k) Withdrawal of Monsoon etc can be observed in
satellite imageries and products.
Different features are depicted in the following figures.
(a)1100 UTC (b)1200 UTC
Fig-21 Kalpana -1 IR imageries with CTT contour analysis of (a) 27th (0300UTC) and (b) 28th May 2007 showing increase of convection over area 0 -15°N and east of long 60°E and its gradual movement towards west coast before onset of monsoon
Fig-22 (a) OLR on 1st June 2013
Fig-22 (b) SSM/I derived (i) wind speed and (ii) Columnar water vapour on 30th May 2008 indicating maximum
wind speed greater than 16ms-1 and water vapour more than 6 gm/cm2 in the box defined by 5-10°N and 55-
80°E before onset of monsoon.
(a)Visible image 0300 UTC 7th June 2008 (b) IR image with CTT analysis 0300 UTC 7th June 2008
(c ) Water vapour image of 00UTC 7th June 2008
Fig-23(a-c) Satellite imageries showing progress of monsoon. The overlying green line over water vapour
imagery is the northern limit of monsoon as on 7th June, 2008.
Fig-24 METEOSAT-7 derived low level winds of 9th August 2008(0000 UTC) showing LLJ stream.
Fig-25(a) Kalpana-1 IR imagery of 7th August, 2008 shows location of tropical easterly Jet.
Fig-25(b) Meteosat-7 derived water vapour winds of 7th August, 2008 showing tropical easterly Jet stream.
Fig-26 Visible image of 16th Sept,2009(0300UTC) depicting monsoon depression
Fig-27 Kalpana-1 visible image of 29th August 2008(0600 UTC) shows cloud organization indicating circulation
(MTC) over Gujarat adjoining NE Arabian Sea.
Fig-28 Meteosat derived water vapour winds of 21st July 2008 (00UTC) showing the location of Tibetan High.
Fig-29 Scatterometer surface winds of 23rd June 2008 indicating the position of
Mascarine High near 33.00 S/60.00E.
Fig-30 Kalpana-1 IR image (02.08.2007 1200UTC indicating cloud
pattern in association with active monsoon current.
Fig-31 Kalpana-1 (a) Visible and (b) Infrared with CTT analysis imageries of week monsoon day 13th July 2008.
Fig-32 Water vapour imageries of 26 -29th September 2008 shows gradual decrease of moisture over
northwest and central India which is an indicator of withdrawal of monsoon.
4.9 Snow covered area
Snow, as a ground features can be best seen in visible imageries. It appears bright white to light gray depending
on the reflectivity of the snow in the visible imageries. Generally fresh snow has the higher reflectivity than old
snow. Also rain falling over snow covered area will reduce its reflectivity. The lower elevation area or valleys in
the snow covered mountainous region are seen as a black area due to lack of snow over those particular
portions. This pattern is known as ‘Dendritic Pattern’ (Fig-33). Fresh snow may appear very white and resemble
cloud cover. To distinguish between the two it is very useful to see the animation of a series of imageries as the
cloud usually move but snow does not.
Fig-33(a) Kalpana-I VHRR and (b) INSAT-3A CCD visible images for 1st Jan’2010 showing snow cover over Jammu and Kashmir and neighbourhood.
Sunglint is simply a bright area, often seen in visible imagery, produced by reflection of the Sun’s disc off water
surface of large water bodies like oceans, large lakes or rivers. It can be seen as small very bright spot or a large
dull area with diffuse boundaries depending on the location, roughness or smoothness of water surface and
even the distribution of low level aerosols. Reason of appearance of sunglint in visible imagery is illustrated in
Fig-34. If the water surface is smooth, the reflectance is similar to that of a mirror and the sun rays will be
reflected at point ‘B’ into the satellite sensor directly and ‘B’ will appear very bright in imagery. Outside this
area, at point ‘A’, sunlight reflected from the water surface completely misses the satellite sensor, as shown by
‘C’. At ‘A’ Satellite see only reflections from outer space (D) and A will appear as dark on the imagery. Sunglint
always be seen between satellite subpoint (location directly below the spacecraft) and solar subpoint (the point
where the sun’s direct rays strike the earth). It may seem that sunglint is a nuisance in image but interestingly it
provides some clues about the sea state weather. Appearance of very bright sunglint(Fig-35) indicates calm or
light surface winds over the area (Smooth surface) whereas weaker or diffuse sunglint(Fig-36) attributed to the
relatively rough sea surface or higher waves.
(a) Kalpana-I VHRR
30 70 70
Fig-34 Creation of Sunglint (not drawn to scale).
Fig-35 Bright sunglint in (a)visible image and (b)corresponding IR image. .
Fig-36 Diffuse sunglint in (a) Visible image and (b) corresponding IR image.
(a)17.03.2009 0800 UTC (b)17.03.2009 0800UTC
(a)16.03.2009 0730 UTC (b)16.03.2009 0730UTC
5 Satellite observation and analysis of Tropical Cyclones
A Tropical cyclone is a very intense low pressure system in which maximum sustained wind speed at surface
level exceeds 33 knots. Climatologically cyclones are developed over Indian Seas during pre-monsoon and post-
monsoon season with a primary peak in November and a secondary peak in May. The classification of low
pressure systems over Sea based on maximum sustained wind speed at surface level associated with the system
as adopted in India is mentioned in the Table-1.
Table-1 Classification of low pressure systems over Sea.
Systems Maximum sustained wind
speed in Knots
Maximum sustained wind
speed in KMPH
Low pressure area <17 <31
Depression 17 - 27 31-49
Deep Depression 28 -33 50-61
Cyclonic Storm 34 - 47 62-88
Severe Cyclonic Storm(SCS) 48 - 63 89-117
Very Severe Cyclonic Storm(VSCS) 64 - 119 119-221
Super Cyclonic Storm >119 >220
Analysis of tropical cyclones is being carried out at Satellite Meteorology division of India Meteorological
Department by using Dvorak Technique. Here a brief of the Technique is described in this chapter.
5.1 Dvorak technique to estimate tropical cyclone position and intensity
The Dvorak technique is based on the analysis of cloud patterns in visible and infrared imagery from
geostationary and polar-orbiting satellites. The technique evolved during 1970 -1984 and matured over an
extended period based on the studies of tropical cyclones over West Pacific and Atlantic basins so that there is
no single reference that wholly defines the application of the technique. However the document “Workbook on
Tropical Cloud Systems.’ published in 1990; tries to brings together a collection of notes regarding application of
the technique as a reference for operational forecasters.
5.2 Physical Basics of the Technique
The technique mainly based on four distinct geophysical properties viz., Vorticity, Vertical Wind Shear,
Convection and Core Temperature that relate organized cloud patterns to TC intensity. The vorticity, a
measurement of strength and distribution of circular winds organizes the clouds into patterns that Dvorak
relates to the Maximum sustained Wind (MSW) associated with tropical cyclone. The shear is kinematics force
that acts to distort the vorticity consequently the cloud pattern. Dvorak found that degree distortion was also
related to the MSW. The thermodynamic parameter convection in the bands of the outer core of the cyclone
also figures in the cloud pattern recognisation and scene type assignment. Another thermodynamic property the
inner core temperature relates convective vigor to intensity in the technique.
5.3 Evolution of the Technique
Initially Dvorak derived an empirical method relating TC clouds structure to storm intensity using a simple
numerical index the Current Intensity (CI) corresponding to the maximum sustained wind (MSW) as shown in the
Table.5.2 (Dvorak 1972, 1973). Large evolution of the technique had done during 1970-1980s which was mostly
reliant on pattern-matching concepts and the application of Dvorak’s development/decay model. The significant
revisions of 1982 and 1984 shifted the emphasis of the technique toward direct measurement of cloud features.
Table-2 The empirical relationship between CI and MSW.
Current Intensity Maximum Sustained Wind(MSW) in
Maximum Sustained Wind(MSW) in
1.0 25 46.3
1.5 25 46.3
2.0 30 55.6
2.5 35 64.9
3.0 45 83.4
3.5 55 101.9
4.0 65 120.5
4.5 77 142.7
5.0 90 166.8
5.5 102 189.0
6.0 115 213.1
6.5 127 235.4
7.0 140 259.5
7.5 155 287.3
8.0 170 315.1
5.4 Basic Steps in Dvorak Technique
In Dvorak technique mainly Visible and Enhanced Infrared (EIR) imagery and sometimes Digital Infrared imagery
are used for analysis. The analysis consist ten basic steps as shown in the flow chart (Fig-37)
Fig-37 Flow chart for determining Cyclone intensity
For details of the technique please refer “Tropical Cyclone Intensity Analysis Using Satellite Data” by Vernon F
Dvorak (NOAA Technical Report NESDIS 11, Sept 1984)
6 Most recent Indian Geo-stationary satellites INSAT-3D and
INSAT-3D which is an exclusive meteorological geostationary satellite carries advanced meteorological
payloads of a six channel imager and 19-channel sounder. It has a Data Relay Transponder (DRT)
similar to Kalpana-1 and INSAT-3A. The characteristics of different channels of INSAT-3D imager are
listed in Table.3. Also the same of KALPANA-1 Satellite also included in this Table for comparison.
Table.3: INSAT-3D imager channels characteristics.
Spectral Band Wave length (m) Ground Resolution (km)
INSAT-3D KALPANA-1 INSAT-3D KALPANA-1
VIS 0.55-0.75 0.55-0.75 1 2
SWIR 1.55-1.70 1
MIR 3.80-4.00 4
WV 6.50-7.10 6.50-7.10 8 8
TIRI 10.3-11.3 4
TIR2 11.5-12.5 11.5-12.5 4 8
9.1.1 Various Meteorological products of INSAT-3D and expected improvements
Higher resolution imageries from different channels of INSAT -3D Imager and multi- channel imaging facility is
expected to improve the better understanding of different types of weather analysis through satellite technique
especially meso-scale weather phenomena. In addition, accuracy in detection of centre & estimation of intensity
of tropical cyclone is expected to improve as higher resolution imageries will be available for analysis. The
geophysical Parameters derived from INSAT -3D Imager are mentioned in Table.4. Some new
meteorological/geophysical parameters are evaluated in addition to the improvement of current available
products obtained from Kalpana-1/INSAT-3A as mentioned below. The INSAT -3D products is available in every
half hour interval.
Table.4. Geophysical Parameters to be derived from INSAT -3D (sounder)
Parameters Input Channels Sl.
Parameters Input Channels
1. Outgoing Long wave
TIR -1, TIR -2,
10. Water Vapor Wind
WV, TIR -1, TIR -2
TIR -1, TIR -2,
11. Upper Tropospheric
WV, TIR -1, TIR -2
3. Sea Surface
SWIR,TIR -1, TIR
12. Temperature, Humidity
profile & Total ozone
4. Snow Cover VIS, SWIR, TIR -
1, TIR -2
13. Value added parameters
from sounder products
5. Snow Depth VIS, SWIR, TIR -
1, TIR -2
14. FOG SWIR, MIR , TIR -
1, TIR -2
6. Fire MIR, TIR -1 15. Normalized Difference
7. Smoke VIS, TIR -1,
TIR -2, MIR
16. Flash Flood Analyzer TIR -1, TIR -2, VIS
8. Aerosol VIS, TIR -1, TIR -
17. HSCAS VIS
9. Cloud Motion Vector
VIS, TIR -1, TIR -
18. Tropical Cyclone-intensity
Quantitative Precipitation Estimate (QPE):
Hydro-Estimate is used instead of presently used Arkin’s technique to evaluate QPE which able to identify
convective & non-convective clouds and limitation of 72mm in three hour is removed.
Outgoing Long-wave Radiation (OLR):
Algorithm for derivation of this parameter are same as earlier i,e SBDART (Santa Barbara DISORT Atmosphere
Radiative Transfer model) however there are be three input channels data viz., TIR1, TIR2 & WV.
Fog can also be detected at night time in INSAT-3D as it is retrieved by using BT difference between 10.8 &
3.9µm channel. At present fog can be seen during day-time through visible imagery.
Sea surface SST:
In INSAT-3D multiple channel (SWIR, TIR -1, TIR -2, MIR) MODTRAN, which ensure better accuracy are used to
retrieve SST whereas at present Mean Estimate Histogram technique is used for single channel SST
Cloud Motion Vector (CMV):
In INSAT-3D, TIR1, TIR2 & WV Band are used to derive CMV. Pattern matching is carrying out by Genetic
algorithm and H2O plus IR-Window intercept technique is used for height assignment.
Water Vapour Winds (WVW):
Recently WV winds are derived by using WV band from Kalpana-1 only in INSAT-2E system. In INSAT-3D for
pattern matching Genetic algorithm are used.
The snow cover mapping (SCM) algorithm is use Normalized Difference Snow Index (NDSI) and other spectral
threshold tests (like NDVI & IR BT) SCM is identify snow on a pixel-by-pixel basis.
The INSAT-3D Sounder system has one visible channel and 18 infrared channels with 10x10 Km spatial
resolution for each channel at nadir. It provide vertical profiles of temperature and humidity and total ozone.
Also there is provision for readily availability of some derived parameters. The geophysical Parameters to be
derived from INSAT -3D sounder are mentioned in Table.5.
Table.5. Geophysical Parameters to be derived from INSAT -3D (sounder)
Sl. No. Parameters Input Channels
1. Temperature and
Brightness temperatures for 18 Sounder Channel and gray count for
2. Geo-potential Height Sounder retrieved temperature and humidity profiles at 40 pressure
3. Layer Precipitable
Retrieved humidity at standard pressure levels
4 Total Precipitable water Retrieved humidity at standard pressure levels
5. Lifted Index Sounder retrieved temperature and humidity profiles at standard
6. Dry Microburst Index Sounder retrieved temperature and humidity profiles at standard
7 Maximum Vertical
Sounder retrieved temperature and humidity profiles at standard
8 Wind Index Geo- potential Height and retrieved temperature and humidity profiles at
standard pressure levels
9 Ozone Brightness temperatures for 18 Sounder Channel and gray count for