improved observation of real time events: what can msg provide …rsmc.weathersa.co.za/gdpfs2/day...
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Improved observation of real
time events:
What can MSG provide to us
for nowcasting purposes? Estelle de Coning
South African Weather ServiceSome slides taken from EUMETSAT training events, Jochen
Kerkmann
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• Located along the equatorial plane.
• About 36000 km above the earth
• Has Geo-synchronous orbit
• Period of 1436 minutes
• Good coverage from remote areas
• Has wide field of view ~ 50 degrees
• Has low resolution
• Provides continuous data ~ 15-30 min.
• Not very suitable for vertical soundings
• Near polar orbiting
• 800 -900 km above the earth
• Has Sun-synchronous orbit
• Period of 101 minutes
• Excellent coverage at the poles
• Has relatively narrow field of view
• Has high resolution
• Passes vary with latitude
• Very suitable for vertical soundings
GEO LEO
1. SATELLITE ORBITS
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1. SATELLITE ORBITS (cont)
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1. SATELLITE ORBITS (cont)
GEO satellites
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Meteosat-10
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3 km data sampling intervals, except HRV (1 km)
Images each 15 minutes (5 minutes Met-8 rapid scan)
Band (um) Band (um)
VIS 0.6 0.56 - 0.71 WV 6.2 5.35 - 7.15
VIS 0.8 0.74 - 0.88 WV 7.3 6.85 - 7.85
NIR 1.6 1.50 - 1.78 IR 9.7 9.38 - 9.94
MIR 3.9 3.40 - 4.20 IR 13.4 12.40 - 14.40
IR 8.7 8.30 - 9.10
IR 10.8 9.80 - 11.80 High Res VIS
IR 12.0 11.00 - 13.00 HRV 0.4 - 1.1
The MSG channels
WINDOW channels
MSG Channel Differences Useful to
Monitor Convection
Channel Diff. Application
IR8.7 - IR10.8 Day/Night: optical thickness, phase
IR10.8 - IR12.0 Day/Night: optical thickness
NIR1.6 - VIS0.6 Day: phase (ice index), particle size
IR3.9 - IR10.8 Day: particle size
Night: particle size (only for warm clouds)
WV6.2 - IR10.8 Day/Night: overshooting tops
Why is it important to know whether we see
small/large ice particles and whether
clouds are thin/thick?
• Thick clouds can be Cb
• Ice inside clouds can become hail on the
ground
• Strong updrafts produce small ice particles
which can indicate severe convection
picture form Brian A. Morganti
strong updraft weak updraft
small ice particles large ice particles
picture form Charles Pfeil
Small / Large Ice
Particles in Cb Clouds
MSG Red-Green-Blue(RGB)
combinations
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Standard RGBs
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1.
2.
3a.
3b.
4.
5.
6.
RGB Composite Applications Time
RGB 10-09,09-07,09: Dust, Clouds (thickness, phase), Contrails Day & Night
Fog, Ash, SO2, Low-level Humidity
RGB 05-06,08-09,05 Severe Cyclones, Jets, PV Analysis Day & Night
RGB 10-09,09-04,09: Clouds, Fog, Contrails, Fires Night
RGB 02,04r,09: Clouds, Convection, Snow, Fog, Fires Day
RGB 05-06,04-09,03-01: Severe Convection Day
RGB 02,03,04r: Snow, Fog Day
RGB 03,02,01: Vegetation, Snow, Smoke, Dust, Fog Day
R = Channel 02 (VIS0.8)
G = Channel 04r (IR3.9, solar component)
B = Channel 09 (IR10.8)
RGB 02, 04r, 09
("Day Microphysical")
Applications: Cloud Analysis, Convection, Fog, Snow, Fires
Area: Full MSG Viewing Area
Time: Day-Time
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RGB 02, 04r, 09: Interpretation of Colours
for High-level Clouds
Deep precipitating cloud
(precip. not necessarily
reaching the ground)
- bright, thick
- large ice particles
- cold cloud
Deep precipitating cloud
(Cb cloud with strong
updrafts and severe
weather)*
- bright, thick
- small ice particles
- cold cloud
*or thick, high-level lee
cloudiness with small ice
particles
Thin Cirrus cloud
(large ice particles)
Thin Cirrus cloud
(small ice particles)
Ocean Veg. Land Fires / Desert Snow
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RGB 02, 04r, 09: Interpretation of Colours
for Mid-level Clouds
Supercooled, thick
water cloud
- bright, thick
- large droplets
Supercooled, thick
water cloud
- bright, thick
- small droplets
Supercooled thin water
cloud with large droplets
Supercooled, thin water
cloud with small droplets *
* or, in rare occasions,
thin Ci cloud with small
ice particles
Ocean Veg. Land Fires / Desert Snow
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RGB 02, 04r, 09: Interpretation of Colours
for Low-level Clouds
Thick water cloud
(warm rain cloud)
- bright, thick
- large droplets
Thick water cloud
(no precipitation)
- bright, thick
- small droplets
Thin water cloud with
large droplets
Thin water cloud
with small droplets
Ocean Veg. Land Fires / Desert Snow
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Maputo
MSG-1, 6 November 2004, 12:00 UTC, RGB VIS0.8, IR3.9r, IR10.8
Thick Ice Cloud
(small ice)
Thick Ice Cloud
(large ice)
Example: Cloud Particle Size
RGB 02, 04r, 09 Example: Fires
MSG-1, 7 September 2003, 11:45 UTC ("winter" enhancement)
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R = Difference WV6.2 - WV7.3
G = Difference IR3.9 - IR10.8
B = Difference NIR1.6 - VIS0.6
RGB 05-06, 04-09, 03-01
("Convective Storms")
Applications: Severe Convective Storms
Area: Full MSG Viewing Area
Time: Day-Time
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RGB 05-06, 04-09, 03-01:
Interpretation of Colours
Deep precipitating cloud
(precip. not necessarily
reaching the ground)
- high-level cloud
- large ice particles
Ocean Land
Thin Cirrus cloud
(large ice particles)
Thin Cirrus cloud
(small ice particles)
Deep precipitating cloud
(Cb cloud with strong
updrafts and severe
weather)*
- high-level cloud
- small ice particles
*or thick, high-level lee
cloudiness with small ice
particles
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Maputo
MSG-1, 6 November 2004, 12:00 UTC, RGB 05-06, 04-09, 03-01
Thin Ice Cloud
(small ice)
Thick Ice Cloud
(small ice)
Thick Ice Cloud
(large ice)
Thin Ice Cloud
(large ice)
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Colour enhanced HRV RGB
(HRV, HRV, IR10.8i)
Channel 12 (HRV) RGB HRV-HRV-IR10.8i
MSG-1, 8 September 2003, 15:00 UTC
Cold, thick, high-level clouds Thin Cirrus clouds / Contrails
over vegetated land / ocean over sand desert
Ocean Warm Desert Cold Desert Warm Land Cold Land
RGB 24-hour (Dust) Microphysics:
Interpretation of Colours for High-level Clouds
RGB 24-hour (Dust) Microphysics:
Interpretation of Colours for
Low/Mid-level Clouds
Ocean Warm Desert Cold Desert Warm Land Cold Land
Thick, mid-level
cloud
Thin, mid-level
cloud
Low-level cloud
(cold atmosphere,
Europe)
Low-level cloud
(warm atmosphere,
Africa)
Dust Storm
night
day
Example: Dust (Day)
MSG-1, 14 July 2003, 10:00 UTC
EUMETSAT case study website
• http://www.eumetsat.int/website/home/Images/ImageLibrary/index.html
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Back to 16 October 2014
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ConvRGB
0600 –
1500 UTC
Back to 16 October 2014
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DayM RGB
0800 – 1500
UTC
Back to 16 October 2014
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HRVRGB
0600 –
1500 UTC
Back to 16 October 2014
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Dust RGB
0900 on 16
Oct to 0500
UTC on 17
Oct
Case study on dust stormhttp://www.eumetsat.int/website/home/Images/Ima
geLibrary/DAT_2358887.html
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Summary• MSG images/RGBs provide more than the usual
amount of information on real time features in
satellite
• Different RGB products exist for different
purposes. Using the standard RGBs provided,
gives us common ground from comparisons
• Nowcasting of Convection is done best with the
Convection RGB, DayM, HRV RGB
• Convection and the dust storm could clearly be
seen using these RGBs on 16 October 2014
• Severe weather (hail and tornado) could not be
seen clearly 31
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