improved observation of real time events: what can msg provide …rsmc.weathersa.co.za/gdpfs2/day...

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

1

• 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

2

1. SATELLITE ORBITS (cont)

3

1. SATELLITE ORBITS (cont)

GEO satellites

4

Meteosat-10

5

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

9

Standard RGBs

10

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

11

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


(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

12


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


13


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


14

15

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)

16

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

17

RGB 05-06, 04-09, 03-01:

Interpretation of Colours


(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)


(Cb cloud with strong

updrafts and severe

weather)*

- high-level cloud

- small ice particles

*or thick, high-level lee

cloudiness with small ice

particles

18

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)

19

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

25

http://www.eumetsat.int/website/home/Images/ImageLibrary/index.html

Back to 16 October 2014

26

ConvRGB

0600 –

1500 UTC


27

DayM RGB

0800 – 1500

UTC


28

HRVRGB

0600 –

1500 UTC


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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

30

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

improved observation of real time events: what can msg provide …rsmc.weathersa.co.za/gdpfs2/day...

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