Effective training and use of RGB

satellite products for Forecasters

Incorporating feedback from EumetSAT RGB Satellite Products Workshop: 17-19 September 2012

Feedback from Jochen Kerkmann, Bureau staff and forecasters.

Material from EumetSAT, JMA, SAWS, UKMO

Topics covered here

• What are the Red/Green/Blue (RGB) products and why do we need to use these ?.

• European Organisation for the exploitation of Meteorological Satellites (EUMETSAT) recommendations for the use of RGB image products within an operational environment

• Strategies for effective training and presentation of RGB products within the Bureau of Meteorology (BOM) forecasting environment.

• RGB product visualisation and training resources currently available

from JMA

Timeline for Himawari 8/9

April

NOW – MTSAT 2

FROM 2015 – Himawari 8

Changes in satellite data for BOM – data volume

Changes in satellite data for BOM – temporal frequency

FROM 2015 – Himawari 8

Using MODIS imagery to create RGB product (Dust RGB)

IR 12.0

IR 10.8

IR 10.8

IR 10.8

IR 8.7

Red beam

Green beam

Blue beam

Final Microphysics Dust RGB

-

-

North-western Australia, 10 October 2012

Using MODIS imagery to create RGB product (Dust RGB)

North-western Australia, 10 October 2012

Creating an RGB image

The process of creating an RGB has five steps.

Step 1: Determine the purpose of the product

Step 2: Based on experience or scientific information, select three

appropriate channels or channel derivatives (such as an inter-channel difference) that provide useful information for the product

Step 3: Pre-process the images as needed to ensure that they provide or

emphasize the most useful information. Washed out image changed to one with high contrast.

Step 4: Assign the three spectral channels or channel derivatives to the

three RGB color components. To assign the spectral channels to the right

primary colors, we need to know how each channel responds to key atmospheric and surface features.

Step 5: Review the resulting product for appearance and effectiveness.

Most natural looking product. Highlight colours (red, yellow etc.) for most important phenomena (severe storm tops etc.)

From the COMET module “Multispectral Satellite Applications: RGB PRODUCTS EXPLAINED”http://www.meted.ucar.edu/npoess/multispectral_topics/rgb/

Condensate / phase

WV6.2 -

WV7.3

Optical thickness

IR3.9 -

IR10.8

Condensate / phase

NIR1.6 -

VIS0.6

Example: Severe Convection RGB; northern QLD, 1 November 2009 0435 UTC

Severe Convection RGB beams explained

• Yellow is made by mixing red and green

• Magenta is made by mixing red and blue

• Cyan is made by mixing green and blue

Large ice particles +26 to +35 K. Small ice particles +65 to +73 K. (Kerkmann)

IR3.9-IR10.8

Large negative RD1.6−−−−0.6 indicates ice clouds – black in the RGB

Much larger RD1.6−−−−0.6 is typical for the surface. (Lensky et al.

2008)

1.6-0.6 reflectance

Overshooting Cb clouds have near zero or even slightly positive BTD6.2−−−−7.3

The surface shows large negative BTD6.2−−−−7.3 values. (Lensky et

al. 2008)

BTD6.2−−−−7.3

Combining beams

from RGB Products Overview (RGB Tutorial)J. Kerkmann EumetSAT

Comparing the single infrared channel versus the 24 hour microphysical (Dust) RGB. North Africa

What are the advantages of using the RGB

image over the single channel image ?. What are the disadvantages ?.

Improvements• Texture of clouds (combines VIS and IR attributes)

• Higher information content – many colours.

• Defines features (dust cloud) that are not visible in the infrared.

Disadvantages

• Lots of colours / colour gradations – interpretation more difficult. More subjective. Animation of images may help – differentiate surface from atmosphere.

• Colourblind people will have major problems using this data

RGB products for Operational Forecasting –EumetSAT recommendation

Five application specific RGBs

24 hour Microphysical RGB Airmass RGB

Day

Microphysical

RGB

Night

Microphysical

RGB

Day Severe

Convection

RGB

Snow / fog

RGB

Natural

Colours RGB

Two RGB composites which complement each other

from RGB Products Overview (RGB

Tutorial)J. Kerkmann EumetSAT

EUMETSAT strategy of using RGB products – 2 “24-hour products” that are used all the time and 5

application specific RGB products.

At WMO level: agree on a strict minimum of harmonised RGB composites. The following strategies for the application of RGB

products to the forecasting routine were outlined:

Two RGB composites which complement each other are used

all of the time. These are the 24 hour Microphysics RGB and the Airmass RGB.

Five application specific RGB products (Day Microphysics RGB,

Night Microphysics RGB, Day Convective Storm RGB, Day Snow-Fog RGB, Natural Colours RGB) are used selectively

when appropriate.

24 hour RGB composites

North Africa South Atlantic

24-h Microphysics RGB

(Dust RGB) Airmass RGB

Cold, thick high-level

clouds

Thick mid level

cloud Cold Airmass

Jet (high PV)

Warm Airmass

Thick, high level clouds

Thick low level

clouds (cold

airmass)

Thick, mid level clouds

Low-level cloud

(cold atmosphere)

Warm Desert

Dust (day)

Dust (night)

Ocean / warm

land

From RGB Products Overview (RGB Tutorial) J. Kerkmann EumetSAT, also EumetSAT Image Library

Channel combination “recipes’ of the 24 hour

Microphysics (Dust) RGB vs the Airmass RGB

1.01.0+243 ... +208 KWV6.2Blue

1.01.0-40 ... +5 KIR9.7 – IR10.8Green

1.01.0-25 ... 0 KWV6.2 - WV7.3Red

Gamma 2GammaRangeChannelBeam

Airmass RGB

1.0+261 ... +289 KIR10.8Blue

2.50 ... +15 KIR10.8 – IR8.7Green

1.0-4 ... +2 KIR12.0 – IR10.8Red

Gamma 2GammaRangeChannelBeam

24 hour dust microphysics RGB

1.0

1.0

1.0

Actually, there are three 24 hour Microphysics RGB products with subtle differences.

8 November 2005, 12:00 UTC

From RGB Products Overview (RGB Tutorial) J. Kerkmann EumetSAT

Airmass RGB

24-h Microphysics RGB(Dust RGB)

24-h Microphysics RGB(Ash RGB)

24-h Microphysics RGB(Cloud RGB)

The reason why the ranges for the blue beams in the ash RGB and the dust RGB

are different. Dust clouds are usually lower and warmer than ash clouds.

The ranges for the green beam are different because dust over desert needs a

range of 0 to 15 K (to account for the low emissivity of sand in IR8.7) while SO2

clouds are better visible when the range is lower from -4 to +6K (J.Kerkmann pers.

comm. 2012)

24 hour Ash

Microphysics RGB

24 hour Dust

Microphysics RGB

24 hour Cloud

Microphysics RGB

1.0+243...+3031.0+261...+2891.0+248...+303IR10.8Blue

1.0-4 ... +5 K2.50 ... +15 K1.20 ... +6 KIR10.8 – IR8.7Green

1.0-4 ... +2 K1.0-4 ... +2 K1.0-4 ... +2 KIR12.0 – IR10.8Red

GammaRangeGammaRangeGammaRangeChannelBeam

Channel combination “recipes” for the three classes of 24-hour Microphysics RGB product

from Tri-spectral Window RGB Applications with MSG SEVIRI (24-h Microphysics RGB) J. Kerkmann

Application specific RGB’s

Day Microphysical RGB Night Microphysical RGB Day Convection RGB

Snow / fog RGB

Natural Colours RGB

Natural ColoursNatural Colours

RGBRGB

Applications:Applications:Vegetation, Dust, Smoke, Fog, Snow

Time:Time:Day-Time

Day Micro Day Micro ––

physical RGBphysical RGB

Applications: Applications: Cloud

Analysis (most

sensitive to cloud drop

size), Convection,

Fog, Snow, Fires.

Time:Time: Day-Time

Day Convection Day Convection

RGB RGB

Applications: Applications: Severe Convective Storms

Time:Time: Day-Time

Night Micro Night Micro --

physical RGBphysical RGB

Applications: Applications: Cloud

Analysis, Fog,

Contrails

Time:Time: Night-Time

Snow/fog RGBSnow/fog RGB

Applications:Applications:Fog/low cloud, snow

Time:Time:

Day-Time

Application specific RGB’s Comparison with Derived Products

From RGB Products versus Derived Products J. Kerkmann EumetSAT

RGB vs Quantitative Products - summary

Often reduced horizontal / vertical resolutionFull resolution

Generated later. Forecasters need to be aware

that this product will be superimposed after the

RGB image becomes available.

Usually generated first

RGB product tunes the Quantitative Product

Climatology studies best using QPClimatology studies not so good in RGB

Shallow fog can show shallow fogShallow fog may not be detected in RGB

QP good at all latitudesRGB products no good N or S of 60-70

latitude

Fringes of cloud often not defined in QPFringes of cloud picked up in RGB

Some phenomena have no QPDust can only be detected in RGB

Textures often get lostSees the texture of clouds

Difficult to animateSmooth animation

Often noisyMore continuous colour distribution – adds

value to RGB

Automatic processingVisible inspection

Quantitative ProductsRGB

Strategy of training forecasters to use the RGB products

(input from Vesa Nietosvara’s talk at the EumetSAT Workshop, Sept 2012)

• Important to explain the input beams that go to make up

each RGB.

• Teaching what the different colours in the RGB product

mean

• Instructing how to use other data with RGB products (eg.

Quantitative products)

• Start with simple unambiguous case studies – then introduce more complicated / ambiguous cases

Easy More difficult

Strategy of presenting RGB products within the forecasting environment

A. Forecasters need to be able to access the right

products for the current situation and extract what they need from these products quickly

B. Forecasters need to be able to use the products

effectively and with confidence

C. Forecasters need to have access to case studies, a

showcase of products under development, and new variants to existing products for ongoing training and

feedback

• Satellite data competes with other data.

Satellite data needs to be appropriate and

easy to access and interpret for

forecasters to readily use this.

• Grouping of the satellite products into

“themes” (“fog”, “severe convection”,

“cloud phase”, etc.) helps.

• Forecasters cannot spend time trying to

extract the signal from the noise. A well-

tuned RGB product is important.

• Alerts based upon thresholds applied to

quantitative products (eg. defining

locations of severe convection, fog etc.)

would be very useful to forecasters

A1 - Forecasters have a huge amount of information available to them, they have to be selective in what

they choose

Small ice crystals – strong updraft

Larger ice crystals – weaker updraft

A2 - Timeliness in the product generation and delivery

Presently we are restricted in constructing most of

the RGB products using MODIS data from the

polar orbiting TERRA and AQUA satellites. There

are limitations with this:

• Only a very few passes per day.

• Delay in receipt if this data (~1hour)

• Timing of imagery not so good for some

meteorological phenomena (eg. fog)

• Forecasters would like product Alerts for when the

latest satellite image has become available.

A3 - Easy and appropriate presentation of the product.

• Web-based products or Visual Weather.

• Displays showing broad details, and zoom function

• A good geospatial display is important

to aid navigation

Lat = 22.29 SLong = 128.54 E

x

A3 - Importance of retaining image information when presenting the RGB product to forecasters

• Aside from image navigation, the

forecasters would also like the values of

Red, Green and Blue components at a

point.

• Forecasters would like to analyse the

red, green and blue components of the

product individually and being able to

turn these layers on and off within the GUI.

• Presentation either as layers with

navigation/point values in Visual

Weather, or multiple layers (satellite

data, contoured NWP etc.) within a web

interface as per ePort (see reference

slides).

Lat = 22.29 SLong = 128.54 ER = 142G = 226B = 252

x

B - Forecasters need to be able to use the products effectively and with confidence

• A well tuned RGB product is a useful verification tool.

• Forecasters lose confidence if the RGB colour palette

has glaring ambiguities (unless trained how to deal

with these).

• Important to adapt RGB colour tables to the tropics.

• Problem for people with colour blindness. Contouring

of the signal could help.

B – Adapt RGB colour tables to the tropics

For example, the green beam (IR3.9 – IR10.8) in the Severe Storm RGB.

(Kerkmann pers. comm. 2012)

• For cold, low tropopause conditions, thresholds from 0 to +40 K

• For tropical conditions, thresholds from 0 to +75 K

C - Forecasters need to have access to case studies, a showcase of products under development, and new variants

to existing products for ongoing training and feedback

• Case studies of 10 minute duration.

• Embedding MODIS RGB images into existing Geostationary satellite image loops.

• Maintain a showcase of products under development

• Literature on the performance of RGB’s,

especially in the southern hemisphere and in

the tropics.

Summary

• RGB image products are the result of the meteorological and visually meaningful combination of many single satellite channels into one product

• Use of these products by forecasters will become more widespread over the Australasian region from 2015 with the data from the Himawari 8 geostationary satellite

• It is important to prepare forecasters in the use of these products, and incorporate these products into the forecasters toolkit in an effective way.

• We can do this by utilising the experience of EumetSATand other relevant agencies, in the context of our own requirements.

References

COMET module “Multispectral Satellite Applications: RGB PRODUCTS EXPLAINED” http://www.meted.ucar.edu/npoess/multispectral_topics/rgb/

EumetSAT RGB Satellite Products Workshop: 17-19 September 2012

In particular, the presentations:

“RGB Products Overview (RGB Tutorial)” J. Kerkmann EumetSAT

“RGB Products versus Derived Products” J. Kerkmann EumetSAT

J. Kerkmann, 2010; Tri-spectral Window RGB Applications with MSG SEVIRI (24-h Microphysics RGB)

http://www.rtc.dmi.gov.tr/FILES/KURS/334/DOCS/JochenKerkman2.pdf

Lensky et al. 2008: “Clouds-Aerosols-Precipitation Satellite Analysis Tool (CAPSAT), Atmos. Chem. Phys., 8, 6739-6753.)

WMO RGB Composite Satellite Imagery Workshop, Boulder, CO, USA, 5-6 June 2007. Final Report http://www.wmo.int/pages/prog/sat/documents/RGB-1_Final-Report.pdf