Fuell, Kevin K.

Knaff, John A.

Molthan, Andrew L.

Oswald, Hayden K.

NASA Technical Reports Server

Development of RGB Composite Imagery for Operational Weather Forecasting Applications 
1Andrew L. Molthan, 2Kevin K. Fuell,  3Hayden K. Oswald, and John A. Knaff4 
1NASA Short-term Prediction Research and Transition (SPoRT) Center, NASA MSFC, Huntsville, Alabama,  2University of Alabama Huntsville/SPoRT, Huntsville, Alabama 
3University of Missouri/NASA Summer Intern Program, Columbia, Missouri, 4NOAA/NESDIS Regional and Mesoscale Meteorology Branch, Fort Collins, Colorado andrew.molthan@nasa.gov 
What is an RGB Composite Image? 
An Example of RGB Construction 
MODIS Night Microphysics Composite 
 MODIS Air Mass Composite SEVIRI Multispectral Composites 
GOES Sounder Air Mass Composite Applications in the GOES-R Proving Ground 
Summary and Future Work 
Acknowledgements 
• Current and future satellite instruments provide remote 
sensing at a variety of wavelengths . 
• RGB composite imagery assign individual wavelengths or  
channel differences to the intensities of the red, green, and 
blue components of a pixel color. 
• Each red, green, and blue color intensity is related to 
physical properties  within the final composite image. 
• Final color assignments are therefore related to the 
characteristics of image pixels. 
• Products may simplify the interpretation of data from 
multiple  bands by displaying information in a single image. 
Figure 1.  An example of the red, green, and blue color inputs 
to the “Nighttime Microphysics” product, based upon 
EUMETSAT guidelines, and separation of features by color. 
Figure 2.  Comparison of single channel infrared data and multispectral RGB night 
microphysics imagery for a fog event at 0815 UTC on 24 November 2010.  Data were 
acquired from the MODIS instrument aboard the Aqua satellite and processed 
according to EUMETSAT guidelines. 
• The EUMETSAT “Night Microphysics” product was originally designed for the SEVIRI 
instrument but can also be applied to similar bands available from MODIS. 
• This product allows for color separation of fog and low stratus from other cloud 
types and bare land or open water features.  Input components for this product and 
color separation characteristics are shown in Figure 1. 
• In the image below, the multispectral image improves upon single channel imagery 
by combining four channels of data into vibrant colors that discriminate low clouds 
from other features. 
• Low clouds in characteristic blue shades correspond to reports of low visibility. 
• The EUMETSAT Air Mass  product can also be applied to MODIS. 
• Color separation helps to identify the temperature and moisture characteristics of 
various air masses which are in turn related to various synoptic-scale features. 
• In the image below, a single channel water vapor image is compared to the air mass 
composite.  Vibrant colors in the air mass product correspond to synoptic-scale 
features and air mass characteristics as the storm progressed eastward. 
• Fields from available RUC analysis were used to confirm synoptic-scale features 
evident in the water vapor image and their relationship to the air mass imagery. 
Figure 3.  Comparison of single channel water vapor imagery and multispectral RGB air 
mass imagery for a severe weather event occurring across the southeastern United 
States  at 0315 UTC on 16 April 2011.  Data were acquired from the MODIS instrument 
aboard the Aqua satellite and processed according to EUMETSAT guidelines. 
• Although the current GOES East and West imagers lack all of the spectral 
bands required to produce an air mass image, the GOES Sounder can be 
used to produce similar imagery. 
• CIRA has developed a technique to produce the air mass product from the 
GOES Sounder, withhourly updates of imagery across the United States. 
• In the image below, the CIRA GOES Sounder RGB Air Mass product provides 
continuity to the MODIS imagery by relating color to synoptic-scale features. 
Figure 4.  Air Mass multispectral RGB imagery developed by CIRA based upon 
channels available on the GOES Sounder.  In this case, a midlatitude cyclone was 
moving through the Upper Midwest on November 9, 2011, with various shades 
depicting cloud cover, moisture, and cold air moving in behind the cold front.  
Synoptic features and isobars provided by NOAA/NCEP Hydrometeorological 
Prediction Center. 
• EUMETSAT produces RGB composite imagery in real-time from the SEVIRI 
instrument aboard Meteosat-9.  SPoRT produces equivalent imagery from 
SEVIRI data provided in real-time by NESDIS. 
• SEVIRI products can be used to monitor the Atlantic basin, with multiple 
products helping to confirm features based upon multispectral characteristics. 
• In the case below, various products confirmed an area of lofted dust and 
subsidence off of the coast of Africa. 
Figure 5.  Examples of natural 
color, dust, and air mass products 
generated from SEVIRI input data, 
using EUMETSAT guidelines.  
Analysis of these products 
confirmed an area of lofted dust 
and subsidence off of the African 
coast where storm development 
was unfavorable. 
• Although RGB composite imagery are  24-bit, current AWIPS and 
NAWIPS systems do not support their display. 
• SPoRT has developed a technique to display these images in AWIPS 
and NAWIPS by quantizing each to the number of colors displayable 
with each system.   
• Images are provided to NOAA/NWS WFOs and NOAA/NCEP National 
Centers participating in the GOES-R Proving Ground. 
• These products are evaluated by duty forecasters with responses 
provided to algorithm developers at SPoRT and CIRA in order to 
improve the products prior to their availability in the GOES-R era. 
Figure 6.  Examples of SEVIRI natural color product displayed in the 
current version of NAWIPS, and example of a MODIS air mass product 
displayed in AWIPS.  These systems are used at NOAA/NWS Weather 
Forecast Offices and National Centers to integrate various data sets. 
• The launch of NPP provides additional observations from VIIRS, 
which provides information similar to MODIS and will provide 
additional composites..  
• Interactions with forecasters, algorithm developers at CIRA, and 
discussions with EUMETSAT will continue to improve upon current 
products in advance of their potential availability from GOES-R. 
• Additional forecaster feedback will be acquired to understand how to 
best apply these products to weather forecasting and analysis, with 
feedback implemented into future training materials. 
Product Instruments Purpose 
Air Mass SEVIRI, MODIS, GOES Sounder Air mass type discrimination 
Dust SEVIRI, MODIS, VIIRS Blowing or suspended dust 
Night Microphysics SEVIRI, MODIS, VIIRS Fog and low clouds 
Day Microphysics SEVIRI, MODIS, VIIRS Fog and low clouds 
Day Snow/Fog  SEVIRI, MODIS, VIIRS Fog, low clouds, and snow 
Daytime Storms SEVIRI, MODIS, VIIRS Identifies convective storms 
Natural Color SEVIRI, MODIS, VIIRS Approximates a true color image 
True Color MODIS, VIIRS True color, photograph image 
False Color Snow MODIS, VIIRS Discriminate clouds from snow 
This collaborative work is sponsored in part by the GOES-R Proving 
Ground Activity.  The authors thank collaborators Michael Folmer (HPC) 
and Jack Beven (NHC) for providing examples of product usage at their 
respective NOAA Centers.  Author Hayden Oswald was sponsored by 
the NASA Summer Intern Program at Marshall Space Flight Center. 
Product Development 
• Products shown here were generated based upon recipes 
developed by EUMETSAT.   
• Each individual input channel or paired channel difference 
is assigned a series of thresholds for linear and gamma-
factor image enhancement: 
 
 
• Slight differences in temperature thresholds, brightness 
enhancements, and other characteristics are applied to 
account for differences in instruments. 
Table 1.  Recipe for construction of the “Night Microphysics” 
product designed by EUMETSAT, based upon their “Best 
Practices  for Display of RGB Images” documentation. 
Table 2.  RGB composites expected from various current instruments.. 
https://ntrs.nasa.gov/search.jsp?R=20120004177 2019-08-30T19:42:44+00:00Z


Development of RGB Composite Imagery for Operational Weather Forecasting Applications

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