Regional and Mesoscale Meteorology Branch

Product Examples and Interpetations:

The dust product is an RGB composite based upon infrared channel data from the MSG satellite. It was designed by EUMETSAT to monitor the evolution of dust storms during both day and night. The Dust RGB makes use of channel differences that are close to IR windows near 8.7 µmicro;m and 11 µmicro;m. The resulting product depicts dust in magenta and purple colors over land depending on the whether it is day or night, respectively. A dusty atmosphere can also be tracked the over water as magenta coloring. For more information on interpretation see (Kirkman et al., cited 2010). The product will allow for the monitoring of dust storms over the African Continent and tracking of that plume into the tropical Atlantic waters where easterly waves move and sometimes develop into tropical cyclones. The dust serves as a tracer for a dry mid-level airmass, and has radiative influences on the atmosphere and affects the microphysics of cloud development. Dust plumes in the tropical Atlantic have been hypothesized to slow tropical storm development (Dunion and Velden 2004) and directly affect sea surface temperatures (SSTs) where tropical cyclones form (Evan et al. 2008). An annotated example is provided below.

Figure 2: Dust product example. Dust is shown in magenta (day) or purple (night), water topped clouds show up as yellowish orange, ice topped clouds are shown in reddish orange, and thin cirrus is black.

Google Earth loops of GOES-E imagery over the CONUS are available at http://rammb.cira.colostate.edu/products/google_earth/

Dunion, J. P., and C. S. Velden (2004), The impact of the Saharan air layer on Atlantic tropical cyclone activity, Bull. Am. Meteorol. Soc., 85, 353-365.

Evan, A. T., R. Bennartz, V. Bennington, H. Corrada-Bravo, A. K. Heidinger, N. M. Mahowald, C. S. Velden, G. Myhre & J. P. Kossin (2008) Ocean temperature forcing by aerosols across the Atlantic tropical cyclone development region. Geochem. Geophys. Geosyst., 9, Q05V04, doi:10.1029/2007GC001790.

Kirkman, J., HP. Roesli, G. Bridge and M. König, cited 2010: Applications of Meteosat Second Generation (MSG), RGB Composites with Channels 01-11 and their interpretation. [Available on-line at http://oiswww.eumetsat.org/IPPS/html/bin/guides/msg_rgb_dust.ppt]

Advantages and Limitations:

The RGB dust product provides an additional decision aid tool to NHC forecasters. This product helps tropical cyclone forecasters to track dust plumes in the tropical Atlantic. Dust storms have been hypothesized to slow tropical storm development and directly affect sea surface temperatures (SSTs). The current product is limited to the MSG sector.

Product Information:

Product Description:

Product Examples and Interpretations:

The air mass product is an RGB composite based upon data from infrared and water vapor channels from Meteosat Second Generation (MSG). Originally designed and tuned to monitor the evolution of extra-tropical cyclones, in particular rapid cyclogenesis, jet streaks and PV (potential vorticity) anomalies by scientists at (EUMETSAT), it is also useful for tropical/subtropical applications. The product highlights differences between dry, tropical and cold air masses, as can be seen in the example below. This is accomplished by differencing the two water vapor channels (i.e., ch. 5 at 6.2 µmicro;m and ch. 6 at 7.3 µmicro;m) as depicted in the red colors, where red is associated with dryer air mass conditions locally, by Ozone differences by differencing ch. 8 at 9.7 µmicro;m and ch. 9 at 10.8 µmicro;m, where green indicates low Ozone & typically thus tropical air masses, and by using ch. 5 at 6.2 µmicro;m to indicate gross air mass temperature differences.

The air mass product helps discriminate tropical air masses (i.e., moist and lower ozone) that are predominantly green, from subtropical air masses (i.e., dryer) that are depicted greenish red, and mid-latitude air masses, typically having more blue colors. For tropical applications it should be helpful in determining and tracking the origin of air parcels as they interact with tropical systems, and improved identification of shallow upper level features (cold lows and jets streaks). For more information on the interpretation of this product see (Kirkman, cited 2010). An annotated example is provided below.

Kirkman, J., cited 2010: Applications of Meteosat Second Generation (Meteosat-8), AIRMASS. [available on-line at http://oiswww.eumetsat.org/IPPS/html/bin/guides/msg_rgb_airmass.ppt]

Google Earth loops of GOES-E imagery over the CONUS are available at http://rammb.cira.colostate.edu/products/google_earth/

Advantages and Limitations:

The RGB air mass product provides a simple decision aid tool to NHC forecasters by visually discriminating tropical air masses from subtropical air masses. For tropical applications it should be helpful in determining and tracking the origin of air parcels as they interact with tropical systems, and improved identification of shallow upper level features (cold lows and jets streaks). The current product is limited to the MSG sector.

Product Information:

Product Examples and Interpretations:

The air mass product is an RGB composite based upon data from infrared and water vapor channels from Meteosat Second Generation (MSG) and applied here to the GOES sounder data. Originally designed and tuned to monitor the evolution of extra-tropical cyclones, in particular rapid cyclogenesis, jet streaks and PV (potential vorticity) anomalies by scientists at (EUMETSAT), it is also useful for tropical/subtropical applications. The product highlights differences between dry, tropical and cold air masses, as can be seen in the example below. This is accomplished by differencing the two water vapor channels (i.e., at 6.51 µ and at 7.41 µ) as depicted in the red colors, where red is associated with dryer air mass conditions locally, by Ozone differences by differencing at 9.71 µ and at 11.03 µ, where green indicates low Ozone & typically thus tropical air masses, and by using 6.51 µ to indicate gross air mass temperature differences.

Figure 2: Air mass product example. Warmer air is displayed in green and red where the green regions have higher moisture content than the red regions. Mid-latitude air has a bluish color and areas or dark red show areas of subsidence and high ozone and PV.

There are two situations to consider cloud-free and cloudy areas. In the cloud free regions, the air mass product helps discriminate tropical air masses (i.e., moist and lower ozone) that are predominantly green, from subtropical air masses (i.e., dryer) that are depicted greenish red, and mid-latitude air masses, typically having more blue colors. In the mid-latitude setting the maroon colored regions are characterized by dry and higher ozone. These high-ozone areas are often associated with regions of tropopause folding and high potential vorticity. For mid-latitude applications the product can be used for tracking short-waves and synoptic scale airmass differences. For tropical applications it should be helpful in determining and tracking the origin of air parcels as they interact with tropical systems, and improved identification of shallow upper level features (cold lows and jets streaks). It should be noted that this product can have large diurnal fluctuations over the warm air masses. When the land surface temperatures are very warm the difference between the 11.03 micron and 9.71 become very large. In these cases the blacker the region the higher the upper-level relative humidity.

In cloudy regions, deep and high clouds show up as white and mid-level clouds show up as a beige color. For more information on the interpretation of this product see (Kirkman, cited 2010). An annotated example is provided below.

Kirkman, J., cited 2010: Applications of Meteosat Second Generation (Meteosat-8), AIRMASS. [available on-line at http://oiswww.eumetsat.org/IPPS/html/bin/guides/msg_rgb_airmass.ppt]

Google Earth loops of GOES-E imagery over the CONUS are available at http://rammb.cira.colostate.edu/products/google_earth/

Advantages and Limitations:

The RGB air mass product provides a simple decision aid tool to HPC forecasters by visually discriminating tropical air masses from subtropical air masses. For tropical applications it should be helpful in determining and tracking the origin of air parcels as they interact with tropical systems, and improved identification of shallow upper level features (cold lows and jets streaks). The current product is limited to the GOES Sounder sectors.

This product is affected by surface diurnal temperature changes and viewing angle. At steep viewing angles there is limb darkening of the water vapor (6.51, 7.43) and window (11.03) channels and a warming of the ozone channel (9.71).

This product is affected by surface diurnal temperature changes and viewing angle. At steep viewing angles there is limb darkening of the water vapor (6.51, 7.43) and window (11.03) channels and a warming of the ozone channel (9.71).

Product Information:

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Product Information:

Who is developing and distributing this product?

The Cooperative Institute for Research in the Atmosphere (CIRA) in Fort Collins, Colorado, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) in Madison, Wisconsin, and the Naval Research Laboratory (NRL) in Monterey, California are developing and distributing the Simulated True Color product.

Who is receiving this product, and how?

The Simulated True Color products are sent to the National Weather Service (NWS) Regional Headquarters from which they are distributed to Weather Forecast Offices (WFOs) for display on their local AWIPS systems. Imagery updates are available approximately two times per day from the MODIS sensors on board Terra (~10:30 AM local time) and Aqua (~1:30 PM local time).

What is the product size?

The size of Simulated True Color product images is determined by the span and resolution of the AWIPS domain itself. Since current AWIPS system displays accommodate 1-byte per pixel, a good rule of thumb is that the size of the imagery (in bytes) corresponds roughly to the total number of pixels in a given AWIPS domain. For example, an AWIPS domain having dimensions of 1000 x 1000 pixels will require approximately 1 Megabyte (~106 bytes).

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Product Description:

What is the purpose of this product?

True Color imagery approximates the response of normal human vision, providing a depiction of the satellite-observed scene. The purpose of doing so is to provide a visually intuitive depiction that is useful to experts and non-experts alike, improving the interpretation of various features such as vegetation, water bodies, clouds and snow, deserts, etc., based on usage of natural colors to highlight those features. For this reason, ‘true color’ and ‘natural color’ are often interchanged when referring to this kind of popular satellite imagery.

Why is this a GOES-R Proving Ground Product?

Simulated True Color demonstrates the kind of imagery that will be possible in the GOES-R era. GOES-R will feature the Advanced Baseline Imager (ABI) sensor which when combined with complementary data from the Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) satellites will be able to produce versions of the imagery shown here at much higher time resolution.

How is this product created now?

By combining satellite measurements from bands having responses similar to those of the human retina (namely, blue, green, and red bands), we can create an image that appears as a color photograph. The bands are corrected for atmospheric scattering (otherwise there would be a milky appearance to the imagery, due to the affects of Earth’s atmosphere which accounts for blue skies during the daylight hours). The challenge for the GOES-R ABI is that it will not include one of the required (green) bands. We can overcome this challenge by forming a relationship between the missing green band and nearby bands that we do have. The relationship is formed using a satellite dataset which contains all the ABI bands as well as the green band (here, from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument). Once a relationship is determined, we can use the bands the ABI will have to approximate the green band that it will not. This is why we call it “simulated” true color as opposed to just “true color.” The basic concept of the approach is illustrated below.

Contact:

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Steve Miller

Related Training:

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Data Display:

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Web

WFO/Testbed Feedback:

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WFO

Product/Type:

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New Product

Usage:

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Visualization

Product Examples and Interpretations:

Among 3-color composite imagery, True Color requires perhaps the least amount of user training from the standpoint of interpreting colors. To reasonable approximation, these images resemble what an astronaut on the Space Shuttle or International Space Station might observe from roughly 500 miles above the surface.

Minor exceptions to this statement include the fact that the response of human vision to color is not replicated perfectly by the satellite sensor, and we have taken the additional step of subtracting-away the atmospheric signal which would contribute to a milky “haze” appearance due to the scattering of sunlight – an effect that is particularly strong at more slant-path views through the atmosphere (e.g., toward the horizon).

Despite the visually intuitive nature of the imagery, interpreting various cloud structures, snow cover, and complex topography are inherently challenging due simply to the way these features appear from the satellite vantage point. The examples below demonstrate how true color depicts lush green deciduous forests over Pennsylvania, the tan sediment-laden waters of the Mississippi River delta, and turquoise shallow-water sand bars in the Caribbean.

Advantages and Limitations:

The main advantage of true color imagery over various false color or gray-scale imagery enhancements is the intuitive familiarity of the colors as they relate to physical components of the scene, which reduces the amount of training required to make use of the imagery.

The main limitation at this time, and one that will likely go away with the installation of AWIPS-II, is the limitation of 8-bit color (256 colors) to represent a scene that draws (potentially) from a 24-bit (256^3 = almost 17 million) palette of possible colors. The best approach to dealing with this issue would be to use a unique 8-bit color palette for each new true color image, but this is impractical. The next best approach may be for developers to build palettes that are regionally and seasonally dependent, and install/update these palettes at specific forecast offices.