Night-time Microphysics RGB Imagery Assists with Aviation Forecasting at RAH

WFO Raleigh, NC (RAH) has been collaborating with the NASA/MSFC’s Short-term Prediction Research and Transition (SPoRT) team and evaluating the Night-time Microphysics RGB product from VIIRS and MODIS for use with observing fog and low clouds. The Night-time Microphysics RGB imagery uses the common IR spectral difference for fog/low cloud detection as well as inputs related to optical thickness and the cloud’s thermal property in order to help differentiate low clouds and near-surface fog.

The image below is the Night-Time Microphysics RGB satellite product from 0741 UTC 24 August 2013 along with the 0800 UTC surface ceiling and visibility plot across the mid-Atlantic and Southeast as displayed in AWIPS D2D. This image shows complex cloud conditions with regions of low stratus and higher based stratus clouds across central NC.

ImageIf you examine the RGB closely, you will notice a difference in the shading with the low stratus across the western and northwestern area of the cloud shield shaded in aqua with ceilings of 900-2,500 feet (high-end IFR or MVFR) near Greensboro while further east the clouds are more tan colored and associated with ceilings in the 4,000-5,000 feet range (VFR) near Roanoke Rapids.

The example below shows the 11-3.9 micron product from 0745 UTC on the left and the Night-Time Microphysics RGB satellite product from 0741 UTC on the right. While the 11-3.9 micron product highlights the location of the stratus, the Night-Time Microphysics RGB satellite product provides the user with much more detail including information on the cloud bases and the associated aviation flight category. The increased resolution in the Night-Time Microphysics RGB product also allows the user to much more easily identify details in the clouds field and attribute more confidence to the surface observations. This information was used by the forecaster to correctly update the Terminal Aviation Forecast and produce a better quality forecast product.

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One thought on “Night-time Microphysics RGB Imagery Assists with Aviation Forecasting at RAH

  1. Thanks to RAH for this nice example of identifying multiple cloud types using the Night-time Microphysics RGB as it relates to aviation forecasts. The aqua areas nicely identify low clouds and it’s a good idea to put the observations of cloud levels on the image. The IR channels will be looking from the top downward, so interpreting the cloud base (i.e. ceiling) can be tricky if the RGB imagery is indicating mid-level, thick clouds (as pointed on in the post by the more tan colored areas). Also note, the purple colors in the lower half of the image identifying some relatively thin, and cold features likely to be mid to upper level stratus. Then, more dark reds in the bottom portion of the image representing somewhat thick, very cold clouds. The yellow speckles in the cloud masses in the very bottom of the image are due to the 11-3.9 channel difference resulting in a very large number. There is a rapid drop in brightness temperature in the 3.9 micron shortwave channel compared to the 11 micron channel as very cold temperatures are detected. This causes a large difference between the channels, falsely indicating a microphysical difference and resulting in the maximum amount of green being contributed. This maximum green combined with the large amount of red due to thick towering cumulus, results in a yellow value for the pixel and gives the scene a “noisy” appearance of reds and yellows where large storms with strong updrafts are occurring. Lastly, I liked seeing the areas of fog in the upper left of the image and how the color changed from the low stratus areas of aqua in North Carolina. Some of the observations in that area are between the fog and report no ceiling and 10 miles visibility, but they are surrounded by various areas of fog. In the Night-time Microphysics RGB the fog tends to have a dull aqua to nearly gray color compared to the brighter aqua of the low stratus. Essentially, less green and red tends to be contributed to these fog areas as it is thinner and the 11-3.9 relationship tends to have less of a difference, likely due to some of the IR emissions from the land surface mixing with the cloud/fog IR emissions as seen by the sensor.

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