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GOES-R Cloud Top Phase

Frequently Asked Questions about the GOES-R Cloud Phase Product


1) What is this product?

The GOES-R Cloud Phase product produces cloud phase information for all cloudy pixels.  The categories of cloud phase are: warm liquid water cloud, supercooled liquid water cloud, mixed phase cloud, and ice phase cloud.  The resolution of this product is 2 km.  The GOES-R Cloud Phase product is created both day and night.  The accuracy of the product is 80% correct classifications. The GOES-R Cloud Phase product is considered to be quantitative out to 65 degrees local zenith angle and qualitative beyond that.1

This product is useful when trying to assess the phase of the cloud tops.  Knowing if clouds are made up up ice, liquid water, or supercooled water can be helpful establishing the type of precipitation is likely falling below that cloud.  For example, a liquid cloud will be producing liquid and not ice precipitation.  Information about the vertical temperature profile can also be inferred from this product (i.e. how high is the freezing/melting level).


2) How often do I receive this data?

The cadence of the Cloud Phase product is dependent upon which image from the satellite one is looking at. For Full Disk imagery, an image is produced every 15 minutes.  For CONUS imagery, an image is produced every 5 minutes.  For a Mesoscale scan, an image is produced every 5 minutes.


3) How do I display this product in AWIPS-II?

To display this product in AWIPS-II, go to the "GOES-R" tab of the CAVE menu, then select "Derived Products."  From there, select the region of interest (GOES-E, GOES-W, or GOES Test and Full Disk, CONUS, and Mesoscale).  Then, select the Cloud Phase product.

Alternately, use the AWIPS Product Browser.  Select "Sat", then either "GOES-16" or "GOES-17".  From there, choose "Full Disk", "CONUS", or "Meso", then select "CP."


4) How do I interpret the color maps associated with this product?

Color maps have not yet been created for these products.


5) What other imagery/products might I use in conjunction with this product?

This product can be used in conjunction with visible 0.64um satellite imagery (if available), the 1.61 um satellite imagery (if available), and also 10.33 um satellite imagery.  Having both the visible channel and cloud phase product open in the same AWIPS pane and toggling back and forth can give you an idea of which clouds specifically are liquid, ice, or mixed phase.  The same can be done with the 10.33 um channel during the day or at night.  The 1.61 um channel contains some information about cloud phase, thus it can act as a comparison tool to the product, especially because the cloud phase product does not use the 1.61 um channel in the algorithm calculations.  In the 1.61 um channel, ice clouds have lower brightness temperatures than liquid water clouds.  Thus, when using a standard visible gray scale color curve, ice clouds will look darker than liquid water clouds.


6) How is this product created?

The GOES-R Cloud Phase product is only calculated on pixels that are determined to be either "cloudy" or "probably cloudy" by the GOES-R Cloud Mask algorithm.  It utilizes GOES-R bands 7.4 um, 8.4 um, 11.2 um, and 12.3 um.   The GOES-R Cloud Phase product relies on the infrared observations to avoid discontinuities associated with the transition from day to night.  The algorithm  relies  on  spectral  and  spatial  tests,  as well  as  the  ABI  cloud  mask.    The performance of the cloud type algorithm is therefore sensitive to any imagery artifacts or instrument  noise  as  well  as  the  correct  identification  of  cloudy  pixels.  Calibrated observations  are  also  critical  because  the  cloud  type  compares  the  observed  values  to those  from  a  forward  radiative  transfer  model.

A satellite-measured reflectance is a function of cloud microphysics, surface type, viewing and illumination geometry, and other factors. Due to the complex nature of scattering in  the visible and near-infrared, and our inability to quickly simulate satellite reflectance values, we have chosen to avoid using sunlight contaminated channels at this time.  One advantage of using infrared-only approach is that the algorithm performance is spectrally day/night independent (e.g. the same procedure is applied at all times). 1


The ancillary data used to calculate the cloud top height includes1:

- Surface emissivity of ABI channel 11 (8.4 um): A global database of monthly mean infrared land surface emissivity is required for ABI channel 11. The algorithm utilizes surface emissivity  derived using the Moderate Resolution Imaging Spectroradiometer (MODIS). Emissivity is available globally at ten generic wavelengths (3.6, 4.3, 5.0, 5.8, 7.6, 8.3, 9.3, 10.8, 12.1, and 14.3 microns) with 0.05 degree spatial resolution. The ten wavelengths serve as anchor  points in the linear interpolation to any wavelength between 3.6 and 14.3 microns. The  monthly emissivities have been integrated over the ABI spectral response functions to match the ABI channels.


- Profiles of pressure and temperature: The calculation of cloud  emissivity requires profiles of pressure and temperature from a global Numerical Weather Prediction (NWP) model.    In   addition, knowledge of the location of the surface and tropopause levels is required. While six-hour forecasts were used in the  development of the algorithm and, as such, are recommended, any forecast in the 0 to 24 hour range is acceptable.



The derived data used to calculate the cloud top height includes1:

- Cloud Mask: The algorithm requires the ABI cloud mask described in the cloud mask ATBD.  The cloud mask is used to identify cloudy pixels. The cloud phase is not determined for clear pixels.


- Black cloud radiance profiles for channels 10, 11, 14, and 15: The algorithm requires the radiance emitted upward by a black body surface and transmitted through a non-cloudy atmosphere, with gaseous absorption, to the top of the atmosphere as a function of the atmospheric level of the black surface. The black cloud radiance is computed as a function of NWP grid cells and local zenith angle (it is not computed at the pixel  resolution).


- Top-of-atmosphere clear-sky radiance estimates for channels 10, 11, 14, and 15: The algorithm requires knowledge of the top-of-atmoshere radiance ABI would sense under clear-sky conditions at each pixel.


The spectral sensitivity to cloud composition is perhaps best understood by examining the imaginary index of refraction for liquid and ice,  mi, as a function of wavelength. The imaginary index of refraction is often directly proportional to absorption/emission strength for a  given particle composition, in that larger values are indicative of stronger absorption of radiation at a particular wavelength. However,  absorption  due  to  photon tunneling, which is proportional to the real index of refraction, can also contribute to the observed spectral  absorption under certain circumstances .1



1Pavalonis, Michael. NOAA NESDIS Center for Satellite Applications and Research GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for Cloud Type and Cloud Phase v.2.0. 15 September 2010.

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