SatMet Lab Exercise --

Soundings and Derived Products

Melanie Wetzel / Desert Research Institute
and Stan Kidder / CIRA

The objective of this exercise is to examine the Derived Product Imagery (DPI) obtained by quantitative processing of GOES multispectral data.

Part I : Acquisition of raob data (20 min)

Use NTL/GARP for the 06mar96 dataset to

  1. display the GOES-8 4 km IR image from 1145 UTC / 06mar96
  2. zoom over the southeastern US
  3. overlay the upper air station identifiers (Options:Overlays:Station:Upper Air Stations)
  4. select three rawinsonde observation (RAOB) sounding locations which appear to be cloud-free and three which have cloud cover. Write down their 3-letter station identifier. If you have difficulty distinguishing cloudy from clear locations, you may wish to use the VIS and IR images from 1515 UTC for comparison.
  5. With the 1145 UTC IR image, determine the effective cloud-top temperature at the cloudy stations you selected.

Start the NSHARP program from the NTL menu. (You can run NSHARP and GARP at the same time.) Select the data from 06mar96 at 12:00 UTC (Load:Observed Soundings). Find the soundings from your list. (Not all the sounings are available; modify your list accordingly.) For each sounding, write down the following: parameters:

Now go back to GARP for the next steps (You can exit NSHARP if you wish). Check the locations of your selected sites that are overlaid on the satellite imagery.

Part II : Evaluation of Sounder and Derived Products (25 min)

1. Does the Cloud Top Pressure (CTP) image (above) provide information on cloud structure similar to that provided from Cloud Top Temperature (CTT) in an IR window image (below)?

2. Using the data fields and color bars shown in the above images, estimate the values of CTP and CTT at the locations you selected using GARP and ISP. How well do the DPI estimates compare with your site data? Can you suggest causes for the discrepancies?

3. In the image above, compare the quantitative values indicated by the RAOB contours of precitable water vapor (PW) and the Sounder DPI PW image data distribution. What are the advantages of having an image representation of the PW field?

4. Also using the image above, describe the correspondence between the spatial patterns indicated by the RAOB PW contours and the DPI image.

5. In the image above, determine in what region the Sounder retrieval fields (contours) and RAOBs (point values) show the poorest agreement. Can the cloud distribution help to explain the differences? What other factors may be responsible?

6. For site locations which are affected by cloud, use the image above to find the DPI PW values (blue) and RAOB PW values (green) at a nearby clear location and make a comparison at that alternate point. What are the benefits and risks of using the Derived Product PW dataset in areas of partial cloud cover ?

7. In the image above, compare the values of Lifted Index (LI) from the RAOB data (point values) at your selected cloud-free raob sites against the DPI data (image distribution and contours).

8. Also evaluate the image and contoured field of DPI Lifted Index data. In what geographic area(s) would you expect the DPI LI data be most valuable for synoptic analysis?

III. Use of realtime Derived Product Imagery (25 min)

Access real-time DPI files at the following sites:

Evaluate the information contained in these pages and its usefulness to forecasters.

IV. Summary Discussion (10 min)

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