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Analysis of S’COOL Data: An Introductory Tutorial

National Aeronautics and Space Administration. Analysis of S’COOL Data: An Introductory Tutorial. http://scool.larc.nasa.gov. www.nasa.gov. Finding the Data. Under the first cloud, Select Step 4: Database. Selecting the data. Interact with the data Just yours All OR….

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Analysis of S’COOL Data: An Introductory Tutorial

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  1. National Aeronautics and Space Administration Analysis of S’COOL Data: An Introductory Tutorial http://scool.larc.nasa.gov www.nasa.gov

  2. Findingthe Data Under the first cloud, Select Step 4: Database

  3. Selecting the data • Interact with the data • Just yours • All OR…

  4. Selecting the data • Download all S’COOL and CERES matches (as of Aug. 2004)

  5. Selecting the data • Get ideas for data analysis a) This tutorial b) Excel file 1 c) Excel file 2

  6. Review the Results 4. Read our analysis of the S’COOL and CERES data -We will be happy to post results of student studies here too!

  7. Search Options • Choose a date range And/Or • Choose a lat/long region And/Or • Choose a country And/Or • Choose results with satellite data

  8. Submit Query Request It may take a few minutes to process the search. • Hit Submit when ready

  9. Search Results - Ground Only The student report A graphic representation

  10. Search Results - Ground + SatelliteA No Cloud Case The student report Excellent Agreement! The satellite report

  11. Search Results - Ground + Satellite • Of course, the reports from the ground and the satellite may not always agree • The next few slides illustrate a few examples • Sometimes the disagreement makes sense • Sometimes the disagreement does not make sense • You can look at your own observations to • Quantify the agreement • Find and further study cases that don’t make sense

  12. Search Results - Ground + SatelliteCloudy Case - I The student report Very good Agreement! Only opacity (a subjective measure from the ground) does not match The satellite report

  13. Search Results - Ground + SatelliteCloudy Case - II The student report Near disagreement Cloud Cover differs by one category. May be off only a few percent. The satellite report

  14. Search Results - Ground + SatelliteCloudy Case - III The student report Interesting disagreement Satellite cannot see clouds under opaque top layer The satellite report

  15. Search Results - Ground + SatelliteCloudy Case - IV The student report Interesting disagreement Satellite cannot detect sparse, thin, high clouds The satellite report

  16. Search Results - Ground + SatelliteCloudy Case - V The student report Puzzling disagreement Student comments indicate extensive cloudiness The satellite report

  17. Analyzing the Data - Cloud Cover • So far we have talked about 6 cases (no cloud case, and cloudy cases I, II, III, IV, and V). How could we summarize these? Low cloud Mid-level cloud High cloud All 3/6 50% 5/6 83% 4/6 67%  2/6 33%

  18. Analyzing the Data - Cloud Cover Low cloud Mid-level cloud High cloud All 3/6 50% 5/6 83% 4/6 67%  2/6 33% Cloud Cover is important to understanding the Earth’s Energy Budget, since clouds both reflect sunlight and modulate emission of heat from the Earth.

  19. Analyzing the Data - Cloud Cover • What if we look at total cloud cover (Low + Mid + High)? -Need to decide how to combine levels - do they overlap? -Use a middle value for ground classes (i.e., 5-50 = 27.5%) *No overlap assumed

  20. Analyzing the Data: How Many Cloud Layers Number of Cloud Layers Ground Observations Cloud Layers are of particular interest when comparing the passive satellite view of the Earth from space with the report of human observers on the ground who can distinguish different cloud layers and types. Satellite Observations 3/6 = 50% agree completely 3/6 = 50% off by one class

  21. Analyzing the Data: Which Cloud Levels Cloud Levels seen from Ground Cloud Levels seen from Satellite LM = Low + Mid. etc Cloud Levels are of interest for the same reason, since human observers on the ground can distinguish cloud levels better than the top-level satellite view. 3/6 = 50% agree completely

  22. Analyzing the Data • Of course, these 6 correspondences were hand-picked to illustrate interesting comparisons. • What happens if we look at all the data? • Let’s start with the two-week period (Sept. 1-15, 2002) that includes these examples. It also tells you how many data points were found = 245. At the bottom of the search page, you will find directions, a key to the file, and a link to get the data.

  23. The Downloaded .bin File • The file you get will have a name like 11301239.grn.bin • Decoding: • 1130 is the date (Nov. 30 in this case) you download the file. • 1239 is a time stamp from when you requested the file • grn means Ground • .bin was chosen as the extension so that most browsers will automatically download the file when you click on the link

  24. Inside the .bin file • The .bin file is an ASCII (text) file. • Each line contains the student report and, if available, the corresponding satellite retrieval information. • The lines are very long and will wrap in most text editors (see below). • Fields are tab-separated, so that the file can be imported into a spreadsheet program like Excel.

  25. Importing into Excel • There are several ways to import data into Excel. If you already know how, skip this page. • Open Excel • Under the File menu, choose Open • Find the .bin file you downloaded to your computer. (you may have to Enable: All Documents in the Open menu) • Open the file. A Text Import Wizard should start. • Delimited is default. Next. • Tab is default. Next. • Finish. File should appear as on next page.

  26. The file in Excel - I Row 1: Variable Name Row 2: Units Row 3: Blank Row 4…: Data The key lets you interpret the entries in these columns (see slide 22). You may notice other blank lines. These have to do with line feeds, and can be deleted or ignored.

  27. The file in Excel - II Scrolling to the right in the file, you will find the satellite entries, or the notation NAY (Not Available Yet) If the satellite saw no cloud in a level it will be left blank.

  28. Analyzing data • Now that you have the file open in Excel, you can save it as an Excel workbook, then do all sorts of analyses. • See the two Excel files (refer to slide 5) for some examples and ideas • If you discover anything interesting, share it with the S’COOL Team!

  29. National Aeronautics and Space Administration Langley Research Center Hampton, VA 23681 www.nasa.gov

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