Analysis of S’COOL Data: An Introductory Tutorial National Aeronautics and Space Administration

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Presentation transcript:

Analysis of S’COOL Data: An Introductory Tutorial National Aeronautics and Space Administration

Finding the Data Click on the For Participants tab

Finding the Data Next click on: 4. Database Next click on: 4. Database

Selecting the data 1.Interact with the data a)Just yours b)All OR…

Selecting the data 2.Download data matches by spacecraft name and date.

Selecting the data 3.Get ideas for data analysis a) This tutorial b) Excel file 1 c) Excel file 2

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!

Search Options Choose a date rangeAnd/Or Choose a lat/long regionAnd/Or Choose a countryAnd/Or Choose results with satellite data

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

Search Results - Ground Only The student report A graphic representation

Search Results - Ground + Satellite A No Cloud Case The student report Excellent Agreement! The satellite report

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

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

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

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

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

Search Results - Ground + Satellite Cloudy Case - V The student report Puzzling disagreement Student observations indicate extensive cloudiness The satellite report

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 GrdSat 00 MC  00 PC0X 00 00   X X X X  3/6 50% 50%  5/6 83% 83%  4/6 67% 67%  2/6 33% 33% Grd Ground Sat Satellite 0 No Cloud Cl Clear PC Partly Cloudy MC Mostly Cloudy OV Overcast GrdSat 00 00 PCClX PC0X 00 0X GrdSat 00 PC  00 0X 00 Cl0X

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 GrdSat 00 MC  00 PC0X 00 00   X X X X Grd Ground Sat Satellite 0 No Cloud Cl Clear PC Partly Cloudy MC Mostly Cloudy OV Overcast GrdSat 00 00 PCClX PC0X 00 0X GrdSat 00 PC  00 0X 00 Cl0X Cloud Cover is important to understanding the Earth’s Energy Budget, since clouds both reflect sunlight and modulate emission of heat from the Earth.

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%) CaseGrd* (%)Sat* (%) 1 0.  2 PC+MC =  3 PC =  4 PC+PC+PC=  5 Cl = 2.50 6 PC = 27.50 * No overlap assumed Grd Ground Sat Satellite Cl Clear PC Partly Cloudy MC Mostly Cloudy OV Overcast Grd Ground Sat Satellite 0 No Cloud Cl Clear PC Partly Cloudy MC Mostly Cloudy OV Overcast

Analyzing the Data: How Many Cloud Layers GroundObservations Satellite Observations 01>1 0      1  3/6 = 50% agree completely 3/6 = 50% off by one class Number of Cloud Layers 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.

Analyzing the Data: Which Cloud Levels ClrLowMidLMHiLHMHLMH Clr Low Mid LM Hi LH MH LMH Cloud Levels seen from Ground Cloud Levels seen from Satellite 3/6 = 50% agree completely 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.

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, 2008, that includes these examples. At the bottom of the search page, you will find directions, a key to the file, and a link to get the data. * This can be found at the bottom of the comparison report request. It also tells you how many data points were found = 336.

The Downloaded.xls File The file you get will have a name like grn.xls –Decoding: 1207 is the date (Dec. 07 in this case) you download the file is a time stamp from when you requested the file (8:12 am in this case) grn means Ground.xls was chosen as the extension so that most browsers will automatically download the file when you click on the link

Inside the.xls file The.xls file is a Microsoft Excel 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).

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

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.

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!

National Aeronautics and Space Administration Langley Research Center Hampton, VA