Visualization of the CReSIS Greenland

Datasets for the PolarGrid High

Performance Computing System

AbstractThe Center for Remote Sensing of Ice Sheets (CReSIS) has been compiling

Greenland ice sheet thickness data since 1993. The airborne program utilizes a 150 MHz radar echo sounder to measure the ice thickness. The data is currently available on the CReSIS web site in various formats including PDF, Matlab, and plain text files. These formats are not usable in the classroom environment as a visual representation of the ice depth for each expedition.

During the Undergraduate Research Experience in Ocean, Marine and Polar Science 2009 program, the Greenland Data Visualization Team took the CReSIS data and created a 4-D visualization consisting of depth, time, latitude, and longitude. This visualization was created utilizing HTML, JavaScript, and PHP. Microsoft Excel was used to filter the raw data downloaded from the CReSIS site. The team then statistically analyzed the Greenland ice sheet thickness data for calculated, missing, and actual depth readings. The goal of this project was to present the CReSIS data via the web in a visual format to elementary, undergraduate, and graduate students for research and education. This visualization package and corresponding data will eventually be migrated to the Elizabeth City State University Polar Grid High Performance Computing System. The research that follows involved converting plain text files to comma separated values to be used by PHP and JavaScript to produce data visualizations in Google Maps and HTML pages.

Overview

Data Visualization & Terminology

Excel

Project Phases

Phase One

Download files

Storage on flash drive or personal computers

Phase Two

Index Date Comment

Added Columns

Phase Three

New Longitude formula: =(E1-360)

Replace -999 or NAN to 0 formula: =IF((D1=“0”),”0”-(D1))

Comment in column J formula: =IF((D1=“0”),”M”,IF((I1=“CALCD”), “C”, “A”))

Phase Four

Combine files into one folder

Phase Five

Sort by time and redo index

Phase Six Line Graph

=IF(sheet name_05!$A2/ROUNDUP(COUNT(sheetname_05!$A:$A)/32000,0)=INT(sheet name_05!$A2/ROUNDUP(COUNT(sheet name_05!$A:$A)/32000,0)),sheet name_05!A2,"")

Scatter Plot

Flight Plan

May 30, 2002 data of flight

Phase Seven

Copy phase fiveRecorded and analyzeCount for actual, calculating , and

missing lines

Formula:=COUNTIF(J:J,”A”)

Phase Eight

Formula:

=IF(S1$A1/ROUNDUP(COUNT(S1!$A:$A)/200,0)=INT(S1!$A1/ROUNDUP(COUNT(S1!$A:$A)/200,0))1!A1””)

Copy phase five folder

Reduce to 200 lines

Phase Nine

Deleted columns A, E, H, and I

Replace “p” (paragraph mark ) with ^p for PHP

Phase Ten

Remove calculations and formulas from excel

Delete A, E, H, and I again

Overwritten, Producing In Google Map

Final Product

Flight Pathshttp://mmt.cs.ecsu.edu/pgdataviz/pg-data-set-flightlines.php

4-D Visualizationhttp://mmt.cs.ecsu.edu/pgdataviz/pg-data-set-request.php

Data Downloadshttp://mmt.cs.ecsu.edu/pgdataviz/dd.php

1993 1995 1996 1997 1998 1999 2001 2002 2003 2005 2006 2007

0

100000

200000

300000

400000

500000

600000

700000

139398131401

36976

163261 188814223892

85661133708

110705

605362632087

413628

Total Lines

Outcome

1993 1995 1996 1997 1998 1999 2001 2002 2003 2005 2006 2007

0

2

4

6

8

10

12

14

9 9

3

11 11

13

5

8

6 6

11

5

Days per Year

1993 1995 1996 1997 1998 1999 2001 2002 2003 2005 2006 20070.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

ActualCalculated

Missing

Actual/Calculated/Missing Data Averages by Year

Actual Calculated Missing

Depth Type

Future Work

2008- Present- Future data could can be utilized to produce a more accurate visual of what is happening to the now.

Antarctic Data- The calculation of lost ice could be compared to see if there is the same amount of loss or if the climate is changing differently in the two locations.

Excel Macros-In phases IV and VII macros were used to perform some of the tedious task. In phase IV the task was to combine the data by days. Since there were multiple files per day, Visualization is used often in the area of teaching, research, and development.

Standardized Data Collection Format CReSIS used different formats, which made out work more challenging by précising the information together.

At some point the data will be moved to a high computing cluster at ECSU. This cluster will be able to handle the data faster. The high computer cluster will be located in the E.V. Wilkins Building on the ECSU campus.

Dr. Linda B. Hayden

Acknowledgments

Jeff Wood

CReSIS

CERSER

References

1. http://serc.carleton.edu/introgeo/mathstatmodels/UsingXL.htm

2. (https://www.cresis.ku.edu/research/data/greenland_data.htm

3. Greenland Data Sets,CReSIS,2009- https://www.cresis.ku.edu/research/data/greenland_data.html

4. Climate Change,CReSIS,2008- https://www.cresis.ku.edu/news/documents/ClimateChangeFAQ.pdf

5. Microsoft Excel, 2007 http://office.microsoft.com/en- us/Excel/default.aspx [5] Roman, Steven. Writing Excel Macros with VBA. O'Reilly Media, Inc, 2002.

6. Microsoft, "VBA for Excel". Microsoft. 2008 http://www.Excel- vba.com/Excel-vba-contents.html.