Presentation is loading. Please wait.

Presentation is loading. Please wait.

Ryan O’Connor Geography 199 University of California, Santa Barbara.

Similar presentations


Presentation on theme: "Ryan O’Connor Geography 199 University of California, Santa Barbara."— Presentation transcript:

1 Ryan O’Connor Geography 199 University of California, Santa Barbara

2 Abstract To use data from Antarctic science and weather stations to illustrate temporal trends in temperature Use data to determine extreme temperatures on the Antarctic Peninsula for various times of day and year

3 Methodology Data from four stations used: Esperanza, Faraday(Vernadsky), Marambio, and Rothera Five datasets from each station: 00, 06,12,18 Zulu, as well as averages, all done by month Time frame: past 30 years(1980-2009) Use of statistical methods to determine things such as mean, standard deviation, and z-scores of data sets, and graphs to show trends Very extensive use of graphs to illustrate trends(600+)

4 Station Information Esperanza: Spanish station@63.4° S 57.0° W Elevation: 13 meters Faraday/Vernadsky: Ukrainian station @65.4° S 64.4° W. Elevation: 11 meters Marambio: Argentinean station @64.2° S 56.7° W. Elevation: 198 meters Rothera: British station @67.5° S 68.1° W. Height: 32 meters

5

6

7 Data Issues Missing Values- Data from some points for some stations are missing Questionable Values- some averages not reliable enough or are preliminary in nature Some values for month but none for six hour observations-how is it computed? Completeness of records Only four stations used

8 Some Results Averages seem to rise/fall on a regular basis Rises and drops mostly correlate with each other Some stations show more variation than others, such as Marambio ; others more consistent, such as Faraday Can vary from time to time and month to month; some stations more consistent at some of these points Graphs of z-scores also roughly correlate

9

10

11

12

13 Z-Scores Scores denote number standard deviations from the mean, which here is done by month in each dataset Those +-2 or greater are considered to be statistically significant(68% of data within 1 and 95% of data within 2 Most values of significance were negative Greatest value was more than -4, for Rothera Station in April 1980, for all five datasets

14

15

16

17

18 Extreme Value Counts, where z-score>=2 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecemberTotal 19805105 1252 198155 19821932116 198333 19849110 19850 198618110 198710 20 19880 1989104115 1990415 199166 19925551833 19930 199411617 199511 199633 199766 199810 19990 200077 200110 200255919 2003178 20040 200533 200622 200711 200813 200955 Total24917253419311724282230

19

20 Conclusions Temperature over the last 30 years has risen on the Antarctic Peninsula, though it may be hard to see on graphs shown Temperature can be more extreme at various times of day, as many of my other graphs can show, but not here Many extreme values present as determined by z- scores and abnormal value chart Would be nice to have more consistent data sets, as well as more sets of data


Download ppt "Ryan O’Connor Geography 199 University of California, Santa Barbara."

Similar presentations


Ads by Google