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SLR Global Performance Report Card

January 1, 2001 through December 31, 2001

In addition to the report card are the following graphs. (Performance Graphs in html format (compressed)). Note: Click on the hyperlinks below to go the appropriate graph. Please don't forget to change your printer page format to landscape if you want to print the charts.

Below are the detailed descriptions of each column in the performance report card:

  • Column 1 is the station location name.
  • Column 2 is the monument marker number.
  • Column 3 is the LEO pass total during the past 12 months.
  • Column 4 is the LAGEOS pass total during the past 12 months.
  • Column 5 is the high satellite pass total during the past 12 months.
  • Column 6 is the pass total (i.e., all satellites) during the past 12 months.
  • Column 7 is the LEO NP total during the past 12 months.
  • Column 8 is the LAGEOS NP total during the past 12 months.
  • Column 9 is the high satellite NP total during the past 12 months.
  • Column 10 is the NP total (i.e., all satellites) during the past 12 months.
  • Column 11 is the tracking minutes total (i.e., all satellites) during the past 12 months. This is computed by the summation of the number of normal points multiplied by its bin size in minutes.
  • Column 12 is the average single-shot LAGEOS RMS, in millimeters, during the last quarter.
  • Column 13 is the average LAGEOS normal point RMS, in millimeters, during the last quarter, based on CSR Weekly LAGEOS analysis.
  • Column 14 is the measure of short term bias stability, in millimeters, during the last quarter. The short term stability is computed as the standard deviation about the mean of the pass-by-pass range biases from the CSR Weekly LAGEOS analysis.
  • Column 15 is the measure of long term bias stability, in millimeter, during the past year. The long term stability is the standard deviation of the monthly range bias estimates from the CSR Weekly LAGEOS analysis. A station must have tracked LAGEOS (1,2) in at least 8 of the last 12 months in order to compute this metric.
  • Column 16 is the percentage of LAGEOS normal points that were accepted in CSR weekly LAGEOS analysis.
  • Column 17 is the median data latency, in hours, to the data centers, during the last quarter.
  • Column 18 is the ILRS normal point format revision number used within the last quarter.
  • Column 19 is a yes/no answer to the question of whether or not a site log has been provided to the central bureau. Site logs will be a replacement for the configuration files.

The first entry in the table is for the performance baseline goal. Note: There is no baseline goal for NP data quantities, single shot RMS, and normal point RMS.

Additional Notes: Blanks in any columns mean either that there was no data or that there was insufficient data. Only stations that have supplied data within the last year are included in the table. The table is sorted in descending order by total data volume.

    Data Volume Data Quality Operational Compliance
Column 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Location Station Number LEO Pass Total LAG Pass Total High Pass Total Pass Total LEO NP Total LAGEOS NP Total High NP Total Total NP Minutes of Track SS RMS NP RMS Short Term Long Term % of good LAGEOS NP Data Latency (hours) Format Revision Site logs
Baseline   1000 400 100 1500             10 20 20 95 12 1 yes
Yarragadee 7090 3,850 1,172 1,380 6,402 65,967 14,406 10,640 91,013 103,167 10 2 10 2 98 1 1 yes
Monument Peak 7110 4,586 878 533 5,997 74,923 9,218 4,242 88,383 64,843 9 2 12 4 97 3 1 yes
Greenbelt 7105 4,407 961 432 5,800 83,402 10,837 3,206 97,445 65,596 10 2 11 3 98 2 1 yes
Graz 7839 3,640 722 636 4,998 85,763 10,633 5,538 101,934 75,352 8 2 11 2 99 5 1 yes
Grasse 7835 3,614 746 106 4,466 79,572 8,505 845 88,922 44,938 17 2 10 2 99 3 1 yes
Mt. Stromlo 7849 3,148 870 397 4,415 37,892 7,589 2,419 47,900 41,743 11 3 13 5 99 6 1 yes
Herstmonceux 7840 2,795 985 454 4,234 38,818 12,093 2,556 53,467 49,520 18 2 11 1 99 1 1 yes
McDonald 7080 2,149 714 671 3,534 28,731 6,191 2,576 37,498 34,384 12 3 13 2 99 1 1 yes
Changchun 7237 2,532 509 323 3,364 41,783 4,905 2,348 49,036 35,266 15 6 21 8 98 1 1 yes
Zimmerwald 7810 2,187 685 266 3,138 35,267 9,091 2,191 46,549 41,059 19 3 11 5 99 2 1 yes
Hartebeesthoek 7501 1,679 559 329 2,567 21,756 7,265 2,783 31,804 36,434 10 2 13 7 99 3 1 yes
Arequipa 7403 1,619 257 0 1,876 24,779 2,553 0 27,332 13,608 7 3 17 5 99 3 1 yes
Riyadh 7832 1,067 501 178 1,746 20,380 6,889 1,511 28,780 28,318 17 3 18 3 96 5 0 yes
Simosato 7838 1,290 280 107 1,677 26,348 3,243 670 30,261 18,795 33 6 21 13 95 0 0 yes
San Fernando 7824 1,402 215 0 1,617 22,477 1,341 0 23,818 10,105 18 4 38 80 24 2 1 yes
Shanghai 7837 1,201 279 117 1,597 17,264 2,498 750 20,512 14,623 16 6 29 14 89 2 1 yes
Potsdam 7836 1,276 252 31 1,559 19,065 2,229 145 21,439 10,764 17 6 17 8 96 7 1 yes
Haleakala 7210 946 280 280 1,506 11,889 2,932 1,706 16,527 18,301 10 5 13 7 97 1 1 yes
Wettzell 8834 896 382 138 1,416 14,822 3,853 760 19,435 16,633 21 3 22 7 100 3 1 yes
Beijing 7249 1,130 194 50 1,374 15,663 1,700 300 17,663 10,219 12 21 37 36 55 8 1 yes
Kunming 7820 671 258 124 1,053 10,153 2,187 730 13,070 11,501 36 6 37 29 65 2 0 yes
Grasse (LLR) 7845 15 387 574 976 290 6,698 3,134 10,122 29,139 22 3 11 8 97 1 1 yes
Riga 1884 769 135 0 904 15,935 1,524 0 17,459 7,347 14 5 20 15 91 2 1 yes
Borowiec 7811 443 247 19 709 7,748 2,868 71 10,687 8,432 28 8 18 13 94 3 1 yes
Tateyama 7339 460 79 27 566 5,539 517 130 6,186 3,692 13 3 19 15 91 2 1 yes
Metsahovi 7806 432 97 15 544 9,072 1,328 88 10,488 5,694 21 8 23 12 93 2 1 yes
Simeiz 1873 435 92 1 528 5,073 556 4 5,633 2,711 71 21 42   33 15 0 yes
Golosiiv 1824 349 100 0 449 5,153 627 0 5,780 2,856 78 14 88   32 19 1 yes
Katsively 1893 230 90 13 333 3,939 782 70 4,791 3,206 65 13 23   93 17 0 yes
Mendeleevo 1870 249 0 0 249 2,261 0 0 2,261 711           40 1 no
Matera (MLRO) 7941 112 107 27 246 2,048 1,235 172 3,455 4,079 6 2 14   99 207 1 yes
Tahiti 7124 207 34 0 241 2,996 307 0 3,303 1,728 8 4 15   94   1 yes
Lhasa 7356 102 117 12 231 1,503 1,410 51 2,964 3,610 31 8 24   85 13 1 yes
Helwan 7831 140 0 0 140 1,384 0 0 1,384 457           11 0 yes
Komsomolsk 1868 63 20 14 97 884 130 54 1,068 829 142 32 27   58 156 1 no
Kashima 7335 73 12 6 91 982 130 30 1,142 788               yes
Cagliari 7548 74 7 0 81 1,205 48 0 1,253 572           23 0 yes
Urumqi 7355 31 44 2 77 466 606 15 1,087 1,409               yes
Maidanak 2 1864 12 13 18 43 142 108 60 310 571 91 12 29   36 60 1 no
Maidanak 1 1863 16 15 5 36 202 99 33 334 430         0 120 1 no
Wuhan 7231 6 3 0 9 80 34 0 114 101               yes
Totals   50,303 13,298 7,285 70,886 843,616 149,165 49,828 1,042,609 823,530