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SLR Global Performance Report Card
April 1, 2000 through March 31, 2001
In addition to the report card are the following graphs. (Performance Graphs in powerpoint). 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.
- Total Data Volume (April 2000 - March 2001) by passes, normal points,or minutes of data
- LEO Satellite Data Volume (April 2000 - March 2001) by passes or normal points
- LAGEOS Data Volume (April 2000 - March 2001) by passes or normal points
- High Satellite Data Volume (April 2000 - March 2001) by passes or normal points
- LAGEOS Single Shot RMS (1st Quarter 2001)
- LAGEOS Normal Point RMS (1st Quarter 2001)
- Short Term Bias Stability (1st Quarter 2001)
- Long Term Bias Stability (April 2000 - March 2001)
- Percentage of Good LAGEOS NP (1st Quarter 2001)
- Data Latency (1st Quarter 2001)
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 | 10 | 95 | 12 | 1 | yes | |||||||
Yarragadee | 7090 | 3658 | 1089 | 1499 | 6246 | 60964 | 13564 | 10293 | 84821 | 98502 | 10 | 2 | 13 | 2 | 98 | 2 | 1 | yes |
Mt. Stromlo | 7849 | 3739 | 1343 | 829 | 5911 | 45503 | 13447 | 5301 | 64251 | 70756 | 10 | 3 | 15 | 4 | 97 | 3 | 1 | yes |
Monument Peak | 7110 | 4217 | 855 | 499 | 5571 | 68837 | 9267 | 4343 | 82447 | 63327 | 11 | 3 | 12 | 3 | 98 | 3 | 1 | yes |
Greenbelt | 7105 | 3603 | 738 | 333 | 4674 | 60779 | 8335 | 2175 | 71289 | 48012 | 10 | 2 | 11 | 2 | 98 | 3 | 1 | yes |
Herstmonceux | 7840 | 2489 | 796 | 490 | 3775 | 33116 | 9424 | 2433 | 44973 | 41931 | 17 | 3 | 11 | 3 | 99 | 1 | 1 | yes |
Graz | 7839 | 2448 | 530 | 614 | 3592 | 56526 | 7707 | 5093 | 69326 | 58351 | 8 | 2 | 9 | 3 | 98 | 15 | 1 | yes |
Grasse | 7835 | 2821 | 495 | 35 | 3351 | 60050 | 5947 | 249 | 66246 | 30862 | 17 | 2 | 11 | 3 | 99 | 2 | 1 | yes |
McDonald | 7080 | 2048 | 612 | 566 | 3226 | 29229 | 5461 | 2509 | 37199 | 32664 | 14 | 3 | 12 | 4 | 97 | 2 | 1 | yes |
San Fernando | 7824 | 2518 | 408 | 0 | 2926 | 44926 | 3254 | 0 | 48180 | 21350 | 43 | 10 | 28 | 29 | 83 | 1 | 1 | yes |
Changchun | 7237 | 2054 | 360 | 266 | 2680 | 31855 | 3105 | 1924 | 36884 | 26482 | 19 | 8 | 19 | 9 | 94 | 2 | 1 | yes |
Zimmerwald | 7810 | 1793 | 493 | 148 | 2434 | 27242 | 5956 | 1274 | 34472 | 27544 | 22 | 3 | 15 | 4 | 98 | 3 | 1 | yes |
Simosato | 7838 | 1500 | 298 | 83 | 1881 | 29422 | 3192 | 600 | 33214 | 19374 | 25 | 7 | 25 | 9 | 96 | 2 | 0 | yes |
Potsdam | 7836 | 1458 | 271 | 52 | 1781 | 21356 | 2567 | 259 | 24182 | 13022 | 16 | 4 | 24 | 7 | 97 | 8 | 1 | yes |
Wettzell | 8834 | 955 | 479 | 294 | 1728 | 12613 | 4521 | 1316 | 18450 | 19958 | 25 | 5 | 21 | 6 | 100 | 2 | 1 | yes |
Arequipa | 7403 | 1512 | 192 | 0 | 1704 | 20368 | 1781 | 0 | 22149 | 10669 | 7 | 4 | 21 | 6 | 87 | 4 | 1 | yes |
Shanghai | 7837 | 1018 | 243 | 265 | 1526 | 14530 | 2296 | 1679 | 18505 | 17927 | 18 | 6 | 34 | 6 | 87 | 9 | 1 | yes |
Beijing | 7249 | 1056 | 174 | 64 | 1294 | 14615 | 1342 | 344 | 16301 | 9369 | 24 | 16 | 32 | 30 | 34 | 12 | 1 | yes |
Kunming | 7820 | 773 | 364 | 124 | 1261 | 11164 | 3431 | 763 | 15358 | 14499 | 40 | 7 | 38 | 67 | 15 | 0 | yes | |
Tahiti | 7124 | 847 | 269 | 0 | 1116 | 12908 | 3063 | 0 | 15971 | 10948 | 9 | 2 | 13 | 5 | 95 | 4 | 1 | yes |
Riga | 1884 | 951 | 138 | 0 | 1089 | 18741 | 1759 | 0 | 20500 | 8596 | 25 | 10 | 50 | 25 | 75 | 4 | 1 | yes |
Grasse (LLR) | 7845 | 0 | 270 | 769 | 1039 | 0 | 4028 | 3301 | 7329 | 24561 | 25 | 4 | 14 | 3 | 95 | 1 | 1 | yes |
Borowiec | 7811 | 650 | 208 | 26 | 884 | 11123 | 2593 | 108 | 13824 | 9307 | 30 | 6 | 18 | 10 | 96 | 3 | 1 | yes |
Hartebeesthoek | 7501 | 557 | 172 | 57 | 786 | 6412 | 1693 | 357 | 8462 | 7601 | 9 | 2 | 22 | 9 | 93 | 3 | 1 | yes |
Tateyama | 7339 | 544 | 158 | 67 | 769 | 7442 | 1404 | 327 | 9173 | 7177 | 13 | 3 | 27 | 10 | 80 | 4 | 1 | yes |
Wuhan | 7231 | 483 | 116 | 134 | 733 | 7143 | 1421 | 932 | 9496 | 9966 | 8 | yes | ||||||
Metsahovi2 | 7806 | 483 | 76 | 12 | 571 | 9598 | 1189 | 58 | 10845 | 5426 | 22 | 8 | 19 | 96 | 11 | 1 | yes | |
Kashima | 7335 | 421 | 107 | 32 | 560 | 5471 | 977 | 143 | 6591 | 4732 | 19 | 6 | 23 | 14 | 92 | 4 | 1 | yes |
Haleakala | 7210 | 370 | 97 | 46 | 513 | 4638 | 835 | 227 | 5700 | 4376 | 16 | 6 | 13 | 98 | 11 | 1 | yes | |
Maidanak 2 | 1864 | 346 | 96 | 64 | 506 | 4368 | 684 | 200 | 5252 | 3867 | 32 | 0 | no | |||||
Matera | 7939 | 434 | 56 | 0 | 490 | 8236 | 633 | 0 | 8869 | 4088 | 1 | yes | ||||||
Helwan | 7831 | 426 | 13 | 0 | 439 | 5104 | 64 | 0 | 5168 | 1861 | 2 | 0 | yes | |||||
Beijing (TROS) | 7343 | 250 | 42 | 39 | 331 | 3879 | 535 | 257 | 4671 | 3622 | 1 | yes | ||||||
Golosiiv | 1824 | 290 | 23 | 0 | 313 | 4995 | 166 | 0 | 5161 | 1818 | 182 | 22 | 50 | 44 | 10 | 1 | yes | |
Koganei | 7328 | 225 | 25 | 5 | 255 | 2346 | 198 | 27 | 2571 | 1411 | 1 | yes | ||||||
Riyadh | 7832 | 130 | 72 | 45 | 247 | 2878 | 1097 | 414 | 4389 | 5256 | 30 | 5 | 19 | 92 | 5 | 0 | yes | |
Mendeleevo | 1870 | 222 | 0 | 0 | 222 | 1532 | 0 | 0 | 1532 | 482 | 55 | 1 | no | |||||
Katsively | 1893 | 140 | 46 | 21 | 207 | 2097 | 357 | 111 | 2565 | 1961 | 22 | yes | ||||||
Simeiz | 1873 | 117 | 35 | 4 | 156 | 1294 | 268 | 26 | 1588 | 1098 | 78 | 14 | 42 | 22 | 33 | 0 | yes | |
Komsomolsk | 1868 | 102 | 2 | 9 | 113 | 1388 | 11 | 29 | 1428 | 676 | 0 | 61 | no | |||||
Miura | 7337 | 82 | 8 | 2 | 92 | 918 | 57 | 9 | 984 | 565 | yes | |||||||
Cagliari | 7548 | 60 | 18 | 0 | 78 | 935 | 90 | 0 | 1025 | 568 | yes |
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