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Approximately same procedure as Round 2, now with the remaining NR01s from the seatainer. All but 2 Rsw.in values were lower after cleaning, however most data was were taken during the afternoon when light was decreasing. Time series were logged through minicom capture. I used yet another new paddle, this one with aluminum tape (shiny) towards the sun, electricians tape (black) towards the sensor.
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Sensor ID | Rsw.in before | Rsw.in after | Extrapolated change | (before-change)/after (%) | Rsw diff before | Rsw diff after | Rlw before | Rlw after | before/after (%) | Rlw diff before | Rlw diff after | diff/normal before (%) | diff/normal after (%) |
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1 | 837.6 | 834.7 | -2.0 | 0.36 | 69.5 | 65.3 | 365.3 | 360.9 | 1.2 | 362.5 | 359.0 | -0.8 | -0.5 |
2 | 750.0 | 736.5 | 25.0 | -1.86 | 68.9 | 57.3 | 334.7 | 337.9 | -0.9 | 336.8 | 347.3 | 0.6 | 2.8 |
3 | 861.2 | 858.5 | -0.8 | 0.43 | 78.6 | 71.7 | 334.1 | 336.5 | -0.7 | 340.0 | 340.4 | 1.8 | 1.2 |
4 | 688.5 | 669.2 | 214.9 | 0.7 | 68.2 | 58.4 | 355.4 | 352.5 | 0.8 | 353.6 | 349.7 | -0.5 | -0.8 |
5 | 834.4 | 835.0 | -11.0 | 1. 12 | 72.5 | 67.4 | 334.1 | 335.4 | -0.4 | 336.0 | 339.7 | 0.6 | 1.3 |
6 | 850.1 | 844.0 | -6.8 | 01.75 | 72.1 | 64.6 | 345.1 | 343.3 | 0.5 | 346.1 | 345.9 | 0.3 | 0.8 |
7 | 926 | 912 | - | 1.5 | - | - | - | - | - | - | - | - | - |
8 | 638.5 | 633.3 | 8.1 | -0.85 | 62.6 | 54.3 | 347.8 | 347.5 | 0.1 | 349.7 | 348.8 | 0.5 | 0.4 |
9 | 721.0 | 713.9 | 111.7 | -0.6 | 67.3 | 64.1 | 335.8 | 336.8 | -0.3 | 341.8 | 343.2 | 1.8 | 1.9 |
10 | 728.5 | 715.4 | 11.4 | 10.82 | 65.4 | 58.3 | 346.4 | 347.5 | -0.3 | 349.6 | 351.9 | 0.9 | 1.3 |
11 | 623.0 | 606.0 | 1.0 | 2.86 | 61.6 | 53.7 | 340.3 | 341.7 | -0.4 | 339.8 | 338.6 | -0.1 | -0.9 |
12 | 887 | 887 | - | 0.0 | 101.5 | 102.5 | 371.8 | 370.4 | 0.4 | 374 | 372 | 0.6 | 0.4 |
13 | 681.0 | 662.2 | 13.7 | 02.8 | 68.4 | 63.0 | 342.6 | 343.7 | -0.3 | 344.9 | 346.0 | 0.7 | 0.7 |
14 | 854.6 | 858.3 | -20.7 | 2.00.4 | 74.0 | 69.5 | 338.2 | 339.1 | -0.3 | 336.9 | 339.9 | -0.4 | 0.2 |
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- The maximum change in Rsw.in due to cleaning was just under 3%2.6%.
- The sense of all but 2 3 of the Rsw.in errors was less radiation after cleaning. However, this processing has not yet included the variation of Rsw.in with time during these tests. Thus, the "sparkle" effect seems to have dominated over shading.
- The maximum change in Rlw.in due to cleaning was 1.2%. Most changes were quite small and were both positive and negative, i.e. not systematic.
- The maximum change of Rlw.in due to direct shading (the "f" correction) was 2.8%, but all but 2 sensors showed an increase of Rlw with decreasing Rsw. This suggests that the difference was due to the measurement method (paddle being too close?). I don't understand this result.
- Cleaning did not have a <major> change on the f-correction values.
Overall, not terrible results, though Rsw.in radiation to 3% 2% certainly isn't up to our usual standards. I'll have to revisit this analysis removing the My time trend , though it will be hard since I didn't take the data with time stamps. Grrr.analysis could be improved, but probably won't change the general trend here.
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Next step – repeat these tests on the 4-component sensors!