# GPS Time Series Analysis from Aboa the Finnish Antarctic Research Station
## 4 Discussion  
### What Do Aboa Results Tell to Us? Two PPP-based solutions were produced, compared and validated. These solutions agree very well despite several differences in the processing engine and precise products in use. The achieved level of agreement (2.6 and 6.0 mm in rms error in horizontal and vertical, respectively) brings confidence in the quality of the PPP-derived coordinate time series and its analysis findings. Although the receivers are identical, they have different firmware versions. For code residuals, median rms error accounts for 0.54 m in case of firmware version 2.3, whereas 0.48 m accounts for the firmware version 2.5. It is clear that the version 2.5 brings an improvement in the code tracking of a 10%. Moreover, the receiver with firmware version 2.3 exhibits a mild upwards trend in the code residual. This might be a sign of the equipment ageing. Furthermore, the Antarctic cold environment might also effect the tracking performance as the residuals over the Antarctic winter are slightly lower than the residuals over the Antarctic summer. For the phase residuals, there is little difference between the two firmware versions, with median rms around 7.6 mm. Despite several days exhibiting larger errors, more than 95% of the phase residuals are below 9 mm. The annual and semiannual signals are well-known in GNSS time series and they are also visible in these time series. In addition, the vertical time series of the GIPSY solutions showed periodical signals at roughly 5, 14 and 27 day period at the Up component of the GIPSY solution. The 14 day signals have similar periods as the aliased periods resulted when combining unmodelled short-period tidal signals i.e., diurnal O1 tide and semidiurnal M2 tide [74; 75]. The biweekly period might also be related to semi-monthly Mf tide. On the other hand, the time series reveals no clear draconitic signal at 351.2 days as reported in several studies [76; 77]. According to the Rayleigh criterion, a time series longer than 25 years would be needed to be able to distinguish between the tropical year (365.25 y) and the GPS draconitic year (351.2 y) periodic signals. Taking the environmental loading factors into account did not reduce the rms or the seasonality of the time series. Some components were maybe slightly affected, but no major improvements could be spotted. This is in accordance with our previous studies with Fennoscandian stations. We found that taking the environmental loading into account may or may not reduce the standard deviation in the time series [78]. Even when there is a clear visual correlation, the reduction of, for example non-tidal ocean loading, may not necessarily improve the results [79]. The effect on trend is not clear either, as  
Figure 15: Environmental loading time series at Aboa between 2003–2017: atmospheric loading (**left**) and non-tidal ocean loading (**right**). The red curve is from GFZ loading service and black curve is from EOST. For more details, see the text. the hydrologic or atmospheric models may not be that stable over decadal time scales. The usage of reprocessed atmospheric models is likely to reduce this uncertainty. The choice of the noise model affects at a maximum 0.08 mm/y to the estimated trend (GIPSY Up component), but the estimated uncertainties are on average three times larger for the PL model. In addition, the RTKLIB solution includes larger annual variability compared to the GIPSY solution. The semiannual amplitudes are roughly on the same level. Furthermore, the GIPSY and RTKLIB velocity estimates differ 0.1 mm/y horizontally and 0.3-0.4 mm/y vertically. The difference in vertical velocity estimates also supports the choice of PL noise model for more realistic uncertainty estimation. The choice of PL noise is in agreement with other general studies [33; 80; 81; 82]. The residuals may suggest a different trend for the 2003-2006 period. This can be supported by studies on the snow mass changes in Antarctica showing a significant increase in snow mass after the 2006 in the area of Aboa [83].