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|[[File:GPS MarketSt.jpg|none|thumb|x300px|Here's another example of running down Market Street in San Francisco, where you can see the errors that would add to the distance. ]]
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=GPS Accuracy and Weather=
GPS Accuracy is slightly better with clear skies than with cloud cover. The difference between completely clear and fully overcast is generally less than 0.1% and my testing includes a similar mix of cloud cover for each watch, so I ignore this difference. However, rain can degrade accuracy by 0.3-3.1%, with the better watches being impacted the least. Because it does not rain that frequently where I test, this has created some potential bias in my testing so I now ignore measurements taken during the rain. This has only made a slight difference to the results, but it ensures consistence.
=GPS Accuracy and Seasons=
I run in a wooded area with mostly deciduous trees, so the foliage varies by season. This foliage can have a noticeable impact on GPS accuracy, with better accuracy during the bare winter months than the rest of the year. This difference is mostly 0.1-1.5%, but in some cases can be as large as 2.5%. Because of this, my testing now ignores data from the winter months when the trees are bare. The short winter here in the south of the US means that the impact on the overall results are small, but like the weather impacts noted above, this does ensure greater consistency.
=GPS Accuracy and Pace=
[[File:AccuracyAndPace.jpg|none|thumb|500px| A plot of GPS precision against pace. The red line is the correlation.]]
There have been reports of GPS accuracy changing with pace, but as you can see from the graph above, my testing does not show this.
=GPS Accuracy and Sampling Rate=
GPS watches default to recording a sample frequently enough that accuracy is not compromised. However, several devices offer the option of recording less frequently to improve battery life at the cost of accuracy. These devices actually turn off the GPS receiver, turning it on periodically for just long enough to get a fix. The images below are from the [[2014 Badwater 135]] using the [[Suunto Ambit2| Suunto Ambit2 R]] with recording set to one minute intervals. As you can see, accuracy suffers on curves, but is fine on the straights. For a course like Badwater, the one minute recording interval was fine as the course has few turns.
{| class="wikitable"
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|[[File:GPS Sampling Curve.jpg|none|thumb|x300px|On a curve, the infrequent samples tend to 'cut the corners' and are quite inaccurate.]]
|[[File:GPS Sampling Straight.jpg|none|thumb|x300px|On the straight sections, the one minute sampling does not lose any accuracy.]]
|[[File:GPS Sampling Comparison.jpg|none|thumb|x300px|Here's a comparison of 1 minute sampling (red) with 1 second sampling (blue). On my GPS testing course the 1 minute sampling lost nearly 2 miles over a 16 mile run.]]
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=Device Specific Notes=
For those interested in some of the details of how devices are configured for testing, here are some additional notes.
* Garmin devices are set to 'smart recording'. I did try an informal test with the 620 using 1-second recording, but it appeared to make no difference.
* For details of the calibration of the [[Footpod]] see [[GPS Testing Methodology]].
* The Fenix 2 was tested with and without WAAS support activated; WAAS helped slightly.
* The [[Garmin 920XT]] was tested with Watch Firmware 2.50, GPS Firmware 2.70 using smart recording.
=Garmin 620 Issues=
The Garmin 620 had some notorious problems with its GPS accuracy. The table below shows the changes with various firmware versions, culminating in the GPS-3.30 firmware that resolved the issues. I've including some testing I did without EPO data (NoEPO row below) and with a Footpod (+FP row below).
|[[File:Fenix2 Getting Lost6.jpg|none|thumb|x400px|This GPS track looks reasonable until marker #54, and then the track gets offset, but strangely it stays offset until the last marker.]]
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=Next Steps=
This is an initial analysis of the data I have, and there are a number of further evaluations to do.
