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Fig 1.

Spatial distribution of data.

Coordinates are in latitude and longitude.

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Table 1.

Data description.

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Fig 2.

Surface temperature observations for each RWS road status.

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Fig 3.

Scatterplot of RWS and mobile surface temperature observations.

Nonparametric (LOESS) prediction line is shown in blue, the 0°C level in solid red, and 10°C in dashed red.

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Fig 4.

Scatterplot of RWS surface and air temperature observations.

Nonparametric (LOESS) prediction line is shown in blue, the 0°C level in solid red, and 10°C in dashed red.

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Fig 5.

Histograms of observations on RWS (left) and mobile (right) sensors.

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Fig 6.

Average difference between each mobile–RWS observation pair.

Stations marked with “R” measure surface temperature with a Vaisala DRS511, embedded in the asphalt, while stations marked with “Opt” have optical Vaisala DST111 instruments. When the RWS and/or the mobile observation is above 8°C, the pair is discarded. Further, each mobile–RWS pair have at least 40 measurements.

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Table 2.

Number of distinct sensors per year.

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Table 3.

Number of observations by mobile and RWS road status.

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Fig 7.

Estimates and 95% confidence intervals of fixed coefficients for the inference models.

Model A2 excluded due to term instability.

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Table 4.

Estimates of fixed effect coefficients and quality metrics for the inference models.

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Table 5.

Estimates of fixed effects coefficients and performance metrics for the prediction models.

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Table 6.

Linear coefficients for adjusting the mobile Teconer RTS411 road surface temperature observations.

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