# Cross-Regional Pavement Temperature Prediction Using Transfer Learning and Random Forest
## 3 Analysis of Meteorological Characteristics
### Pavement Temperature Characteristics  
The temperature distribution characteristics at various depths across different sites are shown in Figure 3. From this, the layered response pattern of temperature variation within the pavement structure can be identified. In general, both the maximum temperature and the temperature variation range decrease significantly with increasing depth. The most pronounced fluctuations occur at the surface layer (0 cm), where the widest temperature distribution is observed. This indicates that the surface is directly exposed to environmental conditions and is highly sensitive to meteorological influences. At Site01, for instance, the surface temperatures exceed 60 \({}^{\circ}\)C, with frequent occurrences above 40 \({}^{\circ}\)C. This further confirms the strong environmental impact in this region. At depths of 5 cm and 12 cm, the temperature fluctuations are reduced but still notable. As the depth increases to 30 cm, the temperature variation becomes more stable. The maximum temperature drops below 35 \({}^{\circ}\)C, and extreme values are significantly reduced. The distribution curve flattens, indicating that deeper layers are largely insulated from short-term meteorological fluctuations. Regarding regional differences, notable variations in temperature patterns across sites are observed. At a depth of 0 cm, Site01, Site02, and Site03 exhibit wide temperature ranges, with minimum values falling below 0 \({}^{\circ}\)C. Among these, the maximum temperatures at Site01 and Site03 exceed 60 \({}^{\circ}\)C, indicating pronounced temperature extremes and high fluctuation intensity. This reflects substantial diurnal or seasonal variation. In contrast, Site04 displays the most concentrated distribution. Although the overall temperature range remains relatively high, the median and interquartile range are more stable. This suggests a more regular and predictable temperature pattern. In terms of statistical characteristics, the median temperatures at Site01 and Site03 are close to 20 \({}^{\circ}\)C. The data distributions are relatively balanced, but the long whiskers reflect large fluctuations and strong influence from extreme values. Site02 has a slightly higher median, at around 25 \({}^{\circ}\)C, but a considerable portion of low-temperature data is present, indicating a generally cooler temperature profile. Site04 records the highest median temperature, at approximately 30 \({}^{\circ}\)C, with a narrow distribution. This reflects a warmer and more stable regional climate. Further comparison of the extreme ranges indicates that Site01 exhibits the widest upper and lower whiskers. This suggests that the temperature variation at this site is the most pronounced. In contrast, the distributions at Site02 and Site03 are more convergent; however, a difference in temperature bias is still evident. The minimum value at Site02 is lower than that at Site03, while the maximum value at Site03 exceeds that of Site02. This implies that the temperature amplitude at both sites is similar, but Site02 is generally colder, while Site03 is slightly warmer. Although the extreme range at Site04 is narrower, a higher data density is observed. This reflects strong temperature stability within a typical range. From the perspective of distribution density, most of the temperature values at  
Figure 3: Pavement temperature characteristics at different depths in different regions. Site01, Site02, and Site03 fall within 15 \({}^{\circ}\)C to 30 \({}^{\circ}\)C. In contrast, the dense region of Site04 shifts toward 30 \({}^{\circ}\)C to 40 \({}^{\circ}\)C, confirming both its higher temperature level and stronger thermal stability. As depth increases, the differences in temperature distributions across sites become less pronounced; however, relative distinctions remain. The regional characteristics in terms of amplitude, extreme values, and distribution patterns are still evident at deeper layers, although the overall temperature variation decreases.