Recent climate change has led to a continuous increase in global temperatures and a rise in the frequency and intensity of extreme weather events. Asphalt concrete pavements are particularly sensitive to environmental conditions, and their structural and functional performances are significantly influenced by temperature and moisture. In current pavement design frameworks, such as AASHTO 2002 and the Korea Pavement Research Program, climatic inputs are derived from historical observations and are typically assumed to be stationary, indicating that their statistical properties remain constant over time. However, this assumption may not adequately capture long-term climatic trends, potentially leading to an underestimation of future pavement deterioration. Therefore, this study aimed to evaluate the influence of nonstationary temperature conditions on asphalt pavement performance by incorporating statistically validated climate trends into the MEPDG analysis framework. Hourly temperature data for Gangneung from 1965 to 2024 were collected and analyzed to identify long-term trends and nonstationary characteristics. Stationarity was evaluated using augmented Dickey–Fuller and Kwiatkowski–Phillips–Schmidt–Shin tests across monthly and hourly time series (06:00, 14:00, and 22:00). The results showed that approximately 80.6% of the analyzed time series exhibited nonstationary behavior, indicating statistically significant long-term temperature trends. Based on these findings, future temperature scenarios were constructed considering nonstationary characteristics. A stationary climate scenario was defined as a baseline condition with no climate change, whereas a regression-based scenario was developed to reflect long-term temperature trends. Additionally, two climate change scenarios, SSP2-4.5, and SSP5-8.5, were adopted based on the IPCC projections. These scenarios were converted into hourly climatic inputs compatible with the enhanced integrated climatic model (EICM) within MEPDG. Compared with the stationary condition, the regression-based, SSP2- 4.5, and SSP5-8.5 scenarios showed average temperature increases of approximately 0.83 °C, 1.18 °C, and 2.25 °C, respectively. In particular, for the SSP5-8.5 future temperature scenario, an increase by up to 9.7 °C was observed at 06:00 in April compared with the stationary-based average temperature conditions. When future climate scenarios were applied to the AASHTO 2002 framework, the pavement performance was evaluated under identical structural and traffic conditions, including a 200 mm asphalt concrete surface layer, a 200 mm crushed stone base, a 150 mm subbase, and an A-2-4 subgrade. Pavement distress, including rutting, bottom-up fatigue cracking, top-down fatigue cracking, thermal cracking, and international roughness index (IRI), was predicted and compared across scenarios. The results indicated that rutting and top-down fatigue cracking increased under elevated temperature conditions, whereas bottom-up fatigue cracking, thermal cracking, and IRI exhibited relatively small differences among the scenarios. The total rutting increased from 13.19 mm under the stationary climate condition to 13.71 mm under the regression-based and SSP2-4.5 scenarios, and further to 14.15 mm under the SSP5-8.5 scenario. Similarly, asphalt layer rutting increased from 6.52 mm to 7.43 mm. Top-down fatigue cracking showed the highest sensitivity to temperature changes, increasing from 198.80 m/km under the stationary condition to 209.47 m/km, 208.49 m/km, and 217.76 m/km under the regression-based, SSP2-4.5, and SSP5-8.5 scenarios, respectively. In terms of performance criteria, the design life was maintained at 30 years under stationary climate conditions but decreased to approximately 28 years under the regression-based and SSP2-4.5 scenarios and to approximately 26 years under the SSP5-8.5 scenario because of the earlier exceedance of the top-down cracking criterion. These results indicate that temperature increases associated with nonstationary climatic conditions can accelerate rutting and surface-initiated cracking, leading to a reduction in pavement service life. Therefore, the incorporation of climate change effects into pavement design inputs is necessary for a more realistic performance prediction. These findings demonstrate that conventional pavement design approaches based on stationary climate assumptions may underestimate future pavement deterioration under changing climatic conditions. In particular, nonstationary temperature increases can accelerate key distress mechanisms and potentially reduce pavement service life. Therefore, incorporating nonstationary climate characteristics into pavement design and performance evaluation frameworks is essential for improving the reliability of long-term predictions. Future pavement design, material selection, and maintenance strategies should consider projected climate trends to ensure sustainable infrastructure performance.

ABSTRACT
1. 서론
2. 기후 조건을 고려한 아스팔트 포장 파손 예측모델
    2.1. AASHTO 2002 기반 포장 성능 예측 체계
    2.2. 아스팔트 포장 파손 예측 모델
3. 강릉 지역 기온의 비정상성 분석
    3.1. 시간대별 평균 기온의 장기 추세
    3.2. 비정상성 평가를 위한 통계적 검정
    3.3. 통계적 검정 결과
4. 미래 기온 시나리오 구축
    4.1. 개요
    4.2. 평균 기반 정상성 기후 시나리오
    4.3. 회귀 기반 시나리오
    4.4. SSP 시나리오
    4.5. 시나리오별 기온 변화 비교
5. 기후 시나리오별 아스팔트 포장 성능 예측
    5.1. 포장 구조 및 해석 조건
    5.2. 기후 시나리오별 해석 결과
6. 결론
REFERENCES

• 최예인(강원대학교 토목공학과 박사과정) | Choi Ye In
• 류정희(강원대학교 스마트인프라연구소 연구교수 · 이학박사) | Ryu Jung Hee
• 이승우(강원대학교 건설환경공학부 교수 · 공학박사) | Lee Seung Woo Corresponding author