| 引用本文: | 胡启军，周振翔，曹帮军，何乐平，李泊霖，邱佳，雍沁.2021.川藏铁路沿线地区夏季气温日较差的影响因素研究[J].地球环境学报,(6):654-665 |
| HU Qijun, ZHOU Zhenxiang, CAO Bangjun, HE Leping, LI Bolin, QIU Jia, YONG Qin.2021.Factors influencing summer diurnal temperature range at stations along the Sichuan-Tibet railway[J].Journal of Earth Environment,(6):654-665 |
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| 川藏铁路沿线地区夏季气温日较差的影响因素研究 |
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胡启军，周振翔，曹帮军，何乐平，李泊霖，邱佳，雍沁
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1.西南石油大学 土木工程与测绘学院，成都 610500
2.成都信息工程大学 大气科学学院 高原大气与环境四川省重点实验室，成都 610225
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| 摘要: |
| 利用ERA5再分析资料，分析了1979—2018年川藏铁路沿线区域气候特征。研究了2014—2018年夏季气温日较差（DTR）的变化趋势，以及2014—2018年夏季DTR与地面太阳辐射（SSR）、总降水量（TP）、总云量（TCC）、海拔（DEM）和地表平均蒸发率（MER）的相关性。结果表明：研究区域气温呈上升趋势，2014—2018年气温上升明显，温度升高达到1.8—2.0℃。区域降水集中，夏季多冬季少，降水东部多西部少。DTR在2014—2018年处于下降趋势，趋势为东部大西部小，南部大北部小。DTR与SSR呈正相关（P＜0.05），DTR与TP、TCC、MER呈负相关（P＜0.05），且相关性程度受海拔的影响。DTR与TP、MER的相关性均表现为由东向西减小，与区域内降水东多西少的分布特征相一致。各影响因素与DTR相关性程度为SSR＞MER＞TCC＞TP。 |
| 关键词: 气温日较差 地面太阳辐射 总降水量 总云量 地表平均蒸发率 |
| DOI：10.7515/JEE212010 |
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| 基金项目:四川省省属高校科研创新团队（18TD0014）；四川省杰出青年科技人才项目（2019JDJQ0037）；四川省科技计划项目（2020JDRC0091） |
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| Factors influencing summer diurnal temperature range at stations along the Sichuan-Tibet railway |
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HU Qijun, ZHOU Zhenxiang, CAO Bangjun, HE Leping, LI Bolin, QIU Jia, YONG Qin
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1. School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China
2. Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China
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| Abstract: |
| Background, aim, and scope Climate change is intensifying, with increasing temperatures directly causing sea-level rise and enhanced environmental instability. As a result, it has led to serious environmental threats to the Qinghai-Tibet Plateau region. Today, China’s western regions see many important construction projects, however, changes in the climate may have a negative impact on them. To understand the impact of climate change on the Qinghai-Tibet Plateau, and to ensure the integrity of construction projects, we choose the diurnal temperature range (DTR) as a measure for understanding climate change. This metric is the difference between the daily maximum temperature and the minimum temperature, whereby through this metric, we can identify changes in regional climate. The study area for this paper is the Hengduan Mountains (93°—104°E, 27°—32°N), located in the southeast of the Qinghai-Tibet Plateau and the western Sichuan Basin, which is seeing the construction of the Sichuan-Tibet railway. This area has a relatively special climate and environment, and the climatic changes underway are fairly large. Materials and methods In this study, the ERA5 reanalysis data provided by the Copernicus Climate Change Service (C3S) of the European Centre for Medium-Range Weather Forecasts (ECMWF) was used. From the ERA5 reanalysis data, we have obtained data for the Earth’s surface temperature from 1979 to 2018, and surface solar radiation (SSR), total precipitation (TP), total cloud cover (TCC), and mean evaporation rate (MER) for the summer seasons between 2014 and 2018. We have analyzed the characteristics of climate change over the region for the period 1979 to 2018 using the DTR changes during the summer seasons between 2014 and 2018, and analyses of the relationships between DTR and ground net SSR, TP, TCC, and the correlation between average altitude and surface MER. Results According to the analyses, the temperature in the study area increased significantly between 1979 and 2018, which is consistent with the climate warming characteristics across the country. The years 2014 to 2018 were the five warmest years since complete meteorological observation records were taken in China. For example, in 2017, temperature of the areas such as Batang increased by between 1.8℃ and 2℃ more than the long-term temperature changes between 1981—2010. From 2014 to 2018, the DTR generally presented a decreasing trend, with the absolute value of the trend characterized by increasing from east to west and from south to north. It also shows a negative correlation between the positive correlation between the SSR and DTR, TP, TCC, MER, and DTR. Discussion We find that at the 0.05 confidence level, the average Pearson correlation coefficient between SSR and DTR is close to 0.65, between MER and DTR in the Ya’an segment it reached −0.72, between TP and DTR it is −0.48, and the average value between TCC and DTR is −0.51. Considering the absolute value of the correlation coefficient, the four factors expressing the degree of change in DTR are ranked as SSR＞MER＞TCC＞TP. When the TP is small, it will significantly increase air humidity, reduce evaporation, and have a significant impact on DTR. As humidity increases, it tends to stabilize, and its impact on DTR begins to weaken. When TCC is low, the effect on DTR is weaker. As cloud cover increases, so does the absorption of solar radiation. When the degree of influence of these two factors on DTR increases to a certain value, it begins to weaken gradually. Conclusions From the above analyses, it can be concluded that SSR and MER are the main factors affecting DTR, while TP and TCC are secondary factors. In addition, the higher values of DTR are mainly concentrated in the mountainous area in the middle of the study area. The change in DTR also intensifies with increasing altitude. Recommendations and perspectives The factors influencing DTR in mountainous areas are complex, as it is also susceptible to factors such as surface vegetation and soil moisture. Therefore, there is a need to further explore the influence of the coupling between multiple factors with respect to changes in DTR, so as to more objectively understand the mechanisms behind changes in DTR. |
| Key words: diurnal temperature range surface solar radiation total precipitation total cloud cover mean evaporation rate |
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