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张璐(1999-),女,硕士研究生,主要从事寒旱区生态水文等方面的研究. E-mail: 2022212938@nwnu.edu.cn |
收稿日期: 2024-03-04
修回日期: 2024-05-08
网络出版日期: 2026-03-11
基金资助
第三次新疆综合科学考察——昆仑山北坡区域水文要素变化调查(2021xjkk0101)
国家自然科学基金(42161027)
Investigation and evaluation of surface solar radiation on the north slope of Kunlun Mountains based on multi-source data
Received date: 2024-03-04
Revised date: 2024-05-08
Online published: 2026-03-11
地表太阳辐射在全球能量平衡中起着至关重要的作用,是气候变化和水文循环的主要动力。但由于太阳辐射组分的多样性、测量仪器的高成本,高海拔山区缺乏长期可靠的观测数据。基于高分辨率的均一化中国陆表气候观测格点数据集和ERA5再分析辐射数据集,分析了1984—2023年昆仑山北坡不同时间尺度地表太阳辐射的变化特征,并利用地理探测器模型对地表太阳辐射与大气因子间的关系进行了诊断。结果表明:(1) 昆仑山北坡年均地表太阳辐射在研究时段内呈显著下降趋势,下降速率为-1.24 W·m-2·(10a)-1,季节上以夏季下降趋势最为显著,月均地表太阳辐射表现为先增加后减小,于6月达到最大值。(2) 昆仑山北坡地表太阳辐射空间分布呈由南向北逐渐降低的特征,变化趋势表现出东西部差异,除冬季外,全年和春夏秋季均为东部下降速率快于西部。(3) 根据单因子探测结果,各大气因子对地表太阳辐射空间分异的解释能力存在差异,其中水汽的解释能力较高(q=0.90),表明水汽是影响昆仑山北坡地表太阳辐射空间分布的一个重要因素。
张璐 , 孙美平 , 闫欣 , 王伟生 , 范蕊谊 . 基于多源数据的昆仑山北坡地表太阳辐射调查评估[J]. 干旱区地理, 2024 , 47(8) : 1304 -1313 . DOI: 10.12118/j.issn.1000-6060.2024.140
Surface solar radiation is pivotal in the global energy balance and serves as the primary driver of climate change and the hydrological cycle. Despite its significance, the complexity of solar radiation components and the prohibitive cost of measurement instruments have resulted in a scarcity of long-term, reliable observation data in high-altitude mountain areas. This study utilizes the high-resolution homogeneous grid dataset of Chinese land surface climate observations alongside the ERA5 reanalysis radiation dataset to analyze the variation characteristics of surface solar radiation at different time scales over the north slope of the Kunlun Mountains from 1984 to 2023. Moreover, it employs the geographical detector model to examine the relationship between surface solar radiation and atmospheric factors. The findings indicate that: (1) The average annual surface solar radiation on the north slope of the Kunlun Mountains exhibited a significant decreasing trend during the study period, with a rate of -1.24 W·m-2·(10a)-1. Seasonally, the decline was most pronounced during summer. The monthly average surface solar radiation increased initially, peaking in June, before subsequently declining. (2) The spatial distribution of surface solar radiation on the north slope of the Kunlun Mountains gradually decreases from south to north. The variation trends differ between the east and west; except in winter, the eastern decline rate exceeded that of the west throughout the year, including during spring, summer, and autumn. (3) Single-factor detection results reveal that the explanatory capabilities of atmospheric factors on the spatial differentiation of surface solar radiation vary, with water vapor demonstrating a higher explanatory ability (q=0.90). These findings confirm that water vapor is a critical factor influencing the spatial distribution of solar radiation on the north slope of the Kunlun Mountains.
表1 辐射产品基本信息Tab. 1 Basic information of radiation products |
| 数据类型 | 数据 | 来源 | 数据处理方法 | 时段 | 空间分辨率 | 时间分辨率 |
|---|---|---|---|---|---|---|
| 卫星遥感产品 | 均一化中国陆表气候观测格点数据集(SSR-wang) | 青藏高原科 学数据中心 | 地理加权回归 | 1983.07—2017.06 | 0.1° | 逐月 |
| 全球高分辨率地表太阳辐射数据集(SSR-tang) | SUNFLUX方案 | 1983.07—2018.12 | 0.1° | 3 h | ||
| 中国区域地面气象要素驱动数据集(CMFD) | Yang-混合模型 | 1979.01—2018.12 | 0.1° | 3 h | ||
| 再分析数据 | ERA5 | ECMWF | 4D-Var同化 | 1979年至今 | 0.25°×0.25° | 1 h |
| MERRA-2 | NASA | 4D-Var耦合同化 | 1980年至今 | 0.5°×0.625° | 1 h |
图2 昆仑山北坡5套地表太阳辐射产品数据变化趋势Fig. 2 Variation trend of 5 sets of surface solar radiation product data on the north slope of Kunlun Mountains |
图7 1984—2023年昆仑山北坡大气因子变化趋势注:AOD为气溶胶光学厚度。下同。 Fig. 7 Variation trends of atmospheric factors on the north slope of Kunlun Mountains from 1984 to 2023 |
表2 1984—2023年昆仑山北坡大气因子时间尺度上的变化趋势Tab. 2 Temporal trends of atmospheric factors on the north slope of Kunlun Mountains from 1984 to 2023 |
| 时间尺度 | 总云量/(10a)-1 | 低云量/(10a)-1 | AOD/(10a)-1 | 水汽/kg·m-2·(10a)-1 | 臭氧/DU·(10a)-1 |
|---|---|---|---|---|---|
| 年 | -0.0057 | 0.0019 | 0.0049 | 0.2779* | -2.2210* |
| 春季 | -0.0178* | -0.0024 | 0.0032 | 0.0732 | -3.2164 |
| 夏季 | 0.0091 | 0.0082* | 0.0180* | 0.7234* | -1.5928 |
| 秋季 | 0.0033 | 0.0032* | 0.0045 | 0.3746* | -1.2893 |
| 冬季 | -0.0174* | -0.0013 | -0.0059 | -0.0596 | -2.7857 |
注:*表示通过0.05显著性检验。 |
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