地理科学进展 ›› 2020, Vol. 39 ›› Issue (8): 1283-1295.doi: 10.18306/dlkxjz.2020.08.004

• 研究论文 • 上一篇    下一篇

高分辨红外辐射探测器地表温度数据在江苏地区1980—2009年间适用性评估

史潇1,2,3(), 王国杰3, 孙明2, 李玉涛1,4, 王博妮1,2, 沈婕5   

  1. 1. 中国气象局交通气象重点开放实验室,南京 210008
    2. 江苏省气象服务中心,南京 210008
    3. 南京信息工程大学地理科学学院/气象灾害预报预警与评估协同创新中心,南京 210044
    4. 江苏省气象信息中心,南京 210008
    5. 南京师范大学虚拟地理环境教育部重点实验室,南京 210023
  • 收稿日期:2019-06-25 修回日期:2019-11-22 出版日期:2020-08-28 发布日期:2020-10-28
  • 作者简介:史潇(1989— ),女,江苏南京人,博士生,主要从事卫星遥感在陆表因子方面的应用研究。E-mail: 18801580429@163.com
  • 基金资助:
    江苏省气象局重点项目(KZ201902);江苏省气象局青年科研基金项目(KQ201907);江苏省气象局面上科研项目(KZ201906)

Evaluation of the long-term high-resolution infrared radiation sounder land surface temperature during 1980-2009 in Jiangsu Province, China

SHI Xiao1,2,3(), WANG Guojie3, SUN Ming2, LI Yvtao1,4, WANG Boni1,2, SHEN Jie5   

  1. 1. Key Laboratory of Transportation Meteorology, China Meteorological Administration, Nanjing 210008, China
    2. Jiangsu Meteorological Bureau, Meteorological Services Center, Nanjing 210008, China
    3. School of Geographical Sciences, Nanjing University of Information Science & Technology, Collabrative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing 210044, China
    4. Jiangsu Meteorological Bureau, Meteorological Information Center, Nanjing 210008, China
    5. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
  • Received:2019-06-25 Revised:2019-11-22 Online:2020-08-28 Published:2020-10-28
  • Supported by:
    Key Project of Jiangsu Province Meteorological Bureau Foundation(KZ201902);Jiangsu Province Meteorological Bureau Foundation for the Youth(KQ201907);Jiangsu Province Meteorological Bureau General Foundation(KZ201906)

摘要:

地表温度在物理和生物过程中起着关键作用,也是评价地表热环境的重要指标。因此,了解地表温度时空变化对城市热岛监测及生态质量的评价具有重要意义。高分辨红外辐射探测器地表温度(HIRS LST)是目前时间尺度最长的全球逐小时地温数据集。为了解江苏省地表温度的时空分布情况并研究HIRS LST数据在江苏的适用性,论文选择江苏省1980—2009年49个站点的实测地表温度数据,利用相关系数、偏差、非偏性均方根误差等方法,对HIRS产品从多角度进行了验证。结果表明,HIRS地表温度与站点地表温度数据有较好的一致性。两者相关系数在整个区域都高于0.98,2种数据的距平相关系数在0.65~0.80之间。两者偏差和非偏性均方根误差表明,HIRS的数据在江苏北部和南部部分地区低估了地表温度,主要原因是其对高于32 ℃的地温事件发生次数存在较大程度的低估。然而,HIRS LST在很大程度上高估了在20~30 ℃之间的较高温日数。在年际变化方面,HIRS LST与观测数据在春季的相关性最高,冬季最低。趋势检验表明,2种数据在春、秋、冬3个季节均呈现出明显的增长趋势,增温趋势呈现出相似的空间变化。但是,该地区夏季的地表温度长期趋势被明显高估,HIRS数据并未反映出该地区北部大面积的降温趋势,而在其他季节的地表温度被低估。

关键词: 地表温度, 遥感, HIRS, 卫星产品验证, 趋势分析, 江苏省

Abstract:

Surface temperature plays a key role in physical and biological processes on Earth, and it is an important index for evaluating surface thermal environment. Understanding the temporal and spatial variations of surface temperature is of great significance for urban heat island monitoring and ecological quality evaluation. Current land surface temperature products derived from satellite remote sensing suffer from partial coverage or cloud-cover blockage problems, which have potential limitations on the study of climate and ecological environment. The recently developed NOAA satellites High-Resolution Infrared Radiation Sounder (HIRS) land surface temperature (LST) product is among the longest LST records. To examine the spatiotemporal distribution of LST in Jiangsu Province and data performance of HIRS LST at different temporal scales, we evaluated the HIRS LST and in situ measurement correlation coefficient (R), bias, and unbiased root mean square difference (ubRMSD) using the daily, annual, and seasonal mean values, together with the long-term linear trend during 30 years in the province. Great consistency between the two products is observed. Their correlation coefficients are higher than 0.98 for all stations, and those for daily anomalies range from 0.65 to 0.80 across the region. The bias and the ubRMSD indicate that the HIRS data have generally underestimated the LST across the northern and some southern areas, mainly because of its large underestimation of the occurrences of temperature higher than 32 ℃. Nevertheless, the HIRS LST has largely overestimated the occurrences of summer days with temperature ranging from 20-30 ℃. As for the intraannual variations, the HIRS LST shows highest correlation with in situ measurements in the spring, but the correlation is lowest in the winter. Trend test shows that both sets of data show significant increasing trends with similar patterns in the spring, autumn, and winter. However, the long-term trends are significantly overestimated across the region in the summer, and underestimated in other seasons in the HIRS LST data.

Key words: land surface temperature (LST), remote sensing, High-Resolution Infrared Radiation Sounder (HIRS), product evaluation, tendency analysis, Jiangsu Province