测绘通报 ›› 2021, Vol. 0 ›› Issue (4): 52-59.doi: 10.13474/j.cnki.11-2246.2021.0110

• 学术研究 • 上一篇    下一篇

青藏高原地区大气加权平均温度模型的构建

石灵璠1, 王萍1, 黄良珂2,3,4   

  1. 1. 中国地震局地质研究所地震动力学国家重点实验室, 北京 100029;
    2. 桂林理工大学测绘地理信息学院, 广西 桂林 541004;
    3. 广西空间信息与测绘重点实验室, 广西 桂林 541004;
    4. 武汉大学卫星导航定位技术研究中心, 湖北 武汉 430079
  • 收稿日期:2020-06-05 出版日期:2021-04-25 发布日期:2021-04-30
  • 通讯作者: 王萍。E-mail:1355837527@qq.com
  • 作者简介:石灵璠(1997-),女,硕士生,研究方向为GNSS气象学及构造地貌过程。E-mail:lingfan0110@163.com
  • 基金资助:
    国家自然科学基金(41772199);中央级公益性科研院所基本科研业务专项项目(IGCEA1713)

Construction on atmospheric weighted mean temperature model over the Tibetan Plateau

SHI Lingfan1, WANG Ping1, HUANG Liangke2,3,4   

  1. 1. State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing 100029, China;
    2. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;
    3. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China;
    4. GNSS Research Center, Wuhan University, Wuhan 430079, China
  • Received:2020-06-05 Online:2021-04-25 Published:2021-04-30

摘要: 加权平均温度(Tm)是将天顶湿延迟转换为大气可降水量的关键参数,针对青藏高原地区海拔高、地形起伏大、水汽高度分布复杂的特点,本文利用2010—2014年GGOS Atmosphere Tm格网数据和地表高程数据建立Tm垂直递减率函数,进而建立一种顾及Tm垂直递减率变化的适合青藏高原地区的新模型(QTm模型)。此外,利用2015年青藏高原地区14个探空站和GGOS Atmosphere Tm格网数据评估模型精度和适用性。试验结果表明,与GGOS Atmosphere Tm相比,QTm模型的年均Bias和RMSE分别为0.29和2.49 K,相对于GPT2w-1和GPT2w-5模型,RMSE分别提升了38.97%、67.06%;与探空数据相比,QTm模型的年均Bias和RMSE分别为0.16和2.90 K,相对于GPT2w-1和GPT2w-5模型分别提升了31.12%、39.46%。新模型的构建为青藏高原地区提供了可靠的Tm值,进而提供实时、高精度GNSS水汽信息。

关键词: 青藏高原, QTm模型, GGOS, 探空站, GNSS水汽

Abstract: The weighted average temperature (Tm) is a key parameter that converts the zenith wet delay into atmospheric precipitation. According to the characteristics of high altitude, high terrain fluctuation, and complicated distribution of water vapor in the Tibetan Plateau, this paper uses the GGOS Atmosphere Tm grid from 2010 to 2014 net data and surface elevation data to establish a Tm vertical decline rate function, and then establishes a new model (QTm model) suitable for the Tibet Plateau region that changes in Tm vertical decline rate is taked into account. In addition, the accuracy and applicability of the model are evaluated using 14 radiosonde stations and GGOS Atmosphere Tm grid data from the Tibet Plateau in 2015. The results show that compared with GGOS Atmosphere Tm, the average annual Bias and RMSE of the QTm model are 0.29 and 2.49 K. Compared with the GPT2w-1 and GPT2w-5 models, the RMSE increases by 38.97% and 67.06%. In comparison, the annual average Bias and RMSE of the QTm model are 0.16 and 2.90 K, which are 31.12% and 39.46% higher than GPT2w-1 and GPT2w-5 respectively. The construction of the new model provides a reliable Tm value for the Tibet Plateau region, and thus provides real-time, high-precision GNSS water vapor information.

Key words: Tibetan Plateau, QTm model, GGOS, radiosonde stations, GNSS precipitable water vapor

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