中国区域大气加权平均温度垂直递减率格网模型

doi:10.11947/j.AGCS.2023.20210226

测绘学报 ›› 2023, Vol. 52 ›› Issue (2): 206-217.doi: 10.11947/j.AGCS.2023.20210226

中国区域大气加权平均温度垂直递减率格网模型

谢劭峰^1,2, 王义杰^1,2, 黄良珂^1,2, 彭华¹, 黎峻宇^1,2, 刘立龙^1,2

1. 桂林理工大学测绘地理信息学院, 广西桂林 541004;
2. 广西空间信息与测绘重点实验室, 广西桂林 541004

收稿日期:2021-04-28 修回日期:2022-05-20 发布日期:2023-03-07
通讯作者: 黄良珂 E-mail:lkhuang666@163.com
作者简介:谢劭峰(1969-),男,教授,研究方向为GNSS气象学。E-mail:xieshaofeng@glut.edu.cn
基金资助:
国家自然科学基金（41864002；41704027）；广西自然科学基金（2020GXNSFBA159033；2020GXNSFBA297145；2018GXNSFAA281182）；国家重点研发计划（SQ2018YFC150052）；广西“八桂学者”岗位专项

A grid model for the lapse rate of atmospheric weighted mean temperature over China

XIE Shaofeng^1,2, WANG Yijie^1,2, HUANG Liangke^1,2, PENG Hua¹, LI Junyu^1,2, LIU Lilong^1,2

1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;
2. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China

Received:2021-04-28 Revised:2022-05-20 Published:2023-03-07
Supported by:
The National Natural Science Foundation of China (Nos. 41864002;41704027);The Guangxi Natural Science Foundation of China (Nos. 2020GXNSFBA159033;2020GXNSFBA297145;2018GXNSFAA281182);The National Key Research and Development Program of China (No. SQ2018YFC150052);The "Ba Gui Scholars" Program of the Provincial Government of Guangxi

摘要/Abstract

摘要： 大气加权平均温度（T_m）是全球导航卫星系统（GNSS）反演大气水汽（PWV）的关键参数。然而，已有经验T_m模型难以捕获T_m的日周期变化，限制了其在高时间分辨率GNSS-PWV监测中的应用。利用大气再分析资料可获取高时间分辨率的T_m信息，但需使用高精度的T_m垂直递减率模型对其进行高程改正。针对已有T_m垂直递减率模型建模仅使用单一格网点数据等不足，本文引入滑动窗口算法，利用2012—2016年的MERRA-2再分析资料建立了顾及时变垂直递减率的中国区域水平分辨率分别为1°×1.25°、2°×2.5°和4°×5°的T_m垂直递减率格网模型（简称“CTm-H1、CTm-H2和CTm-H3模型”）。联合2017年的MERRA-2、GGOS大气格网数据和探空站资料，对CTm-H模型进行精度检验，并与中国区域统一的T_m垂直递减率模型（简称“统一模型”）进行比较分析。结果表明：①以MERRA-2格网数据为参考值，通过CTm-H模型将MERRA-2地表格网数据改正到分层格网数据各层高度处检验，CTm-H 3个模型性能相当，在两种T_m数据高程差异较大时，CTm-H模型表现出显著的优势，相比于统一模型，精度（RMS值）整体提高了30%。②以探空站资料为参考值，通过CTm-H模型将MERRA-2地表格网数据和GGOS大气格网产品分别改正到探空站高度处检验，与统一模型相比，CTm-H 3个模型的精度整体分别提高了3%和5%，且CTm-H和统一模型的精度相比于未顾及垂直改正提升较大，尤其在中国西部地区表现出显著的优势。总体而言，CTm-H 3个模型在中国区域均具有较高的精度，不需要实测气象参数即可提供中国区域近地空间范围内（本文指0~10 km的高程范围）任意位置实时高精度的T_m高程改正值，因此，它在中国区域的实时高精度GNSS水汽探测中具有重要的应用。

关键词: 大气加权平均温度, T_m垂直递减率, 滑动窗口算法, GNSS大气水汽, MERRA-2

Abstract: Atmospheric weighted mean temperature (T_m) is an important parameter for retrieving precipitable water vapor (PWV) from GNSS signals. However, current empirical T_m models are difficult to capture the diurnal variation of T_m, which limited its application in high temporal resolution GNSS-PWV monitoring. The T_m information with high temporal resolution can be obtained by atmospheric reanalysis data, which is need to use high-precision T_m lapse rate model for vertical elevation correction. Aiming at the shortages of current T_m lapse rate models, which only single gridded point data is used for modeling, we used MERRA-2 reanalysis data over 6 a period from 2012 to 2016 to develop T_m lapse rate grid model considering the time-varying lapse rate with horizontal resolutions of 1°×1.25°, 2°×2.5° and 4°×5° based on sliding window algorithm, named as CTm-H1, CTm-H2 and CTm-H3 model, respectively. Both MERRA-2, GGOS atmospheric gridded data and radiosonde data from 2017 are treated as reference values to assess the performance of CTm-H models. The results are compared with the united T_m lapse rate model of China, named as united model. The results show that CTm-H models show the similar performance when compared with MERRA-2 gridded data, before MERRA-2 surface gridded data were corrected to each layer height of MERRA-2 pressure level gridded data by CTm-H models, CTm-H models show significant advantages when the height difference between two kinds of T_m data is large. In terms of RMS, CTm-H models have improved by approximately 30% against united model. CTm-H models show the similar performance when compared with radiosonde data, before MERRA-2 surface gridded data and GGOS atmospheric gridded products were corrected to the height of radiosonde data by CTm-H models, respectively. In terms of RMS, CTm-H models have improved by approximately 3% and 5% against united model, respectively. CTm-H and united models show significant advantages compared with the condition without vertical correction, especially in western China. In summary, CTm-H models have a good performance in China, which is provided real-time high-precision T_m elevation correction for any location of the near-earth space range (the height range from 0 to 10 km) in China without any in situ meteorological parameters, thus, which have potential application for real-time high-precision GNSS-PWV retrieval in China.

Key words: atmospheric weighted mean temperature, T_m lapse rate, sliding window algorithm, GNSS precipitable water vapor, MEERA-2

中图分类号:

P228

谢劭峰, 王义杰, 黄良珂, 彭华, 黎峻宇, 刘立龙. 中国区域大气加权平均温度垂直递减率格网模型[J]. 测绘学报, 2023, 52(2): 206-217.

XIE Shaofeng, WANG Yijie, HUANG Liangke, PENG Hua, LI Junyu, LIU Lilong. A grid model for the lapse rate of atmospheric weighted mean temperature over China[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(2): 206-217.

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中国区域大气加权平均温度垂直递减率格网模型

A grid model for the lapse rate of atmospheric weighted mean temperature over China

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