Enhancing GNSS tropospheric delay corrections through an innovative lapse rate grid and adiabatic modelling

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research Pub Date : 2025-02-01 DOI:10.1016/j.asr.2024.11.039

Jian Mao , Di Hu , RuiGuang Li , ChangChen Wu , TieJun Cui

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引用次数: 0

Abstract

Since measurements of meteorological parameters like air pressure, water vapor pressure, and temperature are typically not conducted at the receiving antenna’s height, accurate vertical adjustments are indispensable for the tropospheric delay calculation in GNSS applications. We developed an enhanced GPT3 model named as GPT3a, incorporating a new temperature lapse rate grid model and the adiabatic method. The capabilities of GPT3a in predicting atmospheric parameter profiles are assessed by comparison with radiosonde data, NCEP reanalysis data, and GNSS data. Compared with GPT3, IGPT, UNB3, and the constant model with a value of 6.5 K/km, the accuracy of the GPT3a is improved by 50 %, 26 %, 21 %, and 31 % respectively in predicting lapse rate. The RMSEs of GPT3a, GPT3 and IGPT, across temperature profiles (4.2 K, 10.7 K and 6.6 K, respectively), pressure profiles (5.7 hPa, 18.7 hPa and 6.8 hPa, respectively), and ZHD profiles (16.4 mm, 36.4 mm and 17.5 mm, respectively), demonstrate that GPT3a performs superiorly to the GPT3 and IGPT models. Moreover, in the GNSS-based water vapor retrieval, when there is a large height difference between GNSS sites and the model, the GPT3a obviously outperforms GPT3. In short, GPT3a can be used as an enhancement of GPT3 to support GNSS positioning, GNSS meteorology and atmospheric research, which extends the applicability of GPT3 beyond the Earth’s surface to airspace.

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通过创新的递减率网格和绝热模型增强GNSS对流层延迟校正

由于大气压力、水汽压、温度等气象参数的测量通常不在接收天线的高度进行，因此精确的垂直调整对于GNSS应用中的对流层延迟计算是必不可少的。我们建立了一个增强型GPT3模型，命名为GPT3a，该模型结合了一个新的温度递减率网格模型和绝热方法。通过与探空数据、NCEP再分析数据和GNSS数据的比较，评估了GPT3a预测大气参数剖面的能力。与GPT3、IGPT、UNB3和6.5 K/km的常数模式相比，GPT3a对日减率的预测精度分别提高了50%、26%、21%和31%。GPT3a、GPT3和IGPT在温度剖面（分别为4.2 K、10.7 K和6.6 K）、压力剖面（分别为5.7 hPa、18.7 hPa和6.8 hPa）和ZHD剖面（分别为16.4 mm、36.4 mm和17.5 mm）上的均方根误差表明，GPT3a模型优于GPT3和IGPT模型。此外，在基于GNSS的水汽反演中，当GNSS站点与模型高度差较大时，GPT3a明显优于GPT3。总之，GPT3a可以作为GPT3的增强，支持GNSS定位、GNSS气象和大气研究，将GPT3的适用性从地球表面扩展到空域。

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来源期刊

Advances in Space Research 地学天文-地球科学综合

CiteScore

5.20

自引率

11.50%

发文量

800

审稿时长

5.8 months

期刊介绍： The COSPAR publication Advances in Space Research (ASR) is an open journal covering all areas of space research including: space studies of the Earth''s surface, meteorology, climate, the Earth-Moon system, planets and small bodies of the solar system, upper atmospheres, ionospheres and magnetospheres of the Earth and planets including reference atmospheres, space plasmas in the solar system, astrophysics from space, materials sciences in space, fundamental physics in space, space debris, space weather, Earth observations of space phenomena, etc. NB: Please note that manuscripts related to life sciences as related to space are no more accepted for submission to Advances in Space Research. Such manuscripts should now be submitted to the new COSPAR Journal Life Sciences in Space Research (LSSR). All submissions are reviewed by two scientists in the field. COSPAR is an interdisciplinary scientific organization concerned with the progress of space research on an international scale. Operating under the rules of ICSU, COSPAR ignores political considerations and considers all questions solely from the scientific viewpoint.