Spatio-Temporal Variations of Precipitable Water Vapor and Horizontal Tropospheric Gradients from GPS during Typhoon Lekima

Tu, Manhong; Zhang, Weixing; Bai, Jingna; Wu, Di; Liang, Hong; Lou, Yidong

doi:10.3390/rs13204082

Cited by 6 publications

(6 citation statements)

References 33 publications

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“…The H 2 O columns in the ground layer are higher than those in the troposphere and the entire at-mosphere, especially in summer. This is because H 2 O is mainly distributed in the ground layer [51], and transpiration occurs in summer, mainly at the surface, so a moist atmosphere near the surface leads to more H 2 O in the ground layer [27,43]. The correlation coefficient between XH 2 O values in the ground layer and troposphere is 0.841 (see Figure 13), and the correlation is relatively higher in winter and lower in summer.…”

Section: Time Series Of H 2 O In the Ground Layer The Entire Atmosphe...mentioning

confidence: 99%

Ground-Based Remote Sensing of Atmospheric Water Vapor Using High-Resolution FTIR Spectrometry

Shan

Liu

et al. 2023

Remote Sensing

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Understanding the distribution of atmospheric water vapor (H2O) is crucial for global warming studies and climate change mitigation. In this study, we retrieved the ground layer, tropospheric and total columns of H2O using ground-based high-resolution Fourier transform infrared spectrometry (FTIR). The H2O total columns are obtained from near-infrared (NIR) and mid-infrared (MIR) spectra, and the ground layer and tropospheric H2O columns are retrieved from the MIR spectrum. The total columns of H2O retrieved from NIR and MIR have a good consistency (R = 0.989). Additionally, the ground layer H2O columns have a similar seasonal variation to total columns and tropospheric columns but have a higher seasonal amplitude. The ground layer H2O columns are close to the total columns and tropospheric columns in winter; however, in summer, the average difference between the ground layer and total columns and the value between the ground layer and tropospheric columns are large. This is mostly due to temperature variation. The temperature has a linear response to H2O, and the relationship between surface temperature and ln(XH2O) values in the ground layer, the entire atmosphere and the troposphere show a significantly positive correlation, and the correlation coefficient R is 0.893, 0.882 and 0.683, respectively. Furthermore, we selected the HYSPLIT model to simulate the back trajectories of air parcels in the four seasons in Hefei and find that the air mass transport has a significant impact on the local H2O change. These results demonstrate that ground-based high-resolution FTIR technology has high accuracy and precision in observing the vertical distribution and seasonal changes of H2O in different atmospheres.

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Section: Time Series Of H 2 O In the Ground Layer The Entire Atmosphe...mentioning

confidence: 99%

Ground-Based Remote Sensing of Atmospheric Water Vapor Using High-Resolution FTIR Spectrometry

Shan

Liu

et al. 2023

Remote Sensing

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“…The wind, since it is already a vectorial field, we compared directly with the ZTD horizontal gradients vectors. In spite of this methodology being different from recent studies proposed by Reference [34][35][36], we prefer to perform direct comparisons with atmospheric variables, instead of computing gradients derived from the refractivity computed from NWM. Therefore, we compute the gradients of the water vapor field and the pressure field as:…”

Section: Correlations With Era5mentioning

confidence: 99%

Comprehensive Study on the Tropospheric Wet Delay and Horizontal Gradients during a Severe Weather Event

et al. 2022

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GNSS meteorology is today one of the most growing technologies to monitor severe weather events. In this paper, we present the usage of 160 GPS reference stations over the period of 14 days to monitor and track Hurricane Harvey, which struck Texas in August 2017. We estimate the Zenith Wet Delay (ZWD) and the tropospheric gradients with 30 s interval using TOMION v2 software and carry out the processing in Precise Point Positioning (PPP) mode. We study the relationship of these parameters with atmospheric variables extracted from Tropical Rainfall Measuring Mission (TRMM) satellite mission and climate reanalysis model ERA5. This research finds that the ZWD shows patterns related to the rainfall rate and to the location of the hurricane. We also find that the tropospheric gradients are correlated with water vapor gradients before and after the hurricane, and with the wind and the pressure gradients only after the hurricane. This study also shows a new finding regarding the spectral distribution of the gradients, with a clear diurnal period present, which is also found on the ZWD itself. This kind of study approaches the GNSS meteorology to the increasing requirements of meteorologist in terms of monitoring severe weather events.

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“…Now, PWV is usually analyzed in connection with typhoon and rainfall, where there is a strong correlation between them [14][15][16]. In order to scientifically verify the correlation between PWV, typhoon and rainfall, researchers built models and correlation coefficients [17][18][19]. For the correlation between PWV and rainfall during typhoon transit, the distribution characteristics of PWV and its correlation with actual rainfall during two typical rainfall processes in 2018 were analyzed using the Pearson correlation coefficient method [19].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Temporal and Spatial Characteristics of PWV and Rainfall with the Typhoon Movement: A Case Study of ‘Meihua’ in 2022

Li,

Wang,

Wei

et al. 2023

Atmosphere

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The serious and frequent typhoon activities can easily cause extreme precipitation weather in the eastern coastal area of China, which is affected by land and sea differences. To explore the temporal and spatial characteristics of Precipitable Water Vapor (PWV) and rainfall during the typhoon period, the data of the conspicuous case named ‘Meihua’ in 2022 is adopted in analysis. In this paper, firstly, the accuracy of the PWV retrieved by ERA5 was evaluated, which met the experimental analysis requirements, compared with the conference value of the Radiosonde (RS). Secondly, the correlation between PWV, rainfall and the typhoon path were analyzed qualitatively and quantitatively, using 16 meteorological stations in the typhoon path. The results indicated that PWV reached its peak value 2–6 h than rainfall, which was an important reference for rainfall forecasting. Then, the ‘Pearson correlation coefficient’ method was used for the quantitative evaluation of the correlation between PWV and the distance of the ‘weather station-typhoon’. The results showed that PWV had an obvious upward trend, with a decrease in the distance between the ‘weather station-typhoon’. The variation in PWV is intense at a reduced distance, and can reach its peak 16 h before the arrival of the typhoon. A strong negative correlation was demonstrated, with an average value of −0.73 for the Pearson correlation coefficient. Analyzing the temporal and spatial changes of the typhoon track, PWV and rainfall, the results show that before the typhoon passes through the region, both the PWV and rainfall certainly reach their maximum. The variation trends of PWV and rainfall in the period of the typhoon are significantly consistent. The center of PWV and rainfall is mainly located on the northwest side of the typhoon center, which showed obvious asymmetry.

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Spatio-Temporal Variations of Precipitable Water Vapor and Horizontal Tropospheric Gradients from GPS during Typhoon Lekima

Cited by 6 publications

References 33 publications

Ground-Based Remote Sensing of Atmospheric Water Vapor Using High-Resolution FTIR Spectrometry

Ground-Based Remote Sensing of Atmospheric Water Vapor Using High-Resolution FTIR Spectrometry

Comprehensive Study on the Tropospheric Wet Delay and Horizontal Gradients during a Severe Weather Event

Analysis of the Temporal and Spatial Characteristics of PWV and Rainfall with the Typhoon Movement: A Case Study of ‘Meihua’ in 2022

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