A New Typhoon-Monitoring Method Using Precipitation Water Vapor

Zhao, Qingzhi; Ma, Xiongwei; Yao, Wanqiang; Yao, Yibin

doi:10.3390/rs11232845

Cited by 29 publications

(28 citation statements)

References 27 publications

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“…This temporal variation trend in PWV, i.e. an increase as a TC approaches and a quick decrease after the TC passage, was consistent with that of many other TC cases [21]- [23]. The low temporal resolution of RS-PWV (twice daily) is not sufficient for the study of the characteristics of the PWV variation, especially for the weather conditions of TCs, not to mention the possible drift of sounding balloons caused by strong winds during the TC occurrence.…”

Section: Temperal Variation In Pwv During Tropical Cyclonessupporting

confidence: 88%

“…Since a large PWV value above each GNSS station was mainly brought by a TC, as a signal at the station, the time of PWV arrival (TOPA) may be used to indicate the movement status of the TC. Based on the times of the signals occurred over several stations, the movement of a typhoon can be estimated, which can be found from very recent researches [21], [22]. However, these study cases were only from super typhoons.…”

Section: F Using Gnss-pwv Signals To Monitor Tropical Cyclonesmentioning

confidence: 99%

“…At present, some studies proved that the variation in GNSS-PWV could reflect a typhoon's life and so GNSS-PWV can be used to forecast short-term rainfall during the typhoon's period [19], [20]. In addition, some researchers proposed to use PWV time series over several GNSS ground tracking stations in a region to estimate the movements of a super typhoon [21], [22]. Many results were based on only one TC case, especially for super typhoons [23]- [25], which might not sufficiently reveal the true characteristics of water vapor or may not be applicable to other cases.…”

mentioning

confidence: 99%

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Precipitable Water Vapor Converted from GNSS-ZTD and ERA5 Datasets for the Monitoring of Tropical Cyclones

Shen

Wan

et al. 2020

IEEE Access

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Tropical cyclones (TCs) are intense rotating storm systems, characterized by strong winds, heavy humidity and storm surges, and usually cause an abnormal increase in regional water vapor during the period of their occurrence. Global navigation satellite system (GNSS) is well-established and initially mainly for positioning, navigation and timing. However, due to their global coverage and 24/7 operability under all weather conditions, GNSS has been widely used in meteorology such as the retrieval of precipitable water vapor (PWV). Since PWV time series obtained from a regional ground GNSS tracking stations network has high temporal and spatial resolutions, in this research, the temporal and spatial variation trends of regional PWVs during several TCs' periods in Hong Kong were investigated, and a new method using high-resolution GNSS-PWV time series to estimate a TC's movement was proposed. Test data were from 15 GNSS tracking stations equipped with meteorological sensors, and three GNSS stations without meteorological sensors but using meteorological data interpolated from ERA5 (fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting) dataset, and six TC events occurred in 2017 were selected for cases studies. Moreover, for a better accuracy of GNSS-PWV, which is converted from the zenith wet delay of the GNSS signal multiplying a conversion factor that uses a weighted mean temperature (T m), a seasonal multi-factor T m model was established and tested. Results showed that the new T m model outperformed the previous regional T m model used in Hong Kong. In addition, based on the temporal variation trend and spatial distribution of the regional PWV, one can determine if a TC approaches the region. A geometric approach to estimating a TC's movement was developed and its test results agreed well with the truth. These results suggest the potential of using GNSS signals to monitor the movements of TCs for short-time TC forecasting due to their high temporal resolution. INDEX TERMS Tropical cyclone, global navigation satellite system, precipitable water vapor, weighted mean temperature, ERA5. I. INTRODUCTION Over recent years, increasing tropical cyclone (TC) events occurred frequently in the North Pacific, Indian Ocean, Southwest Pacific and North Atlantic, causing considerable damage in nearby cities [1]-[5]. Many countries, provinces and cities have set up meteorological departments, which take the early warning and forecasting of TCs as a key task. Water vapor, as a main component of the atmosphere, is a key factor The associate editor coordinating the review of this manuscript and approving it for publication was Gerardo Di Martino. influencing TCs' development [6], [7]. The monitoring of regional water vapor variation is critical for the forecasting of the movement, intensity and rainfall of TCs [8]-[10]. Traditional techniques for the acquisition of atmospheric water vapor, such as infrared satellite remote sensing, radiosondes (RS) and microwave radiometers, have the disa...

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Section: Temperal Variation In Pwv During Tropical Cyclonessupporting

confidence: 88%

Section: F Using Gnss-pwv Signals To Monitor Tropical Cyclonesmentioning

confidence: 99%

mentioning

confidence: 99%

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Precipitable Water Vapor Converted from GNSS-ZTD and ERA5 Datasets for the Monitoring of Tropical Cyclones

Shen

Wan

et al. 2020

IEEE Access

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“…Overall, because a large number of valid signals exhibit a dependent relationship, as shown in Equations (6) and 7, even with the introduction of massive valid signals, the tomography equation will yield minor rank score improvement. However, the massive signals will bring a high condition number to the tomography equation itself, which causes a severe ill-condition problem.…”

Section: General Tomographic Window and Existing Problemsmentioning

confidence: 99%

“…Atmospheric water vapor (WV) drives numerous weather events and climate change [1,2]. Hence, accurately sensing the dynamic variation of WV is beneficial to weather forecasting and warnings for severe weather [3][4][5][6]. However, the traditional WV detection technique exhibits several inevitable shortcomings.…”

Section: Introductionmentioning

confidence: 99%

A Refined Tomographic Window for GNSS-Derived Water Vapor Tomography

Yao

Liu

et al. 2020

Remote Sensing

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Global navigation satellite system (GNSS) tomography can effectively sense the three-dimensional structure of tropospheric water vapor (WV) using the GNSS observations. Numerous studies have utilized a tomographic window to include more epochs of observations, which significantly increases the number of valid signals. However, considering the tomography grid limits, a massive number of valid signals inevitably exhibits linear dependence. This dependence makes it impossible to improve the rank score of the tomography coefficient matrix by blindly introducing a large number of valid rays. Furthermore, excessive valid signals may lead to a high condition number in the coefficient matrix (ill-condition problem), which causes unstable results using the GNSS-WV tomography. Considering these problems, we proposed an improved tomographic approach, which applies a refined tomographic window. It differs from the general tomographic window in that the window is refined to traverse the valid signals available 15 min before and after the target epoch while retaining only the linearly independent parts (characteristic signal). Compared to the conventional method, the proposed method can filter the characteristic signal, which increases the rank score of the coefficient matrix and improves the stability of the tomography model. In this paper, we used GNSS observations from the Hong Kong Satellite Positioning Reference Station Network (SatRef) to validate the performance of the proposed method over the day-of-year (DOY) periods of 130–132, 2019 and 146–148, 2019. The numerical results showed that, by using a refined tomographic window, the proposed method obtained superior WV products in comparison with that of the conventional method.

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4D modeling of precipitable water vapor to assess flood forecasting by using GPS signals

Sorkhabi,

Djamour

2023

Nat Hazards

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Every year the government and people suffer from the cost of damages caused by natural disasters such as hurricanes and oods. Thanks to Global Positioning System (GPS) permanent station data, today it is possible to determine the amount of Water Vapor (WV) very accurately and reliably. GPS signals pass through different layers of the atmosphere, such as the ionosphere and troposphere, and therefore they are delayed. A signi cant part of the delay is due to the troposphere, which is one of the serious sources of error in GPS. In this research, by using 5 GPS permanent stations located in the Arasbaran region, in northwest of Iran, the Precipitable Water Vapor (PWV) is evaluated in order to show the capacity of this method in forecasting the October 2012 ood over the region. The results showed that the amount of PWV in the atmosphere had increased by 2 mm a few hours before the ood, which could be used as a forecast indicator. The Tikhonov regularization for tropospheric tomography covering the GPS stations region was also performed for latitude and altitude components for 3 consecutive days: the day before the ood, the ood day, and the day after the ood. A high amount of PWV was observed in the troposphere on the day before the ood, and especially on the ood day. During the study period, the results from tomography and the radiosonde were in good agreement, with a signi cance correlation of around 0.95. Also, the values of PWV obtained from GPS and MODIS-NIR do not have an absolute error more than 4.4 mm over the 8 days from 8 October 2012 to

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A New Typhoon-Monitoring Method Using Precipitation Water Vapor

Cited by 29 publications

References 27 publications

Precipitable Water Vapor Converted from GNSS-ZTD and ERA5 Datasets for the Monitoring of Tropical Cyclones

Precipitable Water Vapor Converted from GNSS-ZTD and ERA5 Datasets for the Monitoring of Tropical Cyclones

A Refined Tomographic Window for GNSS-Derived Water Vapor Tomography

4D modeling of precipitable water vapor to assess flood forecasting by using GPS signals

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