Estimation of Local-Scale Precipitable Water Vapor Distribution Around Each GNSS Station Using Slant Path Delay: Evaluation of a Severe Tornado Case Using High-Resolution NHM

Shoji, Yasuhiro; Mashiko, Wataru; Satô, Eiichi

doi:10.2151/sola.2015-008

Cited by 12 publications

(9 citation statements)

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“…Possible reasons for the difference in the overlap functions of the two Raman channels at low altitude are the difference in the optical paths ( Fig. 1) and the spatial inhomogeneity of PMT sensitivity (Simeonov et al, 1999;Hamamatsu Photonics, 2007). To correct for the difference, we derived the ratio of beam overlap functions by comparing w obtained with the MRL under the assumption of…”

Section: Beam Overlap Correction For the Raman Channelsmentioning

confidence: 99%

“…The difference in PWV would be large if large horizontal inhomogeneity of the water vapor concentration existed in the observation area. Shoji et al (2015) utilized the slant path delay of the GNSS signal to estimate the horizontal inhomogeneity of water vapor on a scale of several kilometers around the measurement site. The use of a technique that combines MRL and GNSS observations for monitoring the vertical and horizontal distributions of water vapor holds promise, and the development of such a technique is our future task.…”

Section: Comparison With Gnss Pwv Datamentioning

confidence: 99%

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Automated compact mobile Raman lidar for water vapor measurement: instrument description and validation by comparison with radiosonde, GNSS, and high-resolution objective analysis

et al. 2019

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We developed an automated compact mobile Raman lidar (MRL) system for measuring the vertical distribution of the water vapor mixing ratio (w) in the lower troposphere, which has an affordable cost and is easy to operate. The MRL was installed in a small trailer for easy deployment and can start measurement in a few hours, and it is capable of unattended operation for several months. We describe the MRL system and present validation results obtained by comparing the MRL-measured data with collocated radiosonde, Global Navigation Satellite System (GNSS), and high-resolution objective analysis data. The comparison results showed that MRL-derived w agreed within 10 % (rootmean-square difference of 1.05 g kg −1 ) with values obtained by radiosonde at altitude ranges between 0.14 and 1.5 km in the daytime and between 0.14 and 5-6 km at night in the absence of low clouds; the vertical resolution of the MRL measurements was 75-150 m, their temporal resolution was less than 20 min, and the measurement uncertainty was less than 30 %. MRL-derived precipitable water vapor values were similar to or slightly lower than those obtained by GNSS at night, when the maximum height of MRL measurements exceeded 5 km. The MRL-derived w values were at most 1 g kg −1 (25 %) larger than local analysis data. A total of 4 months of continuous operation of the MRL system demonstrated its utility for monitoring water vapor distributions in the lower troposphere.Published by Copernicus Publications on behalf of the European Geosciences Union.

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Section: Beam Overlap Correction For the Raman Channelsmentioning

confidence: 99%

Section: Comparison With Gnss Pwv Datamentioning

confidence: 99%

Automated compact mobile Raman lidar for water vapor measurement: instrument description and validation by comparison with radiosonde, GNSS, and high-resolution objective analysis

et al. 2019

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“…The error due to the mapping will be greatly reduced when the satellite constellation of the four QZSS is completed, and at least one QZSS satellite remains near the zenith. Shoji et al (2014Shoji et al ( , 2015 showed that the error of PWV SPD-H derived from mapping reaches its minimum at the location where the line of sight reaches the scale height of water vapor. Assimilating the PWV SPD-H data as PWV just over the location where the line of sight reaches the scale height of water vapor is recommended.…”

Section: Summary and Discussionmentioning

confidence: 99%

Data assimilation experiment of precipitable water vapor observed by a hyper-dense GNSS receiver network using a nested NHM-LETKF system

Oigawa

Tsuda

Seko

et al. 2018

Earth Planets Space

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We studied the assimilation of high-resolution precipitable water vapor (PWV) data derived from a hyper-dense global navigation satellite system network around Uji city, Kyoto, Japan, which had a mean inter-station distance of about 1.7 km. We focused on a heavy rainfall event that occurred on August 13-14, 2012, around Uji city. We employed a local ensemble transform Kalman filter as the data assimilation method. The inhomogeneity of the observed PWV increased on a scale of less than 10 km in advance of the actual rainfall detected by the rain gauge. Zenith wet delay data observed by the Uji network showed that the characteristic length scale of water vapor distribution during the rainfall ranged from 1.9 to 3.5 km. It is suggested that the assimilation of PWV data with high horizontal resolution (a few km) improves the forecast accuracy. We conducted the assimilation experiment of high-resolution PWV data, using both small horizontal localization radii and a conventional horizontal localization radius. We repeated the sensitivity experiment, changing the mean horizontal spacing of the PWV data from 1.7 to 8.0 km. When the horizontal spacing of assimilated PWV data was decreased from 8.0 to 3.5 km, the accuracy of the simulated hourly rainfall amount worsened in the experiment that used the conventional localization radius for the assimilation of PWV. In contrast, the accuracy of hourly rainfall amounts improved when we applied small horizontal localization radii. In the experiment that used the small horizontal localization radii, the accuracy of the hourly rainfall amount was most improved when the horizontal resolution of the assimilated PWV data was 3.5 km. The optimum spatial resolution of PWV data was related to the characteristic length scale of water vapor variability.

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“…The Earth's atmosphere, including the ionosphere, affects navigation signals transmitted by Global Navigation Satellite Systems (GNSS), which causes positioning errors. It is able to eliminate the ionospheric effect using a pair of GNSS carrier waves, and then GNSS analysis estimates the signal delay by the atmosphere as an unknown parameter [1][2][3][4]. The atmospheric delay is obtained by integrating the refractivity along the ray path, which is calculated with the variables of temperature, pressure, and water vapor pressure in the atmosphere.…”

Section: Introductionmentioning

confidence: 99%

Applications of GNSS Slant Path Delay Data on Meteorology at Storm Scales

Kawabata¹,

Shoji²

2018

Multifunctional Operation and Application of GPS

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This chapter focuses on applications of Global Navigation Satellite Systems (GNSS) slant path delay data (SPD) to obtain signals from thunderstorms or rainbands. Current operational numerical weather prediction systems (NWPs) use water vapor distributions derived by GNSS technology as vital information for predicting convective rainfall. Mostly, zenith total delay or integrated water vapor data are used at horizontal scales of several tens of kilometers for this purpose. Beyond such operational use, SPD can be used to obtain information on storms (cumulonimbus) at horizontal scales of less than 10 km. For instance, found that SPD represents very small-scale phenomena of less than 10 km and can be used to estimate water vapor distribution around a thunderstorm with a strong tornado, and succeeded in improving the forecast skill of a rainband at 10 km scale. This chapter reviews SPD, which is invaluable for predicting thunderstorms and/or rainbands.

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Estimation of Local-Scale Precipitable Water Vapor Distribution Around Each GNSS Station Using Slant Path Delay: Evaluation of a Severe Tornado Case Using High-Resolution NHM

Cited by 12 publications

References 12 publications

Automated compact mobile Raman lidar for water vapor measurement: instrument description and validation by comparison with radiosonde, GNSS, and high-resolution objective analysis

Automated compact mobile Raman lidar for water vapor measurement: instrument description and validation by comparison with radiosonde, GNSS, and high-resolution objective analysis

Data assimilation experiment of precipitable water vapor observed by a hyper-dense GNSS receiver network using a nested NHM-LETKF system

Applications of GNSS Slant Path Delay Data on Meteorology at Storm Scales

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