A Numerical Study on a Mesoscale Convective System over a Subtropical Island with 4D-Var Assimilation of GPS Slant Total Delays

Kawabata, Takuya; Shoji, Yasuhiro; Seko, Hiromu; Saitō, Kazuo

doi:10.2151/jmsj.2013-510

Cited by 36 publications

(31 citation statements)

References 17 publications

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“…With the increasing number of GNSS systems and satellites, the atmosphere scanning will be more complete, hence gaining even more interest. Bauer et al (2011) showed a positive impact of STD assimilation into the Mesoscale Model 5 (MM5) and Kawabata et al (2013) demonstrated a significant advantage of assimilating STDs into a high-resolution model in the case of forecasting local heavy rainfall event against the scenario of assimilating ZTDs only. Also, Shoji et al (2014) and Brenot et al (2013) showed promising techniques for prediction of severe weather events using advanced GNSS tropospheric products such as horizontal gradients and STDs.…”

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confidence: 99%

Inter-technique validation of tropospheric slant total delays

et al. 2017

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Abstract. An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was −0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm ± 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm ± 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at intertechnique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles.

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confidence: 99%

Inter-technique validation of tropospheric slant total delays

et al. 2017

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“…The WVI index is based on the standard deviation of the SPDs measured at a GNSS station, so directional information for each SPD is neglected. However, the results of Kawabata et al (2013) and Sato et al (2013) clearly demonstrate that the slant path direction does provide practical information.…”

Section: Introductionmentioning

confidence: 94%

“…Shoji (2013) proposed two new indices using decomposed components of the gradient and higher-order inhomogeneity: the water vapor concentration (WVC) index, which represents the spatial concentration of water vapor 2 to 3 km above ground, and the water vapor inhomogeneity (WVI) index, which expresses the degree of water vapor variation around each GNSS station on a scale of several kilometers. Using SPD values derived from the procedure of Shoji et al (2013), Kawabata et al (2013) considered the impact of SPD assimilation on the reproduction of small-scale convective precipitation. Sato et al (2013) compared PWV values measured by radiosonde with those derived from the GNSS SPD and found that the SPD closest to the radiosonde path exhibited better agreement than the estimated zenith total delay (ZTD).…”

Section: Introductionmentioning

confidence: 99%

Estimation of Local-scale Precipitable Water Vapor Distribution Around Each GNSS Station Using Slant Path Delay

Shoji¹,

Mashiko²,

Satô³

2014

SOLA

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A procedure for estimating the precipitable water vapor (PWV) distribution around ground-based stations of the global navigation satellite system (GNSS) on a scale of several kilometers is presented. This procedure utilizes the difference between the zenith total delay above a GNSS station and the zenith mapped slant path delay (SPD). This difference can be used to estimate the PWV gradient in each SPD direction by assuming an exponential distribution for the horizontal water vapor gradient.The procedure was tested using an estimation of the PWV variation associated with the parent storm of an F3 Fujita scale tornado that occurred in Ibaraki prefecture on 6 May, 2012. Differential reflectivity observed by a dual-polarimetric radar indicated the existence of a developed parent cloud approximately 1h before the tornado occurred. A high-resolution numerical weather model simulation suggested the existence of a strong PWV gradient around the parent cloud, made evident by the co-existence of a strong updraft and downdraft within an approximately 5-km radius. The PWV gradient, calculated using the GNSS observation network with an average spacing of approximately 17 km, could not detect such a small-scale, strong PWV gradient. The PWV gradient estimated using the proposed procedure revealed a strong PWV gradient and its enhancement. In this case, a higher-order inhomogeneity component of each SPD played a critical role.

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“…In addition, many observational studies were conducted for TMA to analyze two mesocyclones with the surface network and weather radar during TOMACS ; the urban canopy and winds (Kondo et al 2008); wind profiles, static stability, and convergence leading to the development of thunderstorms (Mikami et al 2011); multilayer winds and sea breezes measurements with the Doppler weather radar (Tsunematsu et al 2009); aerosols and sea breeze studies with the Doppler LIDAR (Iwai et al 2011); thermal and geometric studies on surface air temperature (Tomita et al 2007); effects of the Tokyo Bay sea surface temperature on urban temperature (Oda and Kanda 2009); climatology of synoptic winds and surface temperatures (Yoshikado 2013); and lee winds and rainfall in TMA (Inamura et al 2011). Further, many numerical simulations were conducted to study the impacts of land use and alteration on Tokyo surface temperature and sea breeze (Kusaka et al 2000), increased precipitation , energy balance and heat modeling (Ooka et al 2011), local heavy rainfall , Tokyo morphology (Adachi et al, 2014), and advanced data assimilation systems (Saito et al, 2017;Saito et al 2016;Kawabata et al 2011Kawabata et al , 2013Kawabata et al , 2014. Thus, many advanced research studies on convection has been conducted in Japan.…”

Section: Introductionmentioning

confidence: 99%

ARPS Simulations of Convection during TOMACS

Filho

Vemado

Saitō

et al. 2018

Journal of the Meteorological Society of Japan

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The Tokyo Metropolitan Area Convection Study (TOMACS) for extreme-weather-resilient cities is a research and development project (RDP) of the World Weather Research Programme (WWRP).TOMACS provided a multiplatform and high spatiotemporal resolution dataset for the present research on three episodes of deep convection in the Tokyo Metropolitan Area (TMA) under its heat island effect and sea breeze circulations. Heavy rainfall episodes of August 26, 2011, and July 23 and August 12, 2013, were simulated with (and without) the tropical town energy budget (T-TEB) model coupled with the advanced regional prediction system (ARPS). The T-TEB/ARPS system used initial and boundary conditions from the Japan Meteorological Agency (JMA) mesoscale analysis data for 24-hour integration runs at 5-km resolution over Japan and at 1-km resolution over TOMACS area. The 1-km resolution hourly rainfall field simulations were verified against the respective automated meteorological data acquisition system (AMeDAS) rain gauge network measurements. Statistics of the Contingency tables were obtained to estimate the critical success index (CSI), probability of detection (POD), and false alarm rate (FAR) as well as the root mean square error (RMSE). The T-TEB/ARPS simulations improved the south and east sea breeze circulations of TMA and its urban heat island effect.The time evolution of CSI scores improved within the advective time scale, whereas dissipation (phase) errors on precipitation RMSE increased with the integration time and were larger than the dispersion (amplitude) errors. The initial and boundary conditions of JMA greatly improved the simulations as compared to the previous ones performed with the outputs of NCEP's global forecast system as indicated by the TOMACS datasets. Thus, the results represent the temporal and spatial evolutions of the atmospheric conditions leading to the development of a deep convection within TOMACS region.Furthermore, TMA is a good testbed to evaluate the urban surface schemes, such as T-TEB in this study.4

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A Numerical Study on a Mesoscale Convective System over a Subtropical Island with 4D-Var Assimilation of GPS Slant Total Delays

Cited by 36 publications

References 17 publications

Inter-technique validation of tropospheric slant total delays

Inter-technique validation of tropospheric slant total delays

Estimation of Local-scale Precipitable Water Vapor Distribution Around Each GNSS Station Using Slant Path Delay

ARPS Simulations of Convection during TOMACS

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