Assimilation of Nationwide and Global GPS PWV Data for a Heavy Rain Event on 28 July 2008 in Hokuriku and Kinki, Japan

Shoji, Yasuhiro; Kunii, Masaru; Saitō, Kazuo

doi:10.2151/sola.2009-012

Cited by 40 publications

(38 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The Japanese nationwide dense GNSS network (GEONET: GNSS Earth Observation NETwork), operated by the Geospatial Information Authority of Japan (GSI), has been a source of water vapor data for operational numerical weather predictions of the Japan Meteorological Agency (JMA) since 2009 (Ishikawa 2010). Shoji et al (2009) conducted a mesoscale data assimilation experiment using GPS PWV derived from stations in and surrounding Japan for a heavy rainfall event on July 28,2008. Their result demonstrated the importance of water vapor observations to the windward of torrential rainfall.…”

Section: Introductionmentioning

confidence: 99%

PWV Retrieval over the Ocean Using Shipborne GNSS Receivers with MADOCA Real-Time Orbits

Shoji¹,

Sato

Yabuki

et al. 2016

SOLA

Self Cite

View full text Add to dashboard Cite

We conducted observations using four shipborne global navigation satellite system (GNSS) receivers on three research vessels and one passenger ferry to assess the real-time practicality of measuring GNSS-derived precipitable water vapor (PWV) over the ocean. A kinematic precise point positioning strategy was used for the GNSS analysis with a real-time GNSS satellite ephemerides (orbit and clock information). The analyzed time series of PWV was contaminated with unrealistic sharp variations that occasionally occurred. Periodic occurrence of a spiky variation with a cycle of one sidereal day, along with post-fit phase residuals averaged at each elevation and azimuth, indicated that one of the causes of the unrealistically large time variation was interference of reflected signals (multi-path). A simple quality control (QC) procedure based on the amount of PWV time variation was proposed. After the QC was applied, the retrieved PWVs had 3.4−5.4mm root mean square (RMS) differences against radiosonde observations, and 2.3−3.7mm RMS against those retrieved at nearby ground GNSS stations. The proposed QC procedure rejected more than 60 percent of retrieved PWV on research vessels and 6−11 percent on a passenger ferry. The results demonstrate the great potential of the real-time ephemerides and the necessity for careful consideration of the observation environment.(Citation: Shoji, Y., K. Sato, M. Yabuki, and T. Tsuda, 2016: PWV retrieval over the ocean using shipborne GNSS receivers with MADOCA real-time orbits. SOLA, 12, 265-271,

show abstract

Section: Introductionmentioning

confidence: 99%

PWV Retrieval over the Ocean Using Shipborne GNSS Receivers with MADOCA Real-Time Orbits

Shoji¹,

Sato

Yabuki

et al. 2016

SOLA

Self Cite

View full text Add to dashboard Cite

show abstract

“…In Europe, this activity is coordinated mainly in the framework of the EUMETNET EIG GNSS Water Vapour Programme (E-GVAP, 2005(E-GVAP, -2017, phases I-III, http://egvap.dmi.dk). Many recent studies demonstrated a positive impact of the ZTD or integrated water vapour (IWV) assimilation on precipitation weather forecasts, especially of the short-time ones (Vedel and Huang, 2004;Guerova et al, 2006;Shoji et al, 2009;Guerova et al, 2016). In contrast, continuous developments in NWM forecasting and nowcasting tools, as well as increasing needs for better predictions of severe weather events, stress the demand of high-quality humidity observations with high spatial and high temporal resolutions.…”

mentioning

confidence: 99%

Inter-technique validation of tropospheric slant total delays

et al. 2017

View full text Add to dashboard Cite

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.

show abstract

“…2). Shoji et al (2009) also used this procedure to analyze IGS global GPS network data in the original Meso 4D-Var domain. Except for this modification, we followed Shoji (2009) and retrieved the Zenith Tropospheric Delay (ZTD) every 10 min.…”

Section: Analysis Of Gps Stations Around the Bay Of Bengalmentioning

confidence: 99%

“…Shoji (2009) developed a near-realtime (NRT) GPS PWV analysis procedure using predicted GPS satellite ephemeris provided by the International GNSS Service (IGS) and confirmed that the accuracy of the NRT GPS PWV is comparable to those obtained from post-analysis using IGS' precise ephemeris. Shoji et al (2009) conducted a DA experiment on GPS PWV retrieved in NRT for heavy rainfall in Japan. They confirmed that the operational forecast of heavy rainfall is improved by using GEONET PWV data in Japan, and that IGS PWV data around Japan further improves the prediction.…”

Section: Introductionmentioning

confidence: 99%

Mesoscale Data Assimilation of Myanmar Cyclone Nargis Part II: Assimilation of GPS-Derived Precipitable Water Vapor

Shoji¹,

Kunii²,

Saitō³

2011

Journal of the Meteorological Society of Japan

Self Cite

View full text Add to dashboard Cite

Four-dimensional variational (4D-Var) data assimilation (DA) experiments using Global Positioning System (GPS)-derived precipitable water vapor (PWV) were conducted for the tropical cyclone (TC) Nargis in 2008. In order to analyze the initial field at 1200 UTC 30 April 2008, 12, 24, 36, and 48 h sequential DA experiments with 3 h assimilation windows were performed. The initial fields made by these DA experiments were applied to subsequent forecast experiments using a nonhydrostatic model (NHM) with a horizontal resolution of 10 km.NHM predictions using initial fields produced by DA experiments that used only ordinary observational data (without GPS PWV) exhibited a large variation of predicted maximum TC intensity (958 to 983 hPa) for each experiment. In these experiments, a longer assimilation period did not necessarily result in better prediction. The DA of GPS PWV yielded a smaller variation of predicted maximum TC intensity (964 to 974 hPa), and a longer assimilation period tended to bring deeper depression of TC central pressure. Overall, TC intensities determined by DA experiments with GPS data were closer to the best track produced by the Regional Specialized Meteorological Centre (RSMC) New Delhi than the DA experiments without GPS data.The 48 h DA without GPS PWV resulted in the weakest prediction of TC development with the deepest TC central pressure of 983 hPa, while 48 h DA with GPS PWV successfully predicted rapid TC development with the deepest pressure of 967 hPa. One cause of the incomplete development of Nargis in the 48 h DA experiment without GPS PWV was insufficient observations in the Bay of Bengal, especially in the first 12 h. Underestimation of precipitation was conspicuous in the first 12 h of the DA.Implementation of GPS PWV into the DA contributed to increasing the precipitation and changed the fields of pressure and wind in the bay. In the first several hours, modifications of the fields of pressure and wind around the Andaman Islands were conspicuous. These affected areas extended with time and created a more favorable environment for TC development.

show abstract

Assimilation of Nationwide and Global GPS PWV Data for a Heavy Rain Event on 28 July 2008 in Hokuriku and Kinki, Japan

Cited by 40 publications

References 11 publications

PWV Retrieval over the Ocean Using Shipborne GNSS Receivers with MADOCA Real-Time Orbits

PWV Retrieval over the Ocean Using Shipborne GNSS Receivers with MADOCA Real-Time Orbits

Inter-technique validation of tropospheric slant total delays

Mesoscale Data Assimilation of Myanmar Cyclone Nargis Part II: Assimilation of GPS-Derived Precipitable Water Vapor

Contact Info

Product

Resources

About