Yoshinori Shoji

TOKYO METROPOLITAN AREA CONVECTION STUDY FOR EXTREME WEATHER RESILIENT CITIES

The present paper describes background, mission, research topics, and preliminary results of the research project “Tokyo Metropolitan Area Convection Study for Extreme Weather Resilient Cities (TOMACS)”. TOMACS is one of the research projects of “Social System Reformation Program for Adaption to Climate Change” which has been started since July 2010 under the “Special Coordination Funds for Promoting Science and Technology” of the Ministry of Education, Culture, Sports, Science and Technology (MEXT). TOMACS aims to understand the processes and mechanisms of extreme weather, using dense meteorological observation networks designed in the Tokyo metropolitan district, to develop a monitoring and predicting system of extreme phenomena (MPSEP), and to implement social experiments on extreme weather resilient cities in collaboration with related government institutions, local governments, private companies, and residents. More than 25 organizations and over 100 people participate in the present research projects. One of unique features of TOMACS is utilization of dense meteorological instruments in the Tokyo Metropolitan area which is one of the most urbanized areas in the world. The field campaign in the Tokyo metropolitan area, using research instruments and operational meteorological networks is planned by MRI and thirteen groups in the summers of 2011-2013 to target the tropospheric environment, boundary layer, initiation of convections and lifecycle of thunderstorms. Observation on environmental conditions of convections are carried out using radio sonde, wind profiler, GPS network, unmanned air viecle, and network of automated weather stations. Generation and development of convective precipitations are investigated by observations using Doppler lidar, rapid scan geostationary satellite, Kuband polarimetric radar, X-band polarimetric radar network (X-NET) and C-band research polarimetric radar and C-band operational Doppler radars. Several thunderstorms were captured by the dense meteorological network during 2011 campaign observations. The present paper shows preliminary results of the analysis. Social experiments on extreme weather resilient city using radar networks are also presented.

Cloud-Resolving 4D-Var Assimilation of Doppler Wind Lidar Data on a Meso-Gamma-Scale Convective System

AbstractThe authors evaluated the effects of assimilating three-dimensional Doppler wind lidar (DWL) data on the forecast of the heavy rainfall event of 5 July 2010 in Japan, produced by an isolated mesoscale convective system (MCS) at a meso-gamma scale in a system consisting of only warm rain clouds. Several impact experiments using the nonhydrostatic four-dimensional variational data assimilation system (NHM-4DVAR) and the Japan Meteorological Agency nonhydrostatic model with a 2-km horizontal grid spacing were conducted in which 1) no observations were assimilated (NODA), 2) radar reflectivity and radial velocity determined by Doppler radar and precipitable water vapor determined by GPS satellite observations were assimilated (CTL), and 3) radial velocity determined by DWL were added to the CTL experiment (LDR) and five data denial and two observational error sensitivity experiments. Although both NODA and CTL simulated an MCS, only LDR captured the intensity, location, and horizontal scale of the obs...

Semi-diurnal and diurnal variation of errors in GPS precipitable water vapor at Tsukuba, Japan caused by site displacement due to ocean tidal loading

Simultaneous GPS and water vapor radiometer (WVR) observations were carried out at Tsukuba, Japan from May 1 to June 30, 1998. The precise point positioning method of the GIPSY/OASIS-II software package (GIPSY) was used to retrieve precipitable water vapor (GPS_PWV) from GPS data, which was then compared with precipitable water vapor observed by WVR (WVR_PWV). They agreed quite well with the root mean square difference of less than 1.5 mm. However, periodic variations were found in the difference between GPS_PWV and WVR_PWV (dPWV). It was also found that semi-diurnal or diurnal components of these variations had a positive correlation with site displacement due to Ocean Tidal Loading (OTL). Two months of dPWV data were decomposed by the period of a component of OTL, and then composite time series data with a period equal to that of the component were made. This process was performed for K1, O1, M2, and S1 components of OTL. In each component, a periodic variation in dPWV appeared which was similar to those of the simulated GPS_PWV errors from OTL effects calculated with ‘GOTIC’ (Sato and Hanada, 1984), a program for the computation of OTL effect. Inclusion of OTL effects into GIPSY analysis reduced dPWV. Inthe M2 component, the amplitude of the dPWV was reducedby about 80%. This suggests that the OTL components calculated by the GOTIC succeeded in simulating the actual site displacement by OTL effects in Japan. On the other hand, in K1 components, the amplitude of dPWV without OTL in GIPSY is 1.5 times larger than the simulated GPS PWV error, with considerable error remaining even in the case of GIPSY analysis with OTL. The error may be due to multi-path effect, temperature dependency on conversion from Zenith Wet Delay to PWV, or instrument dependency of WVR on temperature. Analysis utilizing much longer data periods than the present two months is required to overcome these difficulties.

Estimation of PWC gradients over the Kanto Plain using GPS data: Validation and possible meteorological implications

Simultaneous GPS and water vapor radiometer (WVR) observations were carried out in Tsukuba during May–June 1998, for the validation of precipitable water content (PWC) gradients estimated from single-site GPS data. Slant path PWC observed by WVR were fitted into hourly PWC gradients (WVR gradients) using the least-square method. GPS PWC gradients were retrieved from tropospheric delay gradients that were estimated with GIPSY OASYS 2 package (GIPSY gradients). The results indicate that GIPSY gradients had good, linear correlation with WVR gradients, especially for a large gradient range. Both gradients had spike-shaped, short time-scale (∼ hours) peaks which were mostly associated with synoptic fronts. The GIPSY gradients were also compared with meso-scale PWC gradients calculated from zenith wet delay data of GPS network (NET gradients). The results show that GIPSY gradients did not have very good correlation with NET gradients, and that significant meso-scale discrepancy existed between the two gradients for a cold frontal case on 19 June 1998. One possible reason for this discrepancy is vertical differences in RH gradients, because GIPSY gradients are sensitive to RH gradients around the scale height of humidity (∼2500 m) while RH gradients in lowermost level have largest weights for NET gradients. To study PWC gradients associated with the fronts, GPS gradients were compared with other meteorological data over the Kanto Plain for two frontal cases. The results indicate that large PWC gradient zones with horizontal scale of about several tens kilometers in cross-frontal directions were collocated with the surface wind shear zones of the fronts. This suggests that the large PWC gradients were due to humidity discontinuity around the fronts.

GPS PWV Assimilation with the JMA Nonhydrostatic 4DVAR and Cloud Resolving Ensemble Forecast for the 2008 August Tokyo Metropolitan Area Local Heavy Rainfalls

On 5th August 2008, scattering local heavy rainfalls occurred at various places over the Tokyo metropolitan area, and five drainage workers were claimed by an abrupt increase of water level. The Japan Meteorological Agency (JMA) operational mesoscale model of the day failed to predict occurrence of the local heavy rainfalls, which were brought about by deep convective cells developed on the unstable atmospheric condition without strong synoptic/orographic forcings. A 11-member mesoscale ensemble prediction with a horizontal resolution of 10 km was conducted using the operational mesoscale analysis of JMA and perturbations of the JMA global one-week ensemble prediction system as the initial condition and the initial and lateral boundary perturbations, but the intense rains exceeding 20 mm/3 h were hardly predicted. A downscaling ensemble forecast experiment with a horizontal resolution of 2 km was conducted using the 6 h forecast of the 10 km ensemble as the initial and boundary conditions. Scattered intense rains were predicted in some ensemble members, but their locations and distribution were insufficient. The total precipitatable water vapor (PWV ) observed by the GNSS Earth Observation Network System (GEONET) of Geospatial Information Authority of Japan showed that the JMA mesoscale analysis given by the hydrostatic Meso-4DVAR underestimated water vapor over the Tokyo metropolitan area. To modify the initial condition, a reanalysis data assimilation experiment was conducted with the JMA’s nonhydrostatic 4DVAR (JNoVA) , where PWV data from GEONET were assimilated 2.5 days with 3-h data assimilation cycles. The 2 km downscale ensemble run from the JNoVA analysis properly predicted the areas of scattering local heavy rains. Threat scores and ROC area skill scores suggest that even in the ensemble prediction, accuracy of initial condition is critical to numerically predict small scale convective rains. Fractions skill scores indicated the value of the cloud resolving ensemble forecast for such the unforced convective rain case.

Local-Scale Precipitable Water Vapor Retrieval from High-Elevation Slant Tropospheric Delays Using a Dense Network of GNSS Receivers

Local-scale monitoring of the temporal and spatial variability of precipitable water vapor (PWV) is crucial to improve the nowcasting and forecasting of localized meteorological hazards. While GPS is now routinely employed to retrieve PWV from estimated tropospheric delays (GPS meteorology), even the densest GPS networks available have a spatial resolution of the order of tens of kilometers, which is too coarse for detecting local fluctuations of water vapor. A densification of existing networks, at least in urban areas, is necessary to provide reliable and continuous water vapor monitoring with sufficiently high horizontal resolution. Densifying existing networks down to few kilometers of inter-station distances, however, introduces at least two issues: first, a horizontal smoothing effect occurs, induced by the significant overlapping of the inverse cones above low elevation angles typically used for GPS observation processing; second, an issue of economic nature might arise if geodetic receivers are used for large-scale densifications (e.g. for early warning systems serving large cities). We tackle the first issue by using only high-elevation slant delays for PWV retrieval, and in particular by exploiting the Japanese Quasi-Zenith Satellite System (QZSS), and the second issue by investigating the use of low-cost single-frequency receivers with local ionosphere delay models. In this work we describe the results obtained in PWV retrieval from high-elevation GPS and QZSS slant delays, estimated using a dense network of receivers installed near Kyoto, Japan.

Impact of the CHAMP Occultation Data on the Rainfall Forecast

Impacts of the occultation data observed by CHAMP were investigated using the mesoscale four-dimensional data assimilation system of the Japan Meteorological Agency. We assimilated refractivity data provided from GFZ by using the method of Chen et al., in which the vertical correlation of the observation error was considered. This method was extended to apply the refractivity average along the path from a GPS satellite to a LEO satellite. When this extended method was applied to predict a rainfall system that developed in northern Japan, the rainfall system, which could not be developed without the assimilation of the occultation data, was reproduced. This result demonstrated that occultation data is useful for improving heavy rainfall forecasts.

Special issue “GNSS and SAR Technologies for Atmospheric Sensing”

Recent advances in the field of atmospheric and ionospheric sensing by GNSS and SAR technologies were discussed during two workshops held in February 2016 and October 2016 in Italy, hosted by GEOlab of Politecnico di Milano under partial support of the JSPS Bilateral Open Partnership Joint Research Projects. Another symposium was held in March 2017 at the Research Institute for Sustainable Humanosphere of Kyoto University, to discuss (1) the water vapor and ionospheric maps retrieval from space-borne and airborne SAR, (2) ionosphere and troposphere monitoring by the ground-based GNSS network and radio occultation, (3) mesoscale numerical weather prediction models and data assimilation, and (4) ground-based remote-sensing techniques, such as a wind profiling radar. This special issue collects high-quality papers that describe the findings reported during these three meetings, not limited to GNSS and SAR, but also including ground-based atmospheric sensing systems and numerical weather prediction models.

Refractivity Profiles Obtained by Abel Inversion from a Down Looking GPS Radio Occultation Experiment at Mt. Fuji: Preliminary Results and Future Plan

Down looking (DL) GPS radio occultation can produce an estimate of the atmospheric refractivity profile. The main observations are the bending angle as a function of the impact parameter. DL provides both negative as well as positive elevation angle measurements. Abel inversion can be operated on a profile of partial bending angle found by subtracting the positive elevation measurement from the negative one with the same impact parameter. In order to obtain refractivity profiles within the atmospheric boundary layer, the DL measurement experiment was performed in collaboration with JPL on the top of Mt. Fuji from July 10th to September 25th, 2001. The GPS receiver, Turbo Rogue SNR-8000, and the chock ring antenna were installed at an altitude of 3776m. On average, the numbers of daily occultation that include the negative elevation angles were six events. We succeeded in deriving the refractivity profiles, which were consistent with the radiosonde observation from these DL measurement data by applying Abel inversion. For the future, we intend to realize DL measurement from an airplane to extend the observation range.

Data assimilation of Mt. Fuji observed GPS down-looking occultation data into the JMA mesoscale numerical weather prediction model

A profile of temperature and relative humidity retrieved from Mt. Fuji observed GPS “Downward Looking (DL)” data was assimilated into mesoscale weather prediction model by using four-dimensional variational data assimilation (4D-var) procedure for typhoon case of September 9, 2001. The DL observation offered the profile of the atmosphere over the ocean where typhoon approached. Because the retrieved case was few, the observation error was expediently decided as 1 centigrade for temperature and 4 percent for relative humidity without a statistical investigation. The assimilation results show a small but positive impact for precipitation forecast. But the position of the typhoon center in the initial field slightly shifted to the opposite direction from the best track analysis by the Japan Meteorological Agency (JMA). To decide observation error of DL retrieved refractive index profile, error estimation using a three-dimensional (3D) ray-tracing model which uses mesoscale weather model outputs was executed. The 3D ray-tracing model simulated propagation of GPS signal in the model atmosphere every one-second. Then, Doppler shift, bending angle, partial bending angle (PBA), and finally refractive index profile were retrieved. It was proven that PBAs are able to reproduce from Doppler shift in high accuracy. Error of retrieved refractive index showed high correlation with horizontal variation of refractive index. The results suggest that we should assimilate bending angle or excess phase delay rather than profile of retrieved refractive index, temperature and humidity.