文献一覧: Takuya KAWABATA (著者)

7 0 0 0 OA Forecasts of the July 2020 Kyushu Heavy Rain Using a 1000-Member Ensemble Kalman Filter

著者: Le Duc Takuya Kawabata Kazuo Saito Tsutao Oizumi
出版者: Meteorological Society of Japan
雑誌: SOLA (ISSN:13496476)
巻号頁・発行日: vol.17, pp.41-47, 2021 (Released:2021-03-08)
参考文献数: 21
被引用文献数: 8 15

Forecast performances of the July 2020 Kyushu heavy rain have been revisited with the aim of improving the forecasts for this event. While the Japan Meteorological Agency's (JMA) deterministic forecasts were relatively good, the JMA's ensemble forecasts somehow missed this event. Our approach is to introduce flow-dependence into assimilation by running a 1000-member local ensemble transform Kalman filter (LETKF1000) to extract more information from observations and to better quantify forecast uncertainties. To save computational costs, vertical localization is removed in running LETKF1000. Qualitative and quantitative verifications show that the LETKF1000 forecasts outperform the operational forecasts both in deterministic and probabilistic forecasts.Rather than a trick to save computational costs, removal of vertical localization is shown to be the main contribution to the outperformance of LETKF1000. If vertical localization is removed, forecasts with similar performances can be obtained with 100 ensemble members. We hypothesize that running ensemble Kalman filters with around 1000 ensemble members is more effective if vertical localization is removed at the same time. Since this study examines only one case, to assess benefit of removing vertical localization rigorously when the number of ensemble members is around 1000, a larger set of cases needs to be considered in future.

2023-08-27 21:52:52
7 + 19 Twitter

4 0 0 0 OA Impacts of an Urban Canopy Scheme and Surface Observation Data on a Heavy Rain Event through Data Assimilation

著者: Ken Sawada Naoko Seino Takuya Kawabata Hiromu Seko
出版者: 公益社団法人日本気象学会
雑誌: SOLA (ISSN:13496476)
巻号頁・発行日: vol.19B, no.Special_Edition, pp.1-8, 2023 (Released:2023-03-10)
参考文献数: 23

Considering urbanization effects on atmospheric states and subsequent precipitation is crucial to improve the accuracy of forecasting localized heavy rainfall around urban areas and to mitigate related disasters. For this purpose, it is effective to use a time development model that can accurately represent city-specific effects, such as urban heat island effect, in the assimilation process, and to assimilate high-frequency/high-density surface observation data that have not been used thus far. Therefore, this study incorporated a forecast model with an urban canopy scheme into an ensemble-based assimilation system and assimilated dense surface data from an Atmospheric Environmental Regional Observation System. Then, we performed analysis-forecast experiments for a heavy rain event in Tokyo metropolitan area on 30 August 2017, to examine the impact of urbanization. Our results showed that the urban scheme and surface observation improved near-surface temperature and moisture fields, thereby contributing to the formation of a clearer convergence line between the easterly and southerly winds where it was observed. Consequently, these improvements resulted in an earlier onset of rainfall and better reproduction of the heavy rainfall distribution.

2023-03-16 21:31:55
4 + 4 Twitter

3 0 0 0 OA Observing System Simulation Experiments of a Rich Phased Array Weather Radar Network Covering Kyushu for the July 2020 Heavy Rainfall Event

著者: Yasumitsu Maejima Takuya Kawabata Hiromu Seko Takemasa Miyoshi
出版者: Meteorological Society of Japan
雑誌: SOLA (ISSN:13496476)
巻号頁・発行日: vol.18, pp.25-32, 2022 (Released:2022-03-07)
参考文献数: 35
被引用文献数: 6

This study investigates a potential impact of a rich phased array weather radar (PAWR) network covering Kyushu, Japan on numerical weather prediction (NWP) of the historic heavy rainfall event which caused a catastrophic disaster in southern Kumamoto on 4 July 2020. Perfect-model, identical-twin observing system simulation experiments (OSSEs) with 17 PAWRs are performed by the local ensemble transform Kalman filter (LETKF) with a regional NWP model known as the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM) at 1-km resolution. The nature run is generated by running the SCALE-RM initialized by the Japan Meteorological Agency (JMA) mesoscale model (MSM) analysis at 1800 JST 3 July 2020, showing sustained heavy rainfalls in southern Kumamoto on 4 July. Every 30-second synthetic reflectivity and radial winds are generated from the nature run at every model grid point below 20-km elevation within 60-km ranges from the 17 PAWRs. Two different control runs are generated, both failing to predict the heavy rainfalls in southern Kumamoto. In both cases, assimilating the PAWR data improves the heavy rainfall prediction mainly up to 1-hour lead time. The improvement decays gradually and is lost in about 3-hour lead time likely because the large-scale Baiu front dominates.

2022-03-10 23:17:39
3 + 5 Twitter

2 0 0 0 OA Impacts of an Urban Canopy Scheme and Surface Observation Data on a Heavy Rain Event through Data Assimilation

著者: Ken Sawada Naoko Seino Takuya Kawabata Hiromu Seko
出版者: 公益社団法人日本気象学会
雑誌: SOLA (ISSN:13496476)
巻号頁・発行日: pp.19B-001, (Released:2023-02-13)

Considering urbanization effects on atmospheric states and subsequent precipitation is crucial to improve the accuracy of forecasting localized heavy rainfall around urban areas and to mitigate related disasters. For that purpose, it is effective to use a time development model that can accurately represent city-specific effects, such as urban heat island effect, in the assimilation process, and to assimilate high-frequency/high-density surface observation data that have not been used thus far. Therefore, this study incorporated a forecast model with an urban canopy scheme into an ensemble-based assimilation system and assimilated dense surface data from an Atmospheric Environmental Regional Observation System. Then, we performed analysis-forecast experiments for a heavy rain event in Tokyo metropolitan area on August 30, 2017, to examine the impact of urbanization. Our results showed that the urban scheme and surface observation improved near-surface temperature and moisture fields, thereby contributing to the formation of a clearer convergence line between the easterly and southerly winds where it was observed. Consequently, these improvements resulted in an earlier onset of rainfall and better reproduction of the heavy rainfall distribution.

2023-02-15 19:35:13
2 + 2 Twitter

2 0 0 0 OA Forecasts of the July 2020 Kyushu heavy rain using a 1000-member ensemble Kalman filter

著者: Le Duc Takuya Kawabata Kazuo Saito Tsutao Oizumi
出版者: Meteorological Society of Japan
雑誌: SOLA (ISSN:13496476)
巻号頁・発行日: pp.2021-007, (Released:2021-01-29)
被引用文献数: 15

2021-02-07 07:06:14
2 + 2 Twitter

2 0 0 0 OA Evaluation of Forward Operators for Polarimetric Radars Aiming for Data Assimilation

著者: Takuya KAWABATA Hans-Stefan BAUER Thomas SCHWITALLA Volker WULFMEYER Ahoro ADACHI
出版者: Meteorological Society of Japan
雑誌: Journal of the Meteorological Society of Japan. Ser. II (ISSN:00261165)
巻号頁・発行日: pp.2018-017, (Released:2017-12-27)
被引用文献数: 6

In the preparation for polarimetric radar data assimilation, it is essential to examine the accuracy of forward operators based on different formulations. For this purpose, four forward operators that focus on warm rain condition are compared with both each other and actual observations with respect to their performance for C-band dual polarimetric radars. These operators mutually consider radar beam broadening and climatological beam bending. The first operator derives polarimetric parameters assuming an exponential raindrop size distribution obtained by the models and is based on fitting functions against scattering amplitudes. The other three converters estimate the mixing ratio of rainwater from the measured polarimetric parameters. The second converter uses both the horizontal reflectivity (ZH) and the differential reflectivity (ZDR), the third uses the specific differential phase (KDP), and the fourth uses both KDP and ZDP, respectively. Comparisons with modeled measurements show that the accuracy of the third converter is superior to the other two. Another evaluation with actual observations shows that the first converter has slightly higher fractions skill scores than the other three. Considering the attenuation effect, the fitting function and the operator only with KDP are found to be the most suitable for data assimilation at C-band.

2018-05-13 12:06:52
2 + 1 Twitter

1 0 0 0 OA Recent Progress of the NHM-4DVAR towards a Super-High Resolution Data Assimilation

著者: Takuya Kawabata Kosuke Ito Kazuo Saito
出版者: (公社)日本気象学会
雑誌: SOLA (ISSN:13496476)
巻号頁・発行日: vol.10, pp.145-149, 2014 (Released:2014-10-04)
参考文献数: 27
被引用文献数: 2 5

A new 4-dimensional variational data assimilation system with 0.5-km grid spacing (NHM-4DVAR.v3) was developed by integrating the nonhydrostatic storm-scale 4D-Var (NHM-4DVAR.v2) and the Japan Meteorological Agency (JMA) nonhydrostatic model (NHM) based Variational Data Assimilation System (JNoVA). Both systems are based on the JMANHM, but horizontal resolutions, their formulations, adjoint models of physical processes, and observation operators are different. NHM-4DVAR.v3 comprises advantages of both systems: a penalty term, optimization of lateral boundary conditions, and observation operators for advanced observations. This development aimed at improving the forecast accuracy of hazardous weather at meso-γ-scales (5∼20 km). In this paper, the characteristics of NHM-4DVAR.v3 and some results, including the integrated formulations, are presented. An assimilation experiment of actual observations using NHM-4DVAR.v3 with 2-km grid spacing was found to show improvement over NHM-4DVAR.v2 at the same resolution. As a final goal, NHM-4DVAR.v3 was applied with a 0.5-km resolution. The comparison between assimilation results by NHM-4DVAR.v3 with 0.5- and 2-km horizontal resolutions indicates that analyses with super high resolutions can reproduce more detailed atmospheric features such as convective clouds.

2014-10-07 15:53:58
1 + 0 Twitter