著者

OTSUKA Michiko SEKO Hiromu SHIMOJI Kazuki YAMASHITA Koji

出版者

Meteorological Society of Japan

雑誌

気象集誌. 第2輯 (ISSN:00261165)

巻号頁・発行日

pp.2018-034, (Released:2018-03-23)

被引用文献数

11

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Rapid scan atmospheric motion vectors (RS-AMV) were derived with an algorithm developed by the Meteorological Satellite Center of the Japan Meteorological Agency (JMA) from Himawari-8 rapid scan imagery over the area around Japan. They were computed every 10 min for seven different channels, namely, the visible channel (VIS), near infrared and infrared channels (IR), three water vapor absorption channels (WV), and CO2 absorption channel (CO2), from image triplets with time intervals of 2.5 min for VIS and 5 min for the other six channels. In June 2016, the amount of data was increased by more than 20 times compared to the number of routinely used AMVs. To exploit these high-resolution data in mesoscale data assimilation for the improvement of short-range forecasts, data verification and assimilation experiments were conducted. The RS-AMVs were of sufficiently good quality for assimilation and consistent overall with winds from JMA’s mesoscale analyses, radiosonde, and wind profiler observations. Errors were slightly larger in WV than in VIS and IR channels. Significant negative biases relative to sonde winds were seen at high levels in VIS, IR, and CO2, while slightly positive biases were noticeable in WV at mid- to high levels. Data assimilation experiments with the JMA’s non-hydrostatic model based Variational Data Assimilation System (JNoVA) on a cold vortex event in June 2016 were conducted using RS-AMVs from seven channels. The wind forecasts improved slightly in early forecast hours before 12 hours in northern Japan, over which the vortex passed during the assimilation period. They also showed small improvement at low levels when averaged over the whole forecast period. The results varied slightly depending on the channels used for assimilation, which might be caused by different error characteristics of RS-AMVs in different channels.

著者

FUKUI Shin IWASAKI Toshiki SAITO Kazuo SEKO Hiromu KUNII Masaru

出版者

Meteorological Society of Japan

雑誌

気象集誌. 第2輯 (ISSN:00261165)

巻号頁・発行日

pp.2018-056, (Released:2018-09-14)

被引用文献数

10

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The feasibility of regional reanalysis assimilating only conventional observations was investigated as an alternative to dynamical downscaling to estimate the past three-dimensional high-resolution atmospheric fields with long-term homogeneity over about 60 years. The two types of widely applied dynamical downscaling approaches have problems. One with a serial long-term time-integration often fails to reproduce synoptic-scale systems and precipitation patterns. The other with frequent reinitializations underestimates precipitation due to insufficient spin-up. To address these problems maintaining long-term homogeneity, we proposed the regional reanalysis assimilating only the conventional observations. We examined it paying special attention to summer precipitation, through one-month experiment before conducting a long-term reanalysis. The system is designed to assimilate surface pressure and radiosonde upper-air observations, using the Japan Meteorological Agency's nonhydrostatic model (NHM) and the local ensemble transform Kalman filter (LETKF). It covers Japan and its surrounding area with a 5-km grid spacing and East Asia with a 25-km grid spacing, applying one-way double nesting in the Japanese 55-year reanalysis (JRA-55). The regional reanalysis overcomes the problems with both types of dynamical downscaling approaches. It reproduces actual synoptic-scale systems and precipitation patterns better. It also realistically describes spatial variability and precipitation intensity. The 5-km grid spacing regional reanalysis reproduces frequency of heavy precipitation and describes anomalous local fields affected by topography such as circulations and solar radiation better than the coarser reanalyses. We optimized the NHM-LETKF for long-term reanalysis by sensitivity experiments. The lateral boundary perturbations derived from an empirical orthogonal function analysis of JRA-55 brings stable analysis, saving computational costs. The ensemble size of at least 30 is needed because further reduction significantly degrades the analysis. The deterministic run from non-perturbed analysis is adopted as first guess in LETKF, instead of the ensemble mean of perturbed runs, enabling reasonable simulation of spatial variability in the atmosphere and precipitation intensity.

著者

MAEJIMA Yasumitsu MIYOSHI Takemasa KUNII Masaru SEKO Hiromu SATO Kae

出版者

Meteorological Society of Japan

雑誌

気象集誌. 第2輯 (ISSN:00261165)

巻号頁・発行日

pp.2019-014, (Released:2018-11-16)

被引用文献数

7

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This study aims to investigate the potential impact of surface observations with a high spatial and temporal density on a local heavy rainstorm prediction. A series of Observing System Simulation Experiments (OSSEs) are performed using the Local Ensemble Transform Kalman Filter with the Japan Meteorological Agency non-hydrostatic model at 1-km resolution and with 1-minute update cycles. For the nature run of the OSSEs, a 100-m-resolution simulation is performed for the heavy rainstorm case that caused 5 fatalities in Kobe, Japan on July 28, 2008. Synthetic radar observation data, both reflectivity and Doppler velocity, are generated at 1-km resolution every minute from the 100-m-resolution nature run within a 60-km range, simulating the phased array weather radar (PAWR) at Osaka University. The control experiment assimilates only the radar data, and two sensitivity experiments are performed to investigate the impact of additional surface observations obtained every minute at 8 and 167 stations in Kobe. The results show that the dense and frequent surface observations have a significant positive impact on the analyses and forecasts of the local heavy rainstorm, although the number of assimilated observations is three orders of magnitude less than the PAWR data. Equivalent potential temperature and convergence at the low levels are improved, contributing to intensified convective cells and local heavy rainfalls.