Kisho shushi. Dai1shu/Kisho shushi. Dai2shu/Journal of the Meteorological Society of Japan, 2024
Research on particle filters has been progressing with the aim of applying them to high-dimension... more Research on particle filters has been progressing with the aim of applying them to high-dimensional systems, but alleviation of problems with ensemble Kalman filters (EnKFs) in nonlinear or non-Gaussian data assimilation is also an important issue. It is known that the deterministic EnKF is less robust than the stochastic EnKF in strongly nonlinear regimes. We prove that if the observation operator is linear the analysis ensemble perturbations of the local ensemble transform Kalman filter (LETKF) are uniform contractions of the forecast ensemble perturbations in observation space in each direction of the eigenvectors of a forecast error covariance matrix. This property approximately holds for a weakly nonlinear observation operator. These results imply that if the forecast ensemble is strongly non-Gaussian the analysis ensemble of the LETKF is also strongly non-Gaussian, and that strong non-Gaussianity therefore tends to persist in high-frequency assimilation cycles, leading to the degradation of analysis accuracy in nonlinear data assimilation. A hybrid EnKF that combines the LETKF and the stochastic EnKF is proposed to mitigate non-Gaussianity in nonlinear data assimilation with small additional computational cost. The performance of the hybrid EnKF is investigated through data assimilation experiments using a 40-variable Lorenz-96 model. Results indicate that the hybrid EnKF significantly improves analysis accuracy in high-frequency data assimilation with a nonlinear observation operator. The positive impact of the hybrid EnKF increases with the increase of the ensemble size.
Journal of the Meteorological Society of Japan. Ser. II, 2019
A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmo... more A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmospheric models in cases with insufficient observations of fast variables. This method is based on the conservation and invertibility of potential vorticity (PV). The dynamical state variables in the free atmosphere of forecast ensemble members are decomposed into balanced and unbalanced parts by applying PV inversion to the PV anomalies computed from spatially smoothed state variables. The mass variables of the two parts are adjusted to remove additional sampling errors introduced by the decomposition. The forecast error covariances between those parts are ignored in the Kalman gain to suppress spurious error correlations. This approximation makes it possible to apply different covariance localizations to each part. The Kalman gain thus obtained is used to assimilate observations. The performance of the proposed method is demonstrated with a shallow water model through twin experiments in a perfect model scenario. The results using the same localization radius for the two parts reveal that the proposed EnKF is superior in the accuracy of the analysis to a conventional EnKF unless the ensemble size is sufficiently large. It is found that the adjustment of mass variables is necessary to outperform the conventional EnKF. The benefits of the PV inversion using the Bolin-Charney balance over the quasi-geostrophic inversion are marginal in the experiments.
Journal of the Meteorological Society of Japan. Ser. II, 1991
In order to assess the practical feasibility of a dynamical one-month forecast, we performed seve... more In order to assess the practical feasibility of a dynamical one-month forecast, we performed several sets of ensemble forecasts using the lagged average forecast method. The results obtained by verifying the eight wintertime cases are summarized as follows: (1) The eight-case average anomaly correlation coefficient of the ensemble forecast for the 1-30 day mean 500 hPa geopotential height in the Northern Hemisphere is 0.54, and its average root mean square error is 55 m. The skill of the ensemble forecast is better than that of both the ordinary dynamical forecast starting from the latest intitial state and the climate forecast. So it seems that the one-month forecast using the lagged average method is effective for practical use. (2) For the 10-day mean 500 hPa geopotential field, the merit of ensemble averaging is apparent after the second 10-day mean (11-20). But in the third 10-day mean (21-30), the average root mean square error is slightly larger than that of the climate forecast. So its skill is marginal for practical use.
Journal of the Meteorological Society of Japan. Ser. II, 1989
A statistical study is made of the relationship between the Northern Hemisphere atmospheric circu... more A statistical study is made of the relationship between the Northern Hemisphere atmospheric circulation and tropical convective activity during summer on intraseasonal time scales. An emphasis is placed on differences in the tropical-midlatitude interaction over East Asia between two 50-day periods: May 26-July 14 and July 15-September 2. Each period corresponds to the East Asian rainy season or the East Asian midsummer season, respectively. Barotropic instability of climatological monthly mean 300mb stream functions is also investigated to interpret the observational results. It is found from correlative analysis that the tropical convection is not strongly related to the midlatitude flow over East Asia during the rainy season, and there are no definite indications that the tropical convection forces the midlatitude flow. On the other hand, during the midsummer season convective activity around the Philippines and the Indo-China Peninsula has a large impact on the East Asian atmospheric circulation. In particular, geopotential height over the Yellow Sea is most strongly affected by the tropical convection. Active convection in the western tropical Pacific is accompanied by a wave train with zonal wavenumber 6 over the North Pacific, which originates from the western tropical Pacific. The location of the wave train does not depend strongly on the location of the convective activity. One of the major barotropic unstable modes for the climatological 300mb flow for August resembles the wave train observed over the North Pacific during the midsummer season. It behaves like a standing wave, and has a large amplitude around the Yellow Sea. The e-folding time of this mode is 11 days when dissipation is ignored. Barotropic unstable modes for June do not have large amplitudes over East Asia. These results are consistent with the above observational results and suggest that barotropic instability plays an important role in the tropical-midlatitude interaction over East Asia during the midsummer season.
Journal of the Meteorological Society of Japan. Ser. II, 1987
An observational study is made on the relationship between the development of the subtropical hig... more An observational study is made on the relationship between the development of the subtropical high around Japan and the convective activity in the northwestern tropical Pacific, and their association with wave propagations over the North Pacific during August 1984. It was found that several occasions of intensified convection around the north of the Philippines were immediately accompanied with the development of the barotropic high around Japan, and both of them were followed by eastward propagations of intensified geopotential height anomalies, at a speed of 10-12m/s, from the north of the Philippines (negative height anomaly) through over Japan (positive height anomaly) extending to the west coast of North America. These anomalies were associated with troughs and ridges of zonal wavenumber 6-7 over the North Pacific on the montly mean 500mb height field of August 1984. A comparison was made between the .monthly mean 500mb height anomaly field and propagation of wave packet simulated by a linear barotropic model with a forcing around the north of the Philippines. Both of them showed quite similar patterns, suggesting that the development of the barotropic high around Japan was associated with energy propagations of barotropic Rossby wave excited by intensified convections around the north of the Philippines.
Experiments simulating intense vortices associated with tornadoes that occurred on 6 May 2012 on ... more Experiments simulating intense vortices associated with tornadoes that occurred on 6 May 2012 on the Kanto Plain, Japan, were performed with a nested local ensemble transform Kalman filter (LETKF) system. Intense vortices were reproduced by downscale experiments with a 12-member ensemble in which the initial conditions were obtained from the nested LETKF system analyses. The downscale experiments successfully generated intense vortices in three regions similar to the observed vortices, whereas only one tornado was reproduced by a deterministic forecast. The intense vorticity of the strongest tornado, which was observed in the southernmost region, was successfully reproduced by 10 of the 12 ensemble members. An examination of the results of the ensemble downscale experiments showed that the duration of intense vorticities tended to be longer when the vertical shear of the horizontal wind was larger and the lower airflow was more humid. Overall, the study results show that ensemble forecasts have the following merits: (1) probabilistic forecasts of the outbreak of intense vortices associated with tornadoes are possible; (2) the miss rate of outbreaks should decrease; and (3) environmental factors favoring outbreaks can be obtained by comparing the multiple possible scenarios of the ensemble forecasts.
Two sets of forecast-analysis cycle experiments were performed with and without direct assimilati... more Two sets of forecast-analysis cycle experiments were performed with and without direct assimilation of precipitation amounts using JMA mesoscale four-dimensional variational data assimilation system (Meso4D-Var). With a devised cost function of precipitation observation, which is derived from the exponential distribution, Meso 4D-Var successfully assimilated precipitation data in various weather situations throughout a one-month experiment period. The result of experiments shows that the precipitation assimilation by Meso 4D-Var improves the model forecasts of both weak and moderate precipitation and it ameliorates a spin-up problem of the model precipitation.
In this study, we investigate the impact of Multi-Center Grand Ensemble (MCGE) forecasts, consist... more In this study, we investigate the impact of Multi-Center Grand Ensemble (MCGE) forecasts, consisting of three operational ensemble forecasts by the Japan Meteorological Agency (JMA), the National Centers for Environmental Prediction, and the Canadian Meteorological Center. We verified the skill of MCGE forecasts in comparison with that of JMA ensemble forecast using root mean square error, anomaly correlation, and Brier skill score for 500 hPa geopotential height and 850 hPa temperature in the Northern Hemisphere (20°N 90°N) in September 2005. Our results show that MCGE forecasts are more skillful than single-center ensemble forecast without considering weight among ensemble members and bias corrections. This implies that considering weight or bias corrections may result in further improvement of MCGE forecasts, specifically in probabilistic forecasts.
In this study, we investigate the daily forecast skill of Multi-Center Grand Ensemble (MCGE), con... more In this study, we investigate the daily forecast skill of Multi-Center Grand Ensemble (MCGE), consisting of three operational medium-range ensemble forecast data by the Japan Meteorological Agency (JMA), the National Centers for Environmental Prediction (NCEP), and the Canadian Meteorological Center (CMC). The skill is evaluated by comparison among the daily RMSE of ensemble mean forecasts for 500 hPa geopotential height over the Northern Hemisphere (20°N 90°N) from August 2005 to February 2006. It is found that MCGE with the same ensemble size as that of the JMA ensemble is more skillful than JMA ensemble for about 75% in frequency both in autumn and winter. Reduction of error with MCGE has little dependence on the atmospheric flow. The RMSE of MCGE can be reduced up to about 20% whether the atmospheric field is easily-predictable or not. Even for the case that MCGE is not more skillful than JMA, the RMSE is increased at most 10%. We argue that the major benefit of MCGE is to avoid the poorest forecast.
Atmospheric blocking occurred over the Rocky Mountains at 1200 UTC 15 December 2005. The operatio... more Atmospheric blocking occurred over the Rocky Mountains at 1200 UTC 15 December 2005. The operational medium-range ensemble forecasts of the Canadian Meteorological Center (CMC), the Japan Meteorological Agency (JMA), and the National Centers for Environmental Prediction (NCEP), as initialized at 1200 UTC 10 December 2005, showed remarkable differences regarding this event. All of the NCEP members failed to predict the correct location of the blocking, whereas almost all of the JMA members and most of the CMC members were successful in predicting the correct location. The present study investigated the factors that caused NCEP to incorrectly predict the blocking location, based on an ensemble-based sensitivity analysis and the JMA global spectral model (GSM) multianalysis ensemble forecasts with NCEP, regionally amplified NCEP, and globally amplified NCEP analyses. A sensitive area for the blocking formation was detected over the central North Pacific. In this area, the NCEP control ...
Journal of the Meteorological Society of Japan. Ser. II, 2007
The operational global numerical weather prediction model at the Japan Meteorological Agency (JMA... more The operational global numerical weather prediction model at the Japan Meteorological Agency (JMA) currently adopts a Simple Biosphere (SiB) model. JMA has been developing a new SiB model (New-SiB) as an upgrade to the current SiB model (Op-SiB). New-SiB has improved treatment of soil and snow processes compared with Op-SiB. The results of integration experiments performed over a period of 3 years indicate that New-SiB predicts snow-covered areas more accurately than Op-SiB. Moreover, the monthly mean surface air temperature during the polar night is better simulated using New-SiB. To validate the diurnal cycle of near-surface meteorological elements in New-SiB, short-range forecasts obtained using the two SiB models are verified using CEOP (Coordinated Enhanced Observing Period) in situ observation datasets for the Enhanced Observing Period 3 (EOP-3). New-SiB generally simulates diurnal variations in near-surface temperature more accurately than Op-SiB, especially over snow-covered areas; however, the short-range forecast experiments also reveal a number of shortcomings in both models. The CEOP datasets are highly valuable in evaluating numerical weather-prediction models.
Journal of the Meteorological Society of Japan. Ser. II, 2004
This study conducted data assimilation experiments using the operational mesoscale four-dimension... more This study conducted data assimilation experiments using the operational mesoscale four-dimensional variational data assimilation (4D-Var DA) system of the Japan Meteorological Agency (JMA). Experiments investigated the impacts of GPS-derived water vapor and Doppler radar-derived radial wind (RW) on precipitation prediction for a heavy rain event on 21 July 1999. RW data were obtained from Doppler radars at Narita and Haneda airports. GPS data were obtained from the GPS Earth Observation Network (GEONET) of the Geographical Survey Institute (GSI). Both precipitable water vapor (PWV) and slant water vapor (SWV), which is the amount of water vapor integrated along the slant path between GPS receivers and GPS satellites, were derived from the GPS data. Because SWV contains three-dimensional water vapor distribution information (Seko et al. 2000), we anticipated that assimilating SWV data would more accurately reproduce the moist air inflow at lower layers. Comparisons between observed and model-predicted precipitation regions helped define the impacts of assimilating RW, PWV, and SWV into the model. If the assimilated data included only conventional meteorological data, the model yielded small precipitation regions over a mountainous area far from Tokyo. If the assimilated data included both GPS-derived water vapor data and conventional data, lowlevel inflow in the model was more humid and precipitation occurred along the low-level convergence zone. Because the predicted position of the convergence zone differed from observations, however, the position of the precipitation region was not reproduced correctly. When RW and conventional data were assimilated into the model, low-level northerly flow was reproduced in the northwest of Tokyo. This northerly flow intensified the low-level convergence where precipitation was observed, and the position of the forecasted precipitation was more similar to that of observations. In this model run, however, lowlevel inflow from the south was less humid than observed, and precipitation onset was delayed by 1 hour.
Journal of the Meteorological Society of Japan. Ser. II, 2007
Data assimilation is a methodology for estimating accurately the state of a time-evolving complex... more Data assimilation is a methodology for estimating accurately the state of a time-evolving complex system like the atmosphere from observational data and a numerical model of the system. It has become an indispensable tool for meteorological researches as well as for numerical weather prediction, as represented by extensive use of reanalysis datasets for research purposes. New advances of data assimilation methods emerged from the 1980s. This review paper presents the theoretical background and implementation of two advanced data assimilation methods: four-dimensional variational assimilation (4D-Var) and ensemble Kalman filtering (EnKF), which currently draw much attention in the meteorological community. Recent research results in Japan on those methods are reviewed, especially on mesoscale applications of 4D-Var and tests of the local ensemble transform Kalman filter (LETKF). Comparison of 4D-Var and EnKF is also briefly discussed. An outline of the mesoscale 4D-Var system of the Japan Meteorological Agency, which is the first operational 4D-Var for a mesoscale model, is given in Appendix.
Journal of Atmospheric and Oceanic Technology, 2007
Recently, a humidity estimation technique was developed by using the turbulence echo characterist... more Recently, a humidity estimation technique was developed by using the turbulence echo characteristics detected with a wind-profiling radar. This study is concerned with improvement of the retrieval algorithm for delineating a humidity profile from the refractive index gradient (M) inferred from the echo power. To achieve a more precise estimate of humidity, a one-dimensional variational method is adopted. Because the radar data provide only the absolute value of M, its sign must be determined in the retrieval. A statistical probability for the sign of M [Pr(z)] is introduced to the cost function of the variational method to determine the optimum result with reduced calculation cost. GPS-derived integrated water vapor (IWV) was assimilated together with the radar-derived |M| for constraining the signs of |M| to agree with the radar-derived IWV and the GPS-derived IWV. Humidity profiles were retrieved from the Middle and Upper Atmosphere (MU) radar–Radio Acoustic Sounding System (RASS)...
Journal of the Meteorological Society of Japan, 2007
The Meteorological Research Institute of the Japan Meteorological Agency has developed a cloudres... more The Meteorological Research Institute of the Japan Meteorological Agency has developed a cloudresolving nonhydrostatic 4-dimensional variational assimilation system (NHM-4DVAR), based on the Japan Meteorological Agency Nonhydrostatic Model (JMA-NHM), in order to investigate the mechanism of heavy rainfall events induced by mesoscale convective systems (MCSs). A horizontal resolution of the NHM-4DVAR is set to 2 km to resolve MCSs, and the length of the assimilation window is 1-hour. The control variables of the NHM-4DVAR are horizontal wind, vertical wind, nonhydrostatic pressure, potential temperature, surface pressure and pseudo relative humidity. Perturbations to the dynamical processes, and the advection of water vapor are considered, but these to the other physical processes are not taken into account. The NHM-4DVAR is applied to the heavy rainfall event observed at Nerima, central part of Tokyo metropolitan area, on 21 July 1999. Doppler radar's radial wind data, Global Positioning System's precipitable water vapor data, and surface temperature and wind data are assimilated as high temporal and spatial resolution data. The Nerima heavy rainfall is well reproduced in the assimilation and subse
To investigate the maintenance mechanism of the blocking flow, we performed a numerical experimen... more To investigate the maintenance mechanism of the blocking flow, we performed a numerical experiment using a barotropic spectral model on the sphere. The model is linearized about two types of realistic basic flows. One is a blocking flow near Alaska (blocking flow case) and the other is a zonal flow in the North Pacific (zonal flow case). The model is integrated in time with prescribed high-frequency eddies which are generated in the Far East and propagate eastward along the northern flank of the jet stream. After several days of time integration, time mean vorticity flux divergence is calculated. Then, the resulting vorticity flux divergence field is used as the eddy vorticity forcing to compute the second-order flow induced by eddies. It is found that the induced second-order flow intensifies the blocking for the blocking flow case, and that this is not the case for the zonal flow case. To clarify the reason for the difference between the induced second-order flows, we carried out the singular value decomposition (SVD) of the matrix of the barotropic vorticity equation linearized about the basic flows. For the blocking flow case, spatial distributions of the leading singular modes show blocking patterns which are similar to the blocking in the basic flow. It is found that these modes are effectively excited by the eddy vorticity forcing, and enhance the blocking in the basic flow. On the other hand, for the zonal flow case, leading singular modes do not show blocking patterns. These results indicate that blocking flows tend to have easily excited modes that can reinforce the block, and high-frequency eddies could maintain blocking by exciting these modes. The dependency of results of the experiment on the location of high-frequency eddies is also shown. It indicates the limitation of the model to investigate the high-frequency eddies feedback.
A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmo... more A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmospheric models in cases with insufficient observations of fast variables. This method is based on the conservation and invertibility of potential vorticity (PV). The dynamical state variables in the free atmosphere of forecast ensemble members are decomposed into balanced and unbalanced parts by applying PV inversion to the PV anomalies computed from spatially smoothed state variables. The mass variables of the two parts are adjusted to remove additional sampling errors introduced by this decomposition. The forecast error covariances between those parts are ignored in the Kalman gain to suppress spurious error correlations. This approximation makes it possible to apply different covariance localizations to each part. The Kalman gain thus obtained is used to assimilate observations. The performance of the proposed method is demonstrated with a shallow water model through twin experiments in a perfect model scenario. Results using the same localization radius for the two parts show that the proposed EnKF is superior in the accuracy of the analysis to a conventional EnKF unless the ensemble size is sufficiently large. It is found that the adjustment of mass variables is necessary to outperform the conventional EnKF. The benefits of the PV inversion using the Bolin-Charney balance over the quasi-geostrophic inversion are marginal in the experiments. Keywords ensemble Kalman filter; multi-scale data assimilation; potential vorticity 10 PV behaves like a tracer. However, PV is not a passive tracer but an active tracer. The impermeability theorem for PV (Haynes and McIntyre, 1987, 1990) illustrates that there is a fundamental difference between the behavior of PV and that of chemical tracers. The above discussion suggests that the latter procedure may be preferable, and we take this option. The introduction of spatial smoothing implies that a low-resolution model can be used for the inversion of large-scale PV. The use of a low-resolution model reduces the computational cost of PV inversion and alleviates the difficulty in solving the ill-conditioned three-dimensional elliptic equations. Note that if the large-scale PV is used for deriving the
Kisho shushi. Dai1shu/Kisho shushi. Dai2shu/Journal of the Meteorological Society of Japan, 2024
Research on particle filters has been progressing with the aim of applying them to high-dimension... more Research on particle filters has been progressing with the aim of applying them to high-dimensional systems, but alleviation of problems with ensemble Kalman filters (EnKFs) in nonlinear or non-Gaussian data assimilation is also an important issue. It is known that the deterministic EnKF is less robust than the stochastic EnKF in strongly nonlinear regimes. We prove that if the observation operator is linear the analysis ensemble perturbations of the local ensemble transform Kalman filter (LETKF) are uniform contractions of the forecast ensemble perturbations in observation space in each direction of the eigenvectors of a forecast error covariance matrix. This property approximately holds for a weakly nonlinear observation operator. These results imply that if the forecast ensemble is strongly non-Gaussian the analysis ensemble of the LETKF is also strongly non-Gaussian, and that strong non-Gaussianity therefore tends to persist in high-frequency assimilation cycles, leading to the degradation of analysis accuracy in nonlinear data assimilation. A hybrid EnKF that combines the LETKF and the stochastic EnKF is proposed to mitigate non-Gaussianity in nonlinear data assimilation with small additional computational cost. The performance of the hybrid EnKF is investigated through data assimilation experiments using a 40-variable Lorenz-96 model. Results indicate that the hybrid EnKF significantly improves analysis accuracy in high-frequency data assimilation with a nonlinear observation operator. The positive impact of the hybrid EnKF increases with the increase of the ensemble size.
Journal of the Meteorological Society of Japan. Ser. II, 2019
A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmo... more A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmospheric models in cases with insufficient observations of fast variables. This method is based on the conservation and invertibility of potential vorticity (PV). The dynamical state variables in the free atmosphere of forecast ensemble members are decomposed into balanced and unbalanced parts by applying PV inversion to the PV anomalies computed from spatially smoothed state variables. The mass variables of the two parts are adjusted to remove additional sampling errors introduced by the decomposition. The forecast error covariances between those parts are ignored in the Kalman gain to suppress spurious error correlations. This approximation makes it possible to apply different covariance localizations to each part. The Kalman gain thus obtained is used to assimilate observations. The performance of the proposed method is demonstrated with a shallow water model through twin experiments in a perfect model scenario. The results using the same localization radius for the two parts reveal that the proposed EnKF is superior in the accuracy of the analysis to a conventional EnKF unless the ensemble size is sufficiently large. It is found that the adjustment of mass variables is necessary to outperform the conventional EnKF. The benefits of the PV inversion using the Bolin-Charney balance over the quasi-geostrophic inversion are marginal in the experiments.
Journal of the Meteorological Society of Japan. Ser. II, 1991
In order to assess the practical feasibility of a dynamical one-month forecast, we performed seve... more In order to assess the practical feasibility of a dynamical one-month forecast, we performed several sets of ensemble forecasts using the lagged average forecast method. The results obtained by verifying the eight wintertime cases are summarized as follows: (1) The eight-case average anomaly correlation coefficient of the ensemble forecast for the 1-30 day mean 500 hPa geopotential height in the Northern Hemisphere is 0.54, and its average root mean square error is 55 m. The skill of the ensemble forecast is better than that of both the ordinary dynamical forecast starting from the latest intitial state and the climate forecast. So it seems that the one-month forecast using the lagged average method is effective for practical use. (2) For the 10-day mean 500 hPa geopotential field, the merit of ensemble averaging is apparent after the second 10-day mean (11-20). But in the third 10-day mean (21-30), the average root mean square error is slightly larger than that of the climate forecast. So its skill is marginal for practical use.
Journal of the Meteorological Society of Japan. Ser. II, 1989
A statistical study is made of the relationship between the Northern Hemisphere atmospheric circu... more A statistical study is made of the relationship between the Northern Hemisphere atmospheric circulation and tropical convective activity during summer on intraseasonal time scales. An emphasis is placed on differences in the tropical-midlatitude interaction over East Asia between two 50-day periods: May 26-July 14 and July 15-September 2. Each period corresponds to the East Asian rainy season or the East Asian midsummer season, respectively. Barotropic instability of climatological monthly mean 300mb stream functions is also investigated to interpret the observational results. It is found from correlative analysis that the tropical convection is not strongly related to the midlatitude flow over East Asia during the rainy season, and there are no definite indications that the tropical convection forces the midlatitude flow. On the other hand, during the midsummer season convective activity around the Philippines and the Indo-China Peninsula has a large impact on the East Asian atmospheric circulation. In particular, geopotential height over the Yellow Sea is most strongly affected by the tropical convection. Active convection in the western tropical Pacific is accompanied by a wave train with zonal wavenumber 6 over the North Pacific, which originates from the western tropical Pacific. The location of the wave train does not depend strongly on the location of the convective activity. One of the major barotropic unstable modes for the climatological 300mb flow for August resembles the wave train observed over the North Pacific during the midsummer season. It behaves like a standing wave, and has a large amplitude around the Yellow Sea. The e-folding time of this mode is 11 days when dissipation is ignored. Barotropic unstable modes for June do not have large amplitudes over East Asia. These results are consistent with the above observational results and suggest that barotropic instability plays an important role in the tropical-midlatitude interaction over East Asia during the midsummer season.
Journal of the Meteorological Society of Japan. Ser. II, 1987
An observational study is made on the relationship between the development of the subtropical hig... more An observational study is made on the relationship between the development of the subtropical high around Japan and the convective activity in the northwestern tropical Pacific, and their association with wave propagations over the North Pacific during August 1984. It was found that several occasions of intensified convection around the north of the Philippines were immediately accompanied with the development of the barotropic high around Japan, and both of them were followed by eastward propagations of intensified geopotential height anomalies, at a speed of 10-12m/s, from the north of the Philippines (negative height anomaly) through over Japan (positive height anomaly) extending to the west coast of North America. These anomalies were associated with troughs and ridges of zonal wavenumber 6-7 over the North Pacific on the montly mean 500mb height field of August 1984. A comparison was made between the .monthly mean 500mb height anomaly field and propagation of wave packet simulated by a linear barotropic model with a forcing around the north of the Philippines. Both of them showed quite similar patterns, suggesting that the development of the barotropic high around Japan was associated with energy propagations of barotropic Rossby wave excited by intensified convections around the north of the Philippines.
Experiments simulating intense vortices associated with tornadoes that occurred on 6 May 2012 on ... more Experiments simulating intense vortices associated with tornadoes that occurred on 6 May 2012 on the Kanto Plain, Japan, were performed with a nested local ensemble transform Kalman filter (LETKF) system. Intense vortices were reproduced by downscale experiments with a 12-member ensemble in which the initial conditions were obtained from the nested LETKF system analyses. The downscale experiments successfully generated intense vortices in three regions similar to the observed vortices, whereas only one tornado was reproduced by a deterministic forecast. The intense vorticity of the strongest tornado, which was observed in the southernmost region, was successfully reproduced by 10 of the 12 ensemble members. An examination of the results of the ensemble downscale experiments showed that the duration of intense vorticities tended to be longer when the vertical shear of the horizontal wind was larger and the lower airflow was more humid. Overall, the study results show that ensemble forecasts have the following merits: (1) probabilistic forecasts of the outbreak of intense vortices associated with tornadoes are possible; (2) the miss rate of outbreaks should decrease; and (3) environmental factors favoring outbreaks can be obtained by comparing the multiple possible scenarios of the ensemble forecasts.
Two sets of forecast-analysis cycle experiments were performed with and without direct assimilati... more Two sets of forecast-analysis cycle experiments were performed with and without direct assimilation of precipitation amounts using JMA mesoscale four-dimensional variational data assimilation system (Meso4D-Var). With a devised cost function of precipitation observation, which is derived from the exponential distribution, Meso 4D-Var successfully assimilated precipitation data in various weather situations throughout a one-month experiment period. The result of experiments shows that the precipitation assimilation by Meso 4D-Var improves the model forecasts of both weak and moderate precipitation and it ameliorates a spin-up problem of the model precipitation.
In this study, we investigate the impact of Multi-Center Grand Ensemble (MCGE) forecasts, consist... more In this study, we investigate the impact of Multi-Center Grand Ensemble (MCGE) forecasts, consisting of three operational ensemble forecasts by the Japan Meteorological Agency (JMA), the National Centers for Environmental Prediction, and the Canadian Meteorological Center. We verified the skill of MCGE forecasts in comparison with that of JMA ensemble forecast using root mean square error, anomaly correlation, and Brier skill score for 500 hPa geopotential height and 850 hPa temperature in the Northern Hemisphere (20°N 90°N) in September 2005. Our results show that MCGE forecasts are more skillful than single-center ensemble forecast without considering weight among ensemble members and bias corrections. This implies that considering weight or bias corrections may result in further improvement of MCGE forecasts, specifically in probabilistic forecasts.
In this study, we investigate the daily forecast skill of Multi-Center Grand Ensemble (MCGE), con... more In this study, we investigate the daily forecast skill of Multi-Center Grand Ensemble (MCGE), consisting of three operational medium-range ensemble forecast data by the Japan Meteorological Agency (JMA), the National Centers for Environmental Prediction (NCEP), and the Canadian Meteorological Center (CMC). The skill is evaluated by comparison among the daily RMSE of ensemble mean forecasts for 500 hPa geopotential height over the Northern Hemisphere (20°N 90°N) from August 2005 to February 2006. It is found that MCGE with the same ensemble size as that of the JMA ensemble is more skillful than JMA ensemble for about 75% in frequency both in autumn and winter. Reduction of error with MCGE has little dependence on the atmospheric flow. The RMSE of MCGE can be reduced up to about 20% whether the atmospheric field is easily-predictable or not. Even for the case that MCGE is not more skillful than JMA, the RMSE is increased at most 10%. We argue that the major benefit of MCGE is to avoid the poorest forecast.
Atmospheric blocking occurred over the Rocky Mountains at 1200 UTC 15 December 2005. The operatio... more Atmospheric blocking occurred over the Rocky Mountains at 1200 UTC 15 December 2005. The operational medium-range ensemble forecasts of the Canadian Meteorological Center (CMC), the Japan Meteorological Agency (JMA), and the National Centers for Environmental Prediction (NCEP), as initialized at 1200 UTC 10 December 2005, showed remarkable differences regarding this event. All of the NCEP members failed to predict the correct location of the blocking, whereas almost all of the JMA members and most of the CMC members were successful in predicting the correct location. The present study investigated the factors that caused NCEP to incorrectly predict the blocking location, based on an ensemble-based sensitivity analysis and the JMA global spectral model (GSM) multianalysis ensemble forecasts with NCEP, regionally amplified NCEP, and globally amplified NCEP analyses. A sensitive area for the blocking formation was detected over the central North Pacific. In this area, the NCEP control ...
Journal of the Meteorological Society of Japan. Ser. II, 2007
The operational global numerical weather prediction model at the Japan Meteorological Agency (JMA... more The operational global numerical weather prediction model at the Japan Meteorological Agency (JMA) currently adopts a Simple Biosphere (SiB) model. JMA has been developing a new SiB model (New-SiB) as an upgrade to the current SiB model (Op-SiB). New-SiB has improved treatment of soil and snow processes compared with Op-SiB. The results of integration experiments performed over a period of 3 years indicate that New-SiB predicts snow-covered areas more accurately than Op-SiB. Moreover, the monthly mean surface air temperature during the polar night is better simulated using New-SiB. To validate the diurnal cycle of near-surface meteorological elements in New-SiB, short-range forecasts obtained using the two SiB models are verified using CEOP (Coordinated Enhanced Observing Period) in situ observation datasets for the Enhanced Observing Period 3 (EOP-3). New-SiB generally simulates diurnal variations in near-surface temperature more accurately than Op-SiB, especially over snow-covered areas; however, the short-range forecast experiments also reveal a number of shortcomings in both models. The CEOP datasets are highly valuable in evaluating numerical weather-prediction models.
Journal of the Meteorological Society of Japan. Ser. II, 2004
This study conducted data assimilation experiments using the operational mesoscale four-dimension... more This study conducted data assimilation experiments using the operational mesoscale four-dimensional variational data assimilation (4D-Var DA) system of the Japan Meteorological Agency (JMA). Experiments investigated the impacts of GPS-derived water vapor and Doppler radar-derived radial wind (RW) on precipitation prediction for a heavy rain event on 21 July 1999. RW data were obtained from Doppler radars at Narita and Haneda airports. GPS data were obtained from the GPS Earth Observation Network (GEONET) of the Geographical Survey Institute (GSI). Both precipitable water vapor (PWV) and slant water vapor (SWV), which is the amount of water vapor integrated along the slant path between GPS receivers and GPS satellites, were derived from the GPS data. Because SWV contains three-dimensional water vapor distribution information (Seko et al. 2000), we anticipated that assimilating SWV data would more accurately reproduce the moist air inflow at lower layers. Comparisons between observed and model-predicted precipitation regions helped define the impacts of assimilating RW, PWV, and SWV into the model. If the assimilated data included only conventional meteorological data, the model yielded small precipitation regions over a mountainous area far from Tokyo. If the assimilated data included both GPS-derived water vapor data and conventional data, lowlevel inflow in the model was more humid and precipitation occurred along the low-level convergence zone. Because the predicted position of the convergence zone differed from observations, however, the position of the precipitation region was not reproduced correctly. When RW and conventional data were assimilated into the model, low-level northerly flow was reproduced in the northwest of Tokyo. This northerly flow intensified the low-level convergence where precipitation was observed, and the position of the forecasted precipitation was more similar to that of observations. In this model run, however, lowlevel inflow from the south was less humid than observed, and precipitation onset was delayed by 1 hour.
Journal of the Meteorological Society of Japan. Ser. II, 2007
Data assimilation is a methodology for estimating accurately the state of a time-evolving complex... more Data assimilation is a methodology for estimating accurately the state of a time-evolving complex system like the atmosphere from observational data and a numerical model of the system. It has become an indispensable tool for meteorological researches as well as for numerical weather prediction, as represented by extensive use of reanalysis datasets for research purposes. New advances of data assimilation methods emerged from the 1980s. This review paper presents the theoretical background and implementation of two advanced data assimilation methods: four-dimensional variational assimilation (4D-Var) and ensemble Kalman filtering (EnKF), which currently draw much attention in the meteorological community. Recent research results in Japan on those methods are reviewed, especially on mesoscale applications of 4D-Var and tests of the local ensemble transform Kalman filter (LETKF). Comparison of 4D-Var and EnKF is also briefly discussed. An outline of the mesoscale 4D-Var system of the Japan Meteorological Agency, which is the first operational 4D-Var for a mesoscale model, is given in Appendix.
Journal of Atmospheric and Oceanic Technology, 2007
Recently, a humidity estimation technique was developed by using the turbulence echo characterist... more Recently, a humidity estimation technique was developed by using the turbulence echo characteristics detected with a wind-profiling radar. This study is concerned with improvement of the retrieval algorithm for delineating a humidity profile from the refractive index gradient (M) inferred from the echo power. To achieve a more precise estimate of humidity, a one-dimensional variational method is adopted. Because the radar data provide only the absolute value of M, its sign must be determined in the retrieval. A statistical probability for the sign of M [Pr(z)] is introduced to the cost function of the variational method to determine the optimum result with reduced calculation cost. GPS-derived integrated water vapor (IWV) was assimilated together with the radar-derived |M| for constraining the signs of |M| to agree with the radar-derived IWV and the GPS-derived IWV. Humidity profiles were retrieved from the Middle and Upper Atmosphere (MU) radar–Radio Acoustic Sounding System (RASS)...
Journal of the Meteorological Society of Japan, 2007
The Meteorological Research Institute of the Japan Meteorological Agency has developed a cloudres... more The Meteorological Research Institute of the Japan Meteorological Agency has developed a cloudresolving nonhydrostatic 4-dimensional variational assimilation system (NHM-4DVAR), based on the Japan Meteorological Agency Nonhydrostatic Model (JMA-NHM), in order to investigate the mechanism of heavy rainfall events induced by mesoscale convective systems (MCSs). A horizontal resolution of the NHM-4DVAR is set to 2 km to resolve MCSs, and the length of the assimilation window is 1-hour. The control variables of the NHM-4DVAR are horizontal wind, vertical wind, nonhydrostatic pressure, potential temperature, surface pressure and pseudo relative humidity. Perturbations to the dynamical processes, and the advection of water vapor are considered, but these to the other physical processes are not taken into account. The NHM-4DVAR is applied to the heavy rainfall event observed at Nerima, central part of Tokyo metropolitan area, on 21 July 1999. Doppler radar's radial wind data, Global Positioning System's precipitable water vapor data, and surface temperature and wind data are assimilated as high temporal and spatial resolution data. The Nerima heavy rainfall is well reproduced in the assimilation and subse
To investigate the maintenance mechanism of the blocking flow, we performed a numerical experimen... more To investigate the maintenance mechanism of the blocking flow, we performed a numerical experiment using a barotropic spectral model on the sphere. The model is linearized about two types of realistic basic flows. One is a blocking flow near Alaska (blocking flow case) and the other is a zonal flow in the North Pacific (zonal flow case). The model is integrated in time with prescribed high-frequency eddies which are generated in the Far East and propagate eastward along the northern flank of the jet stream. After several days of time integration, time mean vorticity flux divergence is calculated. Then, the resulting vorticity flux divergence field is used as the eddy vorticity forcing to compute the second-order flow induced by eddies. It is found that the induced second-order flow intensifies the blocking for the blocking flow case, and that this is not the case for the zonal flow case. To clarify the reason for the difference between the induced second-order flows, we carried out the singular value decomposition (SVD) of the matrix of the barotropic vorticity equation linearized about the basic flows. For the blocking flow case, spatial distributions of the leading singular modes show blocking patterns which are similar to the blocking in the basic flow. It is found that these modes are effectively excited by the eddy vorticity forcing, and enhance the blocking in the basic flow. On the other hand, for the zonal flow case, leading singular modes do not show blocking patterns. These results indicate that blocking flows tend to have easily excited modes that can reinforce the block, and high-frequency eddies could maintain blocking by exciting these modes. The dependency of results of the experiment on the location of high-frequency eddies is also shown. It indicates the limitation of the model to investigate the high-frequency eddies feedback.
A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmo... more A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmospheric models in cases with insufficient observations of fast variables. This method is based on the conservation and invertibility of potential vorticity (PV). The dynamical state variables in the free atmosphere of forecast ensemble members are decomposed into balanced and unbalanced parts by applying PV inversion to the PV anomalies computed from spatially smoothed state variables. The mass variables of the two parts are adjusted to remove additional sampling errors introduced by this decomposition. The forecast error covariances between those parts are ignored in the Kalman gain to suppress spurious error correlations. This approximation makes it possible to apply different covariance localizations to each part. The Kalman gain thus obtained is used to assimilate observations. The performance of the proposed method is demonstrated with a shallow water model through twin experiments in a perfect model scenario. Results using the same localization radius for the two parts show that the proposed EnKF is superior in the accuracy of the analysis to a conventional EnKF unless the ensemble size is sufficiently large. It is found that the adjustment of mass variables is necessary to outperform the conventional EnKF. The benefits of the PV inversion using the Bolin-Charney balance over the quasi-geostrophic inversion are marginal in the experiments. Keywords ensemble Kalman filter; multi-scale data assimilation; potential vorticity 10 PV behaves like a tracer. However, PV is not a passive tracer but an active tracer. The impermeability theorem for PV (Haynes and McIntyre, 1987, 1990) illustrates that there is a fundamental difference between the behavior of PV and that of chemical tracers. The above discussion suggests that the latter procedure may be preferable, and we take this option. The introduction of spatial smoothing implies that a low-resolution model can be used for the inversion of large-scale PV. The use of a low-resolution model reduces the computational cost of PV inversion and alleviates the difficulty in solving the ill-conditioned three-dimensional elliptic equations. Note that if the large-scale PV is used for deriving the
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Papers by 義 露木