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radar observations, and the applied quality measures. The ensembles with conventional and stochastic convection parameterization are evaluated in two case studies representing strong and weak large-scale forcing in section 3 in terms of general properties and deterministic and probabilistic forecast quality measures. The results are discussed in section 4 and final conclusions are drawn. 2. Data and methods In this study, ensembles of precipitation forecasts calculated with the COSMO model using
radar observations, and the applied quality measures. The ensembles with conventional and stochastic convection parameterization are evaluated in two case studies representing strong and weak large-scale forcing in section 3 in terms of general properties and deterministic and probabilistic forecast quality measures. The results are discussed in section 4 and final conclusions are drawn. 2. Data and methods In this study, ensembles of precipitation forecasts calculated with the COSMO model using
forecasts by different models is presented in section 3 , followed by a discussion of the influence of T-PARC observations on ECMWF forecasts in midlatitudes over the Pacific and on the Northern Hemisphere in section 4 . The discussion and conclusions are presented in section 5 . 2. Model descriptions a. JMA GSM experiment description To evaluate the impact of the T-PARC 2008 special observations, experiments using the operational global 4D-Var system and the operational JMA global spectral model
forecasts by different models is presented in section 3 , followed by a discussion of the influence of T-PARC observations on ECMWF forecasts in midlatitudes over the Pacific and on the Northern Hemisphere in section 4 . The discussion and conclusions are presented in section 5 . 2. Model descriptions a. JMA GSM experiment description To evaluate the impact of the T-PARC 2008 special observations, experiments using the operational global 4D-Var system and the operational JMA global spectral model
. 2c ) is poor, and other values for s 0 do not solve the problem either [see Zimin et al. (2003) ]. The better performance of the Hilbert transform technique in the above situation seems to suggest that this technique is superior, and possibly this is the reason for its recent popularity. Yet, the example in (5) is somewhat contrived. In real atmospheric flows there is generally a broad spectrum of zonal wavenumbers, and the reconstruction of the envelope is often not very sensitive to the
. 2c ) is poor, and other values for s 0 do not solve the problem either [see Zimin et al. (2003) ]. The better performance of the Hilbert transform technique in the above situation seems to suggest that this technique is superior, and possibly this is the reason for its recent popularity. Yet, the example in (5) is somewhat contrived. In real atmospheric flows there is generally a broad spectrum of zonal wavenumbers, and the reconstruction of the envelope is often not very sensitive to the
forecast performance of the deterministic ECMWF model for this particular event. In the next section the data and tools used in this study will be introduced. Section 3 contains a synoptic description of the cyclone life cycle and an analysis of the structure of the system for each development phase. With the aid of a quasigeostrophic vertical motion diagnostic the influence of the upper-level forcing on the low-level system will be investigated. The forecast performance of this event will be
forecast performance of the deterministic ECMWF model for this particular event. In the next section the data and tools used in this study will be introduced. Section 3 contains a synoptic description of the cyclone life cycle and an analysis of the structure of the system for each development phase. With the aid of a quasigeostrophic vertical motion diagnostic the influence of the upper-level forcing on the low-level system will be investigated. The forecast performance of this event will be
subsets does not show the best performance and the 12–120-h mean track forecast error reduction of allObs is 28%, while 16% can be achieved with the ReObs run and 51% with the ViObs run. Despite the improvement of the track until the recurvature of the storm, the model seems to have problems with the propagation of Sinlaku after recurvature. From 84 h onward, a timing error of all track forecasts is observed ( Fig. 7c ). Even if the track forecast error is reduced with extra observations, the error
subsets does not show the best performance and the 12–120-h mean track forecast error reduction of allObs is 28%, while 16% can be achieved with the ReObs run and 51% with the ViObs run. Despite the improvement of the track until the recurvature of the storm, the model seems to have problems with the propagation of Sinlaku after recurvature. From 84 h onward, a timing error of all track forecasts is observed ( Fig. 7c ). Even if the track forecast error is reduced with extra observations, the error
1. Introduction The large-scale midlatitude flow is dominated by the upper-level jet stream that serves as a waveguide for Rossby waves (e.g., Martius et al. 2010 ). Because their general evolution follows dry dynamics that can be represented at grid scale in numerical weather prediction (NWP) models, Rossby waves may be expected to feature a high degree of predictability ( Grazzini and Vitart 2015 ). However, major forecast uncertainty and error in the midlatitudes in current NWP
1. Introduction The large-scale midlatitude flow is dominated by the upper-level jet stream that serves as a waveguide for Rossby waves (e.g., Martius et al. 2010 ). Because their general evolution follows dry dynamics that can be represented at grid scale in numerical weather prediction (NWP) models, Rossby waves may be expected to feature a high degree of predictability ( Grazzini and Vitart 2015 ). However, major forecast uncertainty and error in the midlatitudes in current NWP
1. Introduction Meteorological research on diabatic Rossby waves (DRWs) has been intensifying in recent years after a DRW was detected for the first time in numerical weather prediction (NWP) model output for a high-impact weather event. According to a mesoscale model hindcast simulation, a DRW served as an important precursor to the “Lothar” storm after Christmas 1999, which was one of the most harmful winter storms over Europe in the last few decades ( Wernli et al. 2002 ). The explosive
1. Introduction Meteorological research on diabatic Rossby waves (DRWs) has been intensifying in recent years after a DRW was detected for the first time in numerical weather prediction (NWP) model output for a high-impact weather event. According to a mesoscale model hindcast simulation, a DRW served as an important precursor to the “Lothar” storm after Christmas 1999, which was one of the most harmful winter storms over Europe in the last few decades ( Wernli et al. 2002 ). The explosive
train. As this wave train is apparent throughout the troposphere ( Orsolini and Nikulin 2006 ), the large-scale flow seems to play an important role in European heat waves. Model simulations indicate that the anomalous circulation during the summer of 2010 over eastern Europe can be ascribed primarily to natural internal atmospheric variability rather than to climate change or ocean boundary conditions like sea surface temperature or sea ice extent ( Dole et al. 2011 ), reflecting changes in the
train. As this wave train is apparent throughout the troposphere ( Orsolini and Nikulin 2006 ), the large-scale flow seems to play an important role in European heat waves. Model simulations indicate that the anomalous circulation during the summer of 2010 over eastern Europe can be ascribed primarily to natural internal atmospheric variability rather than to climate change or ocean boundary conditions like sea surface temperature or sea ice extent ( Dole et al. 2011 ), reflecting changes in the
. Meteor. Soc. , 128 , 93 – 117 , doi: 10.1256/00359000260498806 . Evans , J. L. , and R. E. Hart , 2003 : Objective indicators of the life cycle evolution of extratropical transition for Atlantic tropical cyclones . Mon. Wea. Rev. , 131 , 909 – 925 , doi: 10.1175/1520-0493(2003)131<0909:OIOTLC>2.0.CO;2 . Evans , J. L. , J. M. Arnott , and F. Chiaromonte , 2006 : Evaluation of operational model cyclone structure forecasts during extratropical transition . Mon. Wea. Rev. , 134
. Meteor. Soc. , 128 , 93 – 117 , doi: 10.1256/00359000260498806 . Evans , J. L. , and R. E. Hart , 2003 : Objective indicators of the life cycle evolution of extratropical transition for Atlantic tropical cyclones . Mon. Wea. Rev. , 131 , 909 – 925 , doi: 10.1175/1520-0493(2003)131<0909:OIOTLC>2.0.CO;2 . Evans , J. L. , J. M. Arnott , and F. Chiaromonte , 2006 : Evaluation of operational model cyclone structure forecasts during extratropical transition . Mon. Wea. Rev. , 134
( Tripathi et al. 2015 ). Matsuno (1971) developed a dynamical model of the stratospheric sudden warming phenomena in which tropospheric forced planetary wave packets propagate upward into the stratosphere. The deposition of their easterly angular momentum [Eliassen–Palm flux (EP flux) convergence] leads to a weakening and breakdown of the polar night jet. Several processes influence the occurrence of MSSW events in the Northern Hemisphere: the quasi-biennial oscillation (QBO) and the solar cycle (e
( Tripathi et al. 2015 ). Matsuno (1971) developed a dynamical model of the stratospheric sudden warming phenomena in which tropospheric forced planetary wave packets propagate upward into the stratosphere. The deposition of their easterly angular momentum [Eliassen–Palm flux (EP flux) convergence] leads to a weakening and breakdown of the polar night jet. Several processes influence the occurrence of MSSW events in the Northern Hemisphere: the quasi-biennial oscillation (QBO) and the solar cycle (e
