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terms directly in forecast models to represent the unresolved scales of motion. This idea could be used to generate an ensemble suite by forcing forecast runs to diverge during the course of the forecast integration, even if they started from the same initial conditions. Given a solid scientific basis to generate ensembles of forecasts, it now seemed possible to estimate forecast reliability a priori and thus include confidence as an actual forecast parameter ( Bengtsson 1991 ). With sufficient
terms directly in forecast models to represent the unresolved scales of motion. This idea could be used to generate an ensemble suite by forcing forecast runs to diverge during the course of the forecast integration, even if they started from the same initial conditions. Given a solid scientific basis to generate ensembles of forecasts, it now seemed possible to estimate forecast reliability a priori and thus include confidence as an actual forecast parameter ( Bengtsson 1991 ). With sufficient
techniques to create ensembles with regional, limited-area, convection-parameterizing models (typically at a 10–20-km resolution). Zhang et al. (2006) applied an ensemble Kalman filter (EnKF) approach to generate different ICs. Stensrud et al. (2000) showed that the impact of model errors (represented by different physical parameterizations) and uncertainty on ICs depends on the large-scale forcing for upward motion. Grimit and Mass (2002) used multimodel large-scale conditions to initialize and
techniques to create ensembles with regional, limited-area, convection-parameterizing models (typically at a 10–20-km resolution). Zhang et al. (2006) applied an ensemble Kalman filter (EnKF) approach to generate different ICs. Stensrud et al. (2000) showed that the impact of model errors (represented by different physical parameterizations) and uncertainty on ICs depends on the large-scale forcing for upward motion. Grimit and Mass (2002) used multimodel large-scale conditions to initialize and
explained by downstream baroclinic development. Processes such as stationary waves initiated by orographic forcing or zonal variations in diabatic heating (e.g., Hoskins and Valdes 1990 ) may act to decrease eddy activity and complicate the picture of downstream baroclinic development over the continent. In summary, baroclinic energy conversion is hypothesized to dominate upstream, in locations over the western Pacific Ocean off Japan, while the storm track is extended in the central Pacific via
explained by downstream baroclinic development. Processes such as stationary waves initiated by orographic forcing or zonal variations in diabatic heating (e.g., Hoskins and Valdes 1990 ) may act to decrease eddy activity and complicate the picture of downstream baroclinic development over the continent. In summary, baroclinic energy conversion is hypothesized to dominate upstream, in locations over the western Pacific Ocean off Japan, while the storm track is extended in the central Pacific via
and meridional winds generated on the east side of the trough. This signal weakens the environmental forcing that supports the northeastward motion of Sinlaku, resulting in a track that is not as far to the east or north as the control. Despite a small recurring short-term deterioration of the track forecast, the long-term track forecast improves such that the 5-day error decreases to only 205 km. The opposite effect occurs when the monsoon trough S3 is strengthened. Upon weakening S4 (Tropical
and meridional winds generated on the east side of the trough. This signal weakens the environmental forcing that supports the northeastward motion of Sinlaku, resulting in a track that is not as far to the east or north as the control. Despite a small recurring short-term deterioration of the track forecast, the long-term track forecast improves such that the 5-day error decreases to only 205 km. The opposite effect occurs when the monsoon trough S3 is strengthened. Upon weakening S4 (Tropical
observations on medium-range forecasts of atmospheric flow . Quart. J. Roy. Meteor. Soc. , 134 , 2011 – 2027 . Shutts , G. J. , 1983 : The propagation of eddies in diffluent jet streams: Eddy vorticity forcing of “blocking” flow fields . Quart. J. Roy. Meteor. Soc. , 109 , 737 – 762 . Shutts , G. J. , 1986 : A case study of eddy forcing during an Atlantic blocking episode . Advances in Geophysics, Vol. 29, Academic Press, 135–162 . Szunyogh , I. , Z. Toth , A. V. Zimin , S. J
observations on medium-range forecasts of atmospheric flow . Quart. J. Roy. Meteor. Soc. , 134 , 2011 – 2027 . Shutts , G. J. , 1983 : The propagation of eddies in diffluent jet streams: Eddy vorticity forcing of “blocking” flow fields . Quart. J. Roy. Meteor. Soc. , 109 , 737 – 762 . Shutts , G. J. , 1986 : A case study of eddy forcing during an Atlantic blocking episode . Advances in Geophysics, Vol. 29, Academic Press, 135–162 . Szunyogh , I. , Z. Toth , A. V. Zimin , S. J
. Schemm , W. Shi , and A. Leetmaa , 2000 : Extreme precipitation events in the western United States related to tropical forcing. J. Climate , 13 , 793 – 820 . Hong , S-Y. , and H-L. Pan , 1998 : Convective trigger function for a mass-flux cumulus parameterization scheme
. Schemm , W. Shi , and A. Leetmaa , 2000 : Extreme precipitation events in the western United States related to tropical forcing. J. Climate , 13 , 793 – 820 . Hong , S-Y. , and H-L. Pan , 1998 : Convective trigger function for a mass-flux cumulus parameterization scheme
in the vertical, forcing increments to 0 at 1.5 scale heights (computed as the natural log of the ratio of the pressure of the model level divided by the pressure assigned to the observation location). The reference pressure for radiance observations was set to the maximum in the weighting function for each instrument and channel. System error (including model error) was parameterized with a combination of multiplicative and additive inflation. Since our version of the EnKF used the GSI
in the vertical, forcing increments to 0 at 1.5 scale heights (computed as the natural log of the ratio of the pressure of the model level divided by the pressure assigned to the observation location). The reference pressure for radiance observations was set to the maximum in the weighting function for each instrument and channel. System error (including model error) was parameterized with a combination of multiplicative and additive inflation. Since our version of the EnKF used the GSI
