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on one specific aspect of cyclogenesis downstream of ET, namely the relative importance of the jet streak as compared to that of the upper-level trough. Forecasters often discuss jet streaks and troughs as distinct features. In an idealized baroclinic wave, jet streak formation can be viewed as an intrinsic part of the wave’s amplification ( Rotunno et al. 1994 ; Wandishin et al. 2000 ). During ET, however, there is additional “external” forcing of the jet streak, largely due to the outflow of
on one specific aspect of cyclogenesis downstream of ET, namely the relative importance of the jet streak as compared to that of the upper-level trough. Forecasters often discuss jet streaks and troughs as distinct features. In an idealized baroclinic wave, jet streak formation can be viewed as an intrinsic part of the wave’s amplification ( Rotunno et al. 1994 ; Wandishin et al. 2000 ). During ET, however, there is additional “external” forcing of the jet streak, largely due to the outflow of
observed between 1958 and 2002 in conjunction with a positive North Atlantic Oscillation index during the last decades of the twentieth century ( Isotta et al. 2008 ). Although jet streams in the subtropics appear as a prominent climatological feature (e.g., Koch et al. 2006 ), their location, size, and amplitude are characterized by variability on synoptic time scales. The jet variability on the climatological time scale results from subtle forcing effects of slow-varying boundary conditions (e
observed between 1958 and 2002 in conjunction with a positive North Atlantic Oscillation index during the last decades of the twentieth century ( Isotta et al. 2008 ). Although jet streams in the subtropics appear as a prominent climatological feature (e.g., Koch et al. 2006 ), their location, size, and amplitude are characterized by variability on synoptic time scales. The jet variability on the climatological time scale results from subtle forcing effects of slow-varying boundary conditions (e
2006 ). Multiple integrations of NWP models (ensembles) can be used to provide probabilistic information but can be set up in different ways, depending on the represented sources of uncertainty. Recent studies have shown that in different weather regimes, different sources of uncertainty dominate: in cases of strong large-scale forcing, initial and boundary conditions uncertainty contributes more to the overall uncertainty, whereas in weak large-scale forcing, model error is more important
2006 ). Multiple integrations of NWP models (ensembles) can be used to provide probabilistic information but can be set up in different ways, depending on the represented sources of uncertainty. Recent studies have shown that in different weather regimes, different sources of uncertainty dominate: in cases of strong large-scale forcing, initial and boundary conditions uncertainty contributes more to the overall uncertainty, whereas in weak large-scale forcing, model error is more important
these cyclones. However, these explosive cyclones reach their maximum intensity earlier at the surface than at 500 hPa, which highlights the importance of surface fluxes, diabatically produced positive PV anomalies, and reduced static stability for the rapid development. Deveson et al. (2002) classified 16 cyclones from the Fronts and Atlantic Storm Track Experiment (FASTEX) according to the contributions of the forcing from upper and lower levels to the vertical motion ( U / L ratio) and their
these cyclones. However, these explosive cyclones reach their maximum intensity earlier at the surface than at 500 hPa, which highlights the importance of surface fluxes, diabatically produced positive PV anomalies, and reduced static stability for the rapid development. Deveson et al. (2002) classified 16 cyclones from the Fronts and Atlantic Storm Track Experiment (FASTEX) according to the contributions of the forcing from upper and lower levels to the vertical motion ( U / L ratio) and their
