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.g., Labitzke 1987 ; van Loon and Labitzke 1987 ), zonally asymmetric ozone changes (e.g., Peters et al. 2015 ), El Niño–Southern Oscillation (ENSO) (e.g., Butler and Polvani 2011 ), and the Madden–Julian oscillation (MJO) (e.g., Garfinkel et al. 2012 ; Liu et al. 2014 ). All these processes change the forcing of planetary waves in the troposphere or change the wave propagation into and in the stratosphere (mainly wavenumbers 1–3; Charney and Drazin 1961 ; Dickinson 1969 ). The strong mean
.g., Labitzke 1987 ; van Loon and Labitzke 1987 ), zonally asymmetric ozone changes (e.g., Peters et al. 2015 ), El Niño–Southern Oscillation (ENSO) (e.g., Butler and Polvani 2011 ), and the Madden–Julian oscillation (MJO) (e.g., Garfinkel et al. 2012 ; Liu et al. 2014 ). All these processes change the forcing of planetary waves in the troposphere or change the wave propagation into and in the stratosphere (mainly wavenumbers 1–3; Charney and Drazin 1961 ; Dickinson 1969 ). The strong mean
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
idealized setup ( Keane and Plant 2012 ). Groenemeijer and Craig (2012) implemented it in a limited-area model to show that the scheme adds a significant amount of variability to an ensemble. They found as well that this effect depends on the strength of the synoptic forcing. Keane et al. (2014) showed in global aquaplanet simulations that the variability introduced by the scheme adapts correctly to changes in model resolution. In this study, we investigate if the additional variability introduced
idealized setup ( Keane and Plant 2012 ). Groenemeijer and Craig (2012) implemented it in a limited-area model to show that the scheme adds a significant amount of variability to an ensemble. They found as well that this effect depends on the strength of the synoptic forcing. Keane et al. (2014) showed in global aquaplanet simulations that the variability introduced by the scheme adapts correctly to changes in model resolution. In this study, we investigate if the additional variability introduced
” constitutes a clear example for a two-phase development. The precursor rapidly crossed the North Atlantic as a DRW before it intensified to one of the most harmful storms in central Europe in the last few decades. Wernli et al. (2002) identified an intensive straight zonal jet during the DRW propagation phase of Lothar far to the north of the low-level vortex and excluded a significant upper-level forcing of the surface low due to the absence of waves on the intense jet. They demonstrated that later in
” constitutes a clear example for a two-phase development. The precursor rapidly crossed the North Atlantic as a DRW before it intensified to one of the most harmful storms in central Europe in the last few decades. Wernli et al. (2002) identified an intensive straight zonal jet during the DRW propagation phase of Lothar far to the north of the low-level vortex and excluded a significant upper-level forcing of the surface low due to the absence of waves on the intense jet. They demonstrated that later in
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
section 4 , we investigate the synoptic conditions for WNP recurving TCs with and without a downstream Rossby wave development in a composite view using PV advection diagnostics, eddy kinetic energy analysis, and quasigeostrophic forcing diagnostics. A climatological investigation of forecast uncertainty downstream of recurving TCs in section 5 is followed by a summary and discussion of the results in section 6 . 2. Dataset and methodology a. Tropical cyclone dataset In this study, we focus on
section 4 , we investigate the synoptic conditions for WNP recurving TCs with and without a downstream Rossby wave development in a composite view using PV advection diagnostics, eddy kinetic energy analysis, and quasigeostrophic forcing diagnostics. A climatological investigation of forecast uncertainty downstream of recurving TCs in section 5 is followed by a summary and discussion of the results in section 6 . 2. Dataset and methodology a. Tropical cyclone dataset In this study, we focus on
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
structures. For the first time, airborne observations were collected simultaneously by three research aircraft [Naval Research Laboratory-P3 (NRL-P3), U.S. Air Force-WC130 (USAF-WC130), and DLR-Falcon] during ET and provided unique and detailed insight into a TC approaching a midlatitude baroclinic zone. On 20 September the NRL-P3 and the USAF-WC130 measured the structure and the environment of a deep convective system that developed as Sinlaku was close to the primary midlatitude baroclinic zone. The
structures. For the first time, airborne observations were collected simultaneously by three research aircraft [Naval Research Laboratory-P3 (NRL-P3), U.S. Air Force-WC130 (USAF-WC130), and DLR-Falcon] during ET and provided unique and detailed insight into a TC approaching a midlatitude baroclinic zone. On 20 September the NRL-P3 and the USAF-WC130 measured the structure and the environment of a deep convective system that developed as Sinlaku was close to the primary midlatitude baroclinic zone. The
(TCS08) field campaign, the Naval Research Laboratory (NRL) P-3 and the U.S. Air Force (USAF) WC-130 conducted flights into the inner core region of Typhoon Sinlaku, with the P-3 carrying the Electra Doppler Radar (ELDORA). A unique dataset including a complete view of Sinlaku’s eyewall convection by radar and the release of several dropsondes in the inner core region enables an unprecedented, detailed view of the eyewall structure of a TC during the transformation stage. As will be shown later
(TCS08) field campaign, the Naval Research Laboratory (NRL) P-3 and the U.S. Air Force (USAF) WC-130 conducted flights into the inner core region of Typhoon Sinlaku, with the P-3 carrying the Electra Doppler Radar (ELDORA). A unique dataset including a complete view of Sinlaku’s eyewall convection by radar and the release of several dropsondes in the inner core region enables an unprecedented, detailed view of the eyewall structure of a TC during the transformation stage. As will be shown later
from 8 GP west to 8 GP east and from 6 GP south to 5 GP north of the SLP minimum). This relative humidity value must exceed 90% to indicate saturation and condensational latent heating. Very weak upper-level forcing: The averaged upper-level-induced QG ascent at 700 hPa in the area of the cyclone (large gray box in Fig. 1 ) must be smaller than 0.5 × 10 −2 m s −1 and the averaged PV at 250 hPa in the same box must be less than 1 PVU to exclude significant upper-level induced, synoptic
from 8 GP west to 8 GP east and from 6 GP south to 5 GP north of the SLP minimum). This relative humidity value must exceed 90% to indicate saturation and condensational latent heating. Very weak upper-level forcing: The averaged upper-level-induced QG ascent at 700 hPa in the area of the cyclone (large gray box in Fig. 1 ) must be smaller than 0.5 × 10 −2 m s −1 and the averaged PV at 250 hPa in the same box must be less than 1 PVU to exclude significant upper-level induced, synoptic
