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cyclone-center frequency reflects the average number of cyclone low centers each month. Cyclogenesis (cyclolysis) density and frequency are based on the first (last) low center observed for each cyclone. Cyclone amplitude is the difference between the geopotential height of the low center and the outermost closed contour (at 10-m intervals). Maximum amplitude is the largest amplitude observed during a cyclone’s life cycle. To provide a large-scale perspective, cyclone statistics are presented
cyclone-center frequency reflects the average number of cyclone low centers each month. Cyclogenesis (cyclolysis) density and frequency are based on the first (last) low center observed for each cyclone. Cyclone amplitude is the difference between the geopotential height of the low center and the outermost closed contour (at 10-m intervals). Maximum amplitude is the largest amplitude observed during a cyclone’s life cycle. To provide a large-scale perspective, cyclone statistics are presented
cyclolysis over the SAO region is examined employing the spherical kernel method ( Hodges 1996 ), which depicts the density map by superposing areas of influence of the cyclogenesis (cyclolysis) point for every cyclone. Further information on this technique can be found in Bombardi et al. (2014) , who used this method to construct a density map of total cyclogenesis over the South Atlantic. Most of the cyclogeneses occur in near-coastal SAO regions, as also pointed out by Evans and Braun (2012) ; here
cyclolysis over the SAO region is examined employing the spherical kernel method ( Hodges 1996 ), which depicts the density map by superposing areas of influence of the cyclogenesis (cyclolysis) point for every cyclone. Further information on this technique can be found in Bombardi et al. (2014) , who used this method to construct a density map of total cyclogenesis over the South Atlantic. Most of the cyclogeneses occur in near-coastal SAO regions, as also pointed out by Evans and Braun (2012) ; here
1. Introduction A characteristics feature of the mid- and upper-tropospheric flow is the continuous presence of synoptic-scale waves. These waves have an important role in both the heat and momentum budget, and can induce surface cyclogenesis. Following the Petterssen and Smebye (1971) study, the extratropical cyclones can be classified into types A or B, depending on the configuration of the upper- and lower-level circulation. In type A, the surface cyclone initially develops
1. Introduction A characteristics feature of the mid- and upper-tropospheric flow is the continuous presence of synoptic-scale waves. These waves have an important role in both the heat and momentum budget, and can induce surface cyclogenesis. Following the Petterssen and Smebye (1971) study, the extratropical cyclones can be classified into types A or B, depending on the configuration of the upper- and lower-level circulation. In type A, the surface cyclone initially develops
linked to the number of cyclogenesis events, but a range of other synoptic to large-scale influences should be considered, including variability in cyclolysis and the interaction between the troposphere and stratosphere. Future work may also address differences in the cyclogenesis response to tropical forcing during late fall versus early winter ( King et al. 2018 ), or whether the mechanisms described here are subject to multidecadal variability ( Varino et al. 2018 ). Acknowledgments Sebastian
linked to the number of cyclogenesis events, but a range of other synoptic to large-scale influences should be considered, including variability in cyclolysis and the interaction between the troposphere and stratosphere. Future work may also address differences in the cyclogenesis response to tropical forcing during late fall versus early winter ( King et al. 2018 ), or whether the mechanisms described here are subject to multidecadal variability ( Varino et al. 2018 ). Acknowledgments Sebastian
transition points are defined as the connection points between two adjacent tracks (between the cyclolysis point of cyclone A and the cyclogenesis point of cyclone B). They are hard to be distinguished as weakening points of the previous cyclone or strengthening points of the later cyclone or as track points between two strengthening processes of the same cyclone, which highly depend on the frequency and threshold used in the algorithm. However, this hypothesis cannot fully explain the reduced number
transition points are defined as the connection points between two adjacent tracks (between the cyclolysis point of cyclone A and the cyclogenesis point of cyclone B). They are hard to be distinguished as weakening points of the previous cyclone or strengthening points of the later cyclone or as track points between two strengthening processes of the same cyclone, which highly depend on the frequency and threshold used in the algorithm. However, this hypothesis cannot fully explain the reduced number
1. Introduction The North American Cordillera presents a formidable obstacle to synoptic systems moving eastward through the North Pacific storm-track region, leading to a maximum of cyclolysis upstream of the North American west coast, in particular in the Gulf of Alaska, and a distinct minimum in surface cyclone frequency over the Rocky Mountains (e.g., Wernli and Schwierz 2006 , and references therein). Case studies as well as numerical hindcasts suggest that impinging cyclones can split
1. Introduction The North American Cordillera presents a formidable obstacle to synoptic systems moving eastward through the North Pacific storm-track region, leading to a maximum of cyclolysis upstream of the North American west coast, in particular in the Gulf of Alaska, and a distinct minimum in surface cyclone frequency over the Rocky Mountains (e.g., Wernli and Schwierz 2006 , and references therein). Case studies as well as numerical hindcasts suggest that impinging cyclones can split
-vorticity advection were favorable. The DBVs also tended to form in the transversal trough’s northern section (left column in Fig. 19 ), where there were cyclonic-vorticity maxima and divergence minima (middle column in Fig. 19 ). The low pressure/height and high cyclonic vorticity provided a favorable base state for vortex formation. Similarly, Smith (1984) and Schär (1990) also suggested the importance of a preexisting lower-level shear line in the lee cyclogenesis. All six semi-idealized simulations
-vorticity advection were favorable. The DBVs also tended to form in the transversal trough’s northern section (left column in Fig. 19 ), where there were cyclonic-vorticity maxima and divergence minima (middle column in Fig. 19 ). The low pressure/height and high cyclonic vorticity provided a favorable base state for vortex formation. Similarly, Smith (1984) and Schär (1990) also suggested the importance of a preexisting lower-level shear line in the lee cyclogenesis. All six semi-idealized simulations
the development of low-level cyclogenesis, and there were three distinct positive PV anomalies in an extratropical cyclone: surface, lower-tropospheric, and upper-tropospheric PV anomalies. During the mature phase of the cyclone development, these three positive PV anomalies often became vertically aligned and formed a so-called PV tower, representing a tropospheric spanning column of air with anomalous high-PV values. These three PV anomalies could induce a strong cyclonic circulation extending
the development of low-level cyclogenesis, and there were three distinct positive PV anomalies in an extratropical cyclone: surface, lower-tropospheric, and upper-tropospheric PV anomalies. During the mature phase of the cyclone development, these three positive PV anomalies often became vertically aligned and formed a so-called PV tower, representing a tropospheric spanning column of air with anomalous high-PV values. These three PV anomalies could induce a strong cyclonic circulation extending
from the NCEP reanalysis. Cyclone detection is based on a series of search patterns that test whether a gridpoint SLP value is surrounded by gridpoint values at least 1 hPa higher than the central point tested. Cyclone tracking employs a nearest-neighbor approach that compares system positions for a given 6-h chart with those for the next 6-h chart. Cyclogenesis (cyclolysis) represents the first (last) appearance of a closed 1-hPa isobar. The original algorithm was applied to 12-hourly SLP fields
from the NCEP reanalysis. Cyclone detection is based on a series of search patterns that test whether a gridpoint SLP value is surrounded by gridpoint values at least 1 hPa higher than the central point tested. Cyclone tracking employs a nearest-neighbor approach that compares system positions for a given 6-h chart with those for the next 6-h chart. Cyclogenesis (cyclolysis) represents the first (last) appearance of a closed 1-hPa isobar. The original algorithm was applied to 12-hourly SLP fields
motivated them to assess a range of methods for identifying and tracking midlatitude cyclones. Different tracking methods tend to agree well on the interannual variability and geographical distribution of cyclones, but are less consistent when it comes to the total number of storms, identification of weak storms, cyclogenesis, and cyclolysis. It can be challenging to compare results from studies using different tracking schemes as they may emphasize different aspects of the cyclone life cycle and parts
motivated them to assess a range of methods for identifying and tracking midlatitude cyclones. Different tracking methods tend to agree well on the interannual variability and geographical distribution of cyclones, but are less consistent when it comes to the total number of storms, identification of weak storms, cyclogenesis, and cyclolysis. It can be challenging to compare results from studies using different tracking schemes as they may emphasize different aspects of the cyclone life cycle and parts
