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1. Introduction Algorithms that can extract properties of storm cells 1 and track those properties over time provide information that is important to forecasters in assessing storm intensity, growth, and decay ( Wilson et al. 1998 ). However, associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Because storm-tracking algorithms are a key component of nowcasting systems, the problem of how to track storms has received
1. Introduction Algorithms that can extract properties of storm cells 1 and track those properties over time provide information that is important to forecasters in assessing storm intensity, growth, and decay ( Wilson et al. 1998 ). However, associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Because storm-tracking algorithms are a key component of nowcasting systems, the problem of how to track storms has received
National Hurricane Center (NHC) puts out a summary of the tracks of tropical depressions and named tropical storms every year, the track and intensity of each precursor system is not included. The current study grew out of efforts to describe the location and intensity of WPDs in the east Pacific as a function of time. While numerous automatic tracking methods of meteorological systems exist in the literature, most have been developed with extratropical applications in mind. In many cases, these
National Hurricane Center (NHC) puts out a summary of the tracks of tropical depressions and named tropical storms every year, the track and intensity of each precursor system is not included. The current study grew out of efforts to describe the location and intensity of WPDs in the east Pacific as a function of time. While numerous automatic tracking methods of meteorological systems exist in the literature, most have been developed with extratropical applications in mind. In many cases, these
1. Introduction The Northern Hemisphere (NH) wintertime storm tracks have been the subject of many studies using gridded observational analyses. Sawyer (1970) considered them in terms of daily pressure changes, and Blackmon et al. (1977) introduced the use of the variance of the synoptic time-scale bandpass-filtered fields. A number of studies (e.g., Murray and Simmonds 1991 ; Sinclair 1997 ; Hoskins and Hodges 2002 ) have returned to the earlier notion of the ensemble of tracks of
1. Introduction The Northern Hemisphere (NH) wintertime storm tracks have been the subject of many studies using gridded observational analyses. Sawyer (1970) considered them in terms of daily pressure changes, and Blackmon et al. (1977) introduced the use of the variance of the synoptic time-scale bandpass-filtered fields. A number of studies (e.g., Murray and Simmonds 1991 ; Sinclair 1997 ; Hoskins and Hodges 2002 ) have returned to the earlier notion of the ensemble of tracks of
1. Introduction The winter Northern Hemisphere (NH) storm tracks have been the subject of many previous studies (e.g., Blackmon 1976 ; Chang et al. 2002 ; Hoskins and Valdes 1990 ; Hoskins and Hodges 2002 ), In his seminal study, Nakamura (1992) presented pictures of the annual cycle of the North Pacific and North Atlantic storm tracks based on the high-pass-filtered variance of the geopotential at 250 hPa and the sea level pressure. His focus was on the winter half of the year, and he
1. Introduction The winter Northern Hemisphere (NH) storm tracks have been the subject of many previous studies (e.g., Blackmon 1976 ; Chang et al. 2002 ; Hoskins and Valdes 1990 ; Hoskins and Hodges 2002 ), In his seminal study, Nakamura (1992) presented pictures of the annual cycle of the North Pacific and North Atlantic storm tracks based on the high-pass-filtered variance of the geopotential at 250 hPa and the sea level pressure. His focus was on the winter half of the year, and he
1. Introduction The baroclinic eddies that dominate atmospheric variability and shape the climate in the extratropics are concentrated in storm tracks—regions of maximum transient streamfunction variance or eddy kinetic energy (EKE) ( Blackmon 1976 ; Blackmon et al. 1977 ; Lau 1978 ). In the Northern Hemisphere (NH), there are two primary storm tracks, over the Atlantic and over the Pacific ( Fig. 1b ). It is well established that the formation of storm tracks and the locally enhanced EKE are
1. Introduction The baroclinic eddies that dominate atmospheric variability and shape the climate in the extratropics are concentrated in storm tracks—regions of maximum transient streamfunction variance or eddy kinetic energy (EKE) ( Blackmon 1976 ; Blackmon et al. 1977 ; Lau 1978 ). In the Northern Hemisphere (NH), there are two primary storm tracks, over the Atlantic and over the Pacific ( Fig. 1b ). It is well established that the formation of storm tracks and the locally enhanced EKE are
1. Introduction The cyclones and anticyclones that carry out the bulk of the heat, moisture, and momentum transport in Earth’s extratropical atmosphere are concentrated in storm tracks: regions of enhanced eddy kinetic energy (EKE) in the midlatitudes ( Blackmon 1976 ; Blackmon et al. 1977 ). Storm tracks are found in the Northern Hemisphere primarily over the Atlantic and Pacific Oceans; in the Southern Hemisphere, they are more zonally uniform. In both hemispheres, the storm tracks
1. Introduction The cyclones and anticyclones that carry out the bulk of the heat, moisture, and momentum transport in Earth’s extratropical atmosphere are concentrated in storm tracks: regions of enhanced eddy kinetic energy (EKE) in the midlatitudes ( Blackmon 1976 ; Blackmon et al. 1977 ). Storm tracks are found in the Northern Hemisphere primarily over the Atlantic and Pacific Oceans; in the Southern Hemisphere, they are more zonally uniform. In both hemispheres, the storm tracks
1. Introduction Extratropical cyclones form preferentially in the storm tracks (e.g., Blackmon et al. 1977 ; Hoskins and Valdes 1990 ; Chang et al. 2002 ). These lie at midlatitudes and are intensified over the oceans. In the Northern Hemisphere (NH), where the oceans occupy only a fraction of the surface area, there are two distinct tracks: over the North Atlantic and the North Pacific. In the Southern Hemisphere (SH), where the oceans cover a greater area, a single storm track is found
1. Introduction Extratropical cyclones form preferentially in the storm tracks (e.g., Blackmon et al. 1977 ; Hoskins and Valdes 1990 ; Chang et al. 2002 ). These lie at midlatitudes and are intensified over the oceans. In the Northern Hemisphere (NH), where the oceans occupy only a fraction of the surface area, there are two distinct tracks: over the North Atlantic and the North Pacific. In the Southern Hemisphere (SH), where the oceans cover a greater area, a single storm track is found
1. Introduction Atmospheric storm tracks are very important for climate dynamics. They indicate regions of maximum transient poleward energy transport and zonal momentum transport ( Chang et al. 2002 ) and play an important role in setting the dynamical response of the midlatitudes to global warming through their radiative forcing ( Voigt and Shaw 2015 ). Storm tracks are generally calculated as the standard deviation of atmospheric data that has been filtered in the time domain to isolate
1. Introduction Atmospheric storm tracks are very important for climate dynamics. They indicate regions of maximum transient poleward energy transport and zonal momentum transport ( Chang et al. 2002 ) and play an important role in setting the dynamical response of the midlatitudes to global warming through their radiative forcing ( Voigt and Shaw 2015 ). Storm tracks are generally calculated as the standard deviation of atmospheric data that has been filtered in the time domain to isolate
patterns of SLP variability can be combined to adequately represent the dominant patterns of geopotential height variability at levels extending through the depth of the troposphere. The dominant patterns of midlatitude storm-track variability on time scales of a month or longer have also been documented in a number of previous studies. Lau (1988) identified dominant patterns of Northern Hemisphere winter (November to March) storm-track variability based on principal component analysis of monthly
patterns of SLP variability can be combined to adequately represent the dominant patterns of geopotential height variability at levels extending through the depth of the troposphere. The dominant patterns of midlatitude storm-track variability on time scales of a month or longer have also been documented in a number of previous studies. Lau (1988) identified dominant patterns of Northern Hemisphere winter (November to March) storm-track variability based on principal component analysis of monthly
due to the positive phase of PNA patterns ( Liu et al. 2013 ; Notaro et al. 2006 ). In the East Asia sector, positive PNA events induce positive anomalies in surface air temperature by altering wind patterns. Precipitation over northern Russia drops, while over China, it rises, during the positive polarity of PNA teleconnections ( Justino et al. 2022 ). Besides large-scale circulation anomalies ( Wallace and Gutzler 1981 ; Barnston and Livezey 1987 ), storm tracks representing synoptic
due to the positive phase of PNA patterns ( Liu et al. 2013 ; Notaro et al. 2006 ). In the East Asia sector, positive PNA events induce positive anomalies in surface air temperature by altering wind patterns. Precipitation over northern Russia drops, while over China, it rises, during the positive polarity of PNA teleconnections ( Justino et al. 2022 ). Besides large-scale circulation anomalies ( Wallace and Gutzler 1981 ; Barnston and Livezey 1987 ), storm tracks representing synoptic
