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  • View in gallery

    A two-stage ET classification based on Klein et al. (2000). The onset and completion times correspond to the definitions of Evans and Hart (2003). The “tropical” and “extratropical” labels indicate approximately how the system would be regarded by an operational forecast center. Figure reproduced from Jones et al. (2003, their Fig. 11).

  • View in gallery

    Tracks of TCs that completed the transformation stage of ET for the (a) NATL [1981–2010; ET designations from HURDAT2 best track data, described in Landsea and Franklin (2013)], (b) WNP (1981–2010; ET designations from Japan Meteorological Agency best track data), (c) ENP [1971–2012; reanalysis-derived CPS ET designations by Wood and Ritchie (2014a)], and (d) SWIO [1987–2013; reanalysis-derived ET designations subjectively determined by Griffin and Bosart (2014)]. No attempt is made to account for ET classification practice differences between operational centers or the historical evolution of ET classification practices at these centers.

  • View in gallery

    Conceptual model of the transformation stage of ET in the western North Pacific. Step 1 represents the commencement of the transformation stage, step 2 represents the TC encountering the baroclinic zone, and step 3 represents the TC becoming embedded within the baroclinic zone. Figure reproduced from Klein et al. (2000, their Fig. 5).

  • View in gallery

    Number of TCs (white bars) and number of ET cases (black bars) by month (each per left axis) during 1979–2004 in the WNP, as assessed using Japan Meteorological Agency best track data. The black line indicates the percentage of TCs that undergo ET to the total number of TCs in a given month (per right axis). Figure reproduced from Kitabatake (2011, their Fig. 10a).

  • View in gallery

    Average JRA-55 CPS frequency (e.g., number of times during its life span that a given TC is located at a given location within the CPS, and B only; shaded) per TC during 2001–10 in the (a) ENP (150 TCs) and (b) North Atlantic (here, ATL; 174 TCs). The arrows in each panel indicate the general trajectories that TCs in each basin follow through the CPS. Figure reproduced from Wood and Ritchie (2014a, their Figs. 10a,b).

  • View in gallery

    Summary of TC and ET events in the SWIO west of 90°E by (a) TC season and (b) month for the period 1989–2013. The full height of the bar represents TC events, while the bottom (blue) portion of the bar represents the number of ET events. In (a), the year on the chart refers to the year the TC season ended. In (b), events that occur in two months are included in the month in which the TC dissipated or underwent ET. Figure reproduced from Griffin and Bosart (2014, their Fig. 1).

  • View in gallery

    Azimuthally averaged 10-m wind speed (m s−1) as a function of radius at 0400 UTC 29 Aug (open circles; before ET), 1000 UTC 30 Aug (closed circles; during ET), and 1000 UTC 31 Aug (open squares; after ET) 1998, as obtained from the 12-km fifth-generation Pennsylvania State University–NCAR Mesoscale Model (Dudhia 1993), simulation of NATL TC Bonnie (1998). Figure reproduced from Evans and Hart (2008, their Fig. 5).

  • View in gallery

    Composite surface wind vectors (arrows, reference vector in the top right of each panel) and surface wind speed (isotachs, m s−1) for (a) the subset of TCs (n = 13) with wind maxima both left and right of track that made landfall in Japan from 1979 to 2004 and (b) all TCs (n = 70) that made landfall in Japan from 1979 to 2004. The y axis is taken in the direction of the storm motion. The cross in the center of each panel indicates the storm center. Figure reproduced from Fujibe and Kitabatake (2007, their Figs. 3d,f).

  • View in gallery

    Vertical cross sections of radar reflectivity (dBZ; shaded), tangential wind (m s−1; gray contours), and in-plane wind vectors composed of radial and vertical velocity (m s−1) for each shear-relative quadrant as synthesized by the Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation (SAMURAI; Bell et al. 2012) software tool for the T-PARC research mission into Typhoon Sinlaku on 19 Sep 2008. Cross sections are taken from the corner of the domain to the center, 45° from the x and y axes in each quadrant: (a) upshear left, (b) downshear left, (c) upshear right, and (d) downshear right. Figure reproduced from Foerster et al. (2014, their Fig. 12).

  • View in gallery

    Maximum reflectivity between 0 and 15 km (dBZ; shaded), temperature (K; contours) at 1.5 km, and horizontal wind (m s−1; vectors with reference vector at lower right) at 1.5 km as synthesized by SAMURAI for the T-PARC research mission into Typhoon Sinlaku on 20 Sep 2008. The gray line denotes the flight track of the NRL-P3 and the red line denotes the flight track of the USAF-WC130. Filled circles give positions of dropsondes included in the SAMURAI analysis. Stars indicate positions of dropsondes in Fig. 7 in Quinting et al. (2014), while black arrows along the coordinate axes indicate positions of cross sections in Fig. 6 in Quinting et al. (2014). Figure reproduced from Quinting et al. (2014, their Fig. 4).

  • View in gallery

    Advanced Hurricane Weather Research and Forecasting (AHW; Davis et al. 2010) model-forecast 850-hPa potential temperature (K; shaded), vector wind (half barb = 2.5 m s−1; full barb = 5.0 m s−1; pennant = 25.0 m s−1), and wind speed (solid contours at 40, 45, 50, and 55 m s−1) of Sandy (2012) verifying at (a) 1000 and (b) 2000 UTC 29 Oct 2012. The AHW forecast was initialized at 0000 UTC 28 Oct 2012. Figure reproduced from Galarneau et al. (2013, their Figs. 7b,c).

  • View in gallery

    12-h forward trajectories starting at 925 hPa on a northwest–southeast-directed line crossing Japan at (a) 0000 UTC 19 Sep 2008 and (b) 0000 UTC 20 Sep 2008. The colors of the trajectories represent pressure (hPa). Equivalent potential temperature (K) at 925 hPa at trajectory starting time is given in gray shades. The location of Sinlaku’s simulated mean sea level pressure minimum is marked by a blue cross (at trajectory start) and circle (at trajectory end). Figure reproduced from Lentink (2017, their Figs. 5.3 and 5.20b).

  • View in gallery

    The average absolute and along- and cross-track errors of the NCEP Global Ensemble Forecast System in the NATL and WNP basins for the period 2006–08. Error bars illustrate 95% confidence intervals on the mean as determined using bootstrapping. Both TC and ET tracks are included in the analysis. Along-track error is positive when a forecast lies ahead of its verifying position and cross-track error is positive when a cyclone is forecast to the right of its verifying position. Figure reproduced from Buckingham et al. (2010, their Fig. 4). (b) As in (a), but only TC tracks are included in the analysis (ET tracks excluded). Figure reproduced from Buckingham et al. (2010, their Fig. 5).

  • View in gallery

    Percentage of correctly classified cyclone phase forecasts by the linear discriminant analysis scheme of Aberson (2014) for dependent (short dashed; period of record 1980–2010) and independent (medium dashed; period of record 2011) samples. The long-dashed line indicates the percentage of correctly classified official NHC cyclone phase forecasts (period of record 2011). Note that the two 2011 samples are homogeneous. Figure reproduced from Aberson (2014, their Fig. 3).

  • View in gallery

    Selected regional prediction system forecasts for NATL Hurricane Juan initialized at 0000 UTC 28 Sep 2003. Sea level pressure (solid lines; 4-hPa intervals) and winds (barbs; m s−1) are shown for the (left) initial state and (right) 24-h forecasts valid at 0000 UTC 29 Sep 2003. Model fields are indicated for the (a),(b) NCEP ETA Model; (c),(d) regional version of the Environment Canada Global Environmental Multiscale model (GEM-R); (e),(f) GFDL Hurricane Model (GHM); and (g),(h) Mesoscale Compressible Community (MC2) model. Minimum MSLP contours are 984 hPa in (e) and (f). Please see McTaggart-Cowan et al. (2006a) for relevant model details. Figure reproduced from McTaggart-Cowan et al. (2006a, their Fig. 6).

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The Extratropical Transition of Tropical Cyclones. Part I: Cyclone Evolution and Direct Impacts

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  • 1 University of Wisconsin–Milwaukee, Milwaukee, Wisconsin
  • 2 Mississippi State University, Mississippi State, Mississippi
  • 3 NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, Miami, Florida
  • 4 NOAA/Climate Program Office, Silver Spring, Maryland
  • 5 Embry-Riddle Aeronautical University, Daytona Beach, Florida
  • 6 University at Albany, State University of New York, Albany, New York
  • 7 National Center for Atmospheric Research, Boulder, Colorado
  • 8 University of São Paulo, São Paulo, Brazil
  • 9 Naval Research Laboratory, Monterey, California
  • 10 Canadian Hurricane Center, Dartmouth, Nova Scotia, Canada
  • 11 The University of Arizona, Tucson, Arizona
  • 12 Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
  • 13 RiskPulse, Madison, Wisconsin
  • 14 McGill University, Montreal, Quebec, Canada
  • 15 Florida State University, Tallahassee, Florida
  • 16 Meteorological College, Kashiwa, Chiba, Japan
  • 17 Karlsruhe Institute of Technology, Karlsruhe, Germany
  • 18 Environment and Climate Change Canada, Dorval, Quebec, Canada
  • 19 Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada
  • 20 School of Earth, Atmosphere and Environment, and ARC Centre of Excellence for Climate System Science, Monash University, Clayton, Victoria, Australia
  • 21 Johannes Gutenberg-Universität Mainz, Mainz, Germany
  • 22 University of New South Wales, Canberra, Australia
  • 23 The Pennsylvania State University, University Park, Pennsylvania
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Abstract

Extratropical transition (ET) is the process by which a tropical cyclone, upon encountering a baroclinic environment and reduced sea surface temperature at higher latitudes, transforms into an extratropical cyclone. This process is influenced by, and influences, phenomena from the tropics to the midlatitudes and from the meso- to the planetary scales to extents that vary between individual events. Motivated in part by recent high-impact and/or extensively observed events such as North Atlantic Hurricane Sandy in 2012 and western North Pacific Typhoon Sinlaku in 2008, this review details advances in understanding and predicting ET since the publication of an earlier review in 2003. Methods for diagnosing ET in reanalysis, observational, and model-forecast datasets are discussed. New climatologies for the eastern North Pacific and southwest Indian Oceans are presented alongside updates to western North Pacific and North Atlantic Ocean climatologies. Advances in understanding and, in some cases, modeling the direct impacts of ET-related wind, waves, and precipitation are noted. Improved understanding of structural evolution throughout the transformation stage of ET fostered in large part by novel aircraft observations collected in several recent ET events is highlighted. Predictive skill for operational and numerical model ET-related forecasts is discussed along with environmental factors influencing posttransition cyclone structure and evolution. Operational ET forecast and analysis practices and challenges are detailed. In particular, some challenges of effective hazard communication for the evolving threats posed by a tropical cyclone during and after transition are introduced. This review concludes with recommendations for future work to further improve understanding, forecasts, and hazard communication.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Clark Evans, evans36@uwm.edu

This article has a companion article which can be found at http://journals.ametsoc.org/doi/10.1175/MWR-D-17-0329.1

Abstract

Extratropical transition (ET) is the process by which a tropical cyclone, upon encountering a baroclinic environment and reduced sea surface temperature at higher latitudes, transforms into an extratropical cyclone. This process is influenced by, and influences, phenomena from the tropics to the midlatitudes and from the meso- to the planetary scales to extents that vary between individual events. Motivated in part by recent high-impact and/or extensively observed events such as North Atlantic Hurricane Sandy in 2012 and western North Pacific Typhoon Sinlaku in 2008, this review details advances in understanding and predicting ET since the publication of an earlier review in 2003. Methods for diagnosing ET in reanalysis, observational, and model-forecast datasets are discussed. New climatologies for the eastern North Pacific and southwest Indian Oceans are presented alongside updates to western North Pacific and North Atlantic Ocean climatologies. Advances in understanding and, in some cases, modeling the direct impacts of ET-related wind, waves, and precipitation are noted. Improved understanding of structural evolution throughout the transformation stage of ET fostered in large part by novel aircraft observations collected in several recent ET events is highlighted. Predictive skill for operational and numerical model ET-related forecasts is discussed along with environmental factors influencing posttransition cyclone structure and evolution. Operational ET forecast and analysis practices and challenges are detailed. In particular, some challenges of effective hazard communication for the evolving threats posed by a tropical cyclone during and after transition are introduced. This review concludes with recommendations for future work to further improve understanding, forecasts, and hazard communication.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Clark Evans, evans36@uwm.edu

This article has a companion article which can be found at http://journals.ametsoc.org/doi/10.1175/MWR-D-17-0329.1

1. Introduction

In October 2012, Hurricane Sandy drove a devastating storm surge in excess of 2 m into the northeastern U.S. coastline, tore down trees and power lines that left millions without electricity, and dumped over 900 mm of snow (Blake et al. 2013). As Sandy approached the coast, it acquired structural characteristics consistent with both tropical and extratropical cyclones, with an intact inner–tropical cyclone (TC) warm core embedded within an expansive outer-core wind field (Blake et al. 2013). Contributions from both tropical and baroclinic energy sources caused Sandy to reintensify as it approached the coastline (Galarneau et al. 2013; Shin and Zhang 2017). The TC followed an atypical track northwestward toward the Northeast United States, rather than out to sea, fostered by interaction with an upstream trough (Barnes et al. 2013; Qian et al. 2016) of the type identified by Fujiwhara (1931), the practical predictability of which depended on the modeling system (Bassill 2014; Magnusson et al. 2014; Torn et al. 2015). Sandy tested existing infrastructure for hazard communication (NOAA 2013; Blake et al. 2013) and posed challenges related to risk perception (Meyer et al. 2014) due to its atypical track and forecast structure (Munsell and Zhang 2014) near landfall. Few TCs produce such a broad range of impacts, but Sandy was not ordinary. Rather, Sandy is a dramatic example of the direct impacts, structural evolution, and forecast challenges associated with TCs that become extratropical cyclones, a process known as extratropical transition (ET; Jones et al. 2003).

Tropical cyclones gain energy from warm ocean waters through evaporation and subsequent latent heat release by deep, moist convection. The storm develops a warm core as a result, with the strongest winds near the surface that decrease in strength with height. The wind, precipitation, and temperature fields become more axisymmetric as the TC matures. Conversely, extratropical cyclones are driven by comparatively large temperature and moisture gradients. Within these baroclinic environments, frontal boundaries separate warm, moist air from cool, dry air, resulting in highly asymmetric energy distributions to drive wind and rainfall. In addition, wind speed increases with height due to the cold-core structure of these systems. During ET, the deep warm core associated with the TC becomes shallow and is often replaced by a cold-core, asymmetric structure (e.g., Evans and Hart 2003; Hart et al. 2006), including the development of surface fronts (Klein et al. 2000). This evolution occurs as the TC moves poleward into a baroclinic environment characterized by the aforementioned temperature and moisture gradients as well as increased vertical wind shear, reduced sea surface temperature (SST), and an increasing Coriolis parameter (Fig. 1). Only a subset of TCs complete ET and become fully extratropical, yet even a cyclone that only begins ET can directly produce hazards (such as Hurricane Sandy) and/or generate hazards downstream [e.g., Hurricane Katia in 2011 as described by Grams and Blumer (2015); Typhoon Nabi in 2005 as described by Harr et al. (2008)].

Fig. 1.
Fig. 1.

A two-stage ET classification based on Klein et al. (2000). The onset and completion times correspond to the definitions of Evans and Hart (2003). The “tropical” and “extratropical” labels indicate approximately how the system would be regarded by an operational forecast center. Figure reproduced from Jones et al. (2003, their Fig. 11).

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

An earlier review (Jones et al. 2003) provided a then-current synthesis of the fundamental understanding of ET and its direct impacts. The paper also outlined significant ET-related forecast challenges and research needs that had yet to be addressed. Focusing on ET itself and the direct impacts of transitioning cyclones, the present review documents the extensive research that addresses how those needs have been met in the most recent decade and a half. This review also identifies questions that remain unanswered as well as potential avenues for future research that have been motivated by recent investigations. Section 2 discusses efforts toward a universal definition of, and classifiers for, ET. Section 3 documents the development of, and additions to, new and existing ET climatologies and looks to how ET climatology may change in the future. Section 4 describes the updated understanding of direct impacts associated with wind, waves, and precipitation. Jones et al. (2003) stressed the necessity of improving use of existing observations and exploiting new capabilities for understanding ET itself, as well as forecasting the phenomenon, and section 5 summarizes progress in and ongoing needs for both. Section 6 documents advances in the forecasting and analysis of ET. Finally, this review concludes with recommendations for future research. As noted above, this review focuses on ET and its direct impacts. A companion article (Keller et al. 2018, manuscript submitted to Mon. Wea. Rev., hereafter Part II) covers research progress related to ET’s downstream impacts, including downstream cyclogenesis, cyclone evolution after becoming extratropical, effects on the midlatitude flow and predictability, and phenomena such as predecessor rain events.

2. Classifiers

Jones et al. (2003) discussed the need to develop improved conceptual models of, and diagnostic tools for, ET, with a particular focus toward the development of a universal ET definition that can be applied broadly (including operationally). Since their review, the cyclone phase space (CPS; Hart 2003) has become widely accepted in the research and operational communities as a means of diagnosing ET in reanalysis, observational, and model-forecast datasets (e.g., Evans and Hart 2003). The first CPS parameter assesses the thermal symmetry of the TC. Symmetry is defined as the difference in 900–600-hPa geopotential thickness between the right and left sides of the TC relative to its direction of motion, a value known as B. A mature, axisymmetric TC exhibits B values of less than 10 m, whereas a cyclone with mature or developing frontal structures is characterized by B values exceeding 10 m. The 10-m threshold approximately corresponds to an across-cyclone layer-mean temperature gradient of 0.85°C. The second CPS parameter estimates the thermal wind between 900 and 600 hPa , computed from the change in the horizontal geopotential height gradient with height. Tropical cyclones are warm-core systems characterized by a positive geopotential thickness anomaly near the center, resulting in a positive value of . Extratropical cyclones are generally cold-core systems characterized by a negative geopotential thickness anomaly near the center, producing a negative value of . A third CPS parameter estimates thermal wind in the same manner but between 600 and 300 hPa. Similar metrics for determining ET were obtained by Satake et al. (2013) in the context of a broader TC tracking algorithm.

Within the CPS framework, ET begins when B exceeds the empirically derived value of 10 m and ends when becomes negative (indicating a cold-core thermal structure; Evans and Hart 2003). Both B and are computed from averages taken within 500 km of the cyclone’s center. The CPS parameters are often derived from numerical weather prediction (NWP) model analyses and forecasts, but CPS applications have been expanded to reanalysis datasets (e.g., Wood and Ritchie 2014a; Hodges et al. 2017; Zarzycki et al. 2017) and, in testing, polar-orbiting satellite retrievals as well. Despite its widespread use, the CPS is not without its limitations: it does not resolve a cyclone’s inner-core structure, and it relies on either NWP products, reanalysis datasets, or satellite retrievals.

Because of these CPS limitations, several studies have evaluated other metrics for ET diagnosis, primarily in retrospective analyses, but with an eye toward potential forecast applications. For example, the temperature contrast between the cyclone’s inner core and external environment was used by Garde et al. (2010) to classify both tropical transition and extratropical transition events. A more focused evaluation was conducted by Kofron et al. (2010a), who examined 82 recurving TCs in the North Atlantic (NATL) and western North Pacific (WNP) from 2003 to 2006. Tropical cyclones were classified based upon whether they reintensified (e.g., decreased minimum sea level pressure) after, dissipated (e.g., increased minimum sea level pressure) after, or recurved without becoming extratropical. Tropical cyclones that reintensified were further distinguished based upon their post-ET thermal structure (cold core vs warm seclusion) and their translation into the “northwest” or “northeast” synoptic-scale midlatitude flow regimes of Harr and Elsberry (2000). Metrics such as scalar frontogenesis (Harr and Elsberry 2000), the CPS (Hart 2003), and an open wave at 500 hPa (Demirci et al. 2007) were unable to reliably distinguish between recurving TCs that did and did not become extratropical, independent of their posttransition evolution. Similar findings for the scalar frontogenesis and open wave metrics were obtained by Wang et al. (2012).

Jones et al. (2003) advocated for an evaluation of the utility of potential vorticity (PV) toward diagnosing ET in both numerical models and observations. In conducting such an evaluation, Kofron et al. (2010b) demonstrated that TCs that begin the transformation stage of ET experience a decrease in midtropospheric PV as the cyclone weakens, whereas the subset of TCs that complete ET experience a subsequent rapid increase in midtropospheric PV as the TC interacts with a midlatitude trough. In their study, PV on the 330-K isentropic surface, which is typically located in the midtroposphere prior to ET and in the upper troposphere after, was a good discriminator of ET versus recurvature without ET and of intensity change after a cyclone becomes extratropical (Kofron et al. 2010b). All 82 TCs in the Kofron et al. (2010b) dataset exhibited a minimum value of 330-K isentropic PV averaged within 500 km of the center as they moved into the midlatitudes, and the time at which this value became less than an empirical threshold value was tested as a metric for ET onset. For a threshold value of 1.6 PVU (1 PVU = 10−6 K kg−1 m2 s−1), the ET completion forecast success rate for reintensifying cases was 94.3% with a 27.6% false alarm rate. The 1.6-PVU metric also reliably determined ET onset for two WNP cases studied by Wang et al. (2012); however, substantial timing variability existed between the four datasets considered, and Li and Wang (2013) found this metric was unable to reliably determine ET completion and extratropical phase intensity change in higher-resolution datasets. Thus, more work is necessary to assess the reliability of the 1.6-PVU threshold using datasets of varying resolution and quality.

3. Climatologies

An important application of ET classifiers is for the development of new and/or extension of existing ET climatologies. At the time of Jones et al.’s (2003) publication, at least partial ET climatologies existed for the NATL (Hart and Evans 2001), WNP (Klein et al. 2000), western South Pacific (Sinclair 2002), and west coast of Australia (Foley and Hanstrum 1994). In general, these reflect basins where strong winds and heavy rains associated with ET events preferentially impact some of the most developed nations in the world and/or where ET is a climatologically frequent occurrence. The advent of new ET classifiers, particularly the CPS, has, in part, led to the development of new ET climatologies for the eastern North Pacific (ENP) and southwest Indian Ocean (SWIO) basins. It has also led to the development of updated and/or expanded ET climatologies for the NATL and WNP. A synthesis of these climatologies is provided in Fig. 2. Sections 3ae discuss the results of these studies in greater depth, concluding with a discussion of projected future changes in the global ET climatology.

Fig. 2.
Fig. 2.

Tracks of TCs that completed the transformation stage of ET for the (a) NATL [1981–2010; ET designations from HURDAT2 best track data, described in Landsea and Franklin (2013)], (b) WNP (1981–2010; ET designations from Japan Meteorological Agency best track data), (c) ENP [1971–2012; reanalysis-derived CPS ET designations by Wood and Ritchie (2014a)], and (d) SWIO [1987–2013; reanalysis-derived ET designations subjectively determined by Griffin and Bosart (2014)]. No attempt is made to account for ET classification practice differences between operational centers or the historical evolution of ET classification practices at these centers.

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

a. Western North Pacific

Klein et al. (2000) examined 30 ET cases over a 4-yr period, a relatively brief span of time, to develop a three-dimensional conceptual model of the transformation stage (Fig. 3). Since then, several studies have assessed WNP ET cases over multiple decades. Approximately 40% (for the period 1979–2004; Kitabatake 2011) of WNP TCs within the Japan Meteorological Agency best track database became extratropical prior to dissipation (Fig. 4); a slightly smaller percentage (36.5%, for the period 1979–2009) recurved while becoming extratropical (Archambault et al. 2013). Of the subset of recurving WNP TCs that underwent ET, 42.5% reintensified after completing ET (Archambault et al. 2013, their Fig. 7). Most (91%) WNP TCs become extratropical with a minimum central sea level pressure greater than 970 hPa (Kitabatake 2011); however, a small percentage (9%) of TCs become extratropical with central pressures less than 970 hPa, particularly from September to November. WNP TCs that become extratropical tend to be stronger and larger at recurvature from September to November than at other times of the year (Archambault et al. 2013). Further study is necessary, however, to understand the causes of this seasonality in both size and intensity after becoming extratropical.

Fig. 3.
Fig. 3.

Conceptual model of the transformation stage of ET in the western North Pacific. Step 1 represents the commencement of the transformation stage, step 2 represents the TC encountering the baroclinic zone, and step 3 represents the TC becoming embedded within the baroclinic zone. Figure reproduced from Klein et al. (2000, their Fig. 5).

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

Fig. 4.
Fig. 4.

Number of TCs (white bars) and number of ET cases (black bars) by month (each per left axis) during 1979–2004 in the WNP, as assessed using Japan Meteorological Agency best track data. The black line indicates the percentage of TCs that undergo ET to the total number of TCs in a given month (per right axis). Figure reproduced from Kitabatake (2011, their Fig. 10a).

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

Extratropical transition is not evenly distributed throughout the WNP typhoon season, with the largest number of events found in September (Klein et al. 2000; Kitabatake 2011; Archambault et al. 2013; Quinting and Jones 2016). Note that this contrasts with Jones et al. (2003), who identified August as the peak month for WNP ET events based on Joint Typhoon Warning Center best track data. Although TC frequency increases from June to August, the ratio of TCs that complete ET [based on the Evans and Hart (2003) definition described in section 2] to all TCs is limited to 25%–35% during these months (e.g., Kitabatake 2011; Archambault et al. 2013), likely due to the lower probability of a TC interacting with the midlatitude flow associated with the climatological poleward retreat of the polar jet in boreal summer. September is also the month in which the greatest percentage of recurving WNP TCs reintensify after becoming extratropical (Klein et al. 2000; Archambault et al. 2013). The ET frequency varies both between and within WNP typhoon seasons: it occurs less frequently when the subtropical high is anomalously strong, such that TCs are preferentially steered toward Asia rather than recurving toward higher latitudes (Song et al. 2013). A seasonal influence on ET track is also observed, wherein TCs undergoing recurvature and ET tend to recurve more sharply and at lower latitudes in May and October–December than from June to September (Archambault et al. 2013).

b. North Atlantic

Whereas the initial ET climatology for the WNP only examined cases during a 4-yr period, the initial ET climatology for the NATL (Hart and Evans 2001) examined cases during a much longer period (1950–96). Consequently, research has focused upon expanding, rather than revising or updating, the NATL ET climatology. Specifically, the CPS has been applied to quantify time to ET completion [based on the Evans and Hart (2003) definition described in section 2], post-ET thermal structure, and post-ET intensity change for NATL ET events (Hart et al. 2006). Slow-transitioning TCs were more intense and larger as ET began than their fast-transitioning counterparts. Post-ET weakening was approximately twice as likely as post-ET intensification, whereas post-ET cold-core thermal structure was more than twice as likely as post-ET warm-seclusion thermal structure. Post-ET warm-seclusion cyclones were larger and were located closer to North America as ET began than their post-ET cold-core counterparts. However, more research is needed to quantify the effects of TC size and intensity on the outcome of ET as well as what factors govern post-ET intensity change.

c. Eastern North Pacific

Because of the warm-season climatology of the subtropical ENP, and in contrast to the WNP and NATL, an ENP ET climatology did not exist at the time that Jones et al. (2003) was published. During the North American monsoon (e.g., Adams and Comrie 1997; Vera et al. 2006), the subtropical ridge expands and strengthens north of the ENP main development region. This strong ridge directly reduces the likelihood of midlatitude troughs interacting with ENP TCs, and thus ET likelihood, for most of the hurricane season (e.g., Allard 1984; Corbosiero et al. 2009; Wood and Ritchie 2013, 2014a). Further, ENP TCs rarely survive poleward of 25°N due to the cold California Current and climatologically low SST west of Baja California (Corbosiero et al. 2009). As the monsoon wanes late in the season, however, strong midlatitude troughs extend far enough south to potentially interact with TCs and cause them to recurve toward the north and east (Farfàn 2004; Corbosiero et al. 2009; Ritchie et al. 2011; Wood and Ritchie 2013), bringing heavy precipitation to the southwestern United States (Corbosiero et al. 2009; Ritchie et al. 2011; Wood and Ritchie 2013).

Initial case studies of ENP ET events (Dickinson et al. 2004; Corbosiero et al. 2009; Wood and Ritchie 2012) motivated the development of an ET climatology for the ENP. Because of the aforementioned negative factors of a strong ridge and poleward decreasing SSTs, only 9% of ENP TCs complete ET according to the CPS (Wood and Ritchie 2014a), a much lower frequency than in the NATL or WNP (Fig. 2). ENP ET cases require a southward-digging midlatitude trough to weaken the subtropical ridge and allow the TC to move poleward. However, when an ENP TC completes ET, it does not follow the traditional CPS path found in the WNP (Kitabatake 2011; Song et al. 2011) and NATL (Evans and Hart 2003; Arnott et al. 2004). Instead of losing thermal symmetry but retaining a warm core prior to completing ET, ENP TCs first lose their warm core and then become asymmetric as they complete ET (Fig. 5; Wood and Ritchie 2014a). Rapidly decreasing SSTs may contribute to this type of structural evolution as the loss of convection outpaces changes in the TC’s thermal asymmetry, a hypothesis that is currently being investigated. Warm-core erosion prior to asymmetry development during ET is not limited to the ENP; Kitabatake (2011) found 16.8% of WNP ET cases followed this alternative CPS path. After an ENP TC completes ET, it typically decays without reintensification (Wood and Ritchie 2014a).

Fig. 5.
Fig. 5.

Average JRA-55 CPS frequency (e.g., number of times during its life span that a given TC is located at a given location within the CPS, and B only; shaded) per TC during 2001–10 in the (a) ENP (150 TCs) and (b) North Atlantic (here, ATL; 174 TCs). The arrows in each panel indicate the general trajectories that TCs in each basin follow through the CPS. Figure reproduced from Wood and Ritchie (2014a, their Figs. 10a,b).

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

Similar to other basins, peak ENP ET activity occurs in September and October, which is offset from peak TC activity in July and August due to more frequent midlatitude troughs and a weaker subtropical ridge later (Wood and Ritchie 2014a). ENP ET frequency increases during developing warm-phase El Niño–Southern Oscillation (ENSO) events, as comparatively high subtropical SST and more midlatitude troughs during warm-phase ENSO events may increase the likelihood of a TC being maintained as it moves northward and of that TC subsequently interacting with a trough (Wood and Ritchie 2014a). The ET frequency, however, appears unaffected by the longer-duration Pacific decadal oscillation (PDO; Mantua et al. 1997), possibly due to the weaker PDO influence on subtropical SST than ENSO and, thus, on TC maintenance as these systems gain latitude (Wood and Ritchie 2014a).

d. Southwest Indian

As in the ENP, an SWIO (west of 90°E and south of the equator) ET climatology did not exist when Jones et al. (2003) was published. The recently developed first SWIO ET climatology indicates that nearly 44% of TCs underwent ET during the 1989–2013 SWIO TC seasons1 (Fig. 2d; Griffin and Bosart 2014), rivaling the frequency of ET in the NATL (Jones et al. 2003) and exceeding that of the WNP (Kitabatake 2011; Archambault et al. 2013) and the southwest Pacific (32%; Sinclair 2002). Whereas few ET events are observed early in the SWIO TC season (e.g., prior to January), an average of just under 50% of TCs undergo ET from January to March during the seasonal peak (Fig. 6; Griffin and Bosart 2014). This agrees with the late-season ET bias in the NATL (Hart and Evans 2001), but is a higher frequency than the late-season ET rates of 25%–30% in the southwest Pacific (Sinclair 2002). Further work is needed, however, to determine if this result has similar causes to the late-season ET distributions found in the WNP and NATL.

Fig. 6.
Fig. 6.

Summary of TC and ET events in the SWIO west of 90°E by (a) TC season and (b) month for the period 1989–2013. The full height of the bar represents TC events, while the bottom (blue) portion of the bar represents the number of ET events. In (a), the year on the chart refers to the year the TC season ended. In (b), events that occur in two months are included in the month in which the TC dissipated or underwent ET. Figure reproduced from Griffin and Bosart (2014, their Fig. 1).

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

e. Future climatology

Whereas the climatologies in previous subsections have been backward looking, several studies have used observations and climate model outputs to determine how ET climatologies are currently changing or are likely to change in the future. Near Australia, increased poleward persistence of recurving TCs may result from increased higher-latitude SST and strengthened poleward-directed steering winds (Walsh and Katzfey 2000). Conversely, WNP ET likelihood may decrease as the magnitude of the meridional temperature gradient decreases (Ito et al. 2016). In the NATL, ET frequency increased over the period 1970–2012 (Mokhov et al. 2014), and several studies (Semmler et al. 2008; Haarsma et al. 2013; Baatsen et al. 2015; Liu et al. 2017) suggest further increases in NATL ET frequency in the future, particularly in the eastern portion of the basin. These projected increases were attributed to a poleward expansion of the conditions that support TCs (viz., sufficiently high SST and low deep-layer vertical wind shear) toward latitudes supportive of extratropical cyclone maintenance or intensification. Vortex interactions such as what occurred with Sandy (2012) may become less frequent if midlatitude blocking and cyclonic wave breaking frequencies decrease (Barnes et al. 2013), although there is disagreement on whether midlatitude blocking frequency will decrease in future climates (e.g., Coumou et al. 2014; Francis and Vavrus 2015).

4. Direct impacts

Though climatological studies can help explain the overall characteristics of ET for a given basin, whether in the past, present, or future, the impacts of an individual ET event on lives and property are directly tied to the hazards of strong winds, large waves, and heavy precipitation. During ET, the TC wind field expands and becomes increasingly asymmetric, shifting the coverage and location of maximum wind speeds and thus the regions at risk. The evolving wind field affects the distribution of large waves, and these large waves can directly impact marine interests and coastlines. In addition, extreme inland precipitation can occur within ET systems, sometimes far removed from the cyclone center. Like the wind field, the precipitation distribution tends to shift during the ET process. Jones et al. (2003) emphasized the importance of better understanding the evolution and prediction of these hazards to mitigate the societal impacts of a given ET event. Many studies have responded to these research needs since Jones et al. (2003) was published, and the following subsections examine research progress on each of the three major direct ET hazards.

a. Wind

As the TC near-surface wind field becomes increasingly asymmetric during ET (e.g., Powell 1982; Merrill 1993), with the strongest winds preferentially found to the right of track (e.g., aligned with its motion), the radius of maximum wind (RMW; the distance from the cyclone’s center at which the fastest tangential wind speeds are found) moves away from the center. At the same time, winds outside the RMW increase, flattening the azimuthally averaged tangential wind profile of the cyclone and increasing the cyclone’s integrated kinetic energy (Kozar and Misra 2014). As a result, the wind field expands, as illustrated by Evans and Hart (2008) through numerical simulations of NATL Hurricane Bonnie (1998). The wind field expansion has been ascribed to the following: 1) the import of absolute angular momentum into the cyclone as asymmetry increases, accelerating the wind field beyond the RMW; and 2) temporally and vertically integrated cooling maximized inside the RMW, weakening the radial geopotential height gradient near the center and causing the RMW to move radially outward (Evans and Hart 2008; Fig. 7). The diabatically driven expansion of cyclonic PV associated with TC wind field growth (Hill and Lackmann 2009) or sting jet development along the trailing end of a bent-back front (e.g., Browning 2004) may also contribute to the wind field evolution during ET, although further research is necessary to test these hypotheses.

Fig. 7.
Fig. 7.

Azimuthally averaged 10-m wind speed (m s−1) as a function of radius at 0400 UTC 29 Aug (open circles; before ET), 1000 UTC 30 Aug (closed circles; during ET), and 1000 UTC 31 Aug (open squares; after ET) 1998, as obtained from the 12-km fifth-generation Pennsylvania State University–NCAR Mesoscale Model (Dudhia 1993), simulation of NATL TC Bonnie (1998). Figure reproduced from Evans and Hart (2008, their Fig. 5).

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

Though the wind field expansion is generally associated with strong near-surface winds becoming isolated equatorward (or, for the Northern Hemisphere, right) of the TC’s track during ET (e.g., Fujibe and Kitabatake 2007), in some cases strong winds can also be observed poleward (or, for the Northern Hemisphere, left) of the TC’s track during ET (e.g., Fig. 8; Fujibe et al. 2006; Fujibe and Kitabatake 2007; Kitabatake and Fujibe 2009; Loridan et al. 2014). There exists disagreement, however, as to the frequency of such occurrences, with estimates ranging from 11.4% (Fujibe and Kitabatake 2007; Kitabatake and Fujibe 2009) to 66.7% (Loridan et al. 2014) of WNP TCs near Japan. Potential causes of strong left-of-track winds during ET include frontogenesis along a warm front rearward of the TC (e.g., Riemer et al. 2006), terrain-induced flow channeling (e.g., Mashiko 2008), and the vortex response to sufficiently large vertical wind shear (e.g., Uhlhorn et al. 2014).

Fig. 8.
Fig. 8.

Composite surface wind vectors (arrows, reference vector in the top right of each panel) and surface wind speed (isotachs, m s−1) for (a) the subset of TCs (n = 13) with wind maxima both left and right of track that made landfall in Japan from 1979 to 2004 and (b) all TCs (n = 70) that made landfall in Japan from 1979 to 2004. The y axis is taken in the direction of the storm motion. The cross in the center of each panel indicates the storm center. Figure reproduced from Fujibe and Kitabatake (2007, their Figs. 3d,f).

Citation: Monthly Weather Review 145, 11; 10.1175/MWR-D-17-0027.1

Knowledge of the diverse wind field structures that may arise during ET, even if only incomplete understanding exists of how and why they arise, is necessary to improve parametric wind models that can be used as input for trapped-fetch wave models (MacAfee and Pearson 2006; Bruneau et al. 2017) and catastrophe models (e.g., Loridan et al. 2014, 2015). Parametric wind models typically assume strongest winds right of track, whereas there is a diverse range of near-surface wind fields that are observed during ET. Thus, to improve model skill, adjustments must be made to better represent the diversity of wind field structures observed during ET. This has been done by applying size, shape, storm motion, static stability, and/or bias-correction factors to parametric wind models commonly used at low latitudes (MacAfee and Pearson 2006; Loridan et al. 2015). In the Loridan et al. (2015) formulation, specific term values vary between transitioning TCs with a right-of-track surface wind speed maximum, left-of-track surface wind speed maximum, and right-of-track surface wind speed maximum with small cross-track asymmetry. Applying the Loridan et al. (2015) parametric wind model to storm surge prediction for idealized ET events near Japan resulted in improved storm surge and wave predictions relative to those derived using winds from a purely TC wind model (Bruneau et al. 2017).

b. Waves

The evolving TC wind field during ET has a direct influence upon the cyclone’s ocean-wave field. Large ocean waves in TCs and extratropical cyclones alike pose hazards to marine activities including oil and gas extraction, fisheries, recreation, and transport. Generally, ocean wave growth is tied to cyclone characteristics such as translation speed, wind speed, and trapped-fetch length (Bowyer and MacAfee 2005; MacAfee and Bowyer 2005). Strongly enhanced waves are more likely for strong storms moving quickly with relatively small trapped-fetch lengths, with transitioning TCs having the greatest potential for these enhanced waves (Bowyer and MacAfee 2005).

Waves are small-scale phenomena, however, and their impacts tend to be parameterized in mesoscale models (if represented at all), complicating our ability to analyze and predict these features for ET events. Consequently, in addition to requiring improved inputs from meteorological forecasts, improved wave forecasts require state-of-the-art wave physics that include accurate parameterizations of the physical links between the atmosphere and ocean that govern wave behavior.

One such physical link is the generation of sea spray, which is known to contribute to TC intensification by enhancing surface latent heat flux through evaporation (e.g., Ma et al. 2015). Simulations of two TCs after ET and one of an intense extratropical cyclone demonstrated that including a sea spray parameterization increased extratropical cyclone intensity by 5–10 kt (1 kt = 0.5144 m s−1), depending on the storm, by increasing latent and sensible heat flux at the ocean surface (Perrie et al. 2005). The parameterization improved forecast wind speed estimates compared to those estimated from numerical model outputs and satellite observations. Wind speed, storm size, SST, and cyclone translation speed all affected the impacts of sea spray. Further research is necessary, however, to understand how sea spray generation evolves during ET (i.e., not just for TCs and extratropical cyclones separately).

Another physical link is wave drag, or the amount of friction generated by the production of ocean waves by the wind field. Using a coupled atmosphere–wave–sea spray model to investigate the combined effects of wave generation and sea spray on extratropical cyclone development, Zhang et al. (2006) found that simulated cyclone intensities better resembled their observed counterparts when including wave drag and sea spray compared to simulations without either. The influence of sea spray decreased due to decreasing SSTs as storms moved poleward, which coincided with an increasing influence of wave drag. As with sea spray, however, further research is necessary to understand how wave drag evolves during, and not just after, ET.

c. Precipitation

Although distinct from a transitioning TC’s wind and wave field evolutions, precipitation is perhaps the most notable ET impact to inland locations. Indeed, precipitation from TCs that undergo ET is a partial contributor to the overall precipitation climatologies of locations such as the southeastern United States (Brun and Barros 2014; Mahoney et al. 2016) and northwestern Australia (Ng et al. 2015). Rainfall associated with transitioning TCs can be directly associated with the cyclone itself or well removed (e.g., by >1000 km) from the cyclone. Although these latter events, known as predecessor rain events (e.g., Galarneau et al. 2010), can result in damaging flash floods, they are considered an indirect impact of ET and are discussed in more detail in Part II. Several heavy-precipitation events associated with transitioning TCs have caused historic flash floods in the United States well inland from the Atlantic coast, including Hazel in 1954 (Palmén 1958; Matano 1958), Agnes in 1972 (e.g., Carr and Bosart 1978; Bosart and Dean 1991), and Irene in 2011 (e.g., Milrad et al. 2013; Smith et al. 2016).

Because heavy precipitation associated with ET can occur well inland, as the cases cited above indicate, it is crucial to understand where heavy precipitation occurs during ET and the conditions that cause ET-related heavy-precipitation events to inform timely warnings. During ET, precipitation shifts radially outward and has maximum intensity downshear (Matyas 2010a,b,c). Precipitation coverage grows in areal extent as ET begins, but decreases in areal extent later in the process (Matyas 2013). Whereas TCs are typically characterized by heaviest precipitation to the left of the vertical wind shear (e.g., Lonfat et al. 2004; Chen et al. 2006), which is often right of track in the NATL, the heaviest precipitation during ET may be found either left or right of track (Atallah and Bosart 2003; Atallah et al. 2007; Milrad et al. 2009; Chen 2011; Zhou and Matyas 2017). Left-of-track precipitation is more common under atmospheric conditions resembling those favoring reintensification after becoming extratropical (section 5b), notably a negative-tilted upstream trough near to, and of similar scale as, the TC, with amplified mid- to upper-tropospheric ridging atop and downstream of the TC (Atallah et al. 2007; Milrad et al. 2009). Conversely, cases with right-of-track precipitation maxima generally never completed ET or decayed shortly after becoming extratropical. Despite advanced understanding of precipitation field evolution during ET, however, the extent to which precipitation asymmetries evolve and/or are in phase with the wind, wave, and thermal asymmetries warrants further study.

Though orography has long been known to affect TC precipitation rates, particularly in Taiwan (e.g., Lin et al. 2001; Yu and Cheng 2008, 2013), it may also focus extreme precipitation during ET. For example, Vermont was heavily impacted by flash flooding from NATL TC Irene (2011), largely due to orographic precipitation enhancement in the complex terrain of the Green Mountains (Liu and Smith 2016; Smith et al. 2016). Similarly, as precipitation with NATL TC Sandy (2012) shifted to the left of track during and after ET, upslope flow induced by the cyclone within a highly anomalous antecedent cold air mass along the western slopes of the Appalachian Mountains of North Carolina, Virginia, and West Virginia resulted in up to 900 mm of snowfall (Keighton et al. 2016). Only three prior NATL TCs are known to have produced accumulating snow in the United States, all of which occurred in New England in fall or winter in the presence of elevated terrain and an antecedent cold air mass (Keighton et al. 2016). Orography can also modulate a transit