Although high-impact heavy rainfall events in the Caribbean are typically associated with tropical cyclones (TCs) during the wet season, significant heavy rainfall events can also occur during the Caribbean dry season, absent of TCs. Dry season severe Caribbean rainstorms (CRs) can produce rainfall totals that surpass climatological dry season monthly mean rainfall, ranging from 25 to 200 mm, by > 3 sigma over a relatively short duration (2-16 days), resulting in infrastructure- and life-threatening fl ooding and mudslides. This paper introduces a 35-yr (1983-2017) dry season severe CR climatology derived from the PERSIANN-CDR precipitation dataset, revealing that dry season severe CRs occur, on average, eight times per year with some interannual variability and exhibit a seasonality that includes relative maxima in November/December and April/May as well as a relative minimum in February. Self-organizing map (SOM) analyses are applied to detect subtropical jet stream (STJS) fl ow patterns governing events in this climatology which include an upper- level trough reaching the Caribbean (Trough cases, 23% of all events), a frontal boundary extending into the Caribbean attendant to an extratropical cyclone (EC) at midlatitudes (EC Front cases, 54% of all events), or a potential vorticity stream (PVS) forming near the Caribbean (PVS cases, 7% of all events). In these events, extratropical forcing, occasionally combined with orographic forcing, can promote intense, organized, and widespread deep, moist convection that produces heavy rainfall. The remaining events do not have a discernable extratropical connection and are not considered to be influenced by the STJS (16% of events).

Strong Arctic cyclones (ACs) characterized by low forecast skill of intensity, hereafter referred to as strong low-skill ACs, may pose challenges to human activities in the Arctic. The purpose of this study is to increase understanding of features and processes influencing the evolution and forecast skill of the intensity of strong low-skill ACs. Features and processes influencing the evolution of strong low-skill ACs are examined by constructing AC-centered composites for strong low-skill ACs and by conducting a synoptic–dynamic analysis of a representative strong low-skill AC that occurred during August 2016, hereafter referred to as AC16. Features and processes influencing the forecast skill of the intensity of strong low-skill ACs are examined by utilizing the ensemble-based sensitivity analysis (ESA) technique for AC16. The composite analysis for the strong low-skill ACs and the synoptic–dynamic analysis of AC16 suggest that tropopause polar vortices (TPVs), TPV–AC interactions, baroclinic processes, and latent heating influence the evolution of the strong low-skill ACs and AC16. The ESA suggests that the forecast skill of the intensity of AC16 is sensitive to the amplitude of an upper-tropospheric trough and the strength of an embedded TPV west of AC16, and the amplitude of an upper-tropospheric ridge east of AC16. The ESA also suggests that the forecast skill of the intensity of AC16 is sensitive to the amplitude of a 1000–500-hPa thickness trough and of a 1000–500-hPa thickness ridge in the vicinity of AC16, and the positions of regions of latent heating associated with AC16.

This study explores convection-allowing ensemble (CAE) forecasts of a subset of 24 warm-season (May- August) progressive derechos from 2012 to 2022. The derecho cases were stratified into low predictability and moderate predictability based on the performance of Storm Prediction Center's Convective Outlooks. The Model for Prediction Across Scales (MPAS) is used with a global mesh of varying horizontal resolution, with a 60-km spacing over most of the globe decreasing to a 3-km spacing where the derechos occurred. A 10-member ensemble was initialized at 0000 UTC from 5 days before the derecho (D5) to the day of the event (D1). The CAE is evaluated using objective metrics as well as subjective assessments of convective mode, coverage, initiation timing, and spatial displacement of simulated convection. The objective evaluation indicates that the MPAS CAE has skill in predicting severe wind gusts, even in the medium range (3-5 days before). The skill diminishes faster with lead time in low-predictability cases compared to that of moderate- predictability cases. Overall, more than half of the ensemble members generated a sustained, progressive bowing mesoscale convective system (MCS) on D1 in both low- and moderate-predictability cases, but the percentages decrease substantially for forecasts with progressively greater lead time. Furthermore, the environmental differences among ensemble members that produce bowing MCSs, multicell clusters, and supercells are minimal. These results indicate that correctly predicting sustained bowing MCSs prior to observed derechos is challenging for the MPAS CAE for lead times longer than 1-2 days, reflecting convective-scale complexity and predictability limits. SIGNIFICANCE STATEMENT: This research evaluates the forecast capabilities of an ensemble modeling system with convection-allowing resolution in the prediction of derechos, which are convective events resulting in widespread wind damage. Our study reveals that these ensembles have skill in forecasting damaging wind gusts within both shortterm (1-2 days before) and medium-term (3-5 days before) time frames, with the highest skill at shorter lead times. However, a limitation is found in representing the correct convective organization, which is important in derecho forecasting. The small differences in environments leading to diverse convective organizations suggest that storm-scale stochastic and other internal processes play a crucial role in convective evolution. These f indings underscore the potential utility and weaknesses of medium-range convection-allowing ensembles as guidance for forecasters in predicting derechos.

We present an extended case study analysis based on observed extreme weather events (EWEs) and the planetary- and synoptic-scale variability of a persistent flow regime spanning the month of February 2019 across the North Pacific (NPAC) basin and western North America. The EWEs are clustered into two periods during February 2019: record cold and kona low conditions over Hawaii, lower elevation snow across Washington, and heavy AR-related rainfall in Southern California from 9 to 15 February; and heavy snow in Arizona and Oregon and heavy rainfall in Northern California from 21 to 28 February. From a weather regime perspective, the NPAC flow was dominated by a persistent ridge around 1508W, a retracted NPAC jet stream, repeated western NPAC (WPAC) cyclogenesis events, and frequent positively tilted troughs in the eastern NPAC and over western North America. Dynamically relevant features on the subseasonal-to-seasonal (S2S) time scale include a slowly propagating MJO signal in phases 6 and 7, a rapid NPAC jet retraction around 9 February, and subsequent eastward extension toward a climatological jet position around 21 February. On synoptic time scales, Rossby wave breaking on the southern flank of the NPAC jet and within the aforementioned persistent ridge led to the kona low formation and many of the positively tilted troughs responsible for the extreme precipitation events. In addition, frequent cyclogenesis west of the date line helped to maintain the persistent ridge strength and location through favorable heat and vorticity fluxes. The chronology and complex linkages between these aforementioned features and mechanisms are explained in depth in this paper. SIGNIFICANCE STATEMENT: This study identified several extreme cold, rain, and snow events across the western contiguous United States and Hawaii, showed how these events are all connected to a persistent weather pattern upstream over the North Pacific basin, and identified key mechanisms for why the weather pattern was so persistent. Some of the physical mechanisms for keeping the weather pattern stagnant include anomalous convection within the tropics off the east coast of Asia, breaking waves in the atmosphere like waves breaking on a beach, and repeated cyclone development off the coast of Russia and Alaska. We hope that the results of this paper encourage others to look for similar mechanisms for similar stagnant weather patterns in a more holistic manner.

This study analyzes the operational predictability of warm-season (May-August) progressive derechos. A subset of 47 derechos occurring between 2010 and 2022 were selected based on NCEI Storm Data and radar imagery. The Storm Prediction Center Convective Outlooks issued from 5 days before each derecho to the day of the event were used to determine whether the severe weather and derecho predictability was low, moderate, or high, for each case. The cases were also categorized based on the synoptic-scale midlevel fl ow pattern. Composite maps of synoptic patterns associated with the derecho cases and distributions of severe weather parameters in the derecho inflow region were generated. About 72% of the 47 derechos selected for this study were associated with low predictability, and the remainder were categorized with moderate predictability. None of the cases had high predictability. Most derechos occurring under northwest- and zonal-flow regimes (80% and 85%, respectively) had low predictability. Composites of low- and moderate-predictability derechos indicate that derechos formed in the equatorward entrance region of the upper-level jet, where low-level warm advection exists in conjunction with an equivalent potential temperature maximum. A midlevel trough is located upstream of the derecho initiation point in many of the moderate-predictability composites but is absent in the low-predictability composites, which indicates weaker synoptic-scale forcing for ascent in low-predictability cases. The distributions of severe weather parameters for low- and moderate-predictability derechos are similar, suggesting that these parameters alone are not particularly useful as a discriminator of derecho predictability. SIGNIFICANCE STATEMENT: Derechos are characterized by swaths of damaging wind gusts caused by an organized group of long-lived convective storms. These events are more frequent in the summer and are often difficult to predict far in advance. This study analyzes a subset of derecho cases to better understand the differences between cases with lower and higher predictability. About 72% of the 47 derechos examined in this study had low predictability. In these cases, the development and maintenance of storms are typically associated with larger uncertainty, but if persistent storms do form, there is potential to produce a derecho. These f indings are part of ongoing work that examines ways to improve derecho forecasts with greater lead time.

The prediction of weather conditions in the Arctic is important to human activities in the Arctic. Arctic cyclones (ACs), which are extratropical cyclones that originate within the Arctic or move into the Arctic from lower latitudes, can be associated with hazardous weather conditions that may adversely affect human activities. The purpose of this study is to increase understanding of processes that influence the forecast skill of the synoptic-scale flow over the Arctic and of ACs. The 11-member NOAA Global Ensemble Forecast System (GEFS) reforecast dataset, version 2, is utilized to identify periods of low and high forecast skill of the synoptic-scale flow over the Arctic, hereinafter referred to as low-skill and high-skill periods, respectively, during the summers of 2007-17, and to evaluate the forecast skill of ACs during these respective periods. The ERA-Interim dataset is used to examine characteristics of the Arctic environment and characteristics of ACs during low-skill and high-skill periods. The Arctic environment tends to be characterized by more vigorous baroclinic processes and latent heating during low-skill periods relative to high-skill periods. ACs occur more frequently over much of the Arctic; tend to be stronger; and tend to be located in regions of larger lower-tropospheric baroclinicity, lower-to-midtropospheric Eady growth rate (EGR), and latent heating during low-skill periods relative to high-skill periods. ACs during low-skill periods that are characterized by low forecast skill of intensity tend to be relatively strong and tend to be located in regions of relatively large lower-tropospheric baroclinicity, lower-to-midtropospheric EGR, and latent heating.

We present a comparative analysis of atmospheric rivers (ARs) and Great Plains low-level jets (GPLLJs) in the central United States during April-September 1901-2010 using ECMWF's Coupled Reanalysis of the Twentieth Century (CERA-20C). The analysis is motivated by a perceived need to highlight overlap and synergistic opportunities be-tween traditionally disconnected AR and GPLLJ research. First, using the Guan-Walliser integrated vapor transport (IVT)-based AR classification and Bonner-Whiteman-based GPLLJ classification, we identify days with either an AR and/or GPLLJ spanning 15% of the central United States. These days are grouped into five event samples: 1) all GPLLJ, 2) AR GPLLJ, 3) non-AR GPLLJ, 4) AR non-GPLLJ, and 5) all AR. Then, we quantify differences in the frequency, sea-sonality, synoptic environment, and extreme weather impacts corresponding to each event sample. Over the twentieth cen-tury, April-September AR frequency remained constant whereas GPLLJ frequency significantly decreased. Of GPLLJ days, 36% are associated with a coincident AR. Relative to ARs that are equally probable from April-September, GPLLJs exhibit distinct seasonality, with peak occurrence in July. A 500-hPa geopotential height comparison shows a persistent ridge over the central United States for non-AR GPLLJ days, whereas on AR GPLLJ days, a trough-and-ridge pattern is present over western to eastern CONUS. AR GPLLJ days have 34% greater 850-hPa windspeeds, 53% greater IVT, and 72% greater 24-h precipitation accumulation than non-AR GPLLJ days. In terms of 95th-percentile 850-hPa wind speed, IVT, and 24-h precipitation, that of AR GPLLJs is 25%, 45%, and 23% greater than non-AR GPLLJs, respectively.

High‐resolution Taiwan Climate Change Projection Information and Adaptation Knowledge Platform (TCCIP) gridded precipitation data are used to characterize days in the Mei‐yu season with the most extreme precipitation (EP). These “EP days” are grouped into weather types based on the presence of features such as tropical cyclones (TCs) and atmospheric rivers (ARs), then analyzed from the perspective of weather type frequency and synoptic changes. During the 1979–2019 period, EP days associated with ARs were associated with significant increasing trends in season‐total precipitation. These AR‐related precipitation increases are due to four events in 2005, 2006, 2012, and 2017 which had long duration and unusually intense precipitation, and which were anomalous even within the longer 1960–2019 time period. Meanwhile, TC‐related EP days contribute less precipitation than they did in the 1980s due to decreased frequency of TCs on EP days and in the Mei‐yu season climatology. Over the 1979–2019 period, the AR‐related and TC‐related trends combine to produce EP increases in western Taiwan and decreases in eastern Taiwan. Mei‐yu season southwesterly integrated vapor transport (IVT), wind speed, and specific humidity have all increased in association with these extreme events. Low‐level winds appear to the primary factor influencing the IVT increase, with increased moisture also contributing. The wind trends are consistent with climatological pressure increases south of Taiwan and decreases over the East Asian landmass, which facilitate a strengthened circulation in a corridor extending from the southern China coastline over Taiwan during this season.

This study uses Global Historical Climate Network (GHCN) data in each season to identify the days with the most extreme precipitation ("EP days") in the mid-Atlantic and northeast United States between 1979 and 2019. These days are sorted according to the fraction of extreme precipitation attributed to tropical cyclone (TC), atmospheric river (AR), and extreme integrated vapor transport (IVT) influences. In winter and spring, there have been increases in seasonal precipitation from the most extreme days, associated with a combination of frequency and intensity changes. These increasing trends come primarily from atmospheric rivers. In summer and fall, there have also been large increases in precipitation on extreme days, in this case due entirely to increased event frequency. These changes come from a combination of AR, TC, and extreme IVT influences. Synoptic characteristics of AR-related EP days in winter and spring have changed significantly. In winter, there has been an amplification of the Atlantic ridge and a deepening of the upstream trough over the upper Great Plains, as well as enhanced AR detection and IVT on these days. The composite low has shifted north and intensified. In spring, the trough has weakened and 1000-500-hPa thickness has increased broadly to the south. These changes are related to changes in the large-scale flow. In winter and spring, the North Atlantic subtropical high (NASH) has strengthened and shifted west, leading to increased southwesterly IVT over the mid-Atlantic and Northeast United States. In summer, southerly IVT along the east coast has increased, and 1000-500-hPa climatological thickness has increased broadly in all seasons. Significance StatementThis paper studies the days with the most extreme precipitation over the mid-Atlantic and Northeast United States in each season and finds that there have been large changes in the frequency, intensity, and characteristics of some of these days. Extreme days associated with atmospheric rivers (ARs) and tropical cyclones (TCs) have become more frequent. Precipitation on AR-related days has also become more intense in some areas. On winter extreme days associated with ARs, the pattern has become more amplified and moisture fluxes have become stronger; these changes are likely associated with strengthened high pressure over the Atlantic. Throughout all seasons, there is evidence of warming on extreme days. This is important because it adds to our understanding of how total and AR-related extreme precipitation is changing in a warming climate.

Over the course of his career, Fuqing Zhang drew vital new insights into the dynamics of meteorologically significant mesoscale gravity waves (MGWs), including their generation by unbalanced jet streaks, their interaction with fronts and organized precipitation, and their importance in midlatitude weather and predictability. Zhang was the first to deeply examine "spontaneous balance adjustment"- the process by which MGWs are continuously emitted as baroclinic growth drives the upper-level flow out of balance. Through his pioneering numerical model investigation of the large-amplitude MGW event of 4 January 1994, he additionally demonstrated the critical role of MGW-moist convection interaction in wave amplification. Zhang's curiosity-turned-passion in atmospheric science covered a vast range of topics and led to the birth of new branches of research in mesoscale meteorology and numerical weather prediction. Yet, it was his earliest studies into midlatitude MGWs and their significant impacts on hazardous weather that first inspired him. Such MGWs serve as the focus of this review, wherein we seek to pay tribute to his groundbreaking contributions, review our current understanding, and highlight critical open science issues. Chief among such issues is the nature of MGW amplification through feedback with moist convection, which continues to elude a complete understanding. The pressing nature of this subject is underscored by the continued failure of operational numerical forecast models to adequately predict most large-amplitude MGW events. Further research into such issues therefore presents a valuable opportunity to improve the understanding and forecasting of this high-impact weather phenomenon, and in turn, to preserve the spirit of Zhang's dedication to this subject.

This study analyzes the low short-range predictability of the 3 May 2020 derecho using a 40-member convection-allowing Model for Prediction Across Scales (MPAS) ensemble. Elevated storms formed in south-central Kansas late at night and evolved into a progressive mesoscale convective system (MCS) during the morning while moving across southern Missouri and northern Arkansas, and affected western and middle Tennessee and southern Kentucky in the afternoon. The convective initiation (CI) in south-central Kansas, the organization of a dominant bow echo MCS, and the MCS maintenance over Tennessee were identified as the three main predictability issues. These issues were explored using three MPAS ensemble members, observations, and the Rapid Refresh analyses. The MPAS members were classified as successful or unsuccessful with regard to each predictability issue. CI in south-central Kansas was sensitive to the temperature and dewpoint profiles in low levels, which were associated with greater elevated thermodynamic instability and lower level of free convection in the successful member. The subsequent organization of a dominant bowing MCS was well predicted by the member that had more widespread convection in the early stages and no detrimental interaction with other simulated convective systems. Last, the inability of MPAS ensemble members to predict the MCS maintenance over western and middle Tennessee was linked to a dry bias in low levels and much lower thermodynamic instability ahead of the MCS compared to observations. This case demonstrates the challenges in operational forecasting of warm-season derecho-producing progressive MCSs, particularly when ensemble numerical weather prediction guidance solutions differ considerably.

A spectral analysis of Great Plains 850-hPa meridional winds (V850) from ECMWF’s coupled climate reanalysis of 1901-2010 (CERA-20C) reveals that their warm season (April-September) interannual variability peaks in May with 2-6 year periodicity, suggestive of an underlying teleconnection influence on low-level jets (LLJs). Using an objective, dynamical jet classification framework based on 500-hPa wave activity, we pursue a large scale teleconnection hypothesis separately for LLJs that are uncoupled (LLJUC) and coupled (LLJC) to the upper-level jet stream. Differentiating between jet types enables isolation of their respective sources of variability. In the South Central Plains (SCP), May LLJCs account for nearly 1.6 times more precipitation and 1.5 times greater V850 compared to LLJUCs. Composite analyses of May 250-hPa geopotential height (Z250) conditioned on LLJC and LLJUC frequencies highlight a distinct planetary-scale Rossby wave pattern with wavenumber-five, indicative of an underlying Circumglobal Teleconnection (CGT). An index of May CGT is found to be significantly correlated with both LLJC (r = 0.62) and LLJUC (r = −0.48) frequencies. Additionally, a significant correlation is found between May LLJUC frequency and NAO (r = 0.33). Further analyses expose decadal scale variations in the CGT-LLJC(LLJUC) teleconnection that are linked to the PDO. Dynamically, these large scale teleconnections impact LLJ class frequency and intensity via upper-level geopotential anomalies over the western U.S. that modulate near-surface geopotential and temperature gradients across the SCP.

Coherent vortices in the vicinity of the tropopause, referred to as tropopause polar vortices (TPVs), may be associated with tropospheric-deep cold pools. TPVs and associated cold pools transported from high latitudes to middle latitudes may play important roles in the development of cold air outbreaks (CAOs). The purpose of this study is to examine climatological linkages between TPVs, cold pools, and CAOs occurring in the central and eastern United States. To conduct this study, 1979–2015 climatologies of TPVs and cold pools are constructed using the ERA-Interim dataset and an objective tracking algorithm, and are compared to a 1979–2015 climatology of CAOs occurring in six NCEI-defined climate regions over the central and eastern United States. The climatologies of TPVs and cold pools indicate that central and eastern North America is a preferred corridor for their equatorward transport, and that the occurrence frequency of TPVs and cold pools is higher over northern regions of the United States compared to southern regions of the United States. Correspondingly, there is a higher percentage of CAOs linked to cold pools associated with TPVs over northern regions of the United States (32.1%–35.7%) compared to southern regions of the United States (4.4%–12.5%). TPVs and cold pools contributing to CAOs form most frequently over northern Canada and the Canadian Archipelago, and generally move southeastward toward southern Canada and the northern United States. TPVs and cold pools contributing to CAOs tend to be statistically significantly colder and longer lived when compared to all TPVs and cold pools transported to middle latitudes.

The U.S. Great Plains low-level jet (LLJ) is active on 26% and 62% of May-September days in the northern and southern Plains, respectively. Characterized by a diurnally-oscillating low-level wind maximum below 700 hPa, large vertical wind shear, and enhanced atmospheric moisture convergence, LLJs have been shown to fuel extreme wind- and precipitation generating mesoscale convective systems. Overall, they explain 30-50% of May-September precipitation in the Plains. The considerable societal impacts of LLJs, which span agriculture, severe weather, and wind energy, have long motivated meteorologist-led investigations into their dynamics and predictability. The sensitivity of LLJs to regional soil moisture gradients was established over thirty years ago. However, it was only recently that our work provided the first estimates of the added-value of satellite soil moisture data assimilation (DA) to LLJ forecasts. In this presentation, we review and expand upon our previous analysis of 75 NASA Unified WRF LLJ case studies simulated with- and without weakly-coupled NASA Soil Moisture Active Passive (SMAP) soil moisture DA. Of the 75-jet cases, 43 are uncoupled LLJs and 32 are coupled LLJs. Their dynamical classification corresponds with the probable efficacy of land data assimilation. Cyclone-induced coupled LLJs, found in the warm sector of frontal systems, are strongly driven by synoptics and less likely to be influenced by land forcing. Conversely, uncoupled LLJs that occur during quiescent conditions of an anticyclonic high pressure ridge system are likely to be more strongly affected by terrain and soil moisture gradient-induced circulations. It is shown that SMAP DA is generally more effective in uncoupled LLJ cases. However, significant SMAP DA-induced wind speed differences are noted for both LLJ types at their core and exit regions. Notably, the range of SMAP DA-induced wind speed differences between LLJs of the same class (i.e., uncoupled LLJs) is comparable to the range of differences between LLJs of different classes (i.e., coupled vs. uncoupled). Follow-on analyses presented here address the question of what differs between LLJs with small and large SMAP DA effects. Specifically, we explore attribution of event-scale differences in the added-value of SMAP DA to factors including SMAP spatial coverage, antecedent soil moisture, and the strength of synoptic forcing. Finally, a closer look is given to the verification of jet exit region SMAP DA-induced wind speed shifts using Rapid Refresh.

Taiwan regularly experiences precipitation extremes of hundreds of millimeters per day, especially between May and September. In this study, Taiwan's extreme rainfall (ER) is analyzed over a 56-yr time period in different seasons and geographic regions, using a recently released, high-resolution gridded rainfall dataset. ER is defined using a seasonally and geographically varying 99th-percentile threshold to better resolve the characteristics of the most intense rainfall seen in different locations and times of year. The resulting monthly ER rates are largest in typhoon season and smallest in fall, winter, and spring. ER is spatially homogeneous in the mei-yu and typhoon seasons and concentrated in northern Taiwan during the rest of the year. A trend analysis revealed a positive trend in island-mean ER for the winter, spring, and typhoon seasons. In winter and spring, these trends are most pronounced in the north. In the mei-yu season, ER has increased most over the southwestern mountain slopes; in typhoon season, ER has increased consistently over much of Taiwan. These changes often exceed 1% yr(-1). In many areas, typhoon season accounts for the largest fraction of the observed annual ER trend. TCs produce most of the observed typhoon season ER and ER trend, with nearly half of the typhoon season ER trend being associated with increases in TC frequency and duration around central and northern Taiwan. Certain regional changes in ER characteristics, particularly in areas with low sample size or complex seasonal contributions, merit further investigation in future work.

On 4–5 September 2013, a relatively shallow layer of northerly dry airflow was observed just west of the core deep convection associated with the low-level center of the pre-Gabrielle (2013) tropical disturbance. Shortly thereafter, the core deep convection of the disturbance collapsed after having persisted for well over 24 h. The present study provides an in-depth analysis of the interaction between this dry airflow layer and the pre-Gabrielle disturbance core deep convection using a combination of observations, reanalysis fields, and idealized simulations. Based on the analysis, we conclude that the dry airflow layer played an important role in the collapse of the core deep convection in the pre-Gabrielle disturbance. Furthermore, we found that the presence of storm-relative flow was critical to the inhibitive effects of the dry airflow layer on deep convection. The mechanism by which the dry airflow layer inhibited deep convection was found to be enhanced dry air entrainment.

A polar-subtropical jet superposition represents a dynamical and thermodynamic environment conducive to the production of high-impact weather. Prior work indicates that the synoptic-scale environments that support the development of North American jet superpositions vary depending on the case under consideration. This variability motivates an analysis of the range of synoptic-dynamic mechanisms that operate within a double-jet environment to produce North American jet superpositions. This study identifies North American jet superposition events during November-March 1979-2010 and subsequently classifies those events into three characteristic event types. "Polar dominant" events are those during which only the polar jet is characterized by a substantial excursion from its climatological latitude band, "subtropical dominant" events are those during which only the subtropical jet is characterized by a substantial excursion from its climatological latitude band, and "hybrid" events are those characterized by a mutual excursion of both jets from their respective climatological latitude bands. The analysis indicates that North American jet superposition events occur most often during November and December, and subtropical dominant events are the most frequent event type for all months considered. Composite analyses constructed for each event type reveal the consistent role that descent plays in restructuring the tropopause beneath the jet-entrance region prior to jet superposition. The composite analyses further show that surface cyclogenesis and widespread precipitation lead the development of subtropical dominant events and contribute to jet superposition via their associated divergent circulations and diabatic heating, whereas surface cyclogenesis and widespread precipitation tend to peak at the time of superposition and well downstream of polar dominant events.