1. Introduction
Strong low-level mesoscale winds often develop adjacent to steep terrain away from the Tropics. These winds are commonly referred to as barrier jets (e.g., Parish 1982; Doyle 1997), because the enhanced winds have a significant component in the terrain-parallel direction along the windward slope. Barrier jets are routinely observed in cold air damming events along the East Coast of the United States (Bell and Bosart 1988) as well as around Taiwan (Li and Chen 1998), the western slopes of the Sierra Nevada (Parish 1982; Marwitz 1987), the Front Range of the Colorado Rockies (Marwitz and Toth 1993), Antarctica (Schwerdtfeger 1975), the West Coast of the United States (Doyle 1997), and Alaska (Schwerdtfeger 1974; Overland and Bond 1993).
Formation of a barrier jet can be achieved by low-level flow blocking, which enhances the barrier-parallel pressure gradient. This process can occur via adiabatic cooling from forced ascent (Mass and Ferber 1990). Flow impinging on a mountain range is blocked when the Froude number [Fr = (u/hmN)] is less than one, where u is the ambient barrier-normal velocity component, hm is the height of the barrier, and N is the Brunt–Väisälä frequency. This blocking decelerates the flow via a coupled process of windward mass convergence and pressure rises along the windward slopes. This local disruption of the force balance leads to ageostrophic acceleration parallel to the barrier. The Coriolis force partially determines the upstream extent of the flow blocking, as given by the Rossby radius of deformation (Lr = Nhm/f ) (Pierrehumbert and Wyman 1985). Those coastal barrier jets that have a maritime flow source and develop along the coast by the conventional idea of upstream flow blocking will be referred to as classic barrier jets.
In cases where the windward slope of a mountain range faces east (in the Northern Hemisphere), cold air damming (CAD) may occur if cold air is present to the north. If the mountain blocks this cold low-level flow then a barrier jet may develop that quickly advects cold air southward along the eastern slopes. For many CAD barrier jets (Bell and Bosart 1988; Colle and Mass 1995), there is a force balance between the Coriolis force and the pressure gradient directed away from the mountain, while there is antitriptic balance between friction and pressure gradient in the along-barrier direction.
Conditions suitable for terrain-enhanced winds along mountainous coasts can result from other sources, such as gap flows (Overland and Walter 1981). When there is a significant pressure difference between opposing sides of a mountain range, air from the high pressure side is frequently drawn through the mountain gaps. Upon exiting the gap, this unbalanced flow can be turned by the Coriolis force (Steenburgh et al. 1998). Steenburgh et al. (1998) showed using numerical simulations that the center of the gap-exit flow has radius of curvature determined by an inertial circle. Steenburgh's simulations were done on gap-exit flow at latitudes below 17°N, where the gap-exit flow turned very slowly and thus never became a coastal jet. Because the radius of an inertial circle is inversely proportional to the magnitude of the Coriolis force, however, it is possible for high-latitude gap-exit flow to rapidly turn terrain parallel as it merges with the synoptic flow. In the latter case, the gap-exit flow may develop characteristics of a terrain-parallel barrier jet as it travels away from the gap. Barrier jets that originate from gap flow will be referred to as hybrid jets in this paper, as they are a hybrid of a classic barrier jet and gap flow. Thus, the main difference between classic barrier jets and hybrid jets is the source of the air.
The Alaskan coastline bordering the Gulf of Alaska has numerous topographic barriers near the coast, as well as a variety of bays, straits, and sounds (Fig. 1). Some of the most important near-coast mountains are Mount Fairweather near Glacier Bay National Park, and the Valdez–Cordova mountains to the northwest of Yakutat (labeled on Fig. 1), which are both over 4500 m. The proximity of these steep mountains to the coast favors the development of coastal barrier jets (Overland and Bond 1993), which are treacherous to the aviation and fishing industries in the region. For example, a fisherman was caught in a poorly forecasted barrier jet near Yakutat on 14 March 1979 (Overland and Bond 1993), in which the forecast was for 30-kt winds, but 70-kt winds were reported. The barrier jet responsible for the high wind speeds was associated with a deepening low pressure system that made landfall just northwest of Yakutat, Alaska.
Despite the extensive previous studies of barrier jets there remain a number of open issues pertaining to their synoptic setting, dynamic controls, climatological distribution, and three-dimensional structure. For example, the synoptic setting and dynamical controls for classic barrier jets are well understood for only a few (mostly inland) locales (Parish 1982; Schultz et al. 1997). In contrast, the synoptic conditions that lead to the formation of coastal barrier jets are known only in the most general terms, such as flow blocking ahead of a landfalling front. The climatology and structural details of coastal barrier jets are also poorly documented.
Recent field experiments provide intriguing suggestions that processes beyond simple upstream flow blocking can contribute to coastal barrier jets. Cold air banked along the windward flank of Vancouver Island appears to have enhanced the barrier jet observed during the Coastal Observation and Simulation with Topography Experiment (COAST) (Overland and Bond 1995). Overland and Bond (1995) deemed that this cold air was supplied by gap flow through the Strait of Juan de Fuca. In fact, the numerical modeling experiments by Doyle and Bond (2001) indicated that the cold gap flow through the Strait of Juan de Fuca was at least as important as the orography of Vancouver Island in bringing about enhancement of the along-barrier flow. This result suggests that the traditional view of the synoptic conditions leading to the formation of coastal barrier jets may be overly simplistic. Indeed, given the possibility of gap flows, there may be a relationship between the air mass on the landward side of the barrier and the blocking of flow on the ocean side of the barrier. This relationship needs to be explored because it raises some important questions. Does the presence of cold, dry air near the coast affect the structure of the resulting barrier jet, the maximum speed enhancement, offshore wind speed gradient, barrier jet width, etc.? The Gulf of Alaska provides an ideal laboratory to address these issues because of the intense seasonally varying land–sea temperature differences and the existence of clearly defined gaps in the high coastal terrain. The temporal and spatial climatologies of hybrid jets presented below address these issues.
Examination of synthetic aperture radar (SAR) imagery from the Gulf of Alaska suggests that such remote sensing observations can also shed light on several recent model results. For example, while simulations suggest that barrier jets have significant along-coast variability in the presence of highly three-dimensional terrain (Doyle 1997), verification of this result has not been possible using in situ observations. SAR, with its spatial mapping capability, provides the opportunity do so along the highly three-dimensional coast of Alaska. As will be shown below, the spatial climatology of barrier jets in the Gulf of Alaska is indeed closely linked to the details of the near-shore terrain.
SAR observations of the Gulf of Alaska thus provide us with a unique opportunity to examine the structure and climatology of barrier jets and hybrid jets in the presence of complex coastal terrain where gap flow and onshore flow can coexist and interact. The present study demonstrates the utility of SAR for these types of coastal mesoscale flows and applies these observations to the theoretical questions posed above.
SAR observations of Alaskan barrier jets also have direct operational applications. Predicting the magnitude and occurrence of barrier jets along the Alaskan coast is difficult because of the complex topography of the region as well as the general lack of in situ observations over the coastal waters. To improve forecasting, it would be desirable for forecasters to know the temporal and spatial distributions of barrier jet occurrence along the coastline. By knowing when and where barrier jets typically occur, forecasters can focus their attention on a smaller region of the coastline, and hopefully forecast these wind events with better skill. In addition, the complex coastal topography of the region allows one to determine under what conditions classic barrier jets form as opposed to hybrid jets. With these goals in mind, the questions we seek to answer in this study are as follows:
Where are the favored regions for coastal barrier jet formation in the Gulf of Alaska?
What are the favored seasons for coastal barrier jet formation in the Gulf of Alaska?
Can the seasonal variation in barrier jet formation be explained by the traditional flow-blocking theory?
What are the typical structural properties of the coastal barrier jets found in the Gulf of Alaska?
All of the above questions will be addressed for hybrid jets as well.
Section 2 introduces the data source and methods used in the creation of the climatologies presented. Section 3 focuses on the classic barrier jet distributions, and Section 4 addresses hybrid jet distributions. Typical structural properties of both barrier and hybrid jets are discussed in section 5, while section 6 presents conclusions from the study.
The second part of this paper (Colle et al. 2006, hereafter Part II) utilizes rawinsonde and National Centers for Environmental Prediction (NCEP) reanalysis data (Kalnay et al. 1996) to address in greater depth the thermodynamic and dynamic issues related to structural differences between the various types of barrier jets.
2. Data analysis and procedures
Because this study focuses on a region with little in situ observational data, SAR was the ideal choice for collecting surface wind speed observations (Young et al. 2005). Spaceborne SAR is a satellite-mounted radar that uses a microwave signal to detect the presence of centimeter-scale capillary waves on the surface of the ocean. The backscatter from these capillary waves can be directly related to the instantaneous surface wind stress, which then yields the wind speed at the surface (Stoffelen and Anderson 1993). Converting the backscatter field to wind speed does, however, require knowledge of the wind direction. The required wind directions were obtained from Navy Operational Global Atmospheric Prediction System (NOGAPS) model analyses at 1° grid spacing provided by the Master Environmental Library. The conversion of backscatter intensity to wind speed is done using the CMOD4 algorithm. The algorithm uses the fact that for a given cross section, wind direction relative to the radar look direction, and incidence angle, a unique wind speed exists. The CMOD4 algorithm provides a unique transformation to wind speed given those parameters. For a more detailed explanation see Stoffelen and Anderson (1997) and Thompson and Beal (2000).
SAR wind mapping provides subkilometer-resolution coverage over a swath of mesoscale width (∼500 km) from a polar-orbiting satellite. This combination of subkilometer resolution and mesoscale coverage is crucial for this study because of the small spatial scale of barrier jets and the large extent of the coast to be covered (over 2000 km). Use of remote sensing data to construct a climatology of wind events offshore of Central America has previously been made over a 9-month period using scatterometer data by Chelton et al. (2000).
For this study SAR wind speed data from the Canadian Radarsat-1 satellite (Radarsat) was used (Pichel and Clemente-Colon 2000). These satellite data were collected in “wide-swath mode,” yielding a 450-km-wide image with 100–200-m resolution (Pichel and Clemente-Colon 2000). The higher resolution of SAR allows one to work closer to the coast than with scatterometers (Thompson et al. 2001), a key advantage when studying barrier jets. In contrast, the swath width of this SAR is less than that for operational scatterometers (Weissman et al. 2002), so any given location on the Alaskan coast is imaged less frequently, although still at least once every 3 days.
A collection of all the SAR images of the Gulf of Alaska from 1 May 1998 to 30 April 2003 was processed using the operational wind-speed-processing algorithm developed at Johns Hopkins University Applied Physics Laboratory (Monaldo 2000; Monaldo et al. 2001, 2004). This collection included roughly 3000 images over the 5-yr study period. Figures 2 provides examples of SAR-derived wind speed images. Figure 2a is an image of a classic barrier jet. Notice the slightly onshore-directed flow, with the area of coastal-enhanced winds, in excess of 20 m s−1, signifying the barrier jet. In contrast, Fig. 2b depicts a much weaker example of a classic barrier jet. Figure 2c shows a hybrid jet, with offshore-directed gap outflow coming from Cross Sound, which rapidly turns coast parallel. Conversely, an example of gap outflow from the same gap that does not turn coast parallel, and is therefore not considered a hybrid jet, is show in Fig. 2d.
Several subcategories applicable to both classic and hybrid barrier jets can also be defined. About 33% of jets observed were found to have extremely large wind speed gradients along their outer edge. These are classified as shock jets. This name was selected because the jets have a sharp boundary on the synoptic upstream side reminiscent of the bow shock of a supersonic object. For example, on 22 October 2000 (Fig. 2e), the wind speed rapidly decreases from around 25 m s−1 to around 10 m s−1 within a few kilometers. This intense cyclonic shear boundary suggests a mesoscale temperature gradient near the coast, which requires a confluent boundary between a cold, easterly flow that originates from inland regions (hybrid) or is trapped along the coast (classic) and a surge of warmer air approaching the coast from the southwest. The sharp boundary in wind speed upstream of the coast between the barrier jet and ambient flow also has been observed along the California coast where it has been referred to as a blocking front (P. Neiman 2005, personal communication). In contrast, 23% of all jets have irregular breaks between segmented areas of high wind speed and are classified as variable jets. These events, such as 5 December 1999 (Fig. 2f), appear to be more convective, with the higher-momentum air associated with the barrier jet being transferred locally to the surface via boundary layer mixing or shallow convective downdrafts. The stark difference between the shock and variable types suggests that there are large differences in the static stability profile and airmass origins, differences that are highlighted in Part II. Therefore, these two jet types as well as the other events will be investigated for the region in Fig. 2 using large-scale and sounding composites in Part II. Because the hybrid versus classic jet distinction is closely linked to details of the coastal orography, which varies significantly along the full Alaskan coast, this categorization is used here.
Using SAR data is not without its disadvantages. One shortcoming of SAR is that only surface wind speeds over water can be obtained. Thus, any portion of the barrier jet that is situated over land cannot be seen using SAR. Moreover, at low wind speeds SAR data can be contaminated with oceanographic events, such as current boundaries and internal waves (Jackson and Apel 2004). This low wind speed contamination problem does not affect the current study to a large degree given the high wind speed events under investigation (the weakest jet in the climatology presented below was 8 m s−1). A larger disadvantage for this study is that the ability of the CMOD4 algorithm to convert backscatter to wind speed is questionable at speeds much greater than 20 m s−1 (Donnelly et al. 1999; Monaldo 2000). For this reason, the SAR wind speeds only go up to 25 m s−1 in the available images. Thus, for the intense barrier and hybrid jets, a true maximum wind speed cannot be obtained using SAR.
Another disadvantage of using SAR is that a wind direction must be obtained from an external analysis as discussed above. Because the NOGAPS analyses cannot resolve all the small-scale coastal flows (Mass et al. 2002), there will inherently be error in the SAR-measured wind speeds. The speed error attributable to errors in estimated direction is a function not only of the direction error, but also of incidence angle, the actual wind speed, and the true direction (i.e., whether the radar is looking upwind or crosswind). Figure 3 shows an example of the characteristics of the wind speed error as a function of wind direction error. This figure was generated by inverting CMOD4 for the cross section corresponding to an 8 m s−1 wind (blowing toward the radar at a 0° relative look angle) and then inverting this cross section around the 360° range of azimuth angles. In this way, the angles on the x axis of Fig. 3 are analogous to wind direction error. The error bars included on the wind speed curve shown in Fig. 3 correspond to the addition of a ±2.0 dB error on the cross-section measurement itself. One can see from Fig. 3 that under this worst-case scenario (high incidence angle, radar looking upwind but processed with crosswind directions), wind speed errors on the order of a factor of 2 can exist. In most cases, however, the wind direction errors are not nearly so severe. Depending on the wind direction relative to the look direction, speed errors can be of either sign.
The data used to present climatological values of stability, wind speed, wind direction, pressure, and temperature is the NCEP reanalysis (Kalnay et al. 1996). These data are available four times daily, with a meridional and zonal grid spacing of 2.5°. Only three vertical layers (1000, 925, and 850 mb) exist from the surface to near crest level of the coastal mountains (2000 m). These data yield information about the low-level synoptic-scale features that are important in barrier and hybrid jet formation, but cannot be used to verify the existence of barrier jets. In Part I they are used primarily to diagnose the ambient flow directions for classic and hybrid jets, while in Part II, they are used to construct a composite of the synoptic-scale flow of the various jet types.
To produce an objective event climatology, the event criteria must be unambiguously defined. The criteria used in this study are as follows. A barrier jet is defined as a barrier-parallel wind maximum immediately adjacent to the coast, which is longer in the alongshore direction than the cross-shore direction. The maximum wind speed must be at least 1.5 times greater than the ambient onshore-directed flow, where the ambient flow is defined as the average flow found 10 to 20 km upstream (to the west or south) of the barrier jet. The offshore edge of the barrier jet is defined as being located where the flow speed reaches 1.25 times that of the ambient synoptic flow. Hybrid jets are defined using the same criteria as for classic barrier jets, but must originate via an offshore-directed gap flow that rapidly turns anticyclonically to become shore parallel. The terms used to describe the structure of barrier and hybrid jets are as follows: Strength is defined as the maximum wind speed observed at any point within the jet. Width is defined as the distance from the base of the windward slope of the topography, which is responsible for the jet, to the outer edge of the jet.
Computing the spatial distribution of barrier and hybrid jet occurrence required approximating the irregular coastline with a smooth curve, in this case an eighth-order polynomial function relating latitude to longitude (Fig. 1). Sixty-two data points lying just offshore were used to generate the function via a least squares fit. The function was then divided into 405 segments measuring 5 km each giving a total function length of 2025 km. The starting and ending points of the function are located at latitude and longitude 57.28°N, 156.25°W and 51.92°N, 131.41°W, respectively. A large majority of the points along the function lie approximately 10 km offshore; however, a few points lie a few kilometers inland.
3. Classic barrier jet distributions
a. Temporal distribution
The total number of barrier jets observed for each month of the 5-yr study period was calculated in order to create a temporal distribution of barrier jet occurrence for this section of coast. Figure 4 reflects the distribution of barrier jets by month that would be expected if each month had received equal satellite coverage and each month was 30 days in length. SAR imagery is not available for each point along the coast for all times in the study, so only the relative shape of the distribution has significance. It is not possible to state the exact number of barrier jets that occurred in each month with the data available.
It is clear from Fig. 4 that barrier jets are most common during the cool season. The minimum in barrier jet frequency, however, extends from April through August while the warm season in coastal Alaska lags this by approximately a month and a half. Therefore, the two seasons will be called peak season and lull season rather than cool season and warm season. Personal observations from the recently completed Southern Alaskan Regional Jet (SARJET) experiment near Juneau during September and October 2004 support the September transition from low to high barrier jet frequency. After accounting for the unequal lengths of peak season (7 months) and lull season (5 months), the peak season displays a 65% higher likelihood of barrier jet occurrence for any given day. In fact, the barrier jet frequency in December is nearly twice that in July.
Because the peak season has a much higher percentage of the barrier jets, it is logical to examine the seasonal differences between the three factors that control flow blocking (wind direction, stability, and barrier-normal velocity). All seasonal comparisons are done for a single reanalysis data point located at 60°N, 142.5°W (red square in Fig. 1). This point lies just offshore and very near the Valdez–Cordova mountains, which produce the greatest number of barrier jets (see section 3b). For this particular mountain range, which faces nearly due south, favorable flow directions for barrier jet formation range from 120° to 180°. Geostrophic flow from this range of directions reflects the existence of a barrier-parallel component to the synoptic pressure gradient, which is needed for barrier-parallel acceleration if blocking were to occur. Twenty-seven percent of all peak season observations had favorable flow directions, compared to 22% of lull season observations.
Onshore wind speed versus stability scatterplots of those observations with favorable flow directions as defined above are shown in Fig. 5. These plots suggests that flow blocking should be much more prevalent during the lull season, as a significant number of the observations correspond to low Froude number regimes. The blocked flow during the lull season typically cannot develop into strong barrier jets, however, because of the weak alongshore synoptic pressure gradient as can be inferred from the weak onshore wind speeds. Conversely, the peak season plot (Fig. 5b) reveals a large number of observations with both high stability and large barrier-parallel synoptic pressure gradients. Blocking of the strong onshore flow in these settings could lead to significant acceleration of the flow parallel to the barrier. Thus, it can be concluded that using solely the Froude number as a predictor for barrier jet formation can be misleading. The magnitude of the barrier-normal flow is of great importance as well.
It should be pointed out that the number of events observed was not identical from year to year. Two elements can contribute to this difference: the lack of complete temporal coverage of SAR images and the true interannual variability in the number of events. Because SAR images were not available for all times and places, the 3000 images examined for this study yield sample rather than population statistics on the climatological frequency of events. Confidence bounds on the climatological frequency can be computed by application of the binomial sampling distribution given the average number of images per year and the percentage of those exhibiting jets. For the large samples available here and the observed frequency of barrier jets, one can state with 95% confidence that the true frequency lies within 15% to 20% of the observed value depending on the year-to-year variation in the number of images. Because the observed interannual variability in event frequency exceeds this threshold, some portion of it is probably the result of true interannual variability. Thus, the forecaster should not expect the same number of barrier jets to occur in the Gulf of Alaska each year. Interannual variation in our 5-yr sample is, however, typically under a factor of 2.
b. Spatial distribution
To produce a spatial climatology of barrier jets, each jet was projected onto the coastal function. The total number of barrier jets found at each point along the coastal function was used to create the spatial distribution, which yields the percent of barrier jets found at each point versus the distance along the coastal function. As with the temporal distribution, the spatial distribution required scaling to account for nonuniform SAR spatial coverage. After scaling, the spatial distribution (Fig. 6) clearly shows a maximum in barrier jet occurrence between roughly −136° and −145°, or between Cross Sound and Prince William Sound. The data can also be broken down into seasonal distributions. While there are far fewer barrier jets in the April to August lull season, the shape of the distribution is similar to that in the September to March peak season (not shown).
A comparison of the total distribution in Fig. 6 to near-coast terrain height helps to qualitatively explain why certain areas are favored for barrier jet formation (Fig. 7). The main peak in the barrier jet distribution is found near the Valdez–Cordova mountains. The second largest peak in the distribution is adjacent to the near-coast mountains located in Glacier Bay National Park.
A terrain analysis was done along the entire coastal function to explore the relationship between the near-shore terrain height distribution and that of barrier jets. For each point on the coastal function that is within 50 km of land (points that lie near straits and large bays were not included because of their large distances from land), a line orthogonal to the function was directed inland, and the maximum and the average terrain heights were determined for segments extending inland up to 335 km.
Figure 8a shows the maximum terrain height distribution using the 100-km distance, along with the barrier jet distribution for comparison. The 100-km distribution is shown here because it corresponded more closely than the others with the barrier jet distribution. Linear correlations between the barrier jet spatial distribution and the maximum and average terrain height distributions for various distances inland are shown in Fig. 8b. The correlations increase with increasing distance inland until approximately 100 km, where they level off. Thus, it appears for this coastline that the most important terrain for barrier jet formation is found in the first 100 km inland. This suggests that terrain features on the order of 100 km inland or more are important in barrier jet formation. This result is consistent with the two-dimensional idealized experiments of Braun et al. (1999), which showed the strength of the barrier jet increases as the barrier width increases. The correlation between average terrain height and the barrier jet distribution mirrors that of the maximum terrain height in the first 100 km, suggesting that “profile topography” may be just as relevant to barrier jet formation in this region, at least for these jagged mountain ranges. At distances farther inland, the average terrain correlation with the barrier jet distribution levels off in a similar fashion to the maximum terrain profile, but at a slightly higher correlation. This result supports the conclusion by Braun et al. (1999) concerning the importance of the average terrain height. Both correlations plateau out for distances in excess of 100 km, perhaps as a result of the highest terrain being found in the first 100 km inland. This result has relevance to the choice of terrain formulation for medium-resolution numerical simulation of Alaskan barrier jets.
The slight shift to the left of the barrier jet distribution with respect to the terrain height distribution can be explained by flow-blocking theory. Onshore flow that is blocked by any of the high terrain peaks is able to accelerate down the synoptic pressure gradient to produce the barrier jets. Because of our criteria that the jet wind speed must be 1.5 times greater than the ambient flow, this leftward shift of barrier jet activity most likely reflects the distance that the blocked flow must travel before meeting our criteria.
In order for barrier jets to extend over the waters of the Gulf of Alaska, the terrain producing the barrier jet must impact the flow offshore. This requires that the radius of deformation (Lr) extend well offshore. Using a typical moist static stability for barrier jet cases of Nm = 1 × 10−2 s−1 (Nm from Fig. 13d in Part II), the distance that the radius of deformation extends offshore at each point along the coastal function was calculated by first calculating Lr and then subtracting the distance inland to the high terrain. The results (not shown) are nearly indistinguishable from Fig. 8, suggesting that the offshore extent of the radius of deformation is closely linked to the spatial distribution of overwater barrier jets. The maxima in the offshore distance very closely match the maxima in the observed barrier jet distribution. Therefore, the topography that impacts the flow the greatest distance offshore forces the most overwater barrier jets. Thus, in regions where the coastal plain is relatively wide barrier jets may not be wide enough to extend over the water and be observed by SAR. This may explain the rapid decrease in barrier jet activity to the south and east of point D in Fig. 1. South and east of point D, the coastal plain extends inland much farther than for areas north of point D. This may mean that many more jets may have existed to the south of point D but not extended over the water, and therefore are not included in our climatology.
4. Hybrid jet distributions
Temporal and spatial distributions of hybrid jets for the 5-yr study period were created using the same procedures described for the classic barrier jets including scaling to correct for unequal SAR coverage.
a. Temporal distribution
The hybrid temporal distribution shows that hybrid jet formation is much more likely during the peak (cool) season (Fig. 9). Very few hybrids were observed during June and July, while December produced the maximum number of hybrids. Considering that hybrid jets are defined above as originating from offshore-directed gap flow, it is not surprising that hybrids are more common during the cool season when the contrast between artic or polar anticyclones in the continental interior and lower pressure over the relatively warm offshore waters favors such flow. Moreover, the transition to the lull season is less abrupt for hybrid jets than for barrier jets extending into March and September. Additional evidence is provided by comparison of the mean sea level pressure fields for hybrid jet and classic barrier jet events (Fig. 10). The offshore-directed pressure gradient is higher for hybrid jet events than classic barrier jet events. Figure 10 also shows the mean sea level pressure field for both the April to August lull season and the September to March peak season. These composites demonstrate the existence a higher offshore-directed pressure gradient in the cool season. The large cross-barrier pressure gradient that gives rise to gap flow is more common in the cool season as a result of the large temperature difference between the cold interior and the relatively warm ocean. It follows then, that with a higher occurrence of gap flow, there is a higher likelihood that a hybrid jet will be formed. In addition, the blocking of any gap flow that is turned onshore may be enhanced during the cool season because the gap flow from the continental interior is typically much colder than the marine air it is displacing, leading to a much higher stability.
b. Spatial distribution
Figure 11a shows that the spatial distribution of hybrid jets has many more peaks than the spatial distribution of classic barrier jets (Fig. 6). More importantly, each distinct peak in the hybrid distribution is adjacent to a gap in the near-coast terrain. Figure 11a suggests that gap flows exiting Cross Sound, Yakutat Bay, and Icy Bay produce the most hybrids along the coast. The effectiveness of these gaps most likely results from their location immediately to the right of major mountains when viewed from offshore. For this configuration, gap flow that is turned onshore has a high likelihood of encountering terrain high enough to induce blocking. The starting points of the hybrids, which are defined as the locations where the flows exit the gap prior to hybrid jet formation, are shown in Fig. 11b. The same five gaps that are implicated in Fig. 11a are seen to indeed be the major hybrid producers, with Yakutat Bay being the most profligate. An SAR image that shows the major gaps highlighted in Fig. 11 is shown in Fig. 12.
5. Structural properties of barrier and hybrid jets
Knowing the typical properties of barrier and hybrid jets may be beneficial to the forecasters whose job is to warn the public of these often-dangerous windstorms. For this reason, characteristic values of barrier jet strength and width were calculated.
Perhaps the most important barrier jet property is its strength—most directly measured by the maximum wind speed. While it is true that the maximum wind speed estimates could suffer from the wind direction issues outlined in section 2 and must be viewed carefully, it is still useful to consider the maximum wind speed distribution for the barrier jets analyzed in this study. The distribution of the maximum wind speeds for all barrier and hybrid jet cases (Fig. 13) reveals that a large percentage (18% for barrier and 22% for hybrid) of jets exceed the SAR saturation threshold of 25 m s−1. The median strength of both barrier and hybrid jets is 20 m s−1, suggesting that half of the jets observed contained stronger than gale-force winds. For both barrier and hybrid jets, the monthly median jet strengths tend to be higher in the peak season (not shown). The number of jets with maximum wind speeds greater than 25 m s−1 is much larger in the peak season as well. In fact, 92% of all barrier jets stronger than 25 m s−1 occurred during the peak season. This result is consistent with the observed favored peak season speed and stability combinations discussed earlier.
The median width of the barrier jets (Fig. 14) was found to be around 50 km, where the width is measured as the distance from the base of the terrain to the outer edge of the barrier jet. The median width for hybrid jets was slightly larger (near 60 km), but very few hybrids were observed to have widths greater than 100 km while a slightly greater number of barrier jets did so. Additionally, some of the hybrid jets were observed to detach from the coast over part of their length, typically by about 10 km.
6. Conclusions
Synthetic aperture radar observations of the Gulf of Alaska provide numerous high-resolution mesoscale images of the near-shore surface wind field in the presence of complex three-dimensional coastal terrain. A collection of 3000 images from a 5-yr period of Radarsat observations was used to document the structure and climatology of one such mesoscale flow, coastal barrier jets. The subkilometer resolution of these SAR wind speed images allowed the observed barrier jets to be classified according to their structure and air mass of origin. Classic barrier jets resulting from onshore flow were of frequent occurrence, particularly adjacent to the highest coastal terrain. Likewise, hybrid jets exhibiting characteristics of both offshore gap flow and barrier jets were also frequently observed, generally to the west of major gaps in the coastal topography. The barrier jets could also be categorized by the sharpness of the wind speed discontinuity on their offshore side with shock jets having a near-zero-order discontinuity in contrast to the exponential decay predicted by simple theory. Both types were commonly observed. A fourth categorization results from the degree of variability in the wind speed within the barrier jet. While many barrier jets exhibit little variation in wind speed along their length, others are quite patchy, with the surface wind field being scalloped in a manner reminiscent of convective outflows. Part I of this paper focuses on the most basic categorization, into classic barrier jets and hybrid jets, while Part II documents the shock and variable jets.
Classic barrier jets in the Gulf of Alaska are more common in the cool season than the warm season. Wind directions favorable for barrier jet formation show a slight seasonal cycle with the favored wind directions occurring more often during the peak (cool) season. Combinations of barrier-normal wind speed and stability may favor numerous weak barrier jets during the warm season, and stronger jets during the cool season. The favored locations of barrier jet formation are associated with high terrain within 100 km of the coast, locations where the corresponding large radii of deformation extend out over the coastal waters. Of these sites, the Valdez–Cordova mountains, to the northwest of Yakutat, and Mount Fairweather near Glacier Bay National Park, make the most prominent contribution to the barrier jet climatology.
Hybrid jet formation is almost exclusively observed in the cool season and results from the much greater offshore-directed pressure gradients found in this season. Each distinct maximum in the hybrid spatial distribution is linked to a major gap in the coastal terrain. Thus, the spatial distribution of hybrid jets is linked to a limited number of sites where fjord-like gaps penetrate the coastal mountains: Cross Sound, Yakutat Bay, and Icy Bay.
Coastal barrier jet formation is associated with onshore flow, static stability (see Part II), and maximum terrain heights exceeding 2 km within 100 km of the coast, features that support enhanced near-shore pressure gradients via adiabatic cooling of upslope flow. Hybrid jet formation requires the additional condition of an abnormally large offshore-directed pressure gradient.
Many of the observed barrier jets and hybrid jets were quite strong with winds in excess of 25 m s−1 in approximately one-fifth of the cases. Most of the strongest events occurred in the period of peak event frequency, the cool season. Over half of the events of both types exhibited at least gale-force winds over a mesoscale area. These winds were typically a factor of 2 to 3 greater than those in the ambient synoptic flow, thus posing a significant forecasting challenge with considerable potential for impact on maritime and aviation interests. Classic barrier jets and hybrid jets exhibited rather similar widths, often extending 50 km from the base of the coastal mountains, but only occasionally extending past 100 km. Hybrid jets in particular were prone to detachment from the coast along portions of their length, with detachment distances of around 10 km being typical. Thus, the forecaster is faced with a significant weather phenomenon at or below the resolution limit of most operational numerical weather prediction models.
Both classic barrier jets and hybrid jets exhibit a broad range of locations, intensities, and widths. Likewise, their presence or absence depends on the vagaries of the synoptic situation. This dependence may contribute to the observed interannual variation in event frequency as well as contributing to the annual cycle of intensity and frequency.
Part II of this study includes a synoptic climatology of the conditions that favor barrier jet formation. The climatology includes analysis of the large-scale pressure and temperature patterns prior to and during barrier jet events as well as coastal sounding statistics of stability, moisture, and winds. Future work will relate the variability of these climatologies to the mesoscale structures observed in the SAR imagery. Finally, future work will also involve extension of the synoptic climatology to include frontal features and other thermodynamic features, numerical modeling of case studies, and analysis of aircraft observations from the fall 2004 SARJET experiment conducted near Cross Sound and Mount Fairweather will allow for a three-dimensional view of barrier jet structure and the dynamics of formation.
Acknowledgments
This research was funded by the National Science Foundation Grants ATM-0240869 (Winstead), ATM-0240269 (Young), and ATM-0240402 (Colle). We are also thankful for the satellite imagery provided by Bill Pichel and Karen Friedman of NOAA/NESDIS and the terrain map provided by Ray Sterner at Johns Hopkins APL, and for the constructive comments of all who reviewed this article.
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Topographical map of southern Alaska. The dashed line is the coastal fitting function created for use in computing the spatial distribution of barrier jets. Locations A, B, C, and D correspond to Kodiak Island, Prince William Sound, the Valdez–Cordova mountains to the northwest of Yakutat, and Mount Fairweather near Glacier Bay National Park, key features in the creation of many barrier jets and hybrid jets. The red square at 60°N, 142.5°W is the location of the NCEP reanalysis data point used for the analyses in section 3
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Topographical map of southern Alaska. The dashed line is the coastal fitting function created for use in computing the spatial distribution of barrier jets. Locations A, B, C, and D correspond to Kodiak Island, Prince William Sound, the Valdez–Cordova mountains to the northwest of Yakutat, and Mount Fairweather near Glacier Bay National Park, key features in the creation of many barrier jets and hybrid jets. The red square at 60°N, 142.5°W is the location of the NCEP reanalysis data point used for the analyses in section 3
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Topographical map of southern Alaska. The dashed line is the coastal fitting function created for use in computing the spatial distribution of barrier jets. Locations A, B, C, and D correspond to Kodiak Island, Prince William Sound, the Valdez–Cordova mountains to the northwest of Yakutat, and Mount Fairweather near Glacier Bay National Park, key features in the creation of many barrier jets and hybrid jets. The red square at 60°N, 142.5°W is the location of the NCEP reanalysis data point used for the analyses in section 3
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR-derived surface wind speed analysis of the following: (a) A classic barrier jet in Mar 2000. The shore-parallel band of red shading is the jet. (b) A lull season barrier jet. Notice the slower ambient flow and weaker barrier jet. Image is from May 1998. (c) A hybrid jet. Gap flow can be seen exiting the first gap from the right of the image and rapidly turning shore parallel. (d) Pure gap flow. Notice that the yellow streaks of enhanced wind speed are oriented perpendicular to the shore, indicating offshore-directed gap flow that is not turning coast parallel. (e) A shock barrier jet. Notice the large wind speed gradient on the outer edge of the barrier jet. (f) A variable jet. Notice the “lumpy” appearance of the jet hugging the coastline
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR-derived surface wind speed analysis of the following: (a) A classic barrier jet in Mar 2000. The shore-parallel band of red shading is the jet. (b) A lull season barrier jet. Notice the slower ambient flow and weaker barrier jet. Image is from May 1998. (c) A hybrid jet. Gap flow can be seen exiting the first gap from the right of the image and rapidly turning shore parallel. (d) Pure gap flow. Notice that the yellow streaks of enhanced wind speed are oriented perpendicular to the shore, indicating offshore-directed gap flow that is not turning coast parallel. (e) A shock barrier jet. Notice the large wind speed gradient on the outer edge of the barrier jet. (f) A variable jet. Notice the “lumpy” appearance of the jet hugging the coastline
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR-derived surface wind speed analysis of the following: (a) A classic barrier jet in Mar 2000. The shore-parallel band of red shading is the jet. (b) A lull season barrier jet. Notice the slower ambient flow and weaker barrier jet. Image is from May 1998. (c) A hybrid jet. Gap flow can be seen exiting the first gap from the right of the image and rapidly turning shore parallel. (d) Pure gap flow. Notice that the yellow streaks of enhanced wind speed are oriented perpendicular to the shore, indicating offshore-directed gap flow that is not turning coast parallel. (e) A shock barrier jet. Notice the large wind speed gradient on the outer edge of the barrier jet. (f) A variable jet. Notice the “lumpy” appearance of the jet hugging the coastline
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Results from the inversion of CMOD4 for a cross section corresponding to an 8 m s−1 wind blowing toward the radar. These calculations were for an incidence angle of 60°. Azimuth angles on the x axis are analogous to wind direction error since the assumed true wind direction is 0° relative to the radar look direction. The y axis shows the resulting wind speed after the inversion. The vertical error bars on the wind speed curve show the additional error introduced by a 2-dB error on the cross-section measurement. The maximum wind speed errors of a factor of 2 occur at azimuth angles of 90° and 270°, respectively (90° wind direction error)
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Results from the inversion of CMOD4 for a cross section corresponding to an 8 m s−1 wind blowing toward the radar. These calculations were for an incidence angle of 60°. Azimuth angles on the x axis are analogous to wind direction error since the assumed true wind direction is 0° relative to the radar look direction. The y axis shows the resulting wind speed after the inversion. The vertical error bars on the wind speed curve show the additional error introduced by a 2-dB error on the cross-section measurement. The maximum wind speed errors of a factor of 2 occur at azimuth angles of 90° and 270°, respectively (90° wind direction error)
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Results from the inversion of CMOD4 for a cross section corresponding to an 8 m s−1 wind blowing toward the radar. These calculations were for an incidence angle of 60°. Azimuth angles on the x axis are analogous to wind direction error since the assumed true wind direction is 0° relative to the radar look direction. The y axis shows the resulting wind speed after the inversion. The vertical error bars on the wind speed curve show the additional error introduced by a 2-dB error on the cross-section measurement. The maximum wind speed errors of a factor of 2 occur at azimuth angles of 90° and 270°, respectively (90° wind direction error)
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Temporal climatology of classic barrier jets in the Gulf of Alaska showing the percent of all classic barrier jet cases as a function of month averaged over the 5-yr study period. A warm season lull from Apr to Aug contrasts with a peak season running from Sep through Mar
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Temporal climatology of classic barrier jets in the Gulf of Alaska showing the percent of all classic barrier jet cases as a function of month averaged over the 5-yr study period. A warm season lull from Apr to Aug contrasts with a peak season running from Sep through Mar
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Temporal climatology of classic barrier jets in the Gulf of Alaska showing the percent of all classic barrier jet cases as a function of month averaged over the 5-yr study period. A warm season lull from Apr to Aug contrasts with a peak season running from Sep through Mar
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Seasonal scatterplots of barrier-normal wind speed and stability for only those observations with correct flow directions for classic jet formation. Thick dashed lines are representative Froude numbers derived using a crest level of 2000 m. This analysis was done at a single point (60°N, 142.5°W), shown in Fig. 1. Observations in the upper right of each box would correspond to settings where strong jets may be able to occur. These favorable settings are much more likely to occur during the peak season
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Seasonal scatterplots of barrier-normal wind speed and stability for only those observations with correct flow directions for classic jet formation. Thick dashed lines are representative Froude numbers derived using a crest level of 2000 m. This analysis was done at a single point (60°N, 142.5°W), shown in Fig. 1. Observations in the upper right of each box would correspond to settings where strong jets may be able to occur. These favorable settings are much more likely to occur during the peak season
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Seasonal scatterplots of barrier-normal wind speed and stability for only those observations with correct flow directions for classic jet formation. Thick dashed lines are representative Froude numbers derived using a crest level of 2000 m. This analysis was done at a single point (60°N, 142.5°W), shown in Fig. 1. Observations in the upper right of each box would correspond to settings where strong jets may be able to occur. These favorable settings are much more likely to occur during the peak season
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Spatial climatology of classic barrier jets shown as the percent of all such cases that were found at each location along the coastal function. The geographic locations listed can be seen on the map in Fig. 1
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Spatial climatology of classic barrier jets shown as the percent of all such cases that were found at each location along the coastal function. The geographic locations listed can be seen on the map in Fig. 1
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Spatial climatology of classic barrier jets shown as the percent of all such cases that were found at each location along the coastal function. The geographic locations listed can be seen on the map in Fig. 1
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR wind speed image showing the near-coast high terrain corresponding to the Valdez–Cordova mountains and Glacier Bay National Park. Notice that both terrain features are producing classic barrier jets at this time
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR wind speed image showing the near-coast high terrain corresponding to the Valdez–Cordova mountains and Glacier Bay National Park. Notice that both terrain features are producing classic barrier jets at this time
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR wind speed image showing the near-coast high terrain corresponding to the Valdez–Cordova mountains and Glacier Bay National Park. Notice that both terrain features are producing classic barrier jets at this time
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
(a) Comparison of the maximum terrain height found in the first 100 km inland from the coast to the barrier jet spatial distribution. (b) Linear correlations between the barrier jet spatial distribution and maximum terrain heights (solid line) and average terrain heights (dashed line) encountered by going various distances inland
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
(a) Comparison of the maximum terrain height found in the first 100 km inland from the coast to the barrier jet spatial distribution. (b) Linear correlations between the barrier jet spatial distribution and maximum terrain heights (solid line) and average terrain heights (dashed line) encountered by going various distances inland
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
(a) Comparison of the maximum terrain height found in the first 100 km inland from the coast to the barrier jet spatial distribution. (b) Linear correlations between the barrier jet spatial distribution and maximum terrain heights (solid line) and average terrain heights (dashed line) encountered by going various distances inland
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Percent of all hybrid jet cases that occurred during each month in the 5-yr study period
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Percent of all hybrid jet cases that occurred during each month in the 5-yr study period
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Percent of all hybrid jet cases that occurred during each month in the 5-yr study period
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Mean sea level pressure composites for the Gulf of Alaska for (a) all classic jet events, (b) all hybrid events, (c) lull season, and (d) peak season. The lull season composite includes all days (event and nonevent) from Apr through Aug while the peak season composite includes all days from Sep through Mar
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Mean sea level pressure composites for the Gulf of Alaska for (a) all classic jet events, (b) all hybrid events, (c) lull season, and (d) peak season. The lull season composite includes all days (event and nonevent) from Apr through Aug while the peak season composite includes all days from Sep through Mar
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Mean sea level pressure composites for the Gulf of Alaska for (a) all classic jet events, (b) all hybrid events, (c) lull season, and (d) peak season. The lull season composite includes all days (event and nonevent) from Apr through Aug while the peak season composite includes all days from Sep through Mar
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
(a) Spatial climatology of hybrid jets shown as the percent of all such cases found at each location along the coastal function. (b) The percent of all hybrid jets that started at a particular location
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
(a) Spatial climatology of hybrid jets shown as the percent of all such cases found at each location along the coastal function. (b) The percent of all hybrid jets that started at a particular location
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
(a) Spatial climatology of hybrid jets shown as the percent of all such cases found at each location along the coastal function. (b) The percent of all hybrid jets that started at a particular location
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR image showing the four major gaps associated with hybrid jet formation. Point A is the Copper River Delta, B is Icy Bay, C is Yakutat Bay, and D is Cross Sound
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR image showing the four major gaps associated with hybrid jet formation. Point A is the Copper River Delta, B is Icy Bay, C is Yakutat Bay, and D is Cross Sound
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
SAR image showing the four major gaps associated with hybrid jet formation. Point A is the Copper River Delta, B is Icy Bay, C is Yakutat Bay, and D is Cross Sound
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Maximum intensity climatology for classic barrier jets and hybrid jets. The horizontal axis is the maximum SAR-derived wind speed in 5 m s−1 bins
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Maximum intensity climatology for classic barrier jets and hybrid jets. The horizontal axis is the maximum SAR-derived wind speed in 5 m s−1 bins
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Maximum intensity climatology for classic barrier jets and hybrid jets. The horizontal axis is the maximum SAR-derived wind speed in 5 m s−1 bins
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Jet width climatology for classic barrier jets and hybrid jets. The horizontal axis is the SAR-derivedwidth in 20-km bins. The histogram includes both classic barrier jets in gray and hybrid jets in white
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Jet width climatology for classic barrier jets and hybrid jets. The horizontal axis is the SAR-derivedwidth in 20-km bins. The histogram includes both classic barrier jets in gray and hybrid jets in white
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
Jet width climatology for classic barrier jets and hybrid jets. The horizontal axis is the SAR-derivedwidth in 20-km bins. The histogram includes both classic barrier jets in gray and hybrid jets in white
Citation: Monthly Weather Review 134, 2; 10.1175/MWR3037.1
