Wind Regimes Associated with a Mountain Gap at the Northeastern

1 Wind regimes associated with a mountain gap at the

2 northeastern Adriatic coast

4 Danijel Belušić*, Mario Hrastinski, Željko Večenaj, Branko Grisogono

6 Danijel Belušić 7 Monash Weather and Climate 8 School of Mathematical Sciences 9 Monash University 10 Melbourne, Victoria, Australia 11 12 Mario Hrastinski 13 Croatian Meteorological and Hydrological Service 14 Zagreb, Croatia 15 16 Željko Večenaj and Branko Grisogono 17 Department of Geophysics 18 Faculty of Science 19 University of Zagreb 20 Zagreb, Croatia 21 22 *Corresponding author 23 Danijel Belušić 24 School of Mathematical Sciences 25 Building 28 26 Monash University 27 Clayton, Victoria 3800 28 Australia 29 E-mail: [email protected] 30

1 31 ABSTRACT

33 Winds through the Vratnik Pass, a mountain gap in the Dinaric Alps, Croatia, are

34 polarized along the gap axis that extends in the northeast-southwest direction.

35 Although stronger northeasterly wind at the Vratnik Pass is frequently related to

36 the Adriatic bora wind, especially at the downstream town of Senj, there are

37 many cases when wind at Senj is directionally decoupled from wind at the

38 Vratnik Pass. A cluster analysis reveals that this decoupling is sometimes related

39 to lower wind speeds or shallow southeasterly sirocco wind along the Adriatic,

40 but in many cases the bora blows over a wider region, while only Senj has

41 different wind direction. Several mechanisms can be responsible for the latter

42 phenomenon, including the formation of a lee wave rotor. A numerical model

43 simulation corroborates the decoupling caused by a rotor for a single case.

44 The prevalence of northeasterly winds at the Vratnik Pass during southeasterly

45 sirocco episodes is another result that challenges the current understanding. It is

46 shown that at least in one of the episodes, this phenomenon is related to a

47 secondary mesoscale low-pressure center in the eastern lee of the Apennines

48 that forms as a subsystem of a broader Genoa cyclone.

49 Less frequent southwesterly winds through the gap are predominantly related to

50 the thermal sea-breeze and anabatic circulations that are sometimes

51 superimposed on the geostrophic wind.

2 53 1. Introduction

55 Mean wind patterns over the Adriatic were described decades ago (e.g. Makjanić

56 1978), and classified into four main categories: northeasterly bora, southeasterly

57 Adriatic sirocco (jugo), northwesterly etesian and local thermal circulations (e.g.

58 Prtenjak and Grisogono 2007; Pasarić et al. 2009). Pandžić and Likso (2005)

59 used principal component analysis to classify wind observations along the entire

60 eastern Adriatic coast. Their analysis resulted in 11 wind types that could be

61 condensed into the same four categories as above with an additional near-calm

62 wind type. Local complexities of these flow patterns have been addressed only

63 recently, with the advance and accessibility of limited-area numerical models

64 (e.g. Pasarić et al. 2007; Grisogono and Belušić 2009; Klaić et al. 2009a; Prtenjak

65 and Belušić 2009; Prtenjak et al. 2010). Even more complex situations, with

66 weak to moderate synoptic pressure gradients that are modified by local thermal

67 circulations at the northern Adriatic coast, have been recently analysed using

68 measurements (e.g. Orlić et al. 1988; Prtenjak 2003; Prtenjak and Grisogono

69 2007) and numerical modeling (e.g. Nitis et al. 2005; Prtenjak et al. 2006; 2008).

70 A multitude of spatial flow patterns is possible under those conditions due to

71 variable wind direction and highly complex terrain.

73 The dominant wind at the northeastern Adriatic is bora – for example, bora

74 blows 177 days annually in the town of Senj (e.g. Yoshino 1976; Makjanić 1978;

75 see Fig. 1 for the location). Bora is most frequent in the cold part of the year

76 when persistent anticyclones over the northeastern Europe or cyclones over the

77 Adriatic and Mediterranean ensure the supply of cold continental northeasterly

3 78 air. Bora is a downslope windstorm whose basic characteristics follow the

79 hydraulic flow dynamics with supercritical regions in the mountain lee that are

80 dissipated in hydraulic jumps further downstream (Smith 1987). The upper flow

81 dividing streamline descends in the lee as a result of the presence of an inversion

82 just above the mountain top height or due to mountain wave breaking in the lee

83 (Klemp and Durran 1987). These mesoscale mechanisms generate large cross-

84 mountain pressure gradient and cause acceleration of wind such that the mean

85 speeds in the lee reach 30 m s-1 with gusts surpassing 60 m s-1 (e.g. Jiang and

86 Doyle 2005; Belušić and Klaić 2006; Gohm et al. 2008). The bora jets can extend

87 over the entire width of the Adriatic Sea and reach its western coast (e.g. Dorman

88 et al. 2006; Signell et al. 2010). Bora influences the coastal areas, sea state and

89 circulation, sea and land traffic, tourism and agriculture. It is associated with

90 several specific dynamical features, such as wave-induced rotors, quasi-periodic

91 pulsations of gusts, and potential vorticity banners. It has therefore attracted

92 considerable interest over the years, which has resulted in a large number of

93 studies (see the recent review by Grisogono and Belušić (2009) and references

94 therein).

96 The terrain complexity is evident along the Dinaric Alps, the mountain range that

97 extends along the eastern Adriatic coast separating it from the interior

98 continental region (Fig. 1). The Dinaric Alps have several gaps that influence the

99 spatial flow patterns, particularly during the bora wind (e.g. Grubišić 2004;

100 Belušić and Klaić 2006; Dorman et al. 2006; Gohm et al. 2008; Grisogono and

101 Belušić 2009; Signell et al. 2010). Despite their importance, little work has been

102 done on the examination of flow patterns through these mountain gaps,

4 103 especially over an extended period of time. This study presents the first wind

104 measurements at the Vratnik Pass (Fig. 1) that were collected over a period of

105 about nine months. The dataset length allows for classification of wind regimes

106 at the Vratnik Pass and the nearby coastal and island stations, which is

107 performed using a cluster analysis. Additionally, a preliminary data analysis has

108 indicated several unexpected flow characteristics, such as directional decoupling

109 between the Vratnik Pass and Senj during bora (Večenaj et al. 2011). These

110 situations are captured well by the current classification technique, which

111 enables a more general perspective on the synoptic and mesoscale conditions

112 that generate such situations.

113 The paper is organized as follows: Section 2 presents the data and main results

114 from basic data analysis, which reveals and quantifies some of the intricacies of

115 the local flow characteristics; Section 3 describes the cluster analysis technique;

116 Section 4 presents and discusses the results of clustering, relates them to

117 dominant synoptic conditions and undertakes numerical modeling to resolve the

118 flow complexities that seem unexpected without proper data; and Section 5

119 concludes the study, leaving several open questions for further research.

120

121

122 2. Data and basic analysis

123

124 The first wind measurements at the Vratnik Pass over an extended time period,

125 October 2004 – June 2005, provide a unique opportunity for analysis of wind

126 regimes through a mountain gap. The Vratnik Pass is a pronounced mountain

127 gap located in the northern part of the Dinaric Alps (Fig. 1). It is well known for

5 128 its relation to the bora wind, since it is located upstream of the town of Senj that

129 is famous for its very frequent and persistent bora cases (Poje 1992). The three

130 wind components were recorded at 9.5 m above ground using a Gill WindMaster

131 sonic anemometer with 4-Hz sampling frequency (Belušić and Klaić 2006).

132 Simultaneously, the same type of instrument was located in Senj at 13 m above

133 ground (Klaić et al. 2009b), which enables the analysis of the relationship

134 between the winds at the Vratnik Pass and Senj. The Senj sonic anemometer was

135 mounted on a 3-m mast on the roof of the 10-m tall Senj sea-port captaincy

136 building. It was installed in a location different to the standard Senj weather

137 station, because the standard station is sheltered from the bora wind directions

138 (Klaić et al. 2009b). There were several gaps in the measurements at the Vratnik

139 Pass, mostly shorter in duration except for the one that lasted from late March to

140 early May 2005. Since the measurements were not gathered in the period from

141 July to September, the situations with etesian winds, which appear during the

142 warm part of the year, will not be taken into account in the present analysis.

143

144 We use two additional stations in the local area to provide supplementary

145 information about the flow patterns. These two stations are taken as far away

146 from the coast as possible on an approximately northeast–southwest line

147 connecting them with the Vratnik Pass and Senj (Fig. 1). The reason for the latter

148 will become obvious below, while the distance from the coast is needed to relate

149 the flow patterns at the Vratnik Pass and Senj to the overall larger-scale wind

150 patterns over the northeastern Adriatic. Mali Lošinj is obviously most suited for

151 that geographically, but the limitation is that the anemometers in Mali Lošinj and

6 152 Rab are sheltered at the east and between northeast and south, respectively

153 (Croatian Meteorological and Hydrological Service, personal communication).

154

155 In the following, the terms ‘bora’ and ‘northeasterly wind’ will sometimes be

156 used interchangeably for convenience, disregarding the fact that northeasterly

157 wind is a broader category because some of the northeasterly winds are of

158 thermal origin, unlike the currently accepted dynamical origin of bora (see

159 Grisogono and Belušić 2009). The wind roses for the two main stations, the

160 Vratnik Pass and Senj, are depicted in Fig. 2. Winds at the Vratnik Pass are

161 markedly bimodal and can be classified into northeasterly bora with directions

162 from 30 – 90°, and southwesterly winds with directions ranging from 210 –

163 270°. This polarization is a natural consequence of the geographical orientation

164 of the pass. However, the relationship of these two wind regimes at the Vratnik

165 Pass to the known wind patterns at the coast is not known, and this is examined

166 in the remainder of the paper.

167

168 The wind rose at Senj shows the known predominance of the bora wind for

169 higher wind speeds. However, weak winds are dominantly from the southeast,

170 which indicates that Senj and the Vratnik Pass are directionally decoupled for

171 low wind speeds. Conditional wind roses at Senj shown in Fig. 3 provide

172 additional insight into the level of decoupling. For weak winds at the Vratnik

173 Pass, Senj and the Vratnik Pass are decoupled regardless of the wind direction.

174 Similarly, for southwesterly winds at the Vratnik Pass, Senj and the Vratnik Pass

175 are predominantly decoupled regardless of the wind speed. It is therefore

176 obvious that the coupling between Senj and the Vratnik Pass is associated

7 177 predominantly with strong northeasterly winds, and Fig. 3 shows that the

178 stronger the bora at the Vratnik Pass, the stronger the coupling between Senj

179 and the Vratnik Pass. The coupling starts when wind speed at the Vratnik Pass

180 surpasses 5 m s-1.

181

182 It has been almost tacitly assumed in previous studies that northeasterly winds

183 at Senj and the Vratnik Pass are always coupled, particularly because the bora in

184 Senj is such a predominant wind and is clearly related to the air arriving from the

185 Vratnik Pass. The unexpected result here is that there are situations with weak,

186 moderate and sometimes even strong bora at the Vratnik Pass when Senj does

187 not experience bora at all (Fig. 3b, c). We will refer to these situations as

188 decoupled bora cases.

189

190 Figure 4 depicts different possibilities of the bora occurrence simultaneously at

191 the Vratnik Pass and Senj. The bora occurrence is based on wind direction only,

192 and is defined for both stations as wind blowing continuously during at least 3 h

193 from directions between 30° and 90°. This enforces a rather strict condition on

194 the bora occurrence, but on the other hand does not allow random wind

195 direction variability to be counted as a bora occurrence. Table 1 explains the

196 detector values used in Fig. 4. The detector value of two, indicating the bora

197 occurrence at the Vratnik Pass but not at Senj, i.e. the decoupled situations,

198 appears throughout the observational period. It should be noted that this

199 definition of a bora occurrence means that a decoupled episode can occur even

200 when wind at Senj is between 30° and 90° but lasts less than 3 h. A number of

201 cases with weak-to-moderate wind will naturally enter the latter category, but

8 202 will not be given special consideration here. Understanding the structure and

203 mechanisms of the other decoupled situations is the primary motivation for

204 further analysis.

205

206

207 3. Clustering method

208

209 In order to gain better understanding of the local spatial wind patterns, the

210 winds at the four chosen stations are classified using the K-means clustering

211 method (e.g. Anderberg 1973). This method has been used in many different

212 meteorological contexts, such as for clustering of mesoscale convective systems

213 (e.g. Pope et al. 2009), hurricane tracks (e.g. Elsner 2003) and mesoscale wind

214 fields (e.g. Kaufmann and Weber 1996).

215

216 We use the standard Matlab K-means algorithm with squared Euclidian distance

217 between vectors at each observation location as the measure of similarity. Some

218 authors have suggested using wind vectors scaled by time or space averaged

219 winds, in order to reduce the overweighting of stations with higher wind speeds

220 or to remove the effects of overall scaling factors for otherwise similar spatial

221 wind patterns, respectively (e.g. Weber and Kaufmann 1995; Kaufmann and

222 Whiteman 1999; Burlando et al. 2008; Jiménez et al. 2009). We do neither for a

223 number of reasons. First of all, the Vratnik Pass is characterized by higher wind

224 speeds compared to the other stations. Since we are primarily interested in

225 detailed wind regimes through the Vratnik Pass and only secondary about other

226 stations, this natural overweighting of the Vratink Pass assists the analysis.

9 227 Second, it will be shown later that in our case the differences between clusters

228 that result only from overall scaling factors may point to different physical

229 origins of similar wind patterns. Third, we use only four stations that are located

230 in the region with already known larger-scale wind patterns (Prtenjak 2003;

231 Pandžić and Likso 2005). This makes our analysis and decision-making simpler.

232

233 The latter also means that it is straightforward to visually determine the optimal

234 number of clusters. The cluster analysis was performed with number of clusters

235 increasing from two to ten and the resulting clusters were examined visually for

236 substantial differences. Eight clusters still brought important new information

237 compared to seven clusters, while increasing the number of clusters beyond

238 eight resulted only in splitting of certain clusters to two almost identical wind

239 regimes. Hence we chose eight as the optimal number of clusters in our analysis.

240

241 The reliability of the method is tested by re-running the algorithm several times.

242 Initial cluster centroids are randomly chosen and they always converge to the

243 same final clusters when the number of clusters is eight, which additionally

244 supports this choice for the number of clusters (e.g. Pope et al. 2009). Further

245 evidence of the robustness of clustering results is given in the next section.

246

247

248 4. Results

249

250 a. Cluster analysis

251

10 252 The eight cluster centroids are shown in Fig. 5. They are consistent with the

253 results from a larger-scale classification (Pandžić and Likso 2005). There are

254 only two clusters with southwesterly flow at the Vratnik Pass (clusters 1 and 6),

255 while all the others are dominated by the northeasterly flow. The two clusters

256 with southwesterly wind account for about 29% of the total number of cases.

257 This agrees with the wind rose at the Vratnik Pass, which shows about 30% of

258 cases with southwesterly winds (Fig. 2).

259

260 Further analysis reveals that the most distant members of individual clusters are

261 mostly very similar to their cluster centroids both in magnitude and direction of

262 the wind vector at all stations. Larger differences of the most distant members

263 may occur in wind direction only for clusters and stations with weak winds, such

264 as clusters 1 and 3, and the station Senj in cluster 7. This implies that the clusters

265 are consistent and can be used for mapping the characteristic wind patterns.

266

267 It is possible that some of the clusters represent only transitional features with

268 short duration. Several different tests of duration and consistence of episodes

269 were performed and they agree that all clusters are predominantly composed of

270 well-defined episodes. Average durations of uninterrupted episodes within each

271 cluster are given in Table 2. Clusters 1, 2, 5 and 6 are characterized by on

272 average longer episodes than the other four clusters. This is somewhat

273 unexpected for clusters 2 and 5, because they are predominantly separated by

274 small to moderate differences only in the overall wind speed, i.e. the scaling

275 factor, and not in the direction. One would, therefore, expect numerous

11 276 transitions between clusters 2 and 5 during a single bora episode – yet,

277 continuous episodes longer that 24 h are not rare for each of the two clusters.

278

279 Likewise, the time series of cluster categories shows that successive point-to-

280 point transitions are the most frequent between the same cluster categories and

281 account for about 90% of transitions for clusters 1, 2, 5 and 6, and about 80% of

282 transitions for the other four clusters. The most frequent remaining transitions

283 between different clusters are shown in Table 2 for each cluster category. The

284 latter illustrates typical time evolutions of different flow configurations. For

285 example, the transitions confirm that the strongest bora, cluster 5, is simply a

286 stronger-wind version of cluster 2, as almost all transitions to and from cluster 5

287 occur exclusively through cluster 2. Similarly, for southwesterly winds at the

288 Vratnik Pass, the stronger-wind cluster 6 is reached and left predominantly

289 through the weaker-wind southwesterly cluster 1. An even broader picture is

290 revealed when all clusters with northeasterly winds at the Vratnik Pass and Senj

291 are considered: clusters 3, 4, 2 and 5 form a progression of increasing

292 northeasterly winds at both stations. Their interrelationships are also evident

293 from the transitions: the weakest bora in cluster 3 can transition to either

294 somewhat stronger bora in cluster 4, or, as expected for weak-wind cases,

295 change direction and transition to the weakest southwesterly cluster 1. The

296 moderate bora cluster 4 can go both ways, increasing (cluster 2) or decreasing

297 wind speed (cluster 3), but not changing the wind direction at the Vratnik Pass

298 and Senj. It can also move to cluster 7, which has strong northeasterly winds at

299 the Vratnik Pass and moderate northeasterly winds at the two outer stations, but

300 very weak winds at Senj when compared with the other four northeasterly

12 301 clusters. This is a somewhat different flow setup and will be discussed

302 separately. Finally, cluster 2 has two-way transitions with the weaker cluster 4

303 and, as mentioned before, the strongest cluster 5.

304

305 Cluster 8 represents the airflow pattern associated with the Adriatic sirocco

306 wind (e.g. Jurčec et al. 1996; Brzović and Strelec Mahović 1999). The Adriatic

307 sirocco frequently develops when a cyclone is located northwest of the Adriatic

308 Sea and, assisted by the Dinaric Alps, forces the air to move along the Adriatic

309 Sea from the southeast. As the cyclone propagates towards the southeast, the

310 sirocco over the northern Adriatic gradually transforms to the northeasterly

311 bora wind (e.g. Horvath et al. 2008; Pasarić et al. 2009). This is evident from the

312 cluster transitions, where cluster 8 frequently moves to the weakest bora cluster

313 3, which can later result in strong bora through the aforementioned progression.

314 It also transitions to the weakest southwesterly cluster 1, probably denoting the

315 cessation of main synoptic forcing over the domain of interest. On the other

316 hand, Table 2 indicates that neither of the other clusters frequently transition to

317 cluster 8, but this is due to its rare occurrence of only 3.5% of all cases. It can be

318 shown that the transitions for cluster 8 are two-way, so the relative majority of

319 transitions to cluster 8 come from clusters 1 and 3.

320

321 While different bora scenarios at the Northern Adriatic coast are relatively well

322 known from a multitude of previous studies (e.g. Grubišić 2004; Gohm and Mayr

323 2005; Belušić and Klaić 2006; Večenaj et al. 2010; 2012), the situations with

324 sirocco or weak winds have received much less attention. Vukičević et al. (2005)

325 present an analysis of the Adriatic sirocco flow on 26 December 2004 and show

13 326 that the sirocco is a rather shallow phenomenon with low-level mountain-

327 influenced southeasterly winds turning towards the synoptic southwesterly to

328 westerly flow at heights above 1 km. This agrees with Ivančan-Picek et al.

329 (2006), who extend the analysis to a few other sirocco cases and explain that the

330 predominant sirocco synoptic flow is from the southwest as a result of deep

331 cyclones approaching from the Atlantic to the western Mediterranean. While

332 bora onset is abrupt, sirocco begins and strengthens gradually. On the mesoscale,

333 firstly due to the Dinaric Alps stretching southeast – northwest, the mean wind

334 turns from southwesterly aloft to southeasterly in the boundary layer. Secondly,

335 easterly ageostrophic wind component toward the low pressure approaching

336 from the west develops by the usual wind turning in the boundary layer. Due to

337 these and some other characteristics of sirocco in the Adriatic, Ivančan-Picek et

338 al. (2006) insist that this wind should have a local name "jugo". They also find

339 that it usually does not extend over 2 km in depth; hence, this southeasterly flow

340 often cannot make it over the coastal mountains. The sirocco pattern of cluster 8

341 therefore seems to contradict the expectations based on the current knowledge.

342 While the southeasterly winds at the outer two stations are the obvious sign of

343 sirocco, and the easterly wind at Senj could be explained by the topographic

344 shadowing effects of the station used in this study, the clearly northeasterly wind

345 at the elevated Vratnik Pass is puzzling because it seems to oppose the

346 associated southwesterly geostrophic wind. In order to examine this seeming

347 contradiction, we study the situation from 26 – 28 December 2004 in more detail

348 in a later subsection using a numerical model.

349

14 350 Of particular interest here is the previously raised issue about the directional

351 decoupling between the Vratnik Pass and Senj for northeasterly winds at the

352 Vratnik Pass. Figure 6 shows that these cases are predominantly related to low-

353 to-moderate wind speed clusters (3 and 4), to the sirocco cluster 8, or to the

354 rather special bora cluster 7. Weak winds are characterized by large directional

355 variability (e.g. Belušić and Güttler 2010; Mahrt 2011) and weak vertical

356 coupling (e.g. Mahrt 2010). For clusters 3 and 4, this naturally results in sporadic

357 occurrences of directional decoupling between the Vratnik Pass and Senj, and

358 also in sporadic couplings that last less than 3 h and are not considered to be

359 coupled cases (see Section 2). The occurrence of northeasterly wind at the

360 Vratnik Pass is rather unexpected for the sirocco episodes in cluster 8 and, as

361 already mentioned, this will be further analyzed later. However, even at this

362 point it is easy to understand that with predominantly southeasterly winds over

363 the Adriatic and northeasterly winds at the Vratnik Pass, the direction at Senj can

364 shift between the two directions following probably only small changes of the

365 overall flow pattern. As for cluster 7, a very interesting result is that the

366 decoupled bora cases account for about 87% of its cases (Fig. 6). This makes

367 cluster 7 a representative of these situations. The cluster 7 centroid has

368 northeasterly wind at all stations, but the difference to the usual bora cases is

369 that the wind magnitude at Senj is considerably smaller than at the Vratnik Pass.

370 Inspection of individual cluster members shows that the wind at Senj is highly

371 variable between different members and predominantly weak, so that a few

372 relatively strong northeasterly bora cases dominate the average and result in the

373 cluster centroid.

374

15 375 Independently of this analysis, Večenaj et al. (2011) discuss a possible lee rotor

376 formation with reversed winds at Senj between 0000 and 1200 UTC 5 February

377 2005. The current analysis shows that this exact period belongs to cluster 7, and

378 is immersed within a strong bora episode of cluster 2. The rotors over the

379 eastern Adriatic have been reported in a number of studies (Belušić et al. 2007;

380 Grubišić and Orlić 2007; Gohm et al. 2008; Prtenjak and Belušić 2009; Stiperski

381 et al. 2012), but no systematic knowledge exists about their characteristics and

382 locations. Presently, the only way to verify the hypothesis that a lee rotor

383 formation is responsible for the flow behavior at Senj is to reproduce the

384 situation with a numerical model. This is discussed in a later subsection.

385

386 b. Synoptic situation

387

388 Figure 7 depicts the mean surface synoptic situation obtained from the ERA-

389 Interim reanalysis (Dee et al. 2011) for each cluster. Clusters 1 and 3 are both

390 characterized by weak pressure gradients over the northeastern Adriatic, which

391 favor the development of local mesoscale thermal circulations with low wind

392 speeds, such as the sea/land breeze and katabatic/anabatic winds (e.g. Prtenjak

393 et al. 2006; 2010). Weak synoptic-scale pressure gradient force from the

394 southwest to northeast in cluster 1 might cause pressure-driven channeling (e.g.

395 Carrera et al. 2009) through the Vratnik Pass and hence contribute to the

396 southwesterly wind. However, cluster 1 most frequently occurs in the afternoon

397 hours (not shown), indicating that a large percentage of its cases are related to

398 mesoscale thermal circulations. MSLP for cluster 8 depicts the typical pattern

16 399 related to the Adriatic sirocco, with the cyclone northwest of the region of

400 interest (e.g. Jurčec et al. 1996; Pasarić et al. 2009).

401

402 The flow pattern in cluster 6 is most frequently a consequence of an early stage

403 of the Genoa cyclone. It is more frequent in the afternoon hours than during the

404 night (not shown). It thus appears that the alignment of the geostrophic wind

405 with the afternoon thermal sea-breeze and anabatic circulations, together with

406 the related channeling, results in strong southwesterly winds at the Vratnik Pass.

407 The decoupling of winds at Rab from the southwesterly direction seen at all

408 other stations in cluster 6 is evident also in the results of Pandžić and Likso

409 (2005) for a similar wind pattern (their wind type 8). The exact reasons for this

410 departure are not known, but it is probably related to the complexity of the

411 coastal terrain (e.g. Nitis et al. 2005; Prtenjak et al. 2006). Inspection of the

412 individual cluster members supports the latter: when the winds at Rab and Mali

413 Lošinj are weak to moderate, which is most frequently the case in cluster 6, the

414 wind pattern is very similar to the cluster centroid. However, when the surface

415 wind speeds become higher, the wind direction at Rab aligns with the other

416 stations and becomes southwesterly, implying that the synoptic flow overcomes

417 the local effects.

418

419 Bora clusters (2, 4 and 5) are characterized by the typical northeasterly pressure

420 gradient over the Dinaric Alps. The usual distinction between the cyclonic and

421 anticyclonic bora (e.g. Jurčec 1981; Heimann 2001) is evident here too. Cluster 5

422 is the representative of the cyclonic bora, with the main generating factor being

423 the Genoa cyclone that propagates along the Apennine peninsula towards the

17 424 southeast. Cluster 2 represents the anticyclonic bora where the high-pressure

425 center located northeast of the Adriatic ensures the supply of cold air impinging

426 on the Dinaric Alps as the northeasterly wind. Cluster 4 is characterized by the

427 weakest pressure gradients among the three bora clusters and individual charts

428 show that it is predominantly the anticyclonic bora type, but that it can also be

429 related to a cyclone (not shown).

430

431 The decoupled cases in the special bora cluster 7 are probably local phenomena,

432 so synoptic charts do not provide much insight into their dynamics. The basic

433 synoptic structure seems to be a mixture of an anticyclone affecting the northern

434 Adriatic bora and a cyclone above the northeastern Mediterranean affecting the

435 southern Adriatic bora.

436

437 c. Numerical simulations

438

439 The focus for numerical simulations is on the two puzzling clusters: cluster 7 for

440 bora and cluster 8 for sirocco. Both were discussed above and here we report on

441 the results of simulations of several cases from these two clusters. The Weather

442 Research and Forecasting – Advanced Research WRF (WRF-ARW) model,

443 version 3.3 (Skamarock et al. 2008) is used for this purpose. Initial and boundary

444 conditions are obtained from the ERA-Interim reanalysis, available every 6 h.

445 The setup consists of a number of nested domains with the outermost domain’s

446 grid spacing of 27 km being decreased by the factor of 3 for each nested domain.

447 Two simulations are presented here: the grid spacing of the innermost domain is

448 1 km for the first and 1/3 km for the second simulation. Two-way nesting is used

18 449 for the first and one-way for the second simulation. All domains are centered on

450 the present region of interest (the locations of domains are shown in the figures

451 below). There are 51 vertical levels, with the layer depths gradually increasing

452 with height. Vertical mixing is parameterized using the Mellor-Yamada-Janjić

453 scheme (Janjić 2002).

454

455 One of the questions raised above is about the origin of the unexpected

456 northeasterly wind at the Vratnik Pass during the sirocco episodes of cluster 8.

457 Figure 8 compares the measurements at the Vratnik Pass with the ERA-Interim

458 reanalysis at the point closest to the Vratnik Pass for the long sirocco episode

459 from 26 December – 28 December 2004. The ERA-Interim wind is persistently

460 from the south until the end of the sirocco episode on 28 December 2004.

461 Therefore, the common expectation for this case would be a persistent

462 southwesterly wind at the Vratnik Pass, because one could assume that a

463 synoptically southerly wind would be locally channeled through the gap as a

464 southwesterly wind (e.g. Gaberšek and Durran 2006). However, the wind in the

465 measurements is most frequently from the northeast with only shorter

466 excursions to south and southwest. A similar disagreement between the

467 measurements and reanalyses has been noticed for a number of other episodes

468 as well. In order to study the cause of this discrepancy, a WRF simulation was

469 run from 1200 UTC 26 December – 1200 UTC 28 December 2004. Figure 8

470 shows the comparison of wind directions between the WRF simulation and the

471 measurements. Wind speeds are reproduced reasonably well by the model, but

472 are not shown because they are not as relevant for this analysis. The two outer

473 stations, Rab and Mali Lošinj, clearly indicate the existence of sirocco over the

19 474 northern Adriatic and this is well reproduced by the model. The Vratnik Pass

475 wind direction is simulated rather well after 00 UTC 27 December 2004. While

476 the measured wind at Senj is predominantly from the southeast, the modeled

477 direction at Senj is closely coupled with the modeled direction at the Vratnik

478 Pass, particularly for larger changes of direction, and hence does not

479 satisfactorily reproduce the local wind at Senj. This erroneous coupling between

480 the Vratnik Pass and Senj winds is a common characteristic of many other model

481 simulations performed for this study, regardless of the episode or the changes in

482 the model setup. These unsuccessful simulations will not be reported here.

483

484 Since the modeled direction at the Vratnik Pass is satisfactory, we use the model

485 for further analysis. Two different situations are compared. The surface fields

486 from the ERA-Interim reanalysis and the WRF simulation at the two coarsest

487 grids are shown in Fig. 9 at:

488 (i) 00 UTC 27 December, when ERA-Interim and WRF, and to a certain extent the

489 measurements, agree that the wind at the Vratnik Pass is southerly, and

490 (ii) 06 UTC 27 December, when the measurements and WRF switch to

491 northeasterly flow while ERA-Interim continues to experience the southerly

492 flow.

493 The ERA-Interim spatial pattern does not change much between these two

494 situations. The Genoa cyclone is shown to be the main generator of sirocco over

495 the Adriatic and the southerly wind at the Vratnik Pass. The outermost WRF

496 domain shows good broad agreement with the reanalysis for both situations. The

497 major discrepancy is seen at 06 UTC, when a relatively small closed low-pressure

498 center appears at the west Adriatic coast in the lee of the Apennines only in the

20 499 WRF simulation. The first nested domain with 9-km grid spacing provides more

500 detailed view of the formation of the Adriatic low. It somewhat resembles the

501 twin cyclone formation reported by Horvath et al. (2008), although here the

502 Adriatic low is on a smaller spatial scale. This low bends the isobars over the

503 northern Adriatic and as a result, the wind along the entire northeastern Adriatic

504 turns to easterly and northeasterly direction while the wind further inland

505 becomes easterly to southeasterly. It is this mesoscale wind pattern that forces

506 the channeling of northeasterly wind through the Vratnik Pass. Further details of

507 the flow channeling through the Vratnik Pass are seen from the two domains

508 with smaller grid spacing, but they do not reveal relevant new information and

509 are hence not shown. A similar synoptic situation, but with a more expressed

510 Adriatic low, is seen in the hours following the observed southwesterly flow

511 episode at the Vratnik Pass, thus after 20 UTC 27 December, and before the

512 cessation of sirocco on 28 December. The quick formation and disappearance of

513 the low at 00 UTC 27 December indicates that these secondary lows are transient

514 features. The role of orography in their formation might be partially explained by

515 the mechanisms suggested by Lin (2007), but the detailed analysis of these

516 processes is beyond the scope of this study.

517

518 Another simulation was performed for the cluster-7 episode of 5 February 2005,

519 in order to examine a possible rotor occurrence at Senj (Večenaj et al. 2011) as

520 one of the mechanisms leading to the directional decoupling between the Vratnik

521 Pass and Senj. Figure 10 shows that the model correctly captures the onset and

522 the first few hours of flow reversal at Senj, and that the reversal lasts longer for

523 the domain with smaller grid spacing. It should be mentioned that this

21 524 simulation is the only one that successfully reproduced the Vratnik Pass–Senj

525 decoupling, and this was achieved only after changing the nesting procedure

526 from two-way to one-way. This indicates the high sensitivity of these flow

527 features to details of the model setup, which is in accordance with the

528 conclusions of Gohm et al. (2008). Figure 11 depicts an example of the flow

529 structure during the flow reversal for the innermost domain. There are several

530 disconnected regions of reversed flow just downstream of the mountains that

531 sometimes cover the coastal areas and extend over the sea. These features are

532 highly variable in appearance, extent and duration. The vertical cross-section

533 indicates the existence of a rotor circulation above Senj. The rotor occurs under

534 an undular bore located downstream and below a wave-breaking region, which

535 agrees well with previous studies on rotor dynamics (e.g. Jiang et al. 2007; Smith

536 and Skyllingstad 2009; Stiperski et al. 2012). These results confirm that some of

537 the decoupled situations arise from local rotor circulations. A detailed analysis of

538 this case is left for a separate study.

539

540 5. Conclusions

541

542 First wind measurements over an extended time period at the Vratnik Pass, a

543 mountain gap in the Dinaric Alps, were performed from October 2004 – June

544 2005. Wind roses and cluster analysis reveal that the winds through the Vratnik

545 Pass are highly polarized and come from the two main directions that are

546 parallel to the axis of the gap. These flow patterns depend on the synoptic-scale

547 forcing, but the resulting gap flow is governed by the mesoscale pressure

548 gradient, in accordance with the results of Gaberšek and Durran (2006).

22 549

550 Quite expectedly, moderate to strong northeasterly wind is more frequent and is

551 usually, but not always, related to the northeasterly bora wind at the

552 downstream town of Senj. An unforeseen result is a large number of cases with

553 northeasterly winds at the Vratnik Pass that are decoupled from the winds at

554 Senj. While some of these cases are related to low wind speeds or a shallow

555 southeasterly Adriatic sirocco flow, there are a considerable number of other

556 cases that could not be explained easily. Even the clustering method has grouped

557 the latter cases into a separate cluster. The WRF-ARW model was able to

558 reproduce only one case of the directional decoupling, which was related to a

559 mountain-lee rotor.

560

561 Another unexpected result that disagrees with the previous limited knowledge is

562 the predominance of northeasterly wind at the Vratnik Pass during the Adriatic

563 sirocco episodes. Using a successful WRF-ARW simulation of one such episode,

564 this discrepancy is shown to be a consequence of a mesoscale low-pressure

565 center developing over the Adriatic and is apparently unrelated to the local

566 terrain surrounding the Vratnik Pass.

567

568 Southwesterly wind at the Vratnik Pass is less frequent and is largely related to

569 situations with very weak synoptic pressure gradient when weak mesoscale see-

570 breeze and anabatic circulations dominate (e.g. Prtenjak 2003). Stronger

571 southwesterly wind at the Vratnik Pass appears when this weak circulation is

572 superimposed on a geostrophic wind in the same direction. An additional

573 mechanism for the latter could be the generation of a large mountain wave with

23 574 a strong southeasterly wind in the lee. These flow conditions have not been

575 studied previously, so further analysis is needed for understanding of the exact

576 mechanisms.

577

578 Several interesting dynamical and modeling problems emerge from this study.

579 The model difficulty to reproduce the directional bora decoupling between the

580 Vratnik Pass and Senj is an important challenge for the modeling community.

581 Simulations with different model setups indicate that the model is able to

582 reproduce the decoupling only for a specific constellation of input parameters,

583 which in one case amounted to using one-way instead of two-way nesting. The

584 decoupling is also an interesting dynamical issue, since lee rotors have been

585 reported in many occasions over the Adriatic, but their frequencies, locations

586 and mechanisms are generally not known. The appearance of a relatively small-

587 scale closed low-pressure center over the Adriatic in the lee of the Apennines

588 that is associated with the Genoa cyclone calls for further analysis in order to

589 understand the mechanisms that generate such systems. It is not known how

590 many cases from cluster 8 are related to those systems, but the predominance of

591 northeasterly winds at the Vratnik Pass in cluster 8 indicates that these might be

592 more than rare events. Two features worthy of further investigation emerge also

593 in cluster 6: strong southwesterly winds at the Vratnik Pass in otherwise weak-

594 wind flow that could be related to mountain-wave dynamics, and the strange 90°

595 departure of wind direction at Rab that was only hypothetically related to the

596 influence of the local terrain.

597

598 Acknowledgments

24 599 We thank Vlatko Vukičević for useful discussions about the Adriatic sirocco wind

600 and Maja Telišman Prtenjak for providing the information about the wind

601 sheltering at the measurement stations Rab and Mali Lošinj. Three anonymous

602 reviewers are gratefully acknowledged for their constructive comments and

603 suggestions. The Croatian Meteorological and Hydrological Service kindly

604 provided the data at Rab and Mali Lošinj. The work was partially supported by

605 the Croatian Ministry of Science, Education and Sports (projects BORA 119-

606 1193086-1311 and AQCT 119-1193086-1323) and the Croatian Science

607 Foundation (project CATURBO 09/151).

608

609

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748

749

31 750 TABLES

751

752

753

754 Table 1. A contingency table for the simultaneous occurrence of Bora at the

755 Vratnik Pass (VP) and Senj. Each event at each site has a numerical value

756 assigned to it (in brackets). Different combinations of events observed

757 simultaneously at both sites result in different detector values in the table (see

758 Fig. 4). NaN denotes a data gap.

Senj Bora YES (1) Bora NO (0) NaN (-0.25)

Bora YES (2) 3 2 1.75

Bora NO (0) 1 0 -0.25

NaN (-0.75) 0.25 -0.75 -1

759

760

761

32 762

763

764

765 Table 2. Number (N) and percentage of cases, and the average episode duration

766 (T) for each cluster. Trans denotes other cluster categories that each cluster

767 most frequently transitions to.

Cluster 1 2 3 4 5 6 7 8

N 810 711 689 615 278 273 224 130

[%] 21.7 19.1 18.5 16.5 7.5 7.3 6.0 3.5

T (h) 8.4 8.3 5.2 5.2 9.6 10.5 5.2 5.7

Trans 3, 6 4, 5 1, 4 2, 3, 7 2 1 4, 3, 2 3, 1

768

769

33 770 FIGURE CAPTIONS

771

772 Figure 1. Topography of the northeastern Adriatic region. The four

773 observational stations are indicated: Vratnik Pass (44.979°N, 14.984°E, 698 m

774 above MSL), Senj (44.990°N, 14.899°E, 2 m above MSL), Rab (44.750°N,

775 14.767°E, 24 m above MSL), and Mali Lošinj (44.533°N, 14.467°E, 53 m above

776 MSL). The inset in the upper right corner shows the detailed topography around

777 the Vratnik Pass (contour interval is 75 m).

778

779 Figure 2. Wind roses at (a) the Vratnik Pass, (b) Senj, (c) Rab and (d) Mali Lošinj

780 for the period from October 2004 to June 2005.

781

782 Figure 3. Conditional wind roses at Senj during October 2004 – June 2005 for

783 six different wind speed and direction combinations at the Vratnik Pass. Headers

784 at each subplot denote criteria at the Vratnik Pass for which conditional wind

785 rose at Senj was calculated: (a), (b) and (c) for northeasterly bora direction; (d),

786 (e) and (f) for southwesterly direction; (a) and (d) for weak winds, (b) and (e)

787 for moderate winds, (c) and (f) for strong winds at the Vratnik Pass. The

788 remaining cases (2%) are predominantly related to weak winds at the Vratnik

789 Pass from directions other than bora and southwesterly.

790

791 Figure 4. Detection of the simultaneous bora occurrence at the Vratnik Pass and

792 Senj. The detector value of 2 denotes the decoupled episodes that occur when

793 bora blows at the Vratnik Pass but not at Senj. The values 3 and 0 stand for the

34 794 bora presence and absence at both stations, respectively. See Table 1 for the

795 complete description of the detector values.

796

797 Figure 5. Eight wind regimes represented by the K-means cluster centers. N

798 denotes the number of members in a cluster. Bottom left in each panel is the 5 m

799 s-1 reference vector.

800

801 Figure 6. Relative frequency distribution of the decoupled bora cases over

802 different clusters. The numbers above bars denote the relative contribution of

803 the decoupled cases to each cluster, expressed as the percentage of the total

804 number of cases in a cluster. Zeros for clusters 1, 5 and 6 indicate that there are

805 no decoupled bora episodes associated with these clusters.

806

807 Figure 7. MSLP for each cluster (see Fig. 5), averaged over all members of a

808 cluster. The filled circle denotes the Vratnik Pass.

809

810 Figure 8. Surface wind direction at the four studied stations from

811 measurements and the second nested WRF domain with 3-km grid spacing. ERA-

812 Interim, available every 6 h, is additionally shown at the point closest to the

813 Vratnik Pass.

814

815 Figure 9. MSLP and surface wind vectors from the ERA-Interim reanalysis and

816 WRF outermost and first nested domains on 27 December 2004 at 00 UTC (left)

817 and 06 UTC (right). Bottom left in each panel is the 20 m s-1 reference vector and

818 the circle denotes the Vratnik Pass.

35 819

820 Figure 10. Modeled vs. measured wind speed (top panels) and direction

821 (bottom panels) at the Vratnik Pass (left panels) and Senj (right panels) for the

822 directionally decoupled bora episode from cluster 7 that occurred from 00 – 12

823 UTC 5 February 2005. Model results are shown for two domains with grid

824 spacing of 1 km and 1/3 km.

825

826 Figure 11. The rotor occurrence in the WRF simulation of the decoupled bora

827 episode at 03 UTC 5 February 2005 for the 1/3 km domain. (a) Wind vectors and

828 the zonal wind component (color) at the first model level are shown over a

829 subset of the domain. Axes labels are grid points. Regions of flow reversal are

830 colored blue. Black circles denote Senj and the Vratnik Pass, and the black line

831 indicates the location of the vertical cross-section. (b) The vertical cross-section

832 along the indicated line, showing the wind vectors, turbulent kinetic energy

833 (color) and isentropes (0.5 K interval).

834

835

36 45.02 1500

45 45.6 Senj Vratnik pass 44.98 45.4 44.96

14.9 14.95 15 1000 45.2

Senj 45 Vratnik pass latitude [deg] altitude [m] 44.8 500 Rab

44.6

Mali Lošinj

44.4

0 13.5 14 14.5 15 15.5 longitude [deg] 836

837 Figure 1. Topography of the northeastern Adriatic region. The four

838 observational stations are indicated: Vratnik Pass (44.979°N, 14.984°E, 698 m

839 above MSL), Senj (44.990°N, 14.899°E, 2 m above MSL), Rab (44.750°N,

840 14.767°E, 24 m above MSL), and Mali Lošinj (44.533°N, 14.467°E, 53 m above

841 MSL). The inset in the upper right corner shows the detailed topography around

842 the Vratnik Pass (contour interval is 75 m).

843

844

37 (a) (b) Vratnik Pass Senj N N

75% 75% 50% 50% 25% 25% WEWE

V [m sï1] 10 ï 27 5 ï 10 S 0 ï 5 S

75% 75% 50% 50% 25% 25% WEWE

10 ï 27 ï1 5 ï 10 VS [m s ] 0 ï 5 S 845

846 Figure 2. Wind roses at (a) the Vratnik Pass, (b) Senj, (c) Rab and (d) Mali Lošinj

847 for the period from October 2004 to June 2005.

848

849

38 850

851 Figure 3. Conditional wind roses at Senj during October 2004 – June 2005 for

852 six different wind speed and direction combinations at the Vratnik Pass. Headers

853 at each subplot denote criteria at the Vratnik Pass for which conditional wind

854 rose at Senj was calculated: (a), (b) and (c) for northeasterly bora direction; (d),

855 (e) and (f) for southwesterly direction; (a) and (d) for weak winds, (b) and (e)

856 for moderate winds, (c) and (f) for strong winds at the Vratnik Pass. The

857 remaining cases (2%) are predominantly related to weak winds at the Vratnik

858 Pass from directions other than bora and southwesterly.

859

860

39 3

2 1.75

1 detector

0.25 0 ï0.25

ï0.75 ï1

11 12 01 02 03 04 05 06 month 861 2004 2005

862 Figure 4. Detection of the simultaneous bora occurrence at the Vratnik Pass and

863 Senj. The detector value of 2 denotes the decoupled episodes that occur when

864 bora blows at the Vratnik Pass but not at Senj. The values 3 and 0 stand for the

865 bora presence and absence at both stations, respectively. See Table 1 for the

866 complete description of the detector values.

867

868

40 Cluster 1; N=810 Cluster 2; N=711 46

45.5

latitude (deg) 44.5

Cluster 3; N=689 Cluster 4; N=615 46

45.5

latitude (deg) 44.5

Cluster 5; N=278 Cluster 6; N=273 46

45.5

latitude (deg) 44.5

Cluster 7; N=224 Cluster 8; N=130 46

45.5

latitude (deg) 44.5

44 13 14 15 16 13 14 15 16 longitude (deg) longitude (deg)

869

870 Figure 5. Eight wind regimes represented by the K-means cluster centers. N

871 denotes the number of members in a cluster. Bottom left in each panel is the 5 m

872 s-1 reference vector.

873

874

41 60 78.7

30 87.1 20 Occurrence (%) 18.9 10 52.3 0.0 1.0 0.0 0.0 0 1 2 3 4 5 6 7 8 875 Cluster

876

877 Figure 6. Relative frequency distribution of the decoupled bora cases over

878 different clusters. The numbers above bars denote the relative contribution of

879 the decoupled cases to each cluster, expressed as the percentage of the total

880 number of cases in a cluster. Zeros for clusters 1, 5 and 6 indicate that there are

881 no decoupled bora episodes associated with these clusters.

882

883

42 Cluster 1 Cluster 2

70 1004 1010 1004 1016 60 1010 50 1016 1022 1022 Latitude (deg) 40 1016 1022 1016

Cluster 3 Cluster 4

70 1004 1004 1010 60 1010 1016 1016 50 1022 1022

Latitude (deg) 1016 40 1016

Cluster 5 Cluster 6 992 70 998 998 1004 1010 1016 60 998 1022 1022 1028 1004 50 1016 1022 1010 1016 Latitude (deg) 1010 40

Cluster 7 Cluster 8

70 1004 1004 998 1010 1004 60 1016 1010 1016 1016 50 1022 1022 1028 1016 1028 1010 Latitude (deg) 40 1022 1022

ï20 0 20 40 ï20 0 20 40 Longitude (deg) Longitude (deg)

884

885 Figure 7. MSLP for each cluster (see Fig. 5), averaged over all members of a

886 cluster. The filled circle denotes the Vratnik Pass.

887

43 Vratnik Pass Senj 360 300 240 180

dir (deg) 120 60

0 measurements WRF Rab ERAïInterim Mali Losinj 360 300 240 180

dir (deg) 120 60 0 12 18 00 06 12 18 00 06 12 12 18 00 06 12 18 00 06 12 Time (UTC; 26ï28 Dec 2004) Time (UTC; 26ï28 Dec 2004) 888

889 Figure 8. Surface wind direction at the four studied stations from

890 measurements and the second nested WRF domain with 3-km grid spacing. ERA-

891 Interim, available every 6 h, is additionally shown at the point closest to the

892 Vratnik Pass.

893

894

44 00 UTC 27 Dec 2004; ERA INTERIM 06 UTC 27 Dec 2004; ERA INTERIM 50 50 48 48 1010 1004 1010 46 1010 46 44 44 1016 42 42 998 1016

Latitude (deg) 40 998 Latitude (deg) 40 1004 38 38 1010 36 36 5 10 15 20 25 5 10 15 20 25 Longitude (deg) Longitude (deg)

00 UTC 27 Dec 2004; WRF 27 km 06 UTC 27 Dec 2004; WRF 27 km 50 0 50 101 1016 48 48 1010

1004 1004 1004 46 998 1010 46 1010

44 44 998 42 42

Latitude (deg) 40 Latitude (deg) 40 1016 1016 38 38 36 36 5 10 15 20 25 5 10 15 20 25 Longitude (deg) Longitude (deg)

00 UTC 27 Dec 2004; WRF 9 km 06 UTC 27 Dec 2004; WRF 9 km

1002 47 1002 47 1006

46 46

45 998 45 1002 44 44 998 Latitude (deg) Latitude (deg) 1002 994 998 43 43 1006 998 42 42 12 14 16 18 12 14 16 18 Longitude (deg) Longitude (deg)

895

896 Figure 9. MSLP and surface wind vectors from the ERA-Interim reanalysis and

897 WRF outermost and first nested domains on 27 December 2004 at 00 UTC (left)

898 and 06 UTC (right). Bottom left in each panel is the 20 m s-1 reference vector and

899 the filled circle denotes the Vratnik Pass.

900

901

45 Vratnik Pass Senj 20

V (m/s) 8 measurements 4 WRF 1 km WRF 333 m 0

360 measurements 300 WRF 1 km 240 WRF 333 m 180

dir (deg) 120 60

0 18 21 00 03 06 09 12 15 18 18 21 00 03 06 09 12 15 18 Time (UTC; 4ï5 Feb 2005) Time (UTC; 4ï5 Feb 2005) 902

903 Figure 10. Modeled vs. measured wind speed (top panels) and direction

904 (bottom panels) at the Vratnik Pass (left panels) and Senj (right panels) for the

905 directionally decoupled bora episode from cluster 7 that occurred from 00 – 12

906 UTC 5 February 2005. Model results are shown for two domains with grid

907 spacing of 1 km and 1/3 km.

908

909

46 (a)

910 (b)

911 Figure 11. The rotor occurrence in the WRF simulation of the decoupled bora

912 episode at 03 UTC 5 February 2005 for the 1/3 km domain. (a) Wind vectors and

913 the zonal wind component (color) at the first model level are shown over a

914 subset of the domain. Axes labels are grid points. Regions of flow reversal are

915 colored blue. Black filled circles denote Senj and the Vratnik Pass, and the black

916 line indicates the location of the vertical cross-section. (b) The vertical cross-

917 section along the indicated line, showing the wind vectors, turbulent kinetic

918 energy (color) and isentropes (0.5 K interval).