Impact of U.S. west coastline inhomogeneity and synoptic forcing on winds, wind stress, and wind stress curl during upwelling season

JOURNAL OF GEOPHYSICAL RESEARCH: OCEANS, VOL. 118, 4036 4051, doi:10.1002/jgrc.20282, 2013 Impact of U.S. west coastline inhomogeneity and synoptic forcing on winds, wind stress, and wind stress curl during upwelling season Clive E. Dorman, 1 John F. Mejia, 2 and Darko Koracin 2 Received 18 October 2012; revised 14 June 2013; accepted 20 June 2013; published 5 September 2013. [1] Although buoy and aircraft measurements, as well as numerical simulations, have shown intense over-shelf and slope dynamics of the west coast of the United States in the summer upwelling season, satellite footprint limitations of approximately 25 km resolution have thus far precluded long term, spatially extended monitoring of the near-coastline dynamics. However, recent advancements in satellite data processing have allowed a finer footprint, of approximately 12 km resolution, to investigate further the properties of coastal winds and consequent upwelling. This improved satellite data analysis has confirmed the intense coastal winds over the shelf and slope and revealed their spatial extensions and inhomogeneities on event and multiday scales. The inhomogeneities are dominated by the along-coast pressure gradient modulated by the synoptic effects and topographical forcing of the five major capes, which also generate upwelling wind stress and curl pattern inhomogeneities. Synoptic forcing of the coastal flow was evidenced by high correlation coefficients, in excess of 0.8, between the buoy-measured pressure differences and wind speeds; wind speeds greater than 11 m s 1 occurred only when the along-coast pressure gradient was greater than 0.8 hpa/100 km. Based on Bernoulli flow principles, the observed upper limit of the wind speed on the downwind sides of the major capes is explained by using characteristic values of atmospheric marine layer parameters. Numerical simulations at a similar resolution (12 km) as the new satellite data footprint for June 2001, completed as part of multiyear regional climate modeling efforts, were able to reproduce the main characteristics of the flow. Citation: Dorman, C. E., J. F. Mejia, and D. Koracin (2013), Impact of U.S. west coastline inhomogeneity and synoptic forcing on winds, wind stress, and wind stress curl during upwelling season, J. Geophys. Res. Oceans, 118, 4036 4051, doi:10.1002/jgrc.20282. 1. Introduction [2] The west coast of the United States has long been recognized as one of the world s major wind-driven summer coastal upwelling zones with significant biological importance [Sverdrup et al., 1941]. Although the basic structure of the surface wind field has been determined from ship measurements [Nelson, 1977; Nelson and Husby, 1983], technological advances in measurement systems such as buoys, aircraft and satellites along with numerical models have revealed great along-coast wind variations that are related to the coastal topographic structure. [3] The cause of the coastal winds is the interaction of the large-scale Northeast Pacific anticyclone with the SW U.S. heat low to set up flow from the north along the coast. 1 Integrative Oceanography, Scripps Institution of Oceanography, La Jolla, California, USA. 2 Desert Research Institute, University of Nevada, Reno, Nevada, USA. Corresponding author: C. E. Dorman, Integrative Oceanography, Scripps Institution of Oceanography, La Jolla, CA 92093, USA. (cdorman@ucsd.edu) 2013. American Geophysical Union. All Rights Reserved. 2169-9275/13/10.1002/jgrc.20282 Subsiding air in the eastern half of the North Pacific anticyclone interacting with the sea surface maintains the atmospheric marine layer. This layer, about 50 400 m deep along the coast, is forced to flow equatorward and mostly parallel to the local coastline by the coastal mountains (reviewed in Koracin et al. [2004]). Aircraft, satellites, buoys, and coastal stations show that the marine layer slows and thickens on the upwind side of capes (a narrow compression bulge) and accelerates and thins in the downwind side (a broad expansion fan) [Dorman, 1985; Burk et al., 1998; Rogers et al., 1998; Dorman et al., 1999; Dorman and Winant, 2000; Tjernström and Grisogono, 2000; Ström et al., 2001; Skyllingstad et al., 2002]. The atmospheric marine layer is a dense bottom layer which responds to hydraulic dynamics that are a function of conservation of energy [Winant et al., 1988]. The hydraulic response of the lower atmosphere is an important contributor to the area s unique atmospheric structure, which occurs as supercritical flow when the Froude number is greater than 1.0 or when the layer speed is greater than or equal to that of a long wave in the layer [Samelson, 1992]. Rogerson [1998] found that transcritical flow occurs when the Froude number is between 0.5 and 1.0, which is the condition when a layer inbound to a coastal bend with less than supercritical flow speed accelerates and responds as supercritical. 4036

[4] Atmospheric forcing of upwelled cold ocean water is directly related to the sea surface wind stress component parallel to the local coast and the wind stress curl [Pickett and Paduan, 2003; Koracin et al., 2004; Perlin et al., 2004]. The strongest along-coast wind stress is generally over the Northern California shelf and slope. [5] The purpose of this paper is to investigate the advantages of using a new satellite processing product for a better understanding of coastal dynamics and to identify critical synoptic and boundary layer conditions that lead to the strong inhomogeneity of the wind forcing on the eastern boundary of a midlatitude coastal ocean during the summer season, as well as its wind-driven upwelling that remains incompletely described. An example of a prominent wind expansion fan and its offshore extension downwind of Cape Blanco and Cape Mendocino is shown in Figure 1. The flow inhomogeneity is dominated by three aspects: the along-coast pressure gradient modulated by the synoptic scale, major cape topographical forcing (Figure 2), and significant temporal changes due to strong horizontal gradients on the order of several hours. Correct representation of winddriven coastal upwelling is essential to understanding marine biological productivity, gas exchange, and climate aspects at the ocean-air interface. This paper presents observations and numerical simulation systems in section 2, sea level pressure gradient in section 3, large-scale forcing in section 4, the upper limit of wind speed in section 5, numerical simulation of a characteristic wind event in section 6, and wind stress and curl forcing of the coastal ocean in section 7. 2. Observations and Numerical Simulation System 2.1. NDBC Buoys [6] The U.S. National Data Buoy Center (NDBC) has meteorological buoys anchored on the outer continental shelf Figure 1. QuikSCAT-derived sea surface wind speeds (m s 1 ) at 03 UTC on 17 June 2001. Contour interval is 1ms 1. Figure 2. Buoy locations and five prominent capes along the U.S. west coast used in this study. edge and slope off the U.S. west coast, which are important reference measurements for this study (Figure 2). Each buoy carries mast-mounted, propeller-vane anemometer systems for measuring wind speed and direction and atmospheric pressure. The buoy s anemometer measurements are 8 min averages collected hourly; the anemometer-height wind speeds were adjusted to 10 m equivalent neutral stability speeds using the approach of Liu and Tang [1996]. The winds compare well with instrumented aircraft measurements [Beardsley et al., 1997]. As the coastal wind field inhomogeneity is pronounced around the major capes, this study pairs buoys about the five major capes for the along-coast pressure difference computations. The sixth pair (46054 46047) extends SSE from Point Conception across mostly open water on the western edge of the Southern California Bight. 2.2. QuikSCAT Processing Methodology [7] Surface wind measurements in the open ocean experienced a major advance with the development of detection by satellite-borne microwave systems. However, this did not extend the inner coastal zone which was blocked from coverage by the land mask (initially 50 km, later 25 km). This was a significant deficit as this excluded coverage of the wind maximum (about 15 km from the coast) and winds over the continental shelf which can have larger wind gradients than the open ocean [Rogers et al., 1998; Dorman et al., 1999]. Inclusion of wind direction with QuikSCAT derived winds, which was operational from mid-1999 to late 2008, was a major improvement. Initially, the footprint was 25 km with a 30 km land mask [Jet Propulsion Laboratory, 2006], later improved to 12.5 km resolution with a 20 km land mask [e.g., Hoffman and Leidner, 2005; Jelenak et al., 2002; Jelenak et al., 2002]. While significantly better, this still did not include the wind speed maxima that are associated with the strongest along-coast wind-driven upwelling, nor did it capture the winds between the 4037

maxima and the coast, which is the location of the positive wind curl associated with wind stress curl upwelling [Korain et al., 2004]. [8] The standard 12.5 km QuikSCAT processing was implemented by filtering out all radar backscatter measurements (sigma-0 slices) with centers that fall within 20 km of land. Because the characteristic dimensions of a typical sigma-0 slice used to derive QuikSCAT 12.5 km resolution wind vectors are 4.5 25 km, many uncontaminated measurements are filtered out by this one-size-fits-all mask [Freilich and Vanhoff, 2006; Vanhoff and Freilich, 2008]. [9] In this paper, a special, high-resolution footprint with a narrow land mask for the 12.5 km QuikSCAT data set is used to improve coastal wind data retrievals significantly, so that they extend into the midshelf and wind maxima centers. By looking at the time variability of backscatter measurements as a function of location and slice orientation, it can be determined empirically whether those measurements are tainted by land [Vanhoff and Freilich, 2008]. The width of the new empirical land mask varies from as little as 5 km out to 20 km. The typical land mask is the gap between the colored area and the coastline in Figure 1. 2.3. Application of the Advanced Weather and Research Forecasting Model [10] Earlier analyses have shown that the grid resolution necessary to resolve the significant mesoscale coastal wind structure and maxima should be about 10 km or better [Koracin et al., 2004]. Simulated mesoscale interaction between the airflow and the coastal terrain is evaluated by using fine-scale regional climate modeling output, based on the advanced weather and research forecasting (AWRF V3.2, hereafter WRF) model, with two nested domains at grid spacings of 36 and 12 km, and output archived in hourly increments. The WRF is an atmospheric mesoscale model developed by a community of scientists at many research centers [Skamarock et al., 2006, Skamarock, 2008]. The general model configuration is set to contain 35 terrain-following vertical levels distributed log linearly, keeping at least 18 vertical levels below 700 hpa over the ocean. The finer resolution at lower levels is intended to better represent surface layer and planetary boundary layer (PBL) processes, which in the present case are expected to account for possible changes in the marine layer or marine boundary layer (MBL) structures associated with complex coastal orographic features. Physical parameterizations for these simulations are similar to those used by Salathe etal. [2010], with some modifications. For PBL, we used the Yonsei University (YSU) scheme, nonlocal-k mixing in the dry convective boundary layer and explicit treatment of entrainment, which uses the Richardson number as a predictor of vertical diffusion in the free atmosphere. Other relevant physics schemes include the Unified Noah landsurface model [Ek et al., 2003] and the longwave and shortwave radiation rapid radiative transfer model gas (RRTMG) schemes [Iacono et al., 2008]. While RRTMG uses similar physics and absorption parameters as the RRTM [Mlawer et al., 1997], it represents subgrid-scale cloud variability, and it is more computationally efficient. [11] The boundary condition problem is resolved with forcing data based on the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis products [Kalnay et al., 1996], which are updated every 6 h, and sea surface temperature observations based on the OISSTV2 (available December 1981 to present). The simulation output presented and analyzed in this paper constitutes the model output for June 2001. However, the model was integrated continuously from January 1982 to December 2007, as part of a larger research effort aimed at dynamically downscaling the general circulation model (GCM) output for regional climate variability and change over the intermountain western United States [Mejia et al., 2011]. 3. Wind Forcing by the Along-Coast Sea Level Pressure Gradient [12] Ship [Nelson and Husby, 1983], buoy, and aircraft measurements show that the Southern Oregon and California coastal winds are dominantly along-coast [Halliwell and Allen, 1987; Dorman and Winant, 1995; Rogers et al., 1998; Dorman et al., 1999]. In this paper, the along-coast pressure gradient is approximated by coastal NDBC buoys about 100 km apart, but scaled to approximate the pressure Table 1. Statistics for Buoy Pair Pressure Difference (P Diff) Between the North-Side-of-Cape and South-Side-of-Cape Buoys, South Buoy Wind Speed (Speed), and Along-Coast Wind Component (Comp) a South Buoy (m s 1 ) PDiff-Speed Filter Buoy PDiff (hpa) Speed Comp No Yes Cape N # S # Dist (km) Med SD Med 99% Max SD Med Corr Corr Blanco 50 27 308 0.9 1.1 4.6 17.4 19.3 4.7 2.6 0.79 0.85 Mendocino 22 14 174 1.6 1.1 7.3 15.0 19.2 3.8 6.7 0.80 0.84 Arena 14 13 134 0.5 0.9 9.3 17.5 21.6 4.8 8.6 0.86 0.90 Sur 42 28 123 1.0 0.7 8.4 16.2 18.3 4.2 7.6 0.78 0.82 Conception 11 54 78 1.8 1.0 8.5 15.5 16.9 4.1 7.2 0.84 0.90 O Bight 54 47 221 0.2 0.4 6.4 12.2 14.4 2.9 5.1 0.40 0.60 a For each cape listed on the left, N # is the northern buoy number, S # is the southern buoy number, and Dist is the distance between the two buoys. Med is median, SD is standard deviation, 99% is the value at 99% of occurrence, Max is maximum value, and Corr is the correlation. Filtered as 30 h, low pass time series. Single wind speed greater than 20 m s 1 is bold. Period is 1 May 2001 to 1 Sep 2001. OBight is on the outer, western side of the southern California Bight, between Point Conception and the Mexican border (Figure 2, buoys 46054 and 46047). 4038

Figure 3. Pressure differences between Cape Mendocino NDBC buoys (46022 and 46014) (solid line) and WRF (dashed line) in the upper frame and along-coast wind component for May to August 2001 in the lower two frames, each designated with buoy number. WRF values are from the grid point nearest each buoy. difference over 100 km and paired about a major cape. The scaled pressure difference is highly correlated with the south buoy, along-coast wind component of each of the five major capes (Table 1). The close relationship between the Cape Mendocino buoy pressure difference and the along-coast wind component is apparent in Figure 3, as the two variables track each other well in timing and amplitude, with no major differences. The results for the other four capes are similar (not shown), thus confirming that the WRF pressure difference and along-coast wind based on the closest grid point to each buoy location also closely follow the buoy values, without any major deviations, for Cape Mendocino (Figure 3) and the other capes (not shown), confirming that WRF represents the along-coast winds and pressure field well. [13] Unlike the previous five buoy pairs, the path between the buoys in the sixth pair (buoys 46054 and 46047) is mostly over open water, away from the mainland coast (Figure 2). Most of the marine air passing Point Conception continues in the same direction, causing moderately strong winds at buoy 46047, in contrast to the weak wind speeds in the inner portion of the Bight. However, the marine air decelerates in a negative pressure gradient that is poorly correlated with the wind, in contrast to the other buoy pairs, which are close to a coast that is backed by coastal mountains. [14] QuikSCAT is compared with WRF and buoy 46013 in Figure 4, where the QuikSCAT value is from the pixel nearest the buoy on each of the 12 h passes while the buoy and WRF values are hourly. It is worth noting how persistent the along-coast winds are when the wind is above 5 m Figure 4. (top) Wind speed and (bottom) direction of NDBC buoy 46014 (solid line) on the south side of Cape Mendocino, plotted with values from QuikSCAT s nearest pixel (square) and the WRF grid point nearest each buoy (dotted line) for May to August 2001. s 1 which is true of all buoys along the open coast as shown in Figure 2. The general buoy values are overwhelmingly supported by other nearby buoy measurements and aircraft over flights [e.g., Beardsley et al., 1987, 1997; Dorman and Koracin, 2008]. The WRF wind speed and direction time series follows the buoys closely, especially in the timing and values of the short-term variations. The QuikSCAT wind speed is mostly less than the buoy value by up to 50% while the QuikSCAT wind direction follows the buoy values with an occasional larger deviation. Pickett et al. [2003] reported that comparisons between QuikSCAT and 12 near-shore U.S. west coast buoys showed a speed error of 1.4 m s 1, and a direction error of 37, with a large range of scatter between the QuikSCAT and buoy values. For buoy 46013, the wind-speed error was 3 toþ3.8 ms 1 and the direction error was 50 to þ30 degrees. Sousa et al. [2013] reported mixed results for differences between winds sensed by QuikSCAT, WRF and buoys along the Galician coast. 4. Large-Scale Forcing of the Coastal Flow 4.1. QuikSCAT and WRF Mean Winds in June 2001 [15] Here, the coastal wind fields by WRF and Quik- SCAT are compared. The WRF analysis was based on wind values at 06 and 18 local solar time (LST), to match QuikSCAT pass times (Figure 5). The 8 m s 1 contour is highlighted to show how the two analyses correspond with this area s mean speed value. Both the WRF and QuikS- CAT analyses agree on the general aspect of a California wind maximum extending from Cape Mendocino to Point Conception, with weak winds north of Cape Blanco and southeast of Point Conception. [16] However, there are significant disagreements in the major details of the major cape downwind expansion fan 4039

Figure 5. June 2001 mean wind speed (m s 1 ) and vectors for (a) QuikSCAT and (b) WRF. The 8 m s 1 isotach (mean QuikSCAT speed for the area) is shown for QuikSCAT (solid) and WRF (dotted). Contour interval is 0.5 m s 1. maxima. In northern California, WRF predicts speeds greater than 9 m s 1 extending along the coast from the tip of Cape Mendocino to past Point Arena, with a 10.5 m s 1 closed contour maximum downwind of Point Area and close to the coast. In contrast, QuikSCAT winds show the Cape Mendocino and Point Arena downwind closed contours more than 40 km offshore. Another significant difference is that WRF has a contiguous area of 9 m s 1 from the Point Sur tip to downwind of Point Conception, while in contrast, the QuikSCAT 8 m s 1 isoline extends almost due south of Point Sur, leaving out the central California coast and Point Conception. According to WRF, the QuikSCAT June mean is missing expansion fan maxima close to the coast downwind of Point Sur and Point Conception and a connecting higher speed zone. In all of these differences, buoy and aircraft measurements (including those in Table 1), support WRF over QuikSCAT [Dorman and Winant, 1995, 2000; Rogers et al., 1998; Dorman et al., 1999; Dorman and Koracin, 2008]. In an earlier study, Koracin et al. [2004] used modified Mercalli (MM5) to investigate June winds along Oregon and California, resulting in findings that are generally similar to those of WRF shown in Figure 5. 4.2. Synoptic Pressure Gradients and Coastal Winds in June 2001 [17] Buoy measurements support our hypothesis that the short-term synoptic-scale pressure gradient establishes the along-coast sea level pressure gradient that determines wind direction and strength, followed by a feedback through atmospheric boundary layer hydraulics adjusting to supercritical flow further lowering the downwind pressure and accelerating the surface winds there to a maximum. To test this, a daily event analysis of the buoy-measured sea level winds and pressure about each of the major capes was conducted in June 2001; the results are shown in Tables 2aa and 2bb. It was found that the increased large-scale, along-coast pressure gradient usually covered at least two major capes, and that the winds responded in less than 2 h. For most of the wind speed events, the 8 m s 1 isotach intersected the coast on the north side of either Cape Blanco or Cape Mendocino. When the buoy-measured, along-coast pressure gradient exceeded 0.8 hpa/100 km, the along-coast wind speed was 11 m s 1 or greater, which is at least one standard deviation (3 m s 1 ) above the June mean speed (8 m s 1 ) for the ocean area shown in Figure 5a, as confirmed by QuikSCAT. For all events examined, it was always found that the strongest model winds were over the outer shelf or slope. The result is that this event study strongly supports the model of interaction of the synopticscale along-shore pressure gradient with the topographically anchored supercritical flow responding to hydraulic dynamics, so that the absolute wind speed maxima are downwind of major capes, while the maxima structure extends well downcoast and offshore, and are easily observed in QuikSCAT winds. 4.3. Reanalysis of the Synoptic-Scale Along-Coast Sea Level Pressure Gradient [18] It was established in the previous section that the sea level along-coast pressure gradient forces the alongcoast winds. In this section, we show that the large-scale sea level along-coast pressure gradient determines the zone of higher wind speeds along the coast. To represent the larger synoptic-scale sea level pressure field over the U.S. west coast, we use the North American Regional Reanalysis (NARR), with a 32 km grid separation provided by National Oceanic and Atmospheric Administration/Oceanic and Atmospheric Research/Earth System Research Laboratory Physical Sciences Division (NOAA/OAR/ ESRL PSD), Boulder, Colorado, from their Web site at http://www.esrl.noaa.gov/psd/data/gridded/data.narr.monolevel.html#plot. When compared to the NDBC buoys, NARR had the correct wind direction along the coast between Cape Blanco and north of Point Conception. We found that the NARR large-scale (synoptic) sea level pressure field can be used to identify the portion of the coast 4040

Table 2a. June 2001 Northern Cape Event Pressure Differences and Wind Speeds From Buoys and QuikSCAT a Buoy Data QuikSCAT Cape Blanco Cape Mendocino Pt Arena Day B50 B27 (PDif 0.8 hpa) B27 (wsp 8ms 1 ) B22 B14 (PDif 0.8 hpa) B14 (wsp 8ms 1 ) B14 B13 (PDif 0.8 hpa) B13 (wsp 8ms 1 ) Start Area (wsp 8ms 1 ) 1 (0.7) 8.3 1.3 B 2 2.2 9.4 1.5 14.2 M 3? (7.7) 2.9 16.1 1.4 17.3 M 4 1.8 13.6 2.9 15.6 1.8 18.2? 5 1.3 8.4 2.0 14.9 M 6 1.0 9.4 w, A 7 1.4 2.1 12.8 M 8 1.8 1.3 10.4? 9 0.9 1.3 11.5? 10 0.8 (7.7) 1.8 8.5 1.4 12.9 w, B 11 2.2 14.1 A 12 1.4 12.5? 13 1.5 11.3 2.5 11.2 2.1 16.0 B 14 1.7 13.4 2.7 (7.3) 2.1 13.9 B 15 2.2 15.6 3.2 10.2 1.2 11.7 B 16 2.5 16.0 2.5 (7.8) 1.7 12.9? 17 2.6 17.3 3.2 9.7 1.8 11.9 B 18 2.3 15.4 2.9 10.1 2.6 15.5 B 19 2.4 15.0 3.1 1.7 11.2 B 20 1.9 14.1 2.9 8.7 2.8 17.4? 21 2.0 15.7 3.6 12.0 1.7 14.7 B 22 1.7 13.1 2.9 1.3 9.5 B 23 1.2 8.9 2.4 8.5 2.0 15.0 B 24 1.7 8.6 0.8 11.8? 25 0.8 1.3 10.8 w, M 26 27 28? 29 1.0 (7.2) 1.1 (7.5) 1.2 10.8 M a Only speeds >8 ms 1 and adjusted pressure differences >0.8 hpa/100 km are shown, while those with near but lower values are in parentheses. QuikSCAT wind >8ms 1 starts on the coast at Cape Blanco (B), Cape Mendocino (M), or Point Arena (A).? indicates insufficient QuikSCAT coverage; w ¼ weak QuikSCAT winds. that exhibits a higher pressure gradient and winds higher than the mean (>8ms 1 ). [19] The NARR June 2001 sea level pressure field (Figure 6) shows the North Pacific anticyclone and the heat low over the southwestern United States which sets the synoptic-scale northerly along-coast winds. However, most important to coastal wind speed are the coast-crossing isobars, forming the strongest along-coast sea level pressure gradient on the northern California coast, delimited by line A (Cape Blanco) and line B (38 N), which coincides with the part of the coast with the greatest June 2001 QuikSCAT mean wind speed. [20] A coastal mountain range extending well above the atmospheric marine layer prevents cross-coast movement [Sonderberg, 2001]. The air in the marine boundary layer responds to the pressure gradient by moving southward along and parallel to the coast, with the strongest mean speeds over water between Point Conception and 38 N, as confirmed by buoy and QuikSCAT measurements [Dorman et al., 2000; Koracin et al., 2004]. [21] A representative summer wind field event occurred on 17 June, when the anticyclone was to the north of its mean position and the heat low had deepened over California, causing the strong, southbound, along-coast coastal pressure gradient to shift to the north, so that it extended from Cape Blanco at A to past Point Arena at B (Figure 7). This pressure field drove QuikSCAT-derived double wind maxima, one anchored in each of the downwind sides of Cape Blanco and Cape Mendocino (Figure 1). [22] On 12 June 2001 (not shown), the North Pacific anticyclone shifted from its mean position to the south, while the heat low pressure in California weakened, and the strong, along-coast pressure gradient shifted to a 90 km section of the central California coast, extending equatorward from Point Sur, where coastal QuikSCAT- and buoymeasured southward winds were greater than 11 m s 1.At the same time, a weak, reversed pressure gradient caused a weak, reversed coastal wind along northern California. 5. Wind Speed Upper Limit Under Bernoulli Flow Principle [23] The peak summer NDBC buoy speeds, always found on a major cape downwind side, rarely exceed 18 19 ms 1 (Table 1). Simulations have suggested that marine layer depth and speed are determined mostly by simple 4041

Table 2b. June 2001 Southern Capes Event Pressure Differences and Wind Speeds From Buoys and QuikSCAT a Buoy Data QuikSCAT Pt Sur Pt Conception Day B50 B27 (PDif 0.8 hpa) B27 (wsp 8ms 1 ) B11 B54 (PDif 0.8 hpa) B54 (wsp 8ms 1 ) End Area (wsp 8ms 1 ) 1? 2 0.9 NofSF 3 1.6 14.3 1.4 12.7 Sur 4 1.9 16.3 1.4 13.6 Sur-Con 5 1.1 11.1 8.6? 6 3.0 14.4 1.0 12.0 Sur 7 2.8 13.9 1.3 12.0 Sur-Con 8 2.2 12.7 Sur 9 1.7 12.0 1.4 12.2? 10 1.1 11.5 2.1 14.6 Sur-Con 11 2.5 14.4 2.1 14.9 Sur-Con 12 2.5 14.4 2.4 16.0 Sur-Con 13 1.8 13.2 2.1 16.6? 14 2.3 12.6 1.1 11.5 Sur 15 0.9 N of SF 16 (7.9) 1.5 9.4 Con 17 1.1? 18 1.0 N of SF 19 (0.7) (7.8) 0.8 7.1 N of SF 20 (7.7) NofSF 21 NofSF? 22 NofSF 23 8.8 0.8 N of SF 24 9.1 1.7 10.7 Sur 25 1.6 11.7 1.6 13.3 Sur-? 26 1.3 9.9 1.6 12.0 Sur-C 27 0.9 7.2 No SF 28 1.3 7.1? 29 1.0 10.5 1.9 12.5 Sur-? 30 1.3 12.3 1.8 12.3 Sur a See Table 2aa for explanations. QuikSCAT wind >8 ms 1 usually ends on the coast at Sur or Conception (Con).? indicates insufficient QuikS- CAT coverage. continuity [Koracin and Dorman, 2001]. In this section, we show that the Bernoulli principle can be used to explain this limitation. 5.1. Conceptual Model [24] A conceptual model of the marine layer flow about Cape Mendocino shows the major flow characteristics if the marine layer responds as a single-layer, frictionless, Bernoulli flow, focusing on the expansion fan on the downwind side [Chow, 1959; Winant et al., 1988], and ignoring the compression bulge on the upwind side. Figure 8a shows diagram of the sea surface wind field about Cape Mendocino based upon the QuikSCAT and buoy sea surface wind speed for 17 June 2001, which is typical of any cape when the maximum wind speed is greater than 11 m s 1. The MBL characteristics along the trajectories marked by the dark thick lines labeled A, B, C, and D on the horizontal wind analysis are shown in Figure 8b. The synoptic scale along-coast pressure initially accelerates the flow toward the south (solid line in top, Figure 8b), while the thinning of the layer forced by supercritical flow hydraulic adjustment causes a local pressure minimum (dashed line in top), forcing the layer speeds to further accelerate into the low and then decelerate farther downwind (middle, Figure 8b), so that the marine layer depth thins to a minimum in the low, and then thickens downwind (bottom, Figure 8b). 5.2. Upper Bound of the Wind Speed [25] A simple, single-layer, frictionless Bernoulli flow can be used to explain the upper bound of the marine layer wind speed observed. For simplicity, the denser marine layer forms a surface layer capped by an air temperature inversion with a greater potential temperature. A smoothly increasing potential temperature gradient above the marine layer to the top of the air temperature inversion is assumed. Using the basic hydraulic theory expressed by the Bernoulli energy equation applied to a frictionless marine layer, the energy per unit volume (E) is E ¼ g d h þ V 2 2 þ P ð1þ where is the density of the lower layer, g is the acceleration of gravity, is the potential temperature of the lower layer, d is the potential temperature difference between the top of the layer and the top of the inversion, h is the 4042

Figure 6. NARR reanalysis of the mean sea level pressure (hpa) for June 2001 at 0000 UTC. The strongest along-coast sea level pressure gradient is from Cape Blanco to past Point Arena, delimited by lines A and B. Contour interval is 1 hpa. depth of the lower layer (MBL), V is the velocity average over the marine layer, and P is the atmospheric pressure on top of the marine layer [Winant et al., 1988; Dorman et al., 1999]. As the pressure term contributes little to the energy variation, it can be assumed that the remaining terms are conserved for the marine layer to the first order. Support for this assumption is provided by Dorman et al. [1999], who applied equation (1) to 15 aircraft soundings made over 6 h along three coast-parallel tracks over the sea, within 120 km of Point Sur. The median percentage change in total energy along the tracks was þ9%, with an extreme range of 23% to þ52%. [26] Consider that the strongest of the buoy-measured maximum wind speeds along Oregon and California is near 19 m s 1 (Table 1). We applied equation (1) to the inbound marine layer off southern Oregon to investigate the role of the layer s potential energy. It is assumed that the inbound speed is near zero, and the frictionless layer thins to 50 m (near the shallowest observed by aircraft). Greater inbound layer depth change and potential temperature difference across the top causes faster speeds (Figure 9). Further, there is an observed tendency for the temperature difference to increase with decreasing layer depth, although the maximum observed is less than 15 K for a thin layer. If the inbound layer is 600 m deep, then thins to 50 m and is capped by a 10 K difference, the layer speed will increase to 19 m s 1. This is close to the observed maximum speed, which suggests that the upper limit of the coastal summer wind speed is controlled by the inbound layer depth and temperature difference. The effect of a more realistic assumption of an inbound weak layer speed of about 2 m s 1 might be canceled by the ignored frictional dissipation. [27] The strongest QuikSCAT winds are on the downwind sides of Cape Blanco and Cape Mendocino, which have the thickest inbound marine layers. This is followed closely by Point Arena, which is affected by being close Figure 7. NARR reanalysis of the sea level pressure (hpa) for 17 June 2001 at 0000 UTC. The strongest alongcoast gradient extending from the north side of Cape Blanco (A) to past Point Arena (B) is coincident with the strongest coastal winds measured by buoys and QuikSCAT at this time. Contour interval is 1 hpa. enough to Cape Mendocino that the marine layer inbound to Point Arena is still responding to Cape Mendocino [Haack et al., 2001]. However, along central California, the maximum observed wind speeds are considerably less, 13 15 m s 1 (Tables 2aa and 2ab). The difference is likely related to the marine layer approaching central California being lower after interacting with the three upwind capes and the northern California bend [Dorman et al., 2000], as well as the sea level pressure gradient being weaker. As this basic structure is consistent with repeated observations and numerical simulations, single-layer frictionless Bernoulli flow captures the essence of the marine air dynamic response to a major cape. 6. Numerical Simulation of High-Speed Wind Event [28] In this section, the reanalysis and WRF simulation are used to explore the dynamic nature of a high-speed wind event. 6.1. NARR 10 day Composites of High-Speed and Low-Speed Days in June 2001 [29] In preparation for WRF compositing, which follows in the next subsection, two sets of 10 days were selected from June 2001, based upon buoy (Table 2aa) and QuikS- CAT observations off Cape Mendocino. One set was the 10 4043

Figure 8. (a) Ten meter wind speeds (m s 1 ) for a conceptual model of a frictionless single marine layer flow about Cape Mendocino on 17 June 2001. Bold lines labeled A, B, C, and D represent flow patterns along air parcel trajectories. Values along A D are shown in Figure 8b. Contour interval is 1 m s 1. (b) Flow properties along 10 m trajectories A, B, C, and D shown in Figure 8A as responding to large capes. (top) The solid line is large-scale sea level pressure, and the dashed line is modification of sea level pressure by change in marine layer depth. (middle) Ten meter wind speed along a trajectory. (bottom) Marine layer depth along a trajectory. Flow advances from right to left. strongest-wind days (June 2 4,13,15,17,18, 20, 21, and 24) and the other was the 10 weakest-wind days (June 6 9,11,12, and 25 28). The results, presented in Figure 10, show two composites of NARR sea level pressure. The lower frame shows stronger wind episodes and, as a check, the upper frame shows weaker wind episodes. The strongwind sea level pressure composite has a significantly stronger along-coast pressure gradient on the Northern California coast, while it is weaker for the weak-wind composite due to the North Pacific anticyclone position shifting eastward and extending to the northeast. The composite difference emphasizes that the large-scale atmospheric field sets the stage for the along-shore pressure gradient and the marine layer hydraulic adjustment. Figure 9. Relationship of inbound marine layer depth and potential temperature difference to wind speed, assuming all potential energy goes into a frictionless layer 50 m deep. Units for curves are m s 1. The thick, unlabeled line is the upper limit of observed height and potential temperature difference. Upper limit appears to be 19 m s 1 observed for the buoy summer winds (Table 1). 6.2. WRF 10 day Simulated Composites of Sea Level Pressure [30] WRF composites of the winds, sea level pressure, MBL height, and liquid water path were constructed for the 10 days of strongest flow in June 2001, from a northerly direction around Cape Mendocino, as discussed in the previous section. These are shown in Figure 11, centered on Cape Mendocino. These days exhibited significant hydraulic adjustment effects, such as an expansion fan wind speed maximum close to the coast on the downwind side of every major cape and narrower compression bulges upwind (reviewed in Koracin et al. [2004]), while avoiding mixedproperty dynamics associated with other situations, such as 4044

Figure 10. NARR sea level pressure composites (Pa), each for 10 days in June 2001. The upper frame shows weak-wind days on the northern California coast, and the lower frame shows strong wind days. Contour interval is 100 Pa. periods of a weak coastal wind (such as relaxation [Beardsley et al., 1987]). [31] Wind speeds (Figure 11a) above 8 m s 1 (June area average) extend west and south from Cape Blanco, while the speed above 11 m s 1 (one standard deviation above the area mean) is an isolated expansion fan on the downwind side of Cape Blanco. Approaching the north side of Cape Mendocino, the flow slows in a compression bulge, accelerates above 13 m s 1 in a cape downwind expansion fan, then starts to decelerate. However, when it reaches Point Arena it is accelerated into another cape downwind expansion fan reaching 13 m s 1. The Cape Mendocino-Point Arena strong wind complex ends in the downwind Point Arena expansion fan, north of San Francisco [Haack et al., 2001]. On the upwind side and next to the coast of all three of these capes, the flow slows in a narrow compression bulge. All of these robust hydraulic features are apparent in the QuikSCAT June mean wind speed (Figure 5). [32] The along-shore sea level pressure gradient features (Figure 11b) coincide with the wind structure (Figure 11a). It increases on the downwind side of Cape Blanco, and even more so in the Cape Mendocino-Point Arena area, but then it quickly switches to a weak gradient on the south side of the Point Arena expansion fan maxima (Figure 11a). A weakening of the along-coast pressure gradient in the compression bulge on the upwind side of the capes is most noticeable for the large Cape Mendocino. [33] The marine layer is the WRF PBL, for which the height (Figure 11c) is determined as that where the vertical fluxes are minimum [Hong et al., 2006], and which is near the actual air temperature inversion and cloud base height. The computed height is not sensitive to the smaller-scale flow adjustments apparent in the wind speed (Figure 11a). This computation is only partially successful, in that the WRF coastal PBL height, which is lower than that of the inbound flow north of Cape Blanco, is 150 230 m between 4045

Figure 11. (a) Wind speed in m s 1, contour interval is 1 m s 1 ; (b) sea level pressure in hpa, contour interval is 0.5 hpa; (c) planetary boundary layer height in m, contour interval is 100 m; (d) liquid water path in g m 3, contour interval is 5 g m 3 for the WRF composite mean of 10 days with strong northwesterly flow during June 2001. The surface conditions along the four bold straight lines (transects) in Figure 11a are shown in Figure 8a. Cape Blanco and Point Conception. This is similar to the inversion base height mean range measured along the same area in June July 1996 [Dorman et al., 2000]. [34] The WRF liquid water path (LWP) is in the form of cloud droplets, and the path is the depth of liquid water that would result if all of the drops were collected on the surface below (Figure 11d). During the summer, almost all of the drops over the ocean are in the marine layer [Koracin and Dorman, 2001]. Further, the marine cloud amount tends to be proportional to the marine layer depth through convergence [Dorman et al., 2000; Koracin and Dorman, 2001]. WRF is moderately successful in that the smallest path (and cloud cover) is in the cape downwind expansion fans, with somewhat larger values on the upwind cape compression bulges and much larger values offshore; this is well supported by satellite images [Dorman et al., 2000]. 6.3. WRF 10 Day Simulated Composites and 17 June 2001 Simulated Events Along Transects [35] Figure 11a shows the location of the WRF simulated marine boundary layer properties along transects, which are presented in Figure 12 for the 10 day composite (left) and the 17 June event (right) shown in Figure 1. Flow is from right to left. The similarity between the 10 day composite and the single event supports the composite as statically sound. The vertical lines mark the positions of the three major capes. [36] The transect closest to the coast, A, has the greatest response to the capes, while the farthest offshore transect, D, responds more smoothly to the general area conditions. The others are generally between these two (Figure 12b, left, for composite). The greatest variable response is to Cape Mendocino, followed by Cape Blanco, while there is 4046

Figure 12. (a) WRF simulated sea level pressure (SLP); (b) wind speed; (c) planetary boundary layer height (PBL height); and (d) liquid water path (LWP); along the transects shown in Figure 11a for (left) 10 day composite wind speeds and (right) at 0300 UTC 17 June. North is on the right side of the frames. little response to Point Arena, due its greater distance from the transects. Driving the flow is the large-scale pressure (Figure 11a, transect A), which is lower toward the south and toward the coast. [37] The composite inbound flow approaches the north side of Cape Blanco and responds to the cape (Figure 11, left). The Cape Blanco downwind expansion fan increases along the pressure gradient (Figure 11a, left, transect A), causing a sharp increase in wind speed (left, b), a decrease in the PBL height (left, c), and a modest decrease in the LWP (left, d). The compression bulge on the upwind side of Cape Mendocino weakens the pressure gradient on transect A, resulting in a slowing of speed (left, b), but a jump increase in the PBL height and LWP. Continuing along transect A, the Cape Mendocino downwind expansion fan causes an increase in the pressure gradient, an increase in wind speed (greater than downwind of Cape Blanco), and modest decreases in the PBL height and LWP (and cloud). Similar responses to variables along transects occur in the 17 June single event (right), although the expansion fan wind speed along transect A was greatest on the Cape Blanco downwind side. 7. Wind Stress and Wind Stress Curl Forcing on the Coastal Ocean [38] In the previous section, it was shown that WRF successfully simulates the coastal atmosphere and represents events. The coastal atmosphere drives biologically important coastal ocean upwelling through the forcing of wind stress and wind stress curl. 7.1. Wind Stress Forcing [39] The along-coast wind stress component causes Ekman transport ocean flow across the bottom of the shelf and upwelling cold water over the inner shelf. Upwelling dominates the local lower atmosphere and climate via the marine layer and the cloud field. Feedback to the ocean occurs through thermally driven cross-coast winds, a strengthened air temperature inversion, and a modified drag coefficient. [40] As with the winds, WRF wind stress analysis is based on twice-a-day samples, at 0600 and 1800 LST, to match QuikSCAT passes. As the wind speed is basically squared to derive the wind stress, so the wind maxima in Figure 5 are in the same locations as the wind stress maxima in Figure 13. The significant role of the five major capes in the wind stress field is readily apparent in the WRF June 2001 wind stress field. As expected, the wind stress maxima were within 25 km of the coast on the downwind sides of the major capes. [41] QuikSCAT and WRF agree on the general largescale structure of the west coast wind stress. Both WRF and QuikSCAT have upwind initiation of higher stress starting at Cape Blanco and its downwind termination at Point Conception with the 0.4 Pa contour. Both are similar in terms of the general offshore extent of the central part of the wind stress maximum as represented by the nearaverage contour value of 0.14 Pa which crosses the 36 N latitude at 124.5 W for WRF and at 126 W for QuikSCAT. The highest closed contour values are also similar at 0.22 Pa (WRF) and 0.24 Pa (QuikSCAT). [42] The greatest inconsistency between these analyses is the strength of the stress between Point Sur and Point Conception. WRF s highest closed contour value (0.12 Pa) touching Cape Mendocino and containing all maxima extends 120 km downwind of Point Conception, but according to QuikSCAT this contour (also 0.12 Pa) intersects the coast 155 km to the north of Point Conception. In addition, the cape s downwind expansion fans differ in 4047

Figure 13. June 2001 sea surface wind stress (Pa) for (a) QuikSCAT and (b) WRF. Contours are in 0.2 10 2 Pa. details. For WRF, the strongest stress, as represented by the highest closed contour value (0.22 Pa), is in the expansion fans downwind of both Point Arena and Point Sur and within 25 km of the coast. In contrast, QuikSCAT s greatest stress for the entire coastal area is in an abnormally shaped expansion fan 192 km to the SSW downwind from Cape Mendocino, with a highest closed contour value of 0.26 Pa. The QuikSCAT expansion fan with the second greatest value includes two 0.20 Pa closed contour centers 200 291 km to the SSW of Point Arena. [43] If the buoy and aircraft measurements cited for wind comparison in section 4.1 were converted to stress, they would overwhelmingly support WRF over QuikSCAT, due to the higher stress extending past Point Conception and to the downwind maxima being within 25 km of the coast for the four southern capes. The exception is Cape Mendocino, where the wind stress maximum within 25 km of the downwind side is not apparent in the WRF analysis, due to the scale of the figure and the contour interval, whereas the downwind maximum in the QuikSCAT analysis is to the SSW and separated from the cape. Both of these QuikS- CAT features differ from most other measurements such as aircraft [Winant et al., 1988; Rogers et al., 1998; Dorman et al., 1999; Ström et al., 2001; Edwards, 2000] and numerical modeling [Koracin and Dorman, 2001; Koracin et al., 2004]. However, as all of the observations are from different years and include averages based on different criteria, it is possible that there is no real conflict. [44] Our study is generally consistent with previous studies. Pickett and Paduan [2003] used Coupled Ocean/ Atmosphere Mesoscale Prediction System (COAMPS) with a 9 km grid to compute summer wind stress which agrees with WRF for the expansion fan maxima being within 25 km of the coast on the downwind sides of all major capes. The strongest stress over the analysis area was 0.24 Pa, which was located in the downwind expansion fans of Point Arena, Point Sur and Point Conception, whereas our study showed Pont Conception to weaker than the other two. Cape Mendocino s downwind expansion fan maximum was 0.18 Pa and Cape Blanco s was 0.16 Pa. The highest closed contour wind speed value extending from Cape Mendocino to Point Conception was 0.12 Pa. [45] Koracin et al. [2004] reported a generally similar large-scale maximum with its highest shaded contour value of about 0.08 Pa extending from Cape Mendocino to Point Conception, as well as strong and equal expansion fans close to the downwind sides of Cape Mendocino and Point Arena with maximum shaded contour values between 0.1 Pa and 0.12 Pa. Haack et al. [2001] used COAMPS with a 9 km grid for a 29 day average stress in June 2004 that is similar to the WRF stress in features such as wind stress maxima downwind of every major cape. However, their strongest closed contour in that study was 0.2 Pa downwind of Cape Blanco, followed by lesser values downwind of Cape Mendocino Point Area, and Point Sur, with the lowest value being 0.125 Pa downwind of Point Conception. The largest closed contour value extending from Cape Mendocino to Point Conception was 0.10 Pa, and it extended to north of Cape Blanco. Chelton et al. [2007] based a June to September wind stress study on QuikSCAT with maximum values of about 0.20 Pa. That analysis is generally consistent with the June QuikSCAT analysis shown in Figure 12, but it shows stronger stress associated with Cape Blanco, which might be due to the longer time period and different meteorological setting. 7.2. Wind Stress Curl Forcing [46] Wind stress curl causes ocean upwelling when there are horizontal wind stress gradients. A positive curl upwells cold water to the surface, while a negative curl downwells surface water that is replaced with surrounding surface water. This can result in a higher surface water temperature at a location if upwelling is replaced with downwelling or if the source surface water is from farther offshore, which is usually warmer along the California-Southern Oregon 4048

coast. It might be expected that the strongest positive wind stress curl will occur over the short distance between the midshelf with the strongest wind stress and the coast. However, a dense buoy network reveals rapidly changing, strong alongshore and cross-shore wind stress gradients over the shelf [Dorman et al., 2006]. Wind stress curl upwelling is generally considered to be weaker, but potentially significant, compared to the coast-parallel wind stress upwelling over the shelf. The wind stress curl can be significant even for weaker winds and wind stress [Beg Paklar et al., 2009]. [47] The WRF simulated June 2001 wind stress curl (Figure 14) is dominated by a narrow coastal band of positive curl (upwelling colder water) between Cape Blanco and Point Conception, which typically extending about 40 km offshore but ranging from 20 to 120 km. The major capes have a cross-coast band of positive curl that is 1.4 3.6 times wider on the upwind side than the downwind side. The largest positive wind stress curl area away from the coast is to the southeast of Point Conception, extending from the coast to west of 120 W and to south of 32 N, where the extreme coastal bend at Point Conception causes an open-water positive curl, due to decreasing wind speeds and a cyclonic curvature of marine air turning toward the east [Koracin et al., 2004; Dorman and Koracin, 2008]. In contrast, almost all of the area offshore of the narrow coastal band of positive curl between Cape Blanco and Point Conception has negative wind stress curl (downwelling). The second-most negative closed contour value in the analysis is 40 10 8 Pa m 1, with one downwind of each of the major capes, and the largest extending 340 km in a north-south direction, downwind of Cape Mendocino. [48] The general QuikSCAT wind stress curl features rather agree with those of WRF (Figure 14), which include a zone of positive curl along the inner coast and negative curl over most of the offshore north of 34 N. The significant difference is that the QuikSCAT positive band along the coast between Cape Mendocino and Point Arena is about 120 km wide, similar to the wider positive areas in WRF. However, the QuikSCAT positive band extending 310 km to the west of the coast along 40 N is entirely missing from the WRF analysis. In addition, a smaller-scale structure is obscured in the QuikSCAT wind stress curl analysis as the relatively high wind stress curl standard deviation as compared to the mean (Figure 15a). [49] The QuikSCAT and WRF curl standard deviations (Figure 15) share broad similarities, as the highest values of both are at the coast, exceeding 300 10 8 Pa m 1. However, these values are in a narrow zone within 60 km of the coast in the WRF analyses whereas in QuikSCAT they extend from the coast to 220 km offshore along 40 N, decreasing with the lower latitudes to within 40 km of Point Conception. Another difference is that the WRF wind stress curl is quite weak farther than 80 km offshore of the entire coast with values less than 50 10 8 Pa m 1 whereas the majority of the QuikSCAT values are much larger, ranging 100 400 10 8 Pa m 1 in the area north of 34 N and east of 128 W. [50] Earlier investigations include the Pickett and Paduan [2003] analysis, in which there is a narrow, positive wind stress curl maximum exceeding 800 10 8 Pa m 1 extending less than 30 km offshore downwind of every major cape, with positive wind stress curl extending up to 220 km offshore, much greater than that shown by WRF. Koracin et al. [2004] presented an average June 1999 wind stress curl with most of the positive values within 30 km of the coast and the largest values downwind of the capes, with magnitudes less than 200 10 8 Pa m 1. Most of the area north of 30 N and more than 50 km offshore had weak negative values with magnitudes less than 50 10 8 Pa m 1. Haack et al. [2001] presented a summer mean COAMPS analysis with a positive wind stress curl band along the inner Oregon and California coasts that exceeded 25 10 8 Pa m 1, or 1/6 that of WRF, with cross-coast widths up to 190 km north and up to 260 km south of Point Conception. Negative values in the range of 7.5 to 25 10 8 Pa m 1 Figure 14. June 2001 sea level wind stress curl (Pa m 1 ) for (a) QuikSCAT and (b) WRF. Contour interval varies; see color bar for values. 4049

Figure 15. June 2001 sea level wind stress curl standard deviation (Pa m 2 ) for (a) QuikSCAT and (b) WRF. Contours are 10 8 Pa m 2. Contour intervals vary; see color bar for values. dominate most of the area farther than about 200 km offshore. The greatest wind stress curl standard deviation was in an inshore band less than 200 km wide with values less than 60 10 8 Pa m 1 and values of less than 18 10 8 Pa m 1 that were predominant a greater distance offshore. [51] In summary, there is agreement between WRF and the more recent analyses on a relatively narrow band of positive curl on the coast, where there is significant crosscoast and along-coast structure coincident with the major capes. All the analyses agree on weaker magnitude, negative curl offshore. 8. Conclusions [52] In this study, a high-resolution QuikSCAT footprint with an improved narrow land mask for a 12.5 km data set proved advantageous for investigating a coastal zone with great inhomogeneity and mesoscale coastal wind events along the southern Oregon California coast in June 2001. The nature of atmospheric events for winds greater than one standard deviation above the area speed mean (11 m s 1 ) was examined. It was found that coastal areas with wind speeds greater than 11 m s 1 always include two or more major capes, with the highest wind speed close to the coast and downwind of the major capes. [53] There is a quantitative relationship between the threshold pressure gradient and wind speed, which is that an along-coast pressure gradient greater than 0.8 hpa/100 km about a major cape forces the wind speed above 11 m s 1, or one standard deviation above the area wind speed mean. Based upon the Bernoulli principle, the marine layer depth and inversion strength sets the maximum expected downwind cape surface wind speed at about 19 m s 1. [54] NARR successfully resolves the June large-scale along-coast pressure gradient to the extent that it determines the coastal zone where the along-coast pressure gradient is well above a threshold and the along-coast wind speeds are greater than 11 m s 1. However, NARR cannot resolve the event wind speed and pressure gradient magnitudes. [55] WRF 12 km simulations agree with buoy observations and appear to resolve the sea surface winds and wind stress along the California Southern Oregon coast during the summer. While WRF-12 km simulations of wind stress curl produces plausible results, judgment regarding their success will have to await observations sufficient to provide a critical check. It is concluded that summer coastal meteorological events could be investigated by using regional climate models with resolutions of about 12 km or better. [56] Acknowledgment. Funding for this project was partially provided by NASA UCSD contract 20053743 (CD- Scripps), DRI postdoctoral support (JM), and NSF EPSCoR grant EPS-0814372 (DK and JM- DRI). References Beardsley, R. C., C. E. Dorman, C. A. Friehe, L. K. Rosenfeld, and C. D. Winant (1987), Local atmospheric forcing during the Coastal Ocean Dynamics Experiment, I. A description of the marine boundary layer and atmospheric conditions over a Northern California upwelling region, J. Geophys. Res., 92, 1467 1488. Beardsley, R. C., A. G. Enriquez, C. A. Friehe, and C. A. Alessi (1997), Intercomparison of aircraft and buoy measurements of wind and wind stress during SMILE, J. Atmos. Oceanic Technol., 14, 969 977. Beg Paklar, G., D. Koracin, and C. Dorman (2009) Wind-induced ocean circulation along California and Baja California coasts in June 1999, Atmos. Res., 94, 106 133. Burk, S. D., T. Haack, and R. M. Samelson (1998), Mesoscale simulation of supercritical, subcritical and transcritical flow along coastal topography, J. Atmos. Sci., 56, 2780 2795. Chelton, D. B., M. G. Schlax, R. M. Samelson, and R. A. de Szoeke (2007), Global observations of large oceanic eddies, Geophys. Res. Lett., 34, L15606, doi:10.1029/2007gl030812. Chow, V. T. (1959), Open Channel Hydraulics, 680 pp., McGraw-Hill, New York. Dorman, C. E. (1985), Hydraulic control of the northern California marine layer (abstract), Eos Trans. AGU, 66, 914. Dorman, C. E. and D. Koracin (2008), Interaction of the summer marine layer with an extreme California Coastal Bend, Mon. Weather Rev., 136, 2894 2922. Dorman, C. E., and C. D. Winant (1995), Buoy observations of the atmosphere along the west coast of the United States, 1981 1990, J. Geophys. Res., 100, 16,029 16,044. 4050