Surface Wind Observations Research Articles

Near‐surface wind profiles from numerical model predictions. Part II: Verifications against Australia‐wide surface wind observations

AbstractThe new scheme for deriving the near‐surface wind profiles discussed in Ma (in review) is applied to an Australian Bureau of Meteorology operational convective scale model over various domains. Both the new and conventional schemes' diagnostic 10‐m winds are then verified against Australia‐wide automatic weather station observations. Analyses of bulk statistics reveal that the new scheme's 10‐m wind forecasts have generally better accuracy than the current conventional scheme with a consistent reduction of biases over all domains. A widely recognised diurnal bias pattern of surface wind speed over the land is substantially reduced, and the inclusion of Ekman spiral effect on the 10‐m wind marginally improves statistics of the wind direction during the nighttime. The new scheme introduces no systemic bias, given the histogram of a bulk mean bias is analogiased to a Gaussian distribution, and moves the distribution of diagnostic wind speed closer to that observed.

In Situ Observations at the Air‐Sea Interface by Expendable Air‐Deployed Drifters Under Hurricane Michael (2018)

AbstractAn array of surface drifters deployed ahead of Hurricane Michael measured the surface temperature, pressure, directional wind and wave spectra, and surface currents one day before it made landfall as a Category 5 Hurricane. The drifters, 25–50 km apart, spanned two counter‐rotating ocean eddies as Hurricane Michael rapidly intensified. The drifters measured the shift of wave energy between frequency bands in each quadrant of the storm, the response of upper ocean currents, and the resulting cold wake following Michael's passage. Wave energy was greatest in the front quadrants and rapidly decreased in the left‐rear quadrant, where wind and wave energy were misaligned, and components of the wave field were aligned with currents. Hurricane Michael's wave field agreed with previous studies of nondirectional wave spectra across multiple tropical cyclones but had some unique characteristics. The analysis demonstrates how co‐located surface wind and wave observations can complement existing airborne and satellite observations.

The vortex structure and near‐surface winds of Typhoon Faxai (2019) during landfall. Part I: Observational analysis

AbstractThis two‐part study presents a detailed analysis of (a) the vortex structure, (b) the inner core planetary boundary layer (PBL) wind profile, and (c) the overland surface winds of Typhoon Faxai (2019) during landfall observationally (Part I) and in high‐resolution Weather Research and Forecasting model simulations (Part II). Part I presents a comprehensive observational analysis of (a), (b), and (c) of Typhoon Faxai (2019) based on radar dual‐Doppler analysis and spatially dense surface wind observations over the Kanto region of Japan. An empirical model for the wind reduction factor is proposed and validated with surface observations and radar velocity–azimuth display analyses at Narita and Haneda airports, both of which were affected by the passage of Faxai's inner core. Two distinct PBL jets associated with the inner rain band and the eyewall were observed over Narita Airport, which was located to the right of Faxai's track. Based on the empirical model of , it is found that the maximum surface wind speed observed at Narita Airport was caused by the peak of due to a strong PBL jet associated with the eyewall located as close as 0.3 km from the ground. In addition, the wind swath analysis shows that a large area far inland on the right side of Faxai's track experienced strong surface 10‐min winds due to the combination of the passage of the eyewall PBL jet and the small surface roughness length around agricultural land such as paddy fields and farm fields.

Proxy Observations of Surface Wind from a Globally Distributed Network of Wave Buoys

Abstract In the equilibrium range of the wave spectrum’s high-frequency tail, energy levels are proportional to the wind friction velocity. As a consequence of this intrinsic coupling, spectral tail energy levels can be used as proxy observations of surface stress and wind speed when direct observations are unavailable. Proxy observations from drifting wave-buoy networks can therefore augment existing remote sensing capabilities by providing long dwell observations of surface winds. Here we consider the skill of proxy wind estimates obtained from observations recorded by the globally distributed Sofar Spotter network (observations from 2021 to 2022) when compared with collocated observations derived from satellites (yielding over 20 000 collocations) and reanalysis data. We consider physics-motivated parameterizations (based on frequency−4 universal tail assumption), inverse modeling (estimate wind speed from spectral energy balance), and a data-driven approach (artificial neural network) as potential methods. Evaluation of trained/calibrated models on unseen test data reveals comparable performance across methods with generally of order 1 m s−1 root-mean-square difference with satellite observations.

Characterizing the Effect of Ocean Surface Currents on Advanced Scatterometer (ASCAT) Winds Using Open Ocean Moored Buoy Data

The ocean surface current influences the roughness of the sea surface, subsequently affecting the scatterometer’s measurement of wind speed. In this study, the effect of surface currents on ASCAT-retrieved winds is investigated based on in-situ observations of both surface winds and currents from 40 open ocean moored buoys in the tropical and mid-latitude oceans. A total of 28,803 data triplets, consisting of buoy-observed wind vectors, current vectors, and ASCAT Level 2 wind vectors, were collected from the dataset spanning over 10 years. It is found that the bias between scatterometer-retrieved wind speed and buoy-observed wind speed is negatively correlated with the ocean surface current speed. The wind speed bias is approximately 0.96 times the magnitude of the downwind surface current. The root-mean-square error between the ASCAT wind speeds and buoy observations is reduced by about 15% if rectification with ocean surface currents is involved. Therefore, it is essential to incorporate surface current information into wind speed calibration, particularly in regions with strong surface currents.

An Observational Study of Typhoon Talim over the Northern Part of the South China Sea in July 2023

Extensive surface and upper air measurements of a typhoon over the northern part of the South China Sea, namely, Typhoon Talim in July 2023, are documented and analysed in this paper. A number of features have been observed from the upper air measurements. First, the log law and the power law were found to be appropriate in fitting the wind profiles of the typhoon in the first 1000 m or so above the sea surface. Second, a low-level jet with the height of the maximum wind speed of around 1000 m was observed in the lower troposphere from the observations of the radar wind profilers. This paper is also novel from the perspectives that the vertical wind profile from a Doppler LIDAR on an offshore platform over the northern part of the South China sea and ocean radar data are used to analyse the surface wind observations of a typhoon in the region. The results of this paper would be useful in understanding the structure of tropical cyclones, e.g., in wind engineering applications.

Retrieving Ocean Surface Winds and Waves from Augmented Dual-Polarization Sentinel-1 SAR Data Using Deep Convolutional Residual Networks

Sea surface winds and waves are very important phenomena that exist in the air–sea boundary layer. With the advent of climate change, cascade effects are bringing more attention to these phenomena as warmer sea surface temperatures bring about stronger winds, thereby altering global wave conditions. Synthetic aperture radar (SAR) is a powerful sensor for high-resolution surface wind and wave observations and has accumulated large quantities of data. Furthermore, deep learning methods have been increasingly utilized in geoscience, especially the inversion of ocean information from SAR imagery. Here, we propose a method to invert various parameters of ocean surface winds and waves using Sentinel-1 SAR IW mode data. To ensure this method is more robust and scalable, we augmented the input data with dual-polarized SAR imagery, an incident angle, and a more constrained homogeneity test. This method adopts a deeper structure in order to retrieve more wind and wave parameters, and the use of residual networks can accelerate training convergence and improve regression accuracy. Using 1600 training samples filtered by a novel homogeneity test and with significant wave heights between 0 and 10 m, results from error parameters including the root mean square error (RMSE), scatter index (SI), and correlation coefficient (COR) show the great performance of this proposed method. The RMSE is 0.45 m, 0.76 s, and 1.90 m/s for the significant wave height, mean wave period, and wind speed, respectively. Furthermore, the temporal variation and spatial distribution of the estimates are consistent with China–France Oceanography Satellite (CFOSAT) observations, buoy measurements, WaveWatch3 regional model data, and ERA5 reanalysis data.

A turbulent orographic form drag scheme accounting for anisotropy and orientation for kilometer‐ to subkilometer‐scale models

AbstractThis paper presents a turbulent orographic form drag (TOFD) parameterization scheme that takes into account the directional effects stemming from the angle between the low‐level wind and the principal axis of small‐scale orography. Suitable for models with both kilometer and subkilometer horizontal resolutions, this scheme builds upon prior theoretical and numerical studies to formulate surface TOFD based on the slope and direction of the sinusoidal hills. In this study, we proposed a straightforward function to calculate the surface TOFD for various orographic aspect ratios and directional parameters. The vertical decay of the drag is modeled with a scale twice the standard deviation of the sub‐grid orography. A comparison with numerous large‐eddy simulations featuring a single ellipsoidal hill demonstrates that our scheme effectively captures the dependence of drag on factors such as maximum slope, aspect ratio, the angle between low‐level wind and the principle axis, and hill height. We recommend calculating the sub‐grid orographic parameters using a well‐established method and digital terrain elevation data with a horizontal resolution less than a 100 m. This will allow for representation on orographic scales of both kilometers and subkilometers. Real‐case numerical weather prediction tests are conducted and verified with dense surface wind observations. The proposed scheme improves surface wind simulation compared to a renowned TOFD scheme, and also effectively exhibits the wind response to orographic anisotropy.

Effects of Wind-Induced Error on the Climatology and Trends of Observed Precipitation in China from 1960 to 2018

Abstract Since the 1950s, precipitation has been measured at national weather stations in China using national standard precipitation gauges. Gauges without a wind fence can significantly underestimate precipitation amounts, while this undercatch bias is closely related to surface wind speed and precipitation type. The observed surface wind speed across China has substantially declined during the past decades. Therefore, this study investigated the wind-induced error of the observed precipitation and its impact on regional and national mean trends in precipitation over China due to the reduction in surface wind speed. It was found that the wind-induced error for the mean annual precipitation nationwide was 29.28 mm yr−1, accounting for 3.92% of total precipitation amount. The variation of precipitation at the regional scale was large but the trends were both positive and negative, approximately cancelling at the national level and resulting in a small national mean trend. The raw observation data showed that the national mean precipitation increased at a rate of 1.85 mm yr−1 (10 a)−1 from 1960 to 2018, which was reduced to 0.33 mm yr−1 (10 a)−1 after correction, demonstrating that the correction of wind-induced error had an important impact on the trend of annual precipitation. Meanwhile, the reduction of surface wind speed was consistent at both the regional and national levels. On average, the wind-induced errors decreased at rates of −1.52, −1.34, and −0.14 mm yr−1 (10 a)−1 for total precipitation, rainfall, and snowfall, respectively. It illustrates that the decreases of the wind-induced error result in the increasing precipitation of raw observation.

Homogenization of Observed Surface Wind Speed Based on Geostrophic Wind Theory over China from 1970 to 2017

Abstract The observed surface wind speed (SWS) over China has declined in the past four decades, and recently, the trend has reversed, which is known as SWS stilling and recovery. The observed SWS is vulnerable to changes in nonclimatic factors, i.e., inhomogeneity. Unfortunately, most of the existing studies on the long-term trend of SWS were based on raw datasets without homogenization. In this study, by means of geostrophic wind speed and penalized maximal t test, we conduct a systematic homogeneity test and exploration of the homogenization impact for SWS at over 2000 stations in China from 1970 to 2017. The results show that the inhomogeneity in the observed SWS over China is detectable at 59% of national weather stations. The breakpoint years are mainly concentrated in the late 1970s, mid-1990s, and early 2000s. Overall, 18% of breakpoints are caused by station relocations, and the remaining breakpoints are likely related to anemometer replacement and measurement environment changes that occurred during the mid-1990s and early 2000s. After homogenization, the decreasing trend in SWS during 1970–2017 decreased from −0.15 to −0.05 m s−1 decade−1. The homogenized SWS recovery period advanced from the early twenty-first century to the early 1990s, which is consistent with the SWS variations, excluding the impact of urbanization around weather stations. The phase change in the Western Hemisphere warm pool (WHWP) might be one of the causes of homogenized SWS recovery.

Observed Surface Wind Field Structure of Severe Tropical Cyclones and Associated Precipitation

Using the International Best Track Archive for Climate Stewardship (IBTrACS) dataset, this study assessed the surface wind fields from high spatial resolution Synthetic Aperture Radar (SAR) observations, the fifth generation ECMWF reanalysis for the global climate and weather (ERA5) data and the Tropical Cyclone Winds and Inflow Angle Asymmetry (TCIAA) wind model. The results showed that SAR data are sufficient to reveal the surface wind field near a TC center and can accurately describe TC intensity and size under severe TC conditions. Then, a new, improved statistical wind structure model was set up using ERA5 data alone based on the assessment. In addition, the warm sea surface (SST > 26.5 °C) produced stronger TC wind fields and heavier precipitation. When the SST was higher (lower), the heavy rainfall was located on the left (right) side of the TC track and the strong positive correlation between wind speed and precipitation increased as the SST decreased.

Satellite Remote Sensing of Surface Winds, Waves, and Currents: Where are we Now?

AbstractThis review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields.

Key Role of Subdaily Wind Variability for Tropical Surface Wind Stress

Abstract High-frequency observations of surface winds over the open ocean are available only at limited locations. However, these observations are essential for assessing atmospheric influences on the ocean, validating reanalysis products, and building parameterization schemes. By analyzing high-frequency measurements from the Global Tropical Moored Buoy Array, the effects of subdaily winds on the mean surface wind stress magnitude are systematically examined. Subdaily winds account for 12.4% of the total stress magnitude on average. The contribution is enhanced over the intertropical convergence zone and reaches a maximum (28.5%) in the equatorial western Pacific. The magnitude of the contribution is primarily determined by the kinetic energy of subdaily winds. Compared to the buoy observations, the ERA5 and MERRA2 subdaily winds underestimate this contribution by 51% and 63% due to underestimations of subdaily kinetic energy, leading to 7% and 8% underestimations in the total stress magnitude, respectively. Two new gustiness parameterization schemes related to precipitation are developed to account for the effect of subdaily winds, explaining ∼80% of the contribution from subdaily winds. Considering the importance of wind stress for ocean–atmosphere interactions, the inclusion of these parameterization schemes in climate models is expected to substantially improve simulations of large-scale climate variability. Significance Statement Surface wind stress drives upper-ocean circulation, which is critical for the redistribution of mass, momentum, and energy in the ocean. Moreover, it is one of the key factors controlling oceanic turbulent mixing and therefore has significant impacts on the distribution of temperature, salinity, and associated ocean variability. Using high-resolution buoy observations, this study highlights the importance of subdaily winds for integrated wind stress estimates. In addition, it finds that current state-of-the-art and widely used reanalysis products largely underestimate the effect of subdaily winds. Two new parameterization schemes are developed, leading to a better representation of the effect of subdaily winds. Including the proposed parameterization schemes in climate models is expected to substantially improve their simulations of large-scale climate variability.

Generation of Non-Linear Technique Based 6 Hourly Wind Reanalysis Products Using SCATSAT-1 and Numerical Weather Prediction Model Outputs

We combined observations of ocean surface winds from Indian SCATterometer SATellite-1 (SCATSAT-1) with a background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium-Range Weather Forecast (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. We are following the concept from the modern particle filter technique, which does not represent the model probability density function (PDF) as Gaussian. We generated the 6-hourly hybrid winds for 2018 and validated them using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform (CCMP) dataset and global buoy data from National Data Buoy Centre (NDBC). The results suggest the potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and bias along the swath. The study shows that the generated hybrid winds are of prime quality compared with the already existing daily products available from Indian Space Research Organization (ISRO).

Modeling and estimation of hurricane wind hazard affecting Mexican coastal regions

In the present study, we develop a stochastic track model that can be used to sample the synthetic tropical cyclone (TC) (i.e., hurricane) tracks affecting Mexico with their genesis from the Atlantic basin and the northeastern Pacific basin. The developed model is validated based on the comparison of the statistics of the main characteristics of the historical and synthetic landfalling TC events. We estimate the TC wind hazard for the coastal regions of Mexico by using the historical or synthetic TC tracks in combination with a gradient wind field based model or a vertically averaged boundary layer slab model. Such a TC wind hazard assessment for Mexico is the first of its kind. The results indicate that the use of a short period of the historical tracks for TC wind hazard is inadequate, and the use of the simple gradient wind field based model with well-calibrated scaling factors is efficient and effective for estimating TC wind hazard. The comparison of the probability distributions for the extreme TC winds obtained using the developed stochastic track model to those based on surface wind observations for a few meteorological stations confirms the adequacy of the model.

Evaluation of meteorological reanalysis data over the tropical Western Indian Ocean based on buoy observations in 2022

The Indian Ocean is the least observed of the three oceans, and a large amount of reanalysis data has to be used to study the Indian Ocean. Observations of sea surface winds, temperature, and sea level pressure, measured from Bailong real-time buoy system deployed in the western Indian Ocean, are being used to assess the capabilities of major high-frequency atmospheric reanalysis products in the western Indian Ocean region. During the study period, the atmospheric reanalysis data can accurately reproduce the temperature and sea level pressure fields, but the surface wind fields, especially for the meridional winds, are poorly described. ERA5 provides a better description of temperature and sea level pressure among all datasets. For the surface wind field, the reanalysis dataset overestimate/underestimate the intensity of the zonal/meridional winds, respectively, while the R-2 presents a worse description. Apart from the comparison of raw data, the diurnal variation of the three variables was also evaluated, and the results indicate a significant gap between the observation and reanalysis data. This study suggests that the current high-frequency reanalysis data still have shortcomings in describing atmospheric parameters in the tropical western Indian Ocean region.

Investigation of Tropical Cyclone Wind Models With Application to Storm Tide Simulations

AbstractThe hazards induced by tropical cyclones (TCs), for example, high winds, extreme precipitation, and storm tides, are closely related to the TC surface wind field. Parametric models for TC surface wind distribution have been widely used for hazards and risk analysis due to their simplicity and efficiency in application. Here we revisit the parametric modeling of TC wind fields, including the symmetrical and asymmetrical components, and its applications in storm tide modeling in the North Atlantic. The asymmetrical wind field has been related to TC motion and vertical wind shear; however, we find that a simple and empirical background‐wind model, based solely on a rotation and scaling of the TC motion vector, can largely capture the observed surface wind asymmetry. The implicit inclusion of the wind shear effect can be understood with the climatological relationship between the general TC motion and wind shear directions during hurricane seasons. For the symmetric wind field, the widely used Holland wind profile is chosen as a benchmark model, and we find that a physics‐based complete wind profile model connecting the inner core and outer region performs superiorly compared to a wind analysis data set. When used as wind forcing for storm tide simulations, the physics‐based complete wind profile integrated with the background‐wind asymmetry model can reproduce the observed storm tides with lower errors than the often‐used Holland model coupled with a translation‐speed‐based method.

Modelling wind speed across Zambia: Implications for wind energy

AbstractWind energy is a key option in global dialogues about climate change mitigation. Here, we combined observations from surface wind stations, reanalysis datasets, and state‐of‐the‐art regional climate models from the Coordinated Regional Climate Downscaling Experiment (CORDEX Africa) to study the current and future wind energy potential in Zambia. We found that winds are dominated by southeasterlies and are rarely strong with an average speed of 2.8 m·s−1. When we converted the observed surface wind speed to a turbine hub height of 100 m, we found a ~38% increase in mean wind speed for the period 1981–2000. Further, both simulated and observed wind speed data show statistically significant increments across much of the country. The only areas that divert from this upward trend of wind speeds are the low land terrains of the Eastern Province bordering Malawi. Examining projections of wind power density (WPD), we found that although wind speed is increasing, it is still generally too weak to support large‐scale wind power generation. We found a meagre projected annual average WPD of 46.6 W·m−2. The highest WPDs of ~80 W·m−2 are projected in the northern and central parts of the country while the lowest are to be expected along the Luangwa valley in agreement with wind speed simulations. On average, Zambia is expected to experience minor WPD increments of 0.004 W·m−2 per year from 2031 to 2050. We conclude that small‐scale wind turbines that accommodate cut‐in wind speeds of 3.8 m·s−1 are the most suitable for power generation in Zambia. Further, given the limitations of small wind turbines, they are best suited for rural and suburban areas of the country where obstructions are few, thus making them ideal for complementing the government of the Republic of Zambia's rural electrification efforts.

On the High Winds in the Tianshan Grand Canyon in Northwest China: General Features, Synoptic Conditions, and Mesoscale Structures

This work studies the characteristics of high winds in the Tianshan Grand Canyon (TGC), Northwest China by using surface wind observations at six automatic weather stations during 2017–2018. Three high wind indices are examined, namely, high wind hour (HWH), station high wind event (SHWE) and regional high wind event (RHWE). SHWE denotes persistent high winds of more than 3 h at an individual station while RHWE is defined for the southern TGC as a whole. High winds are mainly northwesterly/westerly, occurring predominantly in southern TGC. HWHs most often occur in spring and summer, while winter and spring HWHs possess the strongest intensity. The occurrence of HWHs exhibits an apparent diurnal variation, most frequent in the afternoon and evening while least from mid-night to early morning. SHWEs and RHWEs are prone to take place in spring, possessing relatively long lifetime and strong intensity. According to composite analysis of the 0.25° FNL reanalysis, favorable synoptic conditions are obtained for the persistent high winds in spring. Of great importance is the mid-tropospheric trough in the mid-high latitudes located to the north (i.e., upstream) of the TGC. The cold advection behind the trough cools and stabilizes the mid-lower troposphere, while the post-trough sinking motion causes a surface high that accelerates the low-level northwesterly wind. The synoptic thermal and dynamical forcing help set an upstream flow of moderate Froude number such that the mesoscale orographic flow traversing the TGC is in the nonlinear high-drag regime. Large-amplitude gravity waves are excited, with the isentropes descending abruptly over the lee slope which resembles internal hydraulic jump. Downslope windstorms are produced at the expense of flow potential energy as the subcritical upstream flow is transitioned to supercritical at the TGC peak. These findings have important implications on the formation and prediction of high winds in the TGC.

The Dynamical Role of the Chesapeake Bay on the Local Ozone Pollution Using Mesoscale Modeling—A Case Study

This study investigated the dynamic influence of the Chesapeake Bay (CB) on local ozone (O3) concentration and distribution using a weather forecasting model. The Weather Research and Forecasting model coupled with Chemistry (WRF–Chem) was employed to simulate O3 production and transportation near the CB. Baseline (water) as well as sensitivity (nowater) model experiments of bay circulation were carried out with and without bay water by changing the water surface from water to land (loam). First, the model performance simulating O3 was evaluated using the baseline experiment results and AirNow surface wind and O3 observations. The results showed that the model overestimates surface O3 by up to 20–30%. Further, the comparisons of the baseline and sensitivity experiments revealed higher O3 mixing ratios, primarily due to the resulting bay breeze circulation. These increases, after considering model overestimation, represent a mean bay dynamics circulation-induced contribution of up to 10% at night and 5% during the day. Furthermore, the boundary layer over northern CB, where it is at its narrowest width, was higher (by 1.2 km on average) during daytime due to higher surface temperatures observed. The boundary layer depth difference between the northern, central, and southern regions of the bay leads to a differential in the role of bay circulation dynamics in the observed O3 increase. The relatively wider swath of water surface over southern CB resulted in a lower boundary layer depth and stronger breeze circulation and this circulation contributed to O3 concentrations. Moreover, since the case selected has a minimal bay breeze circulation, the associated surface ozone enhancements represent what is expected at least at a minimum.