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Transitional changes in the atmospheric boundary layer (ABL) are known to facilitate the onset of terrestrial fog, which is defined as a condition with near‐surface visibility <1 km due to airborne water droplets. In particular, the evening transition from a daytime convective ABL to a night‐time stable ABL provides favorable conditions for fog. This article describes a local fog event observed during the evening transition at a Canadian islet in the north Atlantic known as Sable Island during the "Fog and Turbulence Interactions in the Marine Atmosphere (Fatima)" field campaign. The comprehensive set of data collected using a myriad of instruments covering a wide range of scales allowed identification of a novel mechanism underlying this fog event. Therein an ocean–land discontinuity created a flow regime consisting of several stacked boundary layers, interplay of which produced a thin low‐level cloud that then diffused downward to the surface, causing visibility reduction. This mechanism offers useful insights on the role of boundary layers, stratification, and turbulence in fog genesis over oceanic islands. [ABSTRACT FROM AUTHOR]

First-ever measurements of the turbulent kinetic energy (TKE) dissipation rate in the northeastern Strait of Magellan (Segunda Angostura region) taken in March 2019 are reported here. At the time of microstructure measurements, the magnitude of the reversing tidal current ranged between 0.8 and 1.2 ms−1. The probability distribution of the TKE dissipation rate in the water interior above the bottom boundary layer was lognormal with a high median value ε med MS = 1.2 × 10 - 6 Wkg−1. Strong vertical shear, 1 - 2 × 10 - 2 s−1, in the weakly stratified water interior ensued a sub-critical gradient Richardson number R i < 10 - 1 - 10 - 2 . In the bottom boundary layer (BBL), the vertical shear and the TKE dissipation rate both decreased exponentially with the distance from the seafloor ξ , leading to a turbulent regime with an eddy viscosity K M ∼ 10 - 3 m2/s, which varied with time and location, while being independent of the vertical coordinate in the upper part of BBL (for ξ > ∼ 2 meters above the bottom). [ABSTRACT FROM AUTHOR]

Coastal Santa Barbara is among the most exposed communities to wildfire hazards in Southern California. Downslope, dry, and gusty windstorms are frequently observed on the south-facing slopes of the Santa Ynez Mountains that separate the Pacific Ocean from the Santa Ynez valley. These winds, known as "Sundowners," peak after sunset and are strong throughout the night and early morning. The Sundowner Winds Experiment (SWEX) was a field campaign funded by the National Science Foundation that took place in Santa Barbara, California, between 1 April and 15 May 2022. It was a collaborative effort of 10 institutions to advance understanding and predictability of Sundowners, while providing rich datasets for developing new theories of downslope windstorms in coastal environments with similar geographic and climatic characteristics. Sundowner spatiotemporal characteristics are controlled by complex interactions among atmospheric processes occurring upstream (Santa Ynez valley), and downstream due to the influence of a cool and stable marine boundary layer. SWEX was designed to enhance spatial measurements to resolve local circulations and vertical structure from the surface to the midtroposphere and from the Santa Barbara Channel to the Santa Ynez valley. This article discusses how SWEX brought cutting-edge science and the strengths of multiple ground-based and mobile instrument platforms to bear on this important problem. Among them are flux towers, mobile and stationary lidars, wind profilers, ceilometers, radiosondes, and an aircraft equipped with three lidars and a dropsonde system. The unique features observed during SWEX using this network of sophisticated instruments are discussed here. [ABSTRACT FROM AUTHOR]

Introduction: This study presents the application of machine learning (ML) to evaluate marine fog visibility conditions and nowcasting of visibility based on the FATIMA (Fog and turbulence interactions in the marine atmosphere) campaign observations collected during July 2022 in the North Atlantic in the Grand Banks area and vicinity of Sable Island, northeast of Canada. Methods: The measurements were collected using instrumentation mounted on the Research Vessel Atlantic Condor. The collected meteorological parameters were: visibility (Vis), precipitation rate, air temperature, relative humidity with respect to water, pressure, wind speed, and direction. Using all variables, the droplet number concentration was used to qualitatively indicate and assess characteristics of the fog using the t-distributed stochastic neighbor embedding projection method (t-SNE), which clustered the data into groups. Following t-SNE analysis, a correlation heatmap was used to select relevant meteorological variables for visibility nowcasting, which were wind speed, relative humidity, and dew point depression. Prior to nowcasting, the input variables were preprocessed to generate additional time-lagged variables using a 120-minute lookback window in order to take advantage of the intrinsic time-varying features of the time series data. Nowcasting of Vis time series for lead times of 30 and 60 minutes was performed using the ML regression methods of support vector regression (SVR), least-squares gradient boosting (LSB), and deep learning at visibility thresholds of Vis < 1 km and < 10 km. Results: Vis nowcasting at the 60 min lead time was best with LSB and was significantly more skillful than persistence analysis. Specifically, using LSB the overall nowcasts at Vis 1 < km and Vis 10 < km were RMSE = 0.172 km and RMSE = 2.924 km, respectively. The nowcasting skill of SVR for dense fog (Vis ≤ 400 m) was significantly better than persistence at all Vis thresholds and lead times, even when it was less skillful than persistence at predicting high visibility. Discussion: Thus, ML techniques can significantly improve Vis prediction when either observations or modelbased accurate time-dependent variables are available. The results suggest that there is potential for future ML analysis that focuses on modeling the underlying factors of fog formation. [ABSTRACT FROM AUTHOR]

Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA's 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s−1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model "improvement," such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1's nest producing the smallest errors overall. HRRR's ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement. Significance Statement: Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors. [ABSTRACT FROM AUTHOR]

The focus of the current study is on the anisotropy of stably stratified turbulence that is not only limited to large scales and an inertial subrange but also penetrates to small-scale turbulence in the viscous/dissipation subrange on the order of the Kolmogorov scale. The anisotropy of buoyancy forces is well-known, including ensuing effects such as horizontal layering and pancakes structures. Laboratory experiments in the nineties by Van Atta and his students showed that the anisotropy penetrates to very small scales, but their experiments were performed only at a relatively low Reλ (i.e., at Taylor Reynolds numbers) and, therefore, did not provide convincing evidence of anisotropy penetration into viscous sublayers. Nocturnal katabatic flows having configurations of stratified parallel shear flows and developing on mountain slopes provide high Reynolds number data for testing the notion of anisotropy at viscous scales, but obtaining appropriate time series of the data representing stratified shear flows devoid of unwarranted atmospheric factors is a challenge. This study employed the "in situ" calibration of multiple hot-film-sensors collocated with a sonic anemometer that enabled obtaining a 90 min continuous time series of a "clean" katabatic flow. A detailed analysis of the structure functions was conducted in the inertial and viscous subranges at an Reλ around 1250. The results of DNS simulations by Kimura and Herring were employed for the interpretation of data. [ABSTRACT FROM AUTHOR]

The intermittency of fog occurrence (the switching between fog and no-fog) is a key stochastic feature that plays a role in its duration and the amount of moisture available. Here, fog intermittency is studied by using the visibility time series collected during the month of July 2022 on Sable Island, Canada. In addition to the visibility, time series of air relative humidity and turbulent kinetic energy, putative variables akin to the formation and breakup conditions of fog, respectively, are also analyzed in the same framework to establish links between fog intermittency and the underlying atmospheric variables. Intermittency in the time series is quantified with their binary telegraph approximations to isolate clustering behavior from amplitude variations. It is shown that relative humidity and turbulent kinetic energy bound many stochastic features of visibility, including its spectral exponent, clustering exponent, and the growth of its block entropy slope. Although not diagnostic, the visibility time series displays features consistent with Pomeau–Manneville Type-III intermittency in its quiescent phase duration PDF scaling ( − 3 / 2 ), power spectrum scaling ( − 1 / 2 ), and signal amplitude PDF scaling ( − 2 ). The binary fog time series exhibits properties of self-organized criticality in the relation between its power spectrum scaling and quiescent phase duration distribution. [ABSTRACT FROM AUTHOR]

This paper reports analysis of eddy-covariance data collected during the WFIP2 field campaign in the complex-terrain of the US Pacific Northwest. A 31-day period representative of the region's dry season was used to address the following questions: (1) To what extent does the Constant-Flux Layer (CFL) assumption hold? (2) What is the spatial variability of turbulent and momentum fluxes over km scales? and (3) How skilful are the surface-layer parameterizations of mesoscale models? These questions are directly relevant to subgrid parameterization studies of mesoscale models. Results show that the efficacy of the CFL concept and the spatial variability of turbulent and momentum fluxes are dependent on: (i) the turbulent parameter being analysed, (ii) the measurement's location, (iii) the atmospheric stability regime (determined by the flow and vertical stratification), and (iv) the magnitude of the flux. Finally, the skill of the physics formulation of an often-used surface-layer parameterization scheme available in the Weather Research and Forecasting (WRF) model was also evaluated. Meteorological conditions associated with the highest and the lowest errors were identified. A metric to quantify (time-dependent) flow heterogeneity is proposed, which appears to be a good candidate to predict the skill of idealized surface-layer parameterization schemes in complex terrain. [ABSTRACT FROM AUTHOR]

The formation of a layered structure in the form of vertically separated density steps (staircases) in stably stratified fluids has been reported in many laboratory and oceanic studies as well as in the terrestrial atmospheric boundary layer (ABL) to a lesser extent, with attribution to different dynamical mechanisms. This paper presents observations of layered structures in fog-laden marine ABL, where both fog and density steps appear almost simultaneously following a turbulent mixing event under nocturnal conditions. The observations were made during the C-FOG (2018) field campaign aboard a research vessel using rawinsonde launches, aided by a suite of supporting onboard instruments. This is a case of great practical interest because of the impediment by fog-laden staircases to optical and near-infrared wave propagation in the ABL due to enhanced beam jitter by density steps and beam attenuation by fog. A new mechanism is proposed to explain the genesis of density layering, wherein steps appear when fluid parcels with significant buoyancy differences ( Δ b ) osculate in regions of weak turbulence (local length and velocity scales, L H and u H , respectively) devoid of adequate inertial forces ( ∼ u H 2 / L H ) to cause fluid parcels to stir past each other. This is expressed in terms of a local bulk Richardson number criterion R i = Δ b L H / u H 2 > R i c , where Ri c is a critical value. A simple laboratory experiment with an idealized (three layer) density stratification and a known turbulence source (oscillating grid) was performed to demonstrate the proposed mechanism, and through a combination of measurements and modeling it was found Ri c ≈ 1.5. The proposed criterion was consistent with C-FOG field observations as well as representative previous layering observations in the atmosphere and ocean due to localized turbulence mixing events caused by Kelvin–Helmholtz billowing. [ABSTRACT FROM AUTHOR]

The relationship between eastward-propagating convective equatorial signals (CES) along the equatorial Indian Ocean (EIO) and the northward-propagating monsoon intraseasonal oscillations (MISOs) in the Bay of Bengal (BOB) was studied using observational datasets acquired during the 2018 and 2019 MISO-BOB field campaigns. Convective envelopes of MISOs originating from just south of the BOB were associated with both strong and weak eastward CES (average speed ∼6.4 m s−1). Strong CES contributed to ∼20% of the precipitation budget of BOB, and they spurred northward-propagating convective signals that matched the canonical speed of MISOs (1–2 m s−1). In contrast, weak CES contributed to ∼14% of the BOB precipitation budget, and they dissipated without significant northward propagation. Eastward-propagating intraseasonal oscillations (ISOs; period 30–60 days) and convectively coupled Kelvin waves (CCKWs; period 4–15 days) accounted for most precipitation variability across the EIO during the 2019 boreal summer as compared with that of 2018. An agreement could be noted between high moisture content in the midtroposphere and the active phases of CCKWs and ISOs for two observational locations in the BOB. Basin-scale thermodynamic conditions prior to the arrival of strong or weak CES revealed warmer or cooler sea surface temperatures, respectively. Flux measurements aboard a research vessel suggest that the evolution of MISOs associated with strong CES are signified by local enhanced air–sea interactions, in particular the supply of local moisture and sensible heat, which could enhance deep convection and further moisten the upper troposphere. Significance Statement: Eastward-propagating convective signals along the equatorial Indian Ocean and their relationship to the northward-propagating spells of rainfall that lead to moisture variability in the Bay of Bengal are studied for the 2018 and 2019 southwest monsoon seasons using observational datasets acquired during field campaigns. Strong convective equatorial signals spurred northward-propagating convection, as compared with weak signals that dissipated without significant northward propagation. Wave spectral analysis showed CCKWs (period 4–15 days), and eastward ISOs (period 30–60 days) accounted for most of the precipitation variability, with the former dominating during the 2018 boreal summer. High moisture periods observed from radiosonde measurements show agreement with the active phases of CCKWs and ISOs. [ABSTRACT FROM AUTHOR]

We present high-resolution sustained, persistent observations of the ocean around Sri Lanka from autonomous gliders collected over several years, a region with complex, variable circulation patterns connecting the Bay of Bengal and the Arabian Sea to each other and the rest of the Indian Ocean. The Seaglider surveys resolve seasonal to interannual variability in vertical and horizontal structure, allowing quantification of volume, heat, and freshwater fluxes, as well as the transformations and transports of key water mass classes across sections normal to the east (2014–15) and south (2016–19) coasts of Sri Lanka. The resulting transports point to the importance of both surface and subsurface flows and show that the direct pathway along the Sri Lankan coast plays a significant role in the exchanges of waters between the Arabian Sea and the Bay of Bengal. Significant section-to-section variability highlights the need for sustained, long-term observations to quantify the circulation pathways and dynamics associated with exchange between the Bay of Bengal and Arabian Sea and provides context for interpreting observations collected as "snapshots" of more limited duration. Significance Statement: The strong seasonal variations of the wind in the Indian Ocean create large and rapid changes in the ocean's properties near Sri Lanka. This variable and poorly observed circulation is very important for how temperature and salinity are distributed across the northern Indian Ocean, both at the surface and at depths. Long-term and repeated surveys from autonomous Seagliders allow us to understand how freshwater inflow, atmospheric forcing, and underlying ocean variability act to produce observed contrasts (spatial and seasonal) in upper-ocean structure of the Bay of Bengal and Arabian Sea. [ABSTRACT FROM AUTHOR]

Measurements made in the Columbia River basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modeled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow, which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin-Obukhov similarity; and (ii) a modified Priestley-Taylor (P-T) algorithm with physically based ecophysiological constraints, which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various time scales based on the modeled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP2, a hybrid approach can be used for similar flux-tower sites and field campaigns. [ABSTRACT FROM AUTHOR]

In the realm of boundary layer flows in complex terrain, low-level jets (LLJs) have received considerable attention, although little literature is available for double-nosed LLJs that remain not well understood. To this end, we use the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) dataset to demonstrate that double-nosed LLJs developing within the planetary boundary layer (PBL) are common during stable nocturnal conditions and present two possible mechanisms responsible for their formation. It is observed that the onset of a double-nosed LLJ is associated with a temporary shape modification of an already-established LLJ. The characteristics of these double-nosed LLJs are described using a refined version of identification criteria proposed in the literature, and their formation is classified in terms of two driving mechanisms. The wind-driven mechanism encompasses cases where the two noses are associated with different air masses flowing one on top of the other. The wave-driven mechanism involves the vertical momentum transport by an inertial–gravity wave to generate the second nose. The wave-driven mechanism is corroborated by the analysis of nocturnal double-nosed LLJs, where inertial–gravity waves are generated close to the ground by a sudden flow perturbation. [ABSTRACT FROM AUTHOR]

Two stratus-lowering marine fog events observed on 28 September and 4 October 2018 during the Coastal Fog (C-Fog) field campaign that took place offshore of eastern Canada from 1 September to 6 October 2018 are described. In situ, profiling, and remote sensing observations were made at selected land sites in eastern Newfoundland, Nova Scotia, and aboard the research vessel Hugh R. Sharp cruising in adjoining coastal waters. Synoptic-scale analysis shows that both fog episodes result from the interaction between synoptic-scale surface-level low-pressure systems and a contiguous high-pressure system. At the same time, back trajectories reveal that the bulk of the fog layer is formed due to differential advection. The diameter of the fog droplets at the surface gradually decreases from the centre of the fog layer to its leading/trailing edges. The bimodal fog-droplet diameter distribution with peaks at 5–10 µm and 20–25 µm provide clues on droplet collision and coalescence processes. The observed difference between microphysical variables and droplet distribution between the two fog events and within the same fog layer might be governed by the atmospheric-boundary-layer (e.g., humidity conditions and turbulence) that prevailed in the fog layer. Overall, it is concluded that the life cycle of observed stratus-lowering coastal-fog episodes depends on synoptic conditions and atmospheric-boundary-layer characteristics such as stability, cloud-top cooling, and entrainment. [ABSTRACT FROM AUTHOR]

Sen Wang et al. present a detailed account of a coastal-fog event encountered during C-FOG campaign from the research vessel, and discuss the multi-layered fog-cloud structure and counter-gradient sensible heat fluxes during the event. Fog events are examined for the C-FOG main field site at Ferryland, Newfoundland as well as at other Atlantic Canadian airports. [Extracted from the article]

We evaluate the efficacy of microphysics and planetary-boundary-layer (PBL) parametrizations of the Weather Research and Forecasting (WRF) model for simulation of the coverage and intensity (visibility) of fog during the Coastal Fog (C-FOG) Research Program. The C-FOG observations are used for model validation, particularly focusing on offshore and onshore fog events during 13–14 and 28–29 September 2018. Sensitivity experiments with high horizontal (1 km) and vertical (99 levels) resolution are conducted to elicit possible physical processes underlying the fog life-cycle. Various microphysical and PBL parametrizations, as well as empirical algorithms available for visibility calculations, are evaluated. The model coastal fog formation and characteristics strongly depend on the simulated local meteorology (e.g., temperature, relative humidity, mixing ratio, and wind field) and the microphysical parametrization employed. High space–time resolution simulations for fog coverage and visibility based on the Mansell et al. (J Atmos Sci 67(1):171–194, 2010) microphysical parametrization compare better with data vis-à-vis other microphysical parametrizations, although spatial coverage and visibility are still overestimated. The disparities are likely related to uncertainties of model fog microphysical parameters, including the liquid water content (LWC), droplet number concentration (Nd), and aerosol particle size. It is found that (i) visibility algorithms that use both the variables LWC and Nd, instead of only LWC, provide improved fog estimates; (ii) different PBL parametrizations mainly affect the fog onset and dissipation; (iii) the WRF model has improved performance over the ocean than over land, possibly due to homogeneity of the ocean-surface cover. [ABSTRACT FROM AUTHOR]

Measurements of atmospheric turbulence at a site in Ferryland (Newfoundland) during the C-FOG (Coastal-Fog) field campaign in September–October 2018 are used to study meteorological parameters, turbulence statistics, internal boundary layers, and scaling laws for turbulent mixing in the coastal zone. We observe stable/unstable shallow internal boundary layers with a region of unstable/stable stratification above with onshore flow from a relatively warm/cold sea onto the cold/heated land during the night/day. This study compares surface fluxes and other turbulence statistics as well as different scaling laws with and without fog. While both complexity of the coastal landforms and foggy conditions nominally violate assumptions underlying Monin–Obukhov similarity theory (MOST), our observations show that the non-dimensional standard deviations of the velocity components and the dissipation rate of turbulence kinetic energy obey MOST reasonably well for all measurement levels, stability conditions, and wind directions for both fog and no fog cases. However, the data scatter for the normalized dissipation rate is somewhat greater compared with the normalized standard deviations of the wind components. The bias and relatively larger scatter of normalized standard deviations for scalars in near-neutral conditions is likely associated with the underlying inhomogeneous coastal surface. According to the C-FOG data, during a fog event the moisture flux data become irregular and the latent heat flux is often negative (downward). Our observations also demonstrate poor agreement between normalized standard deviations of specific humidity with MOST for foggy conditions; its statistical dependence on the MOST stability parameter is weak at best in fog. [ABSTRACT FROM AUTHOR]

An interesting mixing-fog event was identified during the C-FOG field campaign, where a cold-frontal airmass arriving from the north-east collided with The Downs peninsula in Ferryland, Newfoundland, Canada, to produce misty/foggy conditions. A comprehensive set of field observations suggests that this collision caused turbulent mixing of nearly saturated ambient air with an almost saturated cold-frontal airmass, creating conditions for mixing fog. To delve into the physical processes underlying this phenomenon, laboratory experiments were performed on the interaction of lock-exchange-induced gravity currents with a rectangular obstacle. Instantaneous velocity and density fields were obtained using particle image velocimetry and planar laser-induced fluorescence. The observations suggest that the obstacle starts affecting the approaching gravity-current propagation at an upstream distance of 2H and, upon collision, the mixing occurs over a length of 0.83H, where H is the depth of the ambient fluid layer. The time for larger-scale turbulent stirring to permeate to the smallest scales of turbulence and activate the condensation nuclei is estimated as 3 t ∗ , where t ∗ = H / g ′ is the intrinsic time scale of the gravity current, and g ′ is the reduced gravity. Extrapolation of laboratory results to field conditions shows a good agreement with observations. [ABSTRACT FROM AUTHOR]

Formation of coastal fog was observed near the southern tip of Nova Scotia when warm, humid air was advected towards the shore over an area of colder water. The sea-surface temperature in the colder and higher salinity patch near the coast was below 14 °C compared to that of the surrounding sea of ≈ 17–18 °C. Measurements of stratification, currents, and the dissipation rate of turbulence kinetic energy (ε) on the Nova Scotia shelf, shelf break, and continental slope revealed the frequent occurrence of shear instability in the pycnocline. The probability of the gradient Richardson number (R i) being less than a critical value of R i cr = 0.25 in the depth range 30–90 m exceeded 50% on the shelf and over the slope, and it was above 75% along the shelf break, while in the open ocean pycnocline the probability of R i < 0.25 is below 5%. The cumulative distribution functions of the dissipation rate in the pycnocline south-east of Nova Scotia followed the Burr probability model with median values from 7.9 × 10 - 9 W kg−1 on the slope to 1.9 × 10 - 8 W kg−1 at the shelf break. The eddy diffusivity ( K N ) estimates follow a generalized extreme value distribution with a high median value of K N = 5.8 × 10 - 5 m2 s−1 at the shelf break. The diffusivity K N depended on Ri in general agreement with the parametrization previously suggested by Lozovatsky and Fernando (Philos Trans R Soc A 371:20120213, 2013) but with a higher level of mixing at R i > 1 . This could be relevant to the nature of turbulence generation near the shelf break by random wave instabilities in the pycnocline at high Richardson and high Reynolds numbers. [ABSTRACT FROM AUTHOR]

Fog simulation is a challenge due to the complex microphysical, radiative, and turbulent processes. C‐FOG (Coastal Fog) was a comprehensive experiment which aimed to improve our understanding and forecasting skill of fog in coastal areas of Atlantic Canada. An intermittent fog event, containing two fog periods occurring over the Grand Banks of Newfoundland beginning at 00:00 UTC on September 13, 2018, is investigated in this study. Our approach is to apply the Weather Research and Forecasting (WRF) model, in conjunction with a 1‐D model for the atmospheric boundary layer, PAFOG (Parameterized Fog model). Model results are evaluated against observations collected onboard the research vessel Hugh R. Sharp. We introduced an advection term to PAFOG to investigate the ability of the model to simulate the two‐level fog/stratus system and we developed a set of sensitivity experiments. Results suggest that PAFOG with the advection terms calculated from ERA5 shows a good ability to simulate intermittent fog caused by fog lifting as stratus, and by comparison, outperform results with advection terms derived from WRF simulations. Regarding the latter, in an experiment with high vertical resolution, WRF gives a delayed fog event, whereas with low vertical resolution, WRF gives descending stratus. Our results provide a possible methodology to study the detailed structure of fog/stratus using PAFOG, a sounding profile as initial conditions, and advection profiles derived from ERA5, with low computing cost. Key Points: PAFOG with advection terms has ability to simulate intermittent fog/stratus system by successfully simulating TKE and radiative coolingHigh vertical resolution in WRF suggests a delayed fog onset; with lower vertical resolution, WRF can simulate descending stratusA detailed inversion structure for the initial vertical profile plays an important role in resulting in success of the PAFOG simulation [ABSTRACT FROM AUTHOR]

Turbulent flow in a weakly convective marine atmospheric boundary layer (MABL) driven by geostrophic winds Vg = 10 m s−1 and heterogeneous sea surface temperature (SST) is examined using fine-mesh large-eddy simulation (LES). The imposed SST heterogeneity is a single-sided warm or cold front with jumps Δθ = (2, −1.5) K varying over a horizontal x distance of 1 km characteristic of an upper-ocean mesoscale or submesoscale front. The geostrophic winds are oriented parallel to the SST isotherms (i.e., the winds are alongfront). Previously, Sullivan et al. examined a similar flow configuration but with geostrophic winds oriented perpendicular to the imposed SST isotherms (i.e., the winds were across-front). Results with alongfront and across-front winds differ in important ways. With alongfront winds, the ageostrophic surface wind is weak, about 5 times smaller than the geostrophic wind, and horizontal pressure gradients couple the SST front and the atmosphere in the momentum budget. With across-front winds, horizontal pressure gradients are weak and mean horizontal advection primarily balances vertical flux divergence. Alongfront winds generate persistent secondary circulations (SC) that modify the surface fluxes as well as turbulent fluxes in the MABL interior depending on the sign of Δθ. Warm and cold filaments develop opposing pairs of SC with a central upwelling or downwelling region between the cells. Cold filaments reduce the entrainment near the boundary layer top that can potentially impact cloud initiation. The surface-wind–SST-isotherm orientation is an important component of atmosphere–ocean coupling. The results also show frontogenetic tendencies in the MABL. [ABSTRACT FROM AUTHOR]

In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon. [ABSTRACT FROM AUTHOR]

The bulk sea surface temperature (SST) simulated by COAMPS/NCOM [Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and the Navy Coastal Ocean Model (NCOM)] compares reasonably well with the bulk SST measured on the North Carolina shelf during the October of 2015 field campaign of the CASPER Project (Wang et al. in Bull Amer Met Soc 99:1449–1471, 2018). The model slightly overestimates the field data by about 0.15 °C; a linear regression is strong with a coefficient of determination r2 > 0.9. In deep waters of the Gulf Stream core, COAMPS/NCOM typically underestimates the measured SST by less than 1 °C except in the cold lens or meander where the temperature gradients were smoothed by the model. It is evident that sub-mesoscale features like frontal eddies, meanders and filaments, require a resolution higher than the 3 km grid spacing adopted for modeling. [ABSTRACT FROM AUTHOR]

Ecosystems in the Sacramento-San Joaquin Delta are changing rapidly, as are ecosystems around the world. Extreme events are becoming more frequent and thresholds are likely to be crossed more often, creating greater uncertainty about future conditions. The accelerating speed of change means that ecological systems may not remain stable long enough for scientists to understand them, much less use their research findings to inform policy and management. Faced with these challenges, those involved in science, policy, and management must adapt and change and anticipate what the ecosystems may be like in the future. We highlight several ways of looking ahead--scenario analyses, horizon scanning, expert elicitation, and dynamic planning--and suggest that recent advances in distributional ecology, disturbance ecology, resilience thinking, and our increased understanding of coupled human-natural systems may provide fresh ways of thinking about more rapid change in the future. To accelerate forward-looking science, policy, and management in the Delta, we propose that the State of California create a Delta Science Visioning Process to fully and openly assess the challenges of more rapid change to science, policy, and management and propose appropriate solutions, through legislation, if needed. [ABSTRACT FROM AUTHOR]

This paper reports the findings of a comprehensive field investigation on flow through a mountain gap subject to a range of stably stratified environmental conditions. This study was embedded within the Perdigão field campaign, which was conducted in a region of parallel double-ridge topography with ridge-normal wind climatology. One of the ridges has a well-defined gap (col) at the top, and an array of in situ and remote sensors, including a novel triple Doppler lidar system, was deployed around it. The experimental design was mostly guided by previous numerical and theoretical studies conducted with an idealized configuration where a flow (with characteristic velocity U0 and buoyancy frequency N) approaches normal to a mountain of height h with a gap at its crest, for which the governing parameters are the dimensionless mountain height G = Nh/U0 and various gap aspect ratios. Modified forms of G were proposed to account for real-world atmospheric variability, and the results are discussed in terms of a gap-averaged value Gc. The nature of gap flow was highly dependent on Gc, wherein a nearly neutral flow regime (Gc < 1), a transitional mountain wave regime [Gc ~ O(1)], and a gap-jetting regime [Gc > O(1)] were identified. The measurements were in broad agreement with previous numerical and theoretical studies on a single ridge with a gap or double-ridge topography, although details vary. This is the first-ever detailed field study reported on microscale [O(100) m] gap flows, and it provides useful data and insights for future theoretical and numerical studies. [ABSTRACT FROM AUTHOR]

Machine learning is quickly becoming a commonly used technique for wind speed and power forecasting. Many machine learning methods utilize exogenous variables as input features, but there remains the question of which atmospheric variables are most beneficial for forecasting, especially in handling non-linearities that lead to forecasting error. This question is addressed via creation of a hybrid model that utilizes an autoregressive integrated moving-average (ARIMA) model to make an initial wind speed forecast followed by a random forest model that attempts to predict the ARIMA forecasting error using knowledge of exogenous atmospheric variables. Variables conveying information about atmospheric stability and turbulence as well as inertial forcing are found to be useful in dealing with non-linear error prediction. Streamwise wind speed, time of day, turbulence intensity, turbulent heat flux, vertical velocity, and wind direction are found to be particularly useful when used in unison for hourly and 3 h timescales. The prediction accuracy of the developed ARIMA-random forest hybrid model is compared to that of the persistence and bias-corrected ARIMA models. The ARIMA-random forest model is shown to improve upon the latter commonly employed modeling methods, reducing hourly forecasting error by up to 5% below that of the bias-corrected ARIMA model and achieving an R² value of 0.84 with true wind speed. [ABSTRACT FROM AUTHOR]

Turbulent flow in a weakly convective marine atmospheric boundary layer (MABL) driven by geostrophic winds Ug = 10 m s−1 and heterogeneous sea surface temperature (SST) is examined using fine-mesh large-eddy simulation (LES). The imposed SST heterogeneity is a single-sided warm or cold front with temperature jumps Δθ = (2, −1.5) K varying over a horizontal distance between [0.1, −6] km characteristic of an upper-ocean mesoscale or submesoscale regime. A Fourier-fringe technique is implemented in the LES to overcome the assumptions of horizontally homogeneous periodic flow. Grid meshes of 2.2 × 109 points with fine-resolution (horizontal, vertical) spacing (δx = δy, δz) = (4.4, 2) m are used. Geostrophic winds blowing across SST isotherms generate secondary circulations that vary with the sign of the front. Warm fronts feature overshoots in the temperature field, nonlinear temperature and momentum fluxes, a local maximum in the vertical velocity variance, and an extended spatial evolution of the boundary layer with increasing distance from the SST front. Cold fronts collapse the incoming turbulence but leave behind residual motions above the boundary layer. In the case of a warm front, the internal boundary layer grows with downstream distance conveying the surface changes aloft and downwind. SST fronts modify entrainment fluxes and generate persistent horizontal advection at large distances from the front. [ABSTRACT FROM AUTHOR]

The mixing coefficient Г = B/ε, defined as the ratio of the magnitude of buoyancy flux B to the rate of turbulent kinetic energy (TKE) dissipation ε, plays a key role in modeling atmospheric and oceanic flows. Г is sometimes estimated using yet another fundamental quantity, the flux Richardson number (or mixing efficiency) Rif = B/P, where P is the rate of production of TKE. In practice, Г and Rif are commonly assumed as constants, but studies show that they depend on multiple parameters determined by the type of flow, for example, the gradient Richardson number Rig for stratified shear flows. During the MATERHORN field program, direct measurements of velocity and temperature profiles as well as B, ε, and P were made over an extended period using a densely instrumented flux tower. A ~ 90 min period of stratified parallel shear flow was identified in the data record, including recurrent intervals of nominally stationary flow. Measurements during this period supported the study of mixing parameters as reported in this paper. Even for this case of nature resembling an ideal flow, Г was found to be dependent on multiple parameters. Nevertheless, for periods robustly identified as shear flow in equilibrium with embedded turbulence, the measurements were in agreement with those of past stratified shear flow experiments in the laboratory. This result points to the challenges of parameterizing turbulent mixing in environmental flow models. [ABSTRACT FROM AUTHOR]

The quantification of turbulent mixing in nature is predicated by inherent randomness of causal events, and obtaining relevant turbulence statistics requires ensemble averaging of identical realizations that are unachievable in field observations or onerous in laboratory situations. Laboratory modeling is often used to study nonstationary natural processes, but jitters due to intrinsic variability of events as well as experimental uncertainties introduce additional (spurious) fluctuations that affect ensemble averaging of individual realizations. In this paper, the phase-aligned ensemble averaging technique (PAET), which aligns the events based on information on flow structures, is introduced in the context of environmental fluid mechanics studies. The accuracy and computational efficiency of PAET are investigated systematically for two cases: (1) synthetic density field alignment and (2) laboratory flows involving collision of counter flowing gravity currents. The latter is a frequent phenomenon in the stable atmospheric boundary layer in mountainous areas. In the synthetic density field case, the PAET aligns the complex structures precisely within the allowable range of measurement accuracy. For the experimental gravity current case, the precisely aligned result is unknown, and the results of PAET are compared with those obtained with the Monte Carlo method, a simulated annealing algorithm, and the gradient descent method; the PAET was found to be the most efficient. This study broaches the PAET as a versatile method for obtaining accurate turbulence statistics in laboratory experiments designed to mimic environmental flows where spatial and temporal inhomogeneities abound. [ABSTRACT FROM AUTHOR]

A three-dimensional thermal lattice Boltzmann model (TLBM) using multi-relaxation time method was used to simulate stratified atmospheric flows over a ridge. The main objective was to study the efficacy of this method for turbulent flows in the atmospheric boundary layer, complex terrain flows in particular. The simulation results were compared with results obtained using a traditional finite difference method based on the Navier–Stokes equations and with previous laboratory results on stably stratified flows over an isolated ridge. The initial density profile is neutral stratification in the boundary layer, topped with a stable cap and stable stratification aloft. The TLBM simulations produced waves, rotors, and hydraulic jumps in the lee side of the ridge for stably stratified flows, depending on the governing stability parameters. The Smagorinsky turbulence parameterization produced typical turbulence spectra for the velocity components at the lee side of the ridge, and the turbulent flow characteristics of varied stratifications were also analyzed. The comparison of TLBM simulations with other numerical simulations and laboratory studies indicated that TLBM is a viable method for numerical modeling of stratified atmospheric flows. To our knowledge, this is the first TLBM simulation of stratified atmospheric flow over a ridge. The details of the TLBM, its implementation of complex boundaries and the subgrid turbulence parameterizations used in this study are also described in this article. [ABSTRACT FROM AUTHOR]

Surface turbulent fluxes provide a key boundary condition for the prediction of weather, hydrology, and atmospheric carbon dioxide. The turbulence cospectrum is assumed to typically follow a −7/3 power-law scaling, which is used for the high-frequency spectral correction of eddy-covariance data. The derivation of this scaling is mostly grounded on dimensional analysis. The dimensional analysis or cospectral budget analyses, however, can lead to alternative cospectral scaling. Here we examine the shape of turbulence cospectra at high Reynolds number and high wavenumbers based on extensive field measurements of wind velocity and temperature in various stably stratified atmospheric conditions. We show that the cospectral scaling deviates from the −7/3 scaling at high wavenumbers in the inertial subrange of the stable atmospheric boundary layer, and appears to follow a −2 power-law scaling. We suggest that −2 power-law scaling is a better alternative for cospectral corrections for eddy-covariance measurements of the stable boundary layer. [ABSTRACT FROM AUTHOR]

Model uncertainty is a significant challenge in the wind energy industry and can lead to mischaracterization of millions of dollars' worth of wind resources. Machine learning methods, notably deep artificial neural networks (ANNs), are capable of modeling turbulent and chaotic systems and offer a promising tool to produce high-accuracy wind speed forecasts and extrapolations. This paper uses data collected by profiling Doppler lidars over three field campaigns to investigate the efficacy of using ANNs for wind speed vertical extrapolation in a variety of terrains, and it quantifies the role of domain knowledge in ANN extrapolation accuracy. A series of 11 meteorological parameters (features) are used as ANN inputs, and the resulting output accuracy is compared with that of both standard log-law and power-law extrapolations. It is found that extracted nondimensional inputs, namely turbulence intensity, current wind speed, and previous wind speed, are the features that most reliably improve the ANN's accuracy, providing up to a 65% and 52% increase in extrapolation accuracy over log-law and power-law predictions, respectively. The volume of input data is also deemed important for achieving robust results. One test case is analyzed in depth using dimensional and nondimensional features, showing that the feature nondimensionalization drastically improves network accuracy and robustness for sparsely sampled atmospheric cases. [ABSTRACT FROM AUTHOR]

Ground-based Doppler-lidar instrumentation provides atmospheric wind data at dramatically improved accuracies and spatial/temporal resolutions. These capabilities have provided new insights into atmospheric flow phenomena, but they also should have a strong role in NWP model improvement. Insight into the nature of model errors can be gained by studying recurrent atmospheric flows, here a regional summertime diurnal sea breeze and subsequent marine-air intrusion into the arid interior of Oregon–Washington, where these winds are an important wind-energy resource. These marine intrusions were sampled by three scanning Doppler lidars in the Columbia River basin as part of the Second Wind Forecast Improvement Project (WFIP2), using data from summer 2016. Lidar time–height cross sections of wind speed identified 8 days when the diurnal flow cycle (peak wind speeds at midnight, afternoon minima) was obvious and strong. The 8-day composite time–height cross sections of lidar wind speeds are used to validate those generated by the operational NCEP–HRRR model. HRRR simulated the diurnal wind cycle, but produced errors in the timing of onset and significant errors due to a premature nighttime demise of the intrusion flow, producing low-bias errors of 6 m s−1. Day-to-day and in the composite, whenever a marine intrusion occurred, HRRR made these same errors. The errors occurred under a range of gradient wind conditions indicating that they resulted from the misrepresentation of physical processes within a limited region around the measurement locations. Because of their generation within a limited geographical area, field measurement programs can be designed to find and address the sources of these NWP errors. [ABSTRACT FROM AUTHOR]

During the second Wind Forecast Improvement Project (WFIP2; October 2015–March 2017, held in the Columbia River Gorge and Basin area of eastern Washington and Oregon states), several improvements to the parameterizations used in the High Resolution Rapid Refresh (HRRR – 3 km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST – 750 m horizontal grid spacing) numerical weather prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configurations, with the EXP configuration including all the improved parameterizations. The impacts of the experimental parameterizations on the forecast of 80 m wind speeds (wind turbine hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and three profiling lidars for comparison. Improvements due to the experimental physics (EXP vs. CNT runs) and those due to finer horizontal grid spacing (HRRRNEST vs. HRRR) and the combination of the two are compared, using standard bulk statistics such as mean absolute error (MAE) and mean bias error (bias). On average, the HRRR 80 m wind speed MAE is reduced by 3 %–4 % due to the experimental physics. The impact of the finer horizontal grid spacing in the CNT runs also shows a positive improvement of 5 % on MAE, which is particularly large at nighttime and during the morning transition. Lastly, the combined impact of the experimental physics and finer horizontal grid spacing produces larger improvements in the 80 m wind speed MAE, up to 7 %–8 %. The improvements are evaluated as a function of the model's initialization time, forecast horizon, time of the day, season of the year, site elevation, and meteorological phenomena. Causes of model weaknesses are identified. Finally, bias correction methods are applied to the 80 m wind speed model outputs to measure their impact on the improvements due to the removal of the systematic component of the errors. [ABSTRACT FROM AUTHOR]

During the second Wind Forecast Improvement Project (WFIP2; Oct 2015-Mar 2017, Columbia River Gorge and Basin area) several improvements to the parameterizations applied in the High Resolution Rapid Refresh (HRRR - 3 km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST - 750 m horizontal grid spacing) Numerical Weather Prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configurations, with the EXP configuration including all the improved parameterizations. The impacts of the experimental parameterizations on the forecast of 80-m wind speeds (hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and 3 profiling lidars for verification. Improvements due to the experimental physics (EXP vs CNT runs) versus those due to finer horizontal grid spacing (HRRRNEST vs HRRR), and the combination of the two are compared, using standard bulk statistics such as Mean Absolute Error (MAE) and Mean Bias Error (bias). On average, the HRRR 80-m wind speed MAE is reduced by 3-4 % due to the experimental physics. The impact of the finer horizontal grid spacing in the CNT runs also shows a positive improvement of 5 % on MAE, which is particularly large at nighttime and during the morning transition. Lastly, the combined impact of the experimental physics and finer horizontal grid spacing produces larger improvements in the 80-m wind speed MAE, up to 7-8 %. The improvements are evaluated as a function of the model's initialization time, forecast horizon, time of the day, season of the year, site elevation, and meteorological phenomena, also looking for the causes of model weaknesses. Finally, bias correction methods are applied to the 80-m wind speed model outputs to measure their impact on the improvements due to the removal of the systematic component of the errors. [ABSTRACT FROM AUTHOR]

Large-eddy simulations are used to investigate the effects of coastal topography and atmospheric stratification on the coastal marine atmospheric surface layer at the Field Research Facility in Duck, North Carolina, USA. Field measurements obtained from the CASPER-EAST intensive field campaign in autumn 2015 are used to determine the inlet and lower boundary conditions. The simulations are performed using the in-house Virtual Flow Simulator code, with the simulated mean streamwise velocity component, mean temperature, Reynolds shear stress, and turbulent heat flux, shown to be in good agreement with measurements. In the coastal area, the complex coastal topography leads to an enhancement of the Reynolds shear stress for both onshore and offshore flows, while the effect of atmospheric stratification on the momentum transfer is less significant than the topography. In contrast to the momentum flux, the heat flux is influenced by both the coastal topography and stratification. For onshore flow and stable stratification, the heat flux is significantly increased near the sand dune due to the enhanced turbulence and vertical temperature gradient. For onshore flow and unstable stratification, the strong turbulent mixing tends to enhance the heat flux, but is suppressed by the reduced vertical temperature gradient, such that the magnitude of the turbulent heat flux remains almost unchanged in comparison with the upstream flow. For offshore flow in both stable and unstable stratification, the heat flux is enhanced due to the flow separation at the sand dune. [ABSTRACT FROM AUTHOR]

An X-band vertical array system is developed for measuring and characterizing electromagnetic (EM) propagation in the marine atmospheric boundary layer. In particular, the evaporation duct that commonly forms over water is investigated as part of the Coupled Air-Sea Processes and Electromagnetic ducting Research (CASPER) at-sea experimental campaign conducted off the coast of Duck, NC, USA, during October–November of 2015. Monte Carlo simulations are first used to develop an optimal array of four vertically spaced receiving antennas. In the experiment, the antennas are mounted on the stern A-frame of a research vessel and measure EM signals transmitted from beacons mounted on another research vessel and on the pier at the Army Field Research Facility. While the propagation loss versus range provides a data set similar to previous work, the vertical array can provide sampling of modes in the leaky waveguide formed in the duct. Combining both the range and height sampling results in a robust inversion method for evaporation duct estimation. In this paper, the efficacy of the four-element array is demonstrated by estimation of the evaporation duct height through comparison with a library of precomputed propagation curves generated using the parabolic wave equation. Low model error gives confidence in the estimates, which are consistent with the concurrent environmental measurements performed by the CASPER team. It is found that the evaporation duct can vary significantly with range and time over the duration of a data collection run. [ABSTRACT FROM AUTHOR]

Collision between two identical counterflowing gravity currents was s⩽died in the laboratory with the goal of understanding the fundamental ⩽rbulent mixing physics of flow collisions in na⩽re, for example katabatic flows and thunderstorm outflows. The ensuing ⩽rbulent mixing is a subgrid process in mesoscale forecasting models, and needs to be parameterized using eddy diffusivity. Laboratory gravity currents were generated by simultaneously removing two identical locks, located at both ends of a long rectangular tank, which separated dense and lighter water columns with free surfaces of the same depth H. The frontal velocity uf and the velocity and density fields of the gravity currents were monitored using time-resolved particle image velocimetry and planar laser-induced fluorescence imaging. Ensemble averaging of identical experimental realizations was used to compute ⩽rbulence statistics, after removing inherent jitter via phase alignment of successive data realizations by iteratively maximizing the cross-correlation of each realization with the ensemble average. Four stages of flow evolution were identified: initial (independent) propagation of gravity currents, their approach while influencing one another, collision and resulting updraughts, and postcollision slumping of collided fluid. The collision stage, in ⩽rn, involved three phases, and produced the strongest ⩽rbulent mixing as quantified by the rate of change of density. Phase I spanned -0:2 6 ⩽f =H < 0:5, where collision produced a rising density front (interface) with strong shear and intense ⩽rbulent kinetic energy production (t is a suitably defined time coordinate such that gravity currents make the initial contact at ⩽f =H D -0:2). In Phase II (0:5 6 ⩽f =H < 1:2), the interface was flat and calm with negligible vertical velocity. Phase III (1:2 6 ⩽f =H < 2:8) was characterized by slumping which led to hydraulic bores propagating away from the collision area. The measurements included root mean square ⩽rbulent velocities and their decay rates, interfacial velocity, rate of change of fluid-parcel density, and eddy diffusivity. These measures depended on the Reynolds number Re, but appeared to achieve Reynolds number similarity for Re > 3000. The eddy diffusivity K T , space-time averaged over the spatial extent (H × H) and the lifetime (t ≈ 3H=u f ) of collision, was K T =ufH D 0:0036 for Re > 3000, with the area A of active mixing being A=H2 D0:037. [ABSTRACT FROM AUTHOR]

Atmospheric turbulence measurements made at the U.S. Army Corps of Engineers Field Research Facility (FRF) located on the Atlantic coast near the town of Duck, North Carolina during the CASPER-East Program (October-November 2015) are used to study air-sea/land coupling in the FRF coastal zone. Turbulence and mean meteorological data were collected at multiple levels (up to four) on three towers deployed at different landward distances from the shoreline, with a fourth tower located at the end of a 560-m-long FRF pier. The data enable comparison of turbulent fluxes and other statistics, as well as investigations of surface-layer scaling for different footprints, including relatively smooth sea-surface conditions and aerodynamically rough dry inland areas. Both stable and unstable stratifications were observed. The drag coefficient and diurnal variation of the sensible heat flux are found to be indicators for disparate surface footprints. The drag coefficient over the land footprint is significantly greater, by as much as an order of magnitude, compared with that over the smooth sea-surface footprint. For onshore flow, the internal boundary layer in the coastal zone was either stable or (mostly) unstable, and varied dramatically at the land-surface discontinuity. The offshore flow of generally warm air over the cooler sea surface produced a stable internal boundary layer over the ocean surface downstream from the coast. While the coastal inhomogeneities violate the assumptions underlying Monin-Obukhov similarity theory (MOST), any deviations from MOST are less profound for the scaled standard deviations and the dissipation rate over both water and land, as well as for stable and unstable conditions. Observations, however, show a poor correspondence with MOST for the flux-profile relationships. Suitably-averaged, non-dimensional profiles of wind speed and temperature vary significantly among the different flux towers and observation levels, with high data scatter. Overall, the statistical dependence of the vertical gradients of scaled wind speed and temperature on the Monin-Obukhov stability parameter in the coastal area is weak, if not non-existent. [ABSTRACT FROM AUTHOR]

Thermal infrared imagery provides a measure of surface temperature by quantifying the thermal emission of radiation from objects. In this work, we propose a novel approach for computing surface sensible heat fluxes from a time series of thermal imagery sampled at 20 Hz. The approach consists of using a surface energy budget, where the ground heat flux is easily computed from limited measurements using a force-restore-type methodology, the latent heat fluxes are neglected, and the energy storage is computed using a lumped capacitance model. Preliminary validation of the method is presented using experimental data acquired at a desert playa in western Utah from an intensive observation period during the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program. The sensible heat fluxes computed from thermal imagery show encouraging agreement (≈4% difference for 1 h averaged fluxes computed with the force-restore method) compared to heat fluxes obtained using the eddy-covariance technique, however additional evaluation is required to confirm the method's validity. Further, the technique illustrates the richness of surface heat flux spatio-temporal structure even over very smooth surfaces. [ABSTRACT FROM AUTHOR]

Scaled acoustic laboratory experiments are used to develop a methodology for obtaining the acoustic characteristics of different barrier top designs and for identifying geometries that may have advantages over the traditional thin vertical screen. The idea is to use a short impulsive spherical sound pulse possessing a broad frequency spectrum. If the duration of the pulse is sufficiently short, the entire primary signal, which travels by the shortest direct route diffracting at the top of the barrier, arrives at the receiver much earlier than any secondary signals reflected from the surroundings. Secondary signals may therefore be ignored and only the information from the primary signal can be analyzed. When the typical frequency band of the sound pulse is about an order of magnitude higher than typical traffic noise spectra, then scaled acoustic modeling using the same scaling factor for lengths and distances is possible. The results of such experiments are reported here for barriers with six different geometries. Using spectral analysis, insertion losses as functions of frequency were calculated for different source-receiver positions and barrier tops. The results were then rescaled for full-size traffic barriers and, using a typical traffic noise spectrum, single number ratings of barrier performance were obtained. [ABSTRACT FROM AUTHOR]

The article focuses on a study related to a campaign ASIRI in Bay of Bengal (BoB) aimed at interaction and processes of lower- atmosphere and upper-ocean in the context of Indian Ocean monsoons (IOM). Topics discussed include ASIRI's objective the determination of freshwater distribution by submesoscale and mesoscale processes, principal investigators lead by ASIRI that focused on BoB modeling and turbulence process modeling.

The atmosphere typically receives heat from the open tropical ocean; an exception is the western and central Arabian Sea during the summer monsoon season. This article analyzes in situ observations from buoys and ships and examines mechanisms responsible for the reverse sea-air interfacial heat flux that have yet to be addressed. Key factors are the horizontal advection of heat and the heat flux derived via mixing and entrainment of air from above the atmospheric mixed layer in a Richardson number regime where shear-driven mixing would not normally be expected. This study invites a fresh look at the physics of entrainment and mixing in the atmospheric boundary layer. The reverse heat flux observations offer an opportunity to test the efficacy of physics encapsulated in boundary layer parameterization schemes for coupled models. [ABSTRACT FROM AUTHOR]

Long-term time series of velocity, hydrographic, and turbulence fields were collected from a six-element subsurface mooring array in the southern Bay of Bengal. The moorings, deployed in December 2013 and recovered in August 2015, were entangled with commercial fishing nets and lines, while top subsurface buoys ended up being serendipitously closer to the surface than planned. In spite of these unexpected events, almost all the sensors and data were recovered. The moorings provided currents between 6 m and 500 m depths from acoustic Doppler current profilers, supplemented by hydrographic data and turbulent dissipation rates at selected depths. The observations captured the summer and winter monsoon currents, eddies, and intraseasonal oscillations. Near-surface currents as large as 1.75 m s-1 were observed in July 2014. Currents stronger than 0.5 m s-1 were confined to the upper 200 m. Observations of currents, temperature, and sea surface height (SSH) fields revealed eddylike features with positive and negative SSH anomalies (~20 cm) moving westward at speeds of about 0.1 m s-1. Intraseasonal oscillations with periods of 30 to 90 days were strongest near the surface. For the duration of the deployment, root-mean-square velocity fluctuations were about 0.1 m s-1 near the surface but decayed with depth and became nearly uniform (~0.03-0.06 m s-1) below 100 m. [ABSTRACT FROM AUTHOR]

The region surrounding Sri Lanka modulates monsoon-driven exchange between the Bay of Bengal and the Arabian Sea. Here, local circulation impacts the pathways followed by the boundary currents that drive exchange, thereby modulating mixing and water mass transformation. From 2013 to 2016, an international partnership conducted sustained measurements around the periphery of Sri Lanka, with the goal of understanding how circulation and mixing in this critical region modulate exchange between the Bay of Bengal and the Arabian Sea. Observations from satellite remote sensing, surface drifters, gliders, current meter moorings, and Pressure Inverted Echo Sounders capture seasonally reversing monsoon currents off the southern tip of Sri Lanka, trace the wintertime freshwater export pathway of the East India Coastal Current, and document the deflection of currents running along the east coast of Sri Lanka by cyclonic and anticyclonic eddies. Measurements also reveal energetic interleaving, indicative of mixing and stirring associated with these flows. Circulation inferred from satellite remote sensing and drifter tracks sometimes differs from that indicated by in situ sections, pointing to the need for observing systems that employ complementary approaches toward understanding this region. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s10546-021-00655-9. Correction to: Boundary-Layer Meteorology https://doi.org/10.1007/s10546-021-00655-9 In the original publication, the last sentence in caption of Fig. Plots in the left panels; a, c, e correspond to unstable conditions, or CBL, <0; the right panels b, d, f represent stable conditions, or SBL, >0. [Extracted from the article]

The interaction of global climate change and urban heat islands (UHI) is expected to have far-reaching impacts on the sustainability of the world's rapidly growing urban population centers. Given that a wide range of spatiotemporal scales contributed by meteorological forcing and complex surface heterogeneity complicates UHI, a multimodel nested approach is used in this paper to study climate-change impacts on the Chicago, Illinois, UHI, covering a range of relevant scales. One-way dynamical downscaling is used with a model chain consisting of global climate (Community Atmosphere Model), regional climate (Weather Research and Forecasting Model), and microscale ('ENVI-met') models. Nested mesoscale and microscale models are evaluated against the present-day observations (including a dedicated urban miniature field study), and the results favorably demonstrate the fidelity of the downscaling techniques that were used. A simple building-energy model is developed and used in conjunction with microscale-model output to calculate future energy demands for a building, and a substantial increase (as much as 26% during daytime) is noted for future (~2080) climate. Although winds and lake-breeze circulation for future climate are favorable for reducing energy usage by 7%, the benefits are outweighed by such factors as exacerbated UHI and air temperature. An adverse change in human-comfort indicators is also noted in the future climate, with 92% of the population experiencing thermal discomfort. The model chain that was used has general applicability for evaluating climate-change impacts on city centers and, hence, for urban-sustainability studies. [ABSTRACT FROM AUTHOR]

Observations were taken on an east-facing sidewall at the foot of a desert mountain that borders a large valley, as part of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) field program at Dugway Proving Ground in Utah. A case study of nocturnal boundary layer development is presented for a night in mid-May when tethered-balloon measurements were taken to supplement other MATERHORN field measurements. The boundary layer development over the slope could be divided into three distinct phases during this night: 1) The evening transition from daytime upslope/up-valley winds to nighttime downslope winds was governed by the propagation of the shadow front. Because of the combination of complex topography at the site and the solar angle at this time of year, the shadow moved down the sidewall from approximately northwest to southeast, with the flow transition closely following the shadow front. 2) The flow transition was followed by a 3-4-h period of almost steady-state boundary layer conditions, with a shallow slope-parallel surface inversion and a pronounced downslope flow with a jet maximum located within the surface-based inversion. The shallow slope boundary layer was very sensitive to ambient flows, resulting in several small disturbances. 3) After approximately 2300 mountain standard time, the inversion that had formed over the adjacent valley repeatedly sloshed up the mountain sidewall, disturbing local downslope flows and causing rapid temperature drops. [ABSTRACT FROM AUTHOR]