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Boundary-layer wind associated with extratropical cyclones (ETCs) is an essential element for posing serious threats to the urban centers of eastern North America. Using a similar methodology for tropical cyclone (TC) wind risk (i.e., hurricane tracking approach), the ETC wind risk can be accordingly simulated. However, accurate and efficient assessment of the wind field inside the ETC is currently not available. To this end, a knowledge-enhanced deep learning (KEDL) is developed in this study to estimate the ETC boundary-layer winds over eastern North America. Both physics-based equations and semi-empirical formulas are integrated as part of the system loss function to regularize the neural network. More specifically, the scale-analysis-based reduced-order Navier–Stokes equations that govern the ETC wind field and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) ERA-interim data-based two-dimensional (2D) parametric formula (with respect to radial and azimuthal coordinates) that prescribes an asymmetric ETC pressure field are respectively employed as rationalism-based and empiricism-based knowledge to enhance the deep neural network. The developed KEDL, using the standard storm parameters (i.e., spatial coordinates, central pressure difference, translational speed, approach angle, latitude of ETC center, and surface roughness) as the network inputs, can provide the three-dimensional (3D) boundary-layer wind field of an arbitrary ETC with high computational efficiency and accuracy. Finally, the KEDL-based wind model is coupled with a large ETC synthetic track database (SynthETC), where 6-hourly ETC center location and pressure deficit are included to effectively assess the wind risk along the US northeast coast in terms of annual exceedance probability.

We used a compact boundary layer wind tunnel equipped with a turbulence generator and a piezoelectric blown-sand meter to investigate the effects of the surface coverage of fine gravel on wind-blown sand flux. The vertical profile of wind-blown sand over a flat sand surface showed an exponential distribution at all wind speeds, whereas the profile over gravel surfaces of 20% or greater coverage showed a non-monotonic vertical distribution. At 20% to 30% gravel coverages, a peak of wind-blown sand flux developed between 6 and 10 cm above the ground at all wind speeds because of less energy loss due to grain-bed collisions at that level. To analyze the erosional state of wind-blown sand, we used the Wu–Ling index (λ) of the mass-flux density of sand-bearing wind. Values of λ for all gravel coverages were greater than 1 at all wind speeds, indicating an unsaturated (erosional) state. Moreover, we found that the wind-blown sand flux at 4 cm height accounted for about 20% of the total flux regardless of wind speed and gravel coverage. This finding can simplify future estimations of total near-surface wind-blown sand flux based on field observations because such measurements can be taken at just one height.

This study examines the boundary layer wind profile and turbulence variables during the landfalls of Hurricanes Ida (2021) and Zeta (2020) using ground‐based Doppler radar observations and a nearby anemometer's wind measurements. While the radar sampled different parts of the hurricane circulation of the two cases, the observed maximum near‐surface wind and frictional velocity were similar. Radar‐retrieved wind profiles in both hurricanes revealed a boundary‐layer jet generally >1 km AGL, descending toward smaller radii as the hurricanes moved inland. A “knee‐like” structure in most wind profiles below the jet suggests an internal boundary layer (IBL) below 200 m and a log layer above it. Among the three methods for estimating near‐surface sustained winds from radar‐retrieved winds, leveraging low‐level IBL winds improves estimation accuracy and reduces the uncertainty to the selection of upstream surface roughness length. These findings offer valuable guidance for developing future probabilistic near‐surface wind products.

The evolution of the tropical cyclone boundary layer (TCBL) wind field before landfall is examined in this study. As noted in previous studies, a typical TCBL wind structure over the ocean features a supergradient boundary layer jet to the left of motion and Earth-relative maximum winds to the right. However, the detailed response of the wind field to frictional convergence at the coastline is less well known. Here, idealized numerical simulations reveal an increase in the offshore radial and vertical velocities beginning once the TC is roughly 200 km offshore. This increase in the radial velocity is attributed to the sudden decrease in frictional stress once the highly agradient flow crosses the offshore coastline. Enhanced advection of angular momentum by the secondary circulation forces a strengthening of the supergradient jet near the top of the TCBL. Sensitivity experiments reveal that the coastal roughness discontinuity dominates the friction asymmetry due to motion. Additionally, increasing the inland roughness through increasing the aerodynamic roughness length enhances the observed asymmetries. Last, a brief analysis of in situ surface wind data collected during the landfall of three Gulf of Mexico hurricanes is provided and compared to the idealized simulations. Despite the limited in situ data, the observations generally support the simulations. The results here imply that assumptions about the TCBL wind field based on observations from over horizontally homogeneous surface types—which have been well documented by previous studies—are inappropriate for use near strong frictional heterogeneity.

This is the second of a two-part study that explores the capabilities of a mesoscale atmospheric model to reproduce the near-surface wind fields in hurricanes over land. The Weather Research and Forecasting (WRF) Model is used with two planetary boundary layer parameterizations: the Yonsei University (YSU) and the Mellor–Yamada–Janjić (MYJ) schemes. The first part presented the modeling framework and initial conditions used to produce simulations of Hurricane Wilma (2005) that closely reproduced the track, intensity, and size of its wind field as it passed over South Florida. This part explores how well these simulations can reproduce the winds at fixed points over land by making comparisons with observations from airports and research weather stations. The results show that peak wind speeds are remarkably well reproduced at several locations. Wind directions are evaluated in terms of the inflow angle relative to the storm center, and the simulated inflow angles are generally smaller than observed. Localized peak wind events are associated with vertical vorticity maxima in the boundary layer with horizontal scales of 5–10 km. The boundary layer winds are compared with wind profiles obtained by velocity–azimuth display (VAD) analyses from National Weather Service Doppler radars at Miami and Key West, Florida; results from these comparisons are mixed. Nonetheless the comparisons with surface observations suggest that when short-term hurricane forecasts can sufficiently predict storm track, intensity, and size, they will also be able to provide useful information on extreme winds at locations of interest.

Wind profiles are fundamental to the research and applications in boundary layer meteorology, air quality and numerical weather prediction. Large-scale wind profile data have been previously documented from network observations in several countries, such as Japan, the USA, various European countries and Australia, but nationwide wind profiles observations are poorly understood in China. In this study, the salient characteristics and performance of wind profiles as observed by the radar wind profiler network of China are investigated. This network consists of more than 100 stations instrumented with 1290 MHz Doppler radar designed primarily for measuring vertically resolved winds at various altitudes but mainly in the boundary layer. It has good spatial coverage, with much denser sites in eastern China. The wind profiles observed by this network can provide the horizontal wind direction, horizontal wind speed and vertical wind speed for every 120 m interval within the height of 0 to 3 km. The availability of the radar wind profiler network has been investigated in terms of effective detection height, data acquisition rate, data confidence and data accuracy. Further comparison analyses with reanalysis data indicate that the observation data at 89 stations are recommended and 17 stations are not recommended. The boundary layer wind profiles from China can provide useful input to numerical weather prediction systems at regional scales.

Wind-tunnel modeling of Atmospheric Boundary Layer flows has primarily consisted of simplified (purely uniform) upwind terrain conditions. This approach is easier to carry out but may not replicate the true wind characteristics of the site. This paper proposes a method to simulate nonuniform terrains in a wind-tunnel and investigates the wind characteristics produced by the method. The proposed method employs the local roughness zones where the given terrain is divided into sub-areas with an approximately uniform roughness length. Next, each sub-area is represented in the wind-tunnel with uniform roughness elements. However, the overall upwind fetch will be composed of roughness elements of various heights. To study the wind characteristics produced by the method, nine different real-world sites were simulated in the Boundary Layer Wind Tunnel at the University of Florida Natural Hazard Engineering Infrastructure Experimental Facility, using a self-configurable (automated) roughness element grid. Compared with the conventional equivalent uniform representation, similarities and differences in the longitudinal mean velocity, turbulence intensity, wind spectrum, and integral length scale profiles are reported and discussed. In particular, a significant difference was observed for the higher-order moments of the longitudinal velocity component, which indicates the need for further studies in wind loads under nonuniform terrains.

During the 2015 Plains Elevated Convection at Night (PECAN) field campaign, several nocturnal low-level jets (NLLJs) were observed with integrated boundary layer profiling systems at multiple sites. This paper gives an overview of selected PECAN NLLJ cases and presents a comparison of high-resolution observations with numerical simulations using the Weather Research and Forecasting (WRF) Model. Analyses suggest that simulated NLLJs typically form earlier than the observed NLLJs. They are stronger than the observed counterparts early in the event, but weaker than the observed NLLJs later in the night. However, sudden variations in the boundary layer winds, height of the NLLJ maximum and core region, and potential temperature fields are well captured by the WRF Model. Simulated three-dimensional fields are used for a more focused analysis of PECAN NLLJ cases. While previous studies often related changes in the thermal structure of the nocturnal boundary layer and sudden mixing events to local features, we hypothesize that NLLJ spatial evolution plays an important role in such events. The NLLJ is shown to have heterogeneous depth, wind speed, and wind direction. This study offers detailed documentation of the heterogeneous NLLJ moving down the slope of the Great Plains overnight. As the NLLJ evolves, westerly advection becomes significant. Buoyancy-related mechanisms are proposed to explain NLLJ heterogeneity and down-slope motion. Spatial and temporal heterogeneity of the NLLJ is suggested as a source of the often observed and simulated updrafts during PECAN cases and as a possible mechanism for nocturnal convection initiation. The spatial and temporal characteristics of the NLLJ are interconnected and should not be treated independently.

Downbursts are negatively buoyant downdrafts that emerge from a storm and spread outward upon hitting the surface. The produced outflow, however, is not spreading through a calm environment, but rather through an atmosphere characterized by larger-scale atmospheric boundary layer (ABL) winds. This interaction between ABL winds and downbursts forms an outflow that is more complex than an outflow created by an isolated downdraft. Here, we propose an analytical solution of the interaction between the ABL winds and an isolated downburst outflow. The model is applicable when the ratio of centerline downdraft velocity to the horizontal ABL velocity at the cloud base is larger than the nondimensional group ( H / D )( r / H ) 1.1 , where H is the cloud-base height, D is the diameter of the downdraft, and r is the distance from the centerline of isolated downdraft. Also, the solution is derived for a specific direction in the outflow when the ABL winds and the isolated downburst outflow are aligned and the vertical profiles of radial velocity are self-similar. The model is based on the use of impinging-jet dynamics, their spreading rates, and a universal renormalization group that describes numerous laboratory measurements of velocity profiles of impinging jets issuing into both quiescent and crossflowing backgrounds. The model assumes a “known” base state corresponding to an isolated downburst, and then derives its interaction with ABL winds by way of perturbation analysis. The radial and vertical profiles of horizontal velocity from our analytical model are compared against field observations of actual downbursts and other analytical models and physical simulations of downburst-like outflows.

Parameterizations of turbulent processes in planetary boundary layer (PBL) schemes impact tropical cyclone (TC) forecasts. Existing PBL schemes are mostly designed for low‐wind conditions, and assessing their uncertainties in hurricane conditions remains challenging, mostly due to very scarce observations. Using a recently developed framework based on large‐eddy simulations (LES), this study evaluates K‐profile parameterization (KPP) and high‐order PBL schemes in hurricane conditions. Among KPP PBL schemes, the Global Forecast System (GFS) scheme tends to produce excessively deep inflow layers with large values of eddy viscosity (Km). Opposite results are found for the Yonsei University (YSU) scheme. Using LES results as a benchmark, the performance of YSU and GFS schemes is improved by modifying the “shape parameter” such that Km is maximized closer to the surface, and by using a new definition of boundary layer height tailored to high‐wind conditions. The LES results also suggest an asymptotic mixing length of ∼40 m can improve the Louis‐type parameterizations of the YSU scheme that operates above the boundary layer. Among high‐order PBL schemes, the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme produces reasonably accurate vertical profiles of eddy viscosity, turbulent stress, and boundary layer winds under different high‐wind conditions. Further analysis of MYNN supports a “three‐layer” strategy for the mixing length parameterization for TCs that represents different types of turbulent regimes. In contrast, the high‐order eddy‐diffusivity mass‐flux scheme produces excessive boundary‐layer vertical mixing and a deeper inflow layer, partly attributable to a notable overestimation of the maximum allowable mixing length in the PBL code. Plain Language Summary Turbulence is made up of random and continuously changing wind. The energy and momentum exchange between the ocean and the lowest ∼1 km atmosphere (i.e., planetary boundary layer or PBL) is through turbulent processes. The size of turbulent eddies, however, is much smaller than the grid spacings of mesoscale numerical models, and thus cannot be directly resolved by model grids. Therefore, parameterizations of boundary‐layer turbulence (or PBL schemes) are involved to mimic the turbulent processes on these small scales. These PBL schemes are typically designed for low‐wind conditions, and uncertainties of directly applying them to high‐wind conditions like hurricanes are not well known, in part due to very scarce turbulence measurements in hurricane boundary layers. This study uses a recently developed modeling framework based on large‐eddy simulation (where model grids are small enough to resolve turbulence) to evaluate two types of PBL schemes in hurricane conditions. The framework reveals the pros and cons of each PBL scheme. Using this insight, we recommend suitable PBL schemes for tropical cyclone (TC) modeling and propose solutions to address identified issues in these PBL schemes. These findings provide valuable guidance to the development of PBL schemes in high‐wind conditions that may improve TC forecasts. Key Points Two types of planetary boundary layer (PBL) schemes are evaluated in hurricane conditions using a recently developed modeling framework K‐profile parameterization PBL schemes are inherently flawed in hurricane boundary layers The Mellor–Yamada–Nakanishi–Niino scheme performs well in hurricane conditions due to its high‐order closure and sophisticated parameterization of mixing length