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The verification of whether small-scale turbulence is isotropic remains a grand challenge. The difficulty arises because the presence of small-scale anisotropy is tied to the dissipation tensor, whose components require the full three-dimensional information of the flow field in both high spatial and temporal resolution, a condition rarely satisfied in turbulence experiments, especially during field scale measurement of atmospheric turbulence. To circumvent this issue, an intermittency-anisotropy framework is proposed through which we successfully extract the features of small-scale anisotropy from single-point measurements of turbulent time series by exploiting the properties of small-scale intermittency. Specifically, this framework quantifies anisotropy by studying the contrasting effects of burstlike activities on the scalewise production of turbulence kinetic energy between the horizontal and vertical directions. The veracity of this approach is tested by applying it over a range of datasets covering an unprecedented range in the Reynolds numbers (Re≈103-106), sampling frequencies (10 kHz to 10 Hz), surface conditions (aerodynamically smooth surfaces to typical grasslands to forest canopies), and flow types (channel flows, boundary-layer flows, atmospheric flows, and flows over forest canopies). For these diverse datasets, the findings indicate that the effects of small-scale anisotropy persists up to the integral scales of the streamwise velocity fluctuations and there exists a universal relationship to predict this anisotropy from the two-component state of the Reynolds stress tensor. This relationship is important towards the development of next-generation closure models of wall turbulence by incorporating the effects of anisotropy at smaller scales of the flow.

Wildland fire–atmosphere interaction generates complex turbulence patterns, organized across multiple scales, which inform fire-spread behaviour, firebrand transport, and smoke dispersion. Here, we utilize wavelet-based techniques to explore the characteristic temporal scales associated with coherent patterns in the measured temperature and the turbulent fluxes during a prescribed wind-driven (heading) surface fire beneath a forest canopy. We use temperature and velocity measurements from tower-mounted sonic anemometers at multiple heights. Patterns in the wavelet-based energy density of the measured temperature plotted on a time–frequency plane indicate the presence of fire-modulated ramp–cliff structures in the low-to-mid-frequency band (0.01–0.33 Hz), with mean ramp durations approximately 20% shorter and ramp slopes that are an order of magnitude higher compared to no-fire conditions. We then investigate heat- and momentum-flux events near the canopy top through a cross-wavelet coherence analysis. Briefly before the fire-front arrives at the tower base, momentum-flux events are relatively suppressed and turbulent fluxes are chiefly thermally-driven near the canopy top, owing to the tilting of the flame in the direction of the wind. Fire-induced heat-flux events comprising warm updrafts and cool downdrafts are coherent down to periods of a second, whereas ambient heat-flux events operate mainly at higher periods (above 17 s). Later, when the strongest temperature fluctuations are recorded near the surface, fire-induced heat-flux events occur intermittently at shorter scales and cool sweeps start being seen for periods ranging from 8 to 35 s near the canopy top, suggesting a diminishing influence of the flame and increasing background atmospheric variability thereat. The improved understanding of the characteristic time scales associated with fire-induced turbulence features, as the fire-front evolves, will help develop more reliable fire behaviour and scalar transport models.

Mesoscale-to-microscale coupling is an important tool for conducting turbulence-resolving multiscale simulations of realistic atmospheric flows, which are crucial for applications ranging from wind energy to wildfire spread studies. Different techniques are used to facilitate the development of realistic turbulence in the large-eddy simulation (LES) domain while minimizing computational cost. Here, we explore the impact of a simple and computationally efficient Stochastic Cell Perturbation method using momentum perturbation (SCPM-M) to accelerate turbulence generation in boundary-coupled LES simulations using the Weather Research and Forecasting model. We simulate a convective boundary layer (CBL) to characterize the production and dissipation of turbulent kinetic energy (TKE) and the variation of TKE budget terms. Furthermore, we evaluate the impact of applying momentum perturbations of three magnitudes below, up to, and above the CBL on the TKE budget terms. Momentum perturbations greatly reduce the fetch associated with turbulence generation. When applied to half the vertical extent of the boundary layer, momentum perturbations produce an adequate amount of turbulence. However, when applied above the CBL, additional structures are generated at the top of the CBL, near the inversion layer. The magnitudes of the TKE budgets produced by SCPM-M when applied at varying heights and with different perturbation amplitudes are always higher near the surface and inversion layer than those produced by No-SCPM, as are their contributions to the TKE. This study provides a better understanding of how SCPM-M reduces computational costs and how different budget terms contribute to TKE in a boundary-coupled LES simulation.

The intensity and frequency of wildfires in California (CA) have increased in recent years, causing significant damage to human health and property. In October 2007, a number of small fire events, collectively referred to as the Witch Creek Fire or Witch Fire started in Southern CA and intensified under strong Santa Ana winds. As a test of current mesoscale modeling capabilities, we use the Weather Research and Forecasting (WRF) model to simulate the 2007 wildfire event in terms of meteorological conditions. The main objectives of the present study are to investigate the impact of horizontal grid resolution and planetary boundary layer (PBL) scheme on the model simulation of meteorological conditions associated with a Mega fire. We evaluate the predictive capability of the WRF model to simulate key meteorological and fire-weather forecast parameters such as wind, moisture, and temperature. Results of this study suggest that more accurate predictions of temperature and wind speed relevant for better prediction of wildfire spread can be achieved by downscaling regional numerical weather prediction products to 1 km resolution. Furthermore, accurate prediction of near-surface conditions depends on the choice of the planetary boundary layer parameterization. The MYNN parameterization yields more accurate prediction as compared to the YSU parameterization. WRF simulations at 1 km resolution result in better predictions of temperature and wind speed than relative humidity during the 2007 Witch Fire. In summary, the MYNN PBL parameterization scheme with finer grid resolution simulations improves the prediction of near-surface meteorological conditions during a wildfire event.

In turbulent flows, energy production is associated with highly organized structures, known as coherent structures. Since these structures are three dimensional, their detection remains challenging in the most common situation in experiments, when single-point temporal measurements are considered. While previous research on coherent structure detection from time series employs a thresholding approach, either in spectral or temporal domain, the thresholds are ad hoc and vary significantly from one study to another. To circumvent this issue, we introduce the level-crossing method and show how specific features of a turbulent time series associated with coherent structures can be objectively identified, without assigning a priori any arbitrary threshold. By using two wall-bounded turbulence time-series datasets (at a Reynolds number of 104), we successfully extract through level-crossing analysis the impacts of coherent structures on turbulent dynamics and therefore open an alternative avenue in experimental turbulence research. By utilizing this framework further, we discover a metric, characterized by a statistical asymmetry between the peaks and troughs of a turbulent signal, to quantify inner-outer interaction in wall turbulence. Most importantly, through phase-randomized surrogate data modeling, we demonstrate that the level-crossing statistics are quite sensitive to the nonlinear dependencies in a turbulent signal. Physically, this finding implies that the large-scale coherent structures modulate the near-wall turbulent dynamics through a nonlinear interaction associated with low-speed streaks, a mechanism not identifiable from spectral analysis alone. Moreover, a connection is established between extreme value statistics and level-crossing analysis, thereby allowing additional possibilities to study extreme events in other dynamical systems.

Shaded fuel breaks are treatments that aim to mitigate wildfires by establishing linearly aligned locations where wildfire suppression efforts can be more effective at stopping wildfires. Despite the potential of fuel breaks to alter fire behavior, there have been limited quantitative assessments of their effectiveness following exposure to wildfires. In addition, wildfires often occur in complex terrains that are difficult to access with ground vehicles and sensors, posing challenges for data acquisition. However, the use of Remote-controlled Aerial Vehicles (RAVs), such as drones, is becoming increasingly popular as a viable means of conducting high-resolution observations in areas of interest. This study presents the results from a unique opportunity to utilize three distinct observation scale platforms (in-situ, aerial, and spaceborne) to investigate the burn severity impacts across a prior shaded fuel break that serendipitously encountered the 2020 Creek Fire in the Sierra Nevada forests of California, USA. To provide a direct measure of fire severity, ground-based measurements determined the percentage crown volume (PCV) of scorch and char as a function of distance from the fuel break edge. Along five transects of the fuel break, we also utilized visible bands from drone imagery and digital photogrammetry, to generate georeferenced orthophotos and quantify vegetation health using the Green Leaf Index (GLI). We also quantified burn severity by computing the Delta Normalized Burn Ratio (dNBR) and vegetation health using the Normalized Difference Vegetation Index (NDVI) from Sentinel 2 spaceborne observations. Our results indicate that within the fuel break, the PCV of char is 2 × less than it was outside of it (with PCV char declining at a rate of 2% per 3 m into the fuel break). Burn severity is 5 × less, and vegetation health is approximately 3 × greater within the fuel break compared to directly outside. Furthermore, postfire vegetation health was only 1 × less within the fuel break compared to the pre fire condition, whereas it was 5 × less in the surrounding region. The results confirm that the fuel break altered the fire behavior, reducing the fire intensity, thereby proving effective at reducing fire burn severity and preserving vegetation health within the fuel break.

Fire-induced turbulence and the feedback into the fire, following ambient changes, differ for forested (sub-canopy) and grassland environments. Here, we synthesize observations from multiple experimental surface fires: two sub-canopy backing fires, one sub-canopy heading fire, and a grassland heading fire. We identify and compare the most essential coherent structures and processes of each case from the turbulent momentum fluxes and turbulent kinetic energy (TKE) budget terms. In the sub-canopy burns, turbulent eddies are strongest near the canopy top: high streamwise turbulent flux accompanies low cross-stream turbulent flux and vice versa. In the grassland fire, both streamwise and cross-stream eddies strengthen simultaneously until a certain height, informing a vertical length scale for the fire-influence. Moreover, the forward sweep from streamwise eddies assists in the fire spread by pushing hot gases towards unburnt fuel. In the sub-canopy fires, shear production and buoyancy production are more substantial near the canopy top for more intense fires, while their magnitudes decrease with decreasing fire intensity. At mid-canopy-height scales, buoyancy production dominates shear production, becoming the key mechanism for vertical transport of TKE. In the grassland fire, shear production dominates buoyancy production near the surface and is insignificant beyond a certain height relative to the flame length, while buoyancy production increases with height, becoming substantial further away from the surface. Turbulent transport terms are also active in both environments. For intense sub-canopy fires, there is a loss in TKE due to its expulsion to the boundary layer aloft via the transport term, compensated by a reversal process: TKE influx via the transport term. In the grassland fire, the transport term mimics this behavior until a certain height. The insights into the relative significance of the respective turbulent fluxes and TKE budget terms in each environment can help simplify the complex system of equations governing fire physics.

The Internet-of-things ecosystem has been a driving force in the creation of smart communities where a variety of physical phenomena can be monitored continuously, e.g., air quality, traffic conditions on roads, energy consumption in buildings, etc. In this paper, we address how IoT can be quickly and effectively deployed for short-term and sporadic events (e.g., fire spread in a wildland area and flood propagation), where monitoring the evolving event is critical. In particular, we propose QuIC-IoT, a model-driven planning platform that aims to temporarily deploy a custom IoT infrastructure for monitoring short-term events, where phenomena-spread is driven by models that are physics-based. Our driving usecase event is a quasi-planned prescribed fire or RxFire - this is a wildfire resilience technique where intentional small fires are ignited apriori by forestry personnel to destroy fuel and help contain the spread of actual wildfires. Anomalies that may occur during these quasi-planned events must be rapidly captured by the IoT deployment, e.g., escaped RxFires can escalate to catastrophic wildfires under unpredictable conditions of wind, vegetation, etc. QuIC-IoT incorporates domain expert-developed models to guide IoT deployment; the event area is partitioned into subregions and a criticality metric that quantifies the likelihood of anomalies at each location is computed. QuIC-IoT allows us to mix fixed and quasi-mobile IoT devices to flexibly deploy IoT in challenging terrain and as the phenomena (RxBurn) evolves. We evaluate QuIC-IoT in two real-world forest settings (large and small) in Blodgett Forest, CA, USA, with concrete burn plans developed by wildfire experts. Our experimental results reveal that QuIC-IoT enables over 3X improvement in cost-effectiveness and performance (timely detection of anomalies) as compared to baseline IoT deployment algorithms.

We develop a Drone-assisted Monitoring system, DOME, that gathers real-time data for situational awareness in emergent and evolving events. The driving use case for this work is a prescribed burn event (Rx fire), o ften u sed t o r educe h azardous f uels i n forests. DOME coordinates the use of multiple heterogeneous drone platforms to support the observation of emergent physical phenomena (e.g., fire spread) by leveraging domain expert input and physics-based modeling/simulation methods. We propose an executable rule-based system for drone task generation; here, a high-level mission specification utilizes physics-based models for fire spread prediction and automatically generates monitoring instructions with locations, periods, and frequency for drones. DOME integrates algorithms for task allocation (mapping tasks to drones) and flight path planning while considering trade-offs between sensing coverage and accuracy. In addition, DOME will guide in-flight drones to store and upload data under challenged communication settings (out of transmission range, external signal blocking by trees). We evaluate the performance of DOME in real events (with expert-developed burn plans). We test the applicability of the DOME system using simulated Rx burns at the Blodgett Forest Research Station and evaluate our proposed algorithms by comparing their performance with multiple baseline algorithms. Our experiments show the effectiveness of the composite mechanisms in DOME that outperforms other approaches with higher rewards (capturing data of higher quality) and coverage (reduction of missed tasks).

Turbulent signals are known to exhibit burstlike activities, which affect the turbulence statistics at both large and small scales of the flow. In our study, we pursue this problem from the perspective of an event-based framework, where bursting events are studied across multiple scales in terms of both their size and duration. To illustrate our method and assess any dependence on the Reynolds number (Re), we use two data sets: from the Melbourne wind tunnel (Re≈14750) and from SLTEST, an atmospheric surface layer experiment (Re≈106). We show that an index, namely, the "burstiness index,"can be used successfully to describe the multiscale nature of turbulent bursting while accounting for the small-scale intermittency effects. With this index, we demonstrate that irrespective of Re, the presence of large amplitude fluctuations in the instantaneous velocity variance and momentum flux signals are governed by the coherent structures in the flow. For small-scale turbulence, a Re dependence is noted while studying the scalewise evolution of the burstiness features of second-order streamwise velocity increments ((Δu)2). Specific to the wind-tunnel data set, the burstiness index of the (Δu)2 signal displays a strong dependence on height and decreases as the scales increase with the maximum being obtained at scales comparable to the dissipative structures. However, such features are nearly absent in the atmospheric flows. To conclude, this research paves a way to evaluate the effect of bursts on the turbulence statistics at any specified scale of the flow.

This study 1) identifies the seasons and biomes that exhibit significant (1980-2019) changes in fire danger potential, as quantified by the Canadian Fire Weather Index (FWI); 2) explores what types of fire behavior potentials may be contributing to changes in fire danger potential, as quantified by the United States Energy Release Component (ERC) and the Ignition Component (IC); 3) provides spatiotemporal insight on how fire danger potential and fire behavior potential are responding in relation to changes in seasonal precipitation totals and seasonal mean air temperature across biomes. Time series of these fire potentials, as well as seasonal mean temperature, and seasonal precipitation totals are generated using data from the 0.25° ECMWF spatial resolution Reanalysis 5th Generation (ERA5) and the Climatic Research Unit gridded Time Series (CRU TS). The Mann-Kendall test is then applied to identify significant spatiotemporal trends across each biome. Results indicate that the September-November season (SON) exhibits the greatest rate of increase in fire danger potential, followed by the June-August season (JJA), December, January-February season (DJF), and March-May season (MAM), and this is predominant over the Tropical and Subtropical Moist Broadleaf Forest Biome, as well as all vegetation types of the temperate biomes. Similarly, the temperate biomes experience the greatest rate of increase in fire intensity potential and ignition potential, but prevalent during the DJF and MAM seasons. Furthermore, there is a significant positive correlation between fire danger potential and seasonal mean air temperature during JJA in the Northern Hemisphere for the temperate biomes in North America and Europe, as well as the Tropical and Subtropical biomes in Africa. Our analysis provides quantitative insight as to how fire danger potential and fire behavior potential have been responding to changes in seasonal mean temperature and seasonal precipitation totals across different ecoregions around the world.

Past studies reported a drastic growth in the wildland–urban interface (WUI), the location where man-made structures meet or overlap wildland vegetation. Fighting fire is difficult in the WUI due to the combination of wildland and structural fuels, and therefore, WUI areas are characterized by frequent damage and loss of structures from wildfires. Recent wildland fire policy has targeted fire prevention, evacuation planning, fuel treatment, and home hardening in WUI areas. Therefore, it is important to understand the occurrence of wildfire events relative to the location of the WUI. In this work, we have reported the occurrences of wildfires with respect to the WUI and quantified how much of the WUI is on complex topography in California, which intensifies fire behavior and complicates fire suppression. We have additionally analyzed the relative importance of WUI-related parameters, such as housing density, vegetation density, and distance to wildfires, as well as topographic factors, such as slope, elevation, aspect, and surface roughness, on the occurrence of large and small wildfires and the burned area of large wildfires near the WUI. We found that a very small percentage of wildfire ignition points and large wildfire-burned areas (>400 ha or 1000 acres) were located in the WUI areas. A small percentage of large wildfires were encountered in WUI (3%), and the WUI area accounted for only 4% of the area burned, which increased to 5% and 56%, respectively, outside WUI (5-km buffer from WUI). Similarly, 66% of fires ignited outside WUI, whereas only 3.6% ignited within WUI. Results from this study have implications for fuel management and infrastructure hardening, as well as for fire suppression and community response.

Flood and debris hazards are heightened following wildfires, but are challenging to quantify due to interdependence between fire frequency and severity, runoff and sediment fluxes during storms, and sedimentation that reduces infrastructure capacity. Herein we present a stochastic simulation framework to estimate compound flood and debris hazards from sequences of wildfires and rainstorms and the accumulation of sediment within flood infrastructure. Application of the framework to a hypothetical watershed representative of southern California shows that the present-day compound hazard may be up to 6 times greater than the marginal hazard posed by peak flows in the absence of wildfire, and that future compound hazards could be up to 11 times greater than the marginal hazard based on future increases in wildfire frequency. Numerous sensitivities are investigated, including infrastructure design and maintenance, which are shown to be crucial for moderating future increases in post-fire flood hazards.

Partitioning evapotranspiration (ET) into its primary components, that is, evaporation (E) and plant transpiration (T), is needed in a range of hydrometeorological applications. Using vegetation index (VI) to obtain spatially resolved T:ET ratio over large areas has emerged as a promising approach in this regard. Here, we assess the effectiveness of this approach in differently managed wheat systems. Results show a weak relation between T:ET and VI in disturbed (i.e., grazed) systems. Furthermore, flux partition based on a canonical T:ET versus VI relation or the relation derived in a neighboring undisturbed wheat system introduce large errors in disturbed systems, thus underscoring the limits on the transferability of the VI-based ET partitioning approach. The effectiveness of the VI-based approach is found to be related to the strength of correlation between VI and vapor pressure deficit and/or radiation. This correlation metric can help identify settings where the approach is likely to be effective.

Prescribed (Rx) burns are conducted on days when the meteorological thresholds of maximum air temperature, relative humidity, and wind speeds are all met (burn window) in order to ensure safe Rx burn practices. Limited burn windows have been consistently identified as one of the most important constraints for conducting Rx burns in California. We investigate whether burn windows across California can be extended from the typical fall season to include other opportune seasons for facilitating specific management objectives. We quantify the seasonal Rx burn efficiencies by assessing the frequency and burned areas using an aggregate of Rx datasets, and we compute the seasonal spatiotemporal trends in the number of days the set of meteorological parameters are met over thirty-five years (1984 to 2019), using the gridMET 4 km dataset. Our results indicate that while fall burns are most frequently executed (40% of the time), the spring (and to a lesser extent winter) seasons yield efficient Rx burns similar to fall because greater acres are being consumed with less burns. In addition, winter and spring seasons experience burn window opportunities (70-90% of the time) over larger areas than the other seasons, and this is predominantly over forested regions in Northern California. Our results also indicate that burn windows in the winter and spring are decreasing at a rate of one day per year over a larger spatial area than that of summer and fall. This decrease is primarily driven by changes in the number of days the relative humidity thresholds are met. Policymakers recognize the critical importance that Rx burns have on a multitude of ecosystem restoration factors, fire behavior dynamics, and firefighter safety. Therefore, there is a need to capitalize on these additional burn windows before these opportunities become less feasible in the future.

We investigate the intermittent dynamics of momentum transport and its underlying time scales in the near-wall region of the neutrally stratified atmospheric boundary layer in the presence of a vegetation canopy. This is achieved through an empirical analysis of the persistence time scales (periods between successive zero-crossings) of momentum flux events, and their connection to the ejection-sweep cycle. Using high-frequency measurements from the GoAmazon campaign, spanning multiple heights within and above a dense canopy, the analysis suggests that, when the persistence time scales of momentum flux events from four different quadrants are separately normalized by (integral time scale of the vertical velocity), their distributions remain height-invariant. This result points to a persistent memory imposed by canopy-induced coherent structures, and to their role as an efficient momentum-transporting mechanism between the canopy airspace and the region immediately above. Moreover, exhibits a power-law scaling at times < tp, with an exponential tail appearing for. By separating the flux events based on, we discover that around 80 % of the momentum is transported through the long-lived events at heights immediately above the canopy, while the short-lived ones (

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

This paper explores the suitability of upcoming novel computing technologies, particularly adiabatic annealing based quantum computers, to solve fluid dynamics problems that form a critical component of several science and engineering applications. For our experiments, we start with a well-studied one-dimensional simple flow problem, and provide a framework to convert such problems in continuum to a form amenable for deployment on such quantum annealers. Since the DWave annealer returns multiple states sampling the energy landscape of the problem, we explore multiple solution selection strategies to approximate the solution of the problem. We analyze the continuum solutions obtained both qualitatively and quantitatively as well as their sensitivities to the particular solution selection scheme.

High frequency (30 Hz) two-dimensional particle image velocimetry data recorded during a field experiment exploring fire spread from point ignition in hand-spread pine needles under calm ambient wind conditions are analysed in this study. In the initial stages, as the flame spreads approximately radially away from the ignition point in the absence of a preferred wind-forcing direction, it entrains cooler ambient air into the warmer fire core, thereby experiencing a dynamic pressure resistance. The fire-front, comprising a flame that is tilted inward, is surrounded by a region of downdraft. Coherent structures describe the initial shape of the fire-front and its response to local wind shifts while also revealing possible fire-spread mechanisms. Vortex tubes originating outside the fire spiral inward and get stretched thinner at the fire-front leading to higher vorticity there. These tubes comprise circulation structures that induce a radially outward velocity close to the fuel bed, which pushes hot gases outward, thereby causing the fire to spread. Moreover, these circulation structures confirm the presence of counter-rotating vortex pairs that are known to be a key mechanism for fire spread. The axis of the vortex tubes changes its orientation alternately towards and away from the surface of the fuel bed, causing the vortex tubes to be kinked. The strong updraft observed at the location of the fire-front could potentially advect and tilt the kinked vortex tube vertically upward leading to fire-whirl formation. As the fire evolves, its perimeter disintegrates in response to flow instabilities to form smaller fire "pockets". These pockets are confined to certain points in the flow field that remain relatively fixed for a while and resemble the behavior of a chaotic system in the vicinity of an attractor. Increased magnitudes of the turbulent fluxes of horizontal momentum, computed at certain such fixed points along the fire-front, are symptomatic of irregular fire bursts and help contextualize the fire spread. Most importantly, the time-varying transport terms of the turbulent kinetic energy budget equation computed at adjacent fixed points indicate that local fires along the fire-front primarily interact via the horizontal turbulent transport term.

Large-scale intermittency is a widely observed phenomenon in convective surface layer turbulence that induces non-Gaussian temperature statistics, while such a signature is not observed for velocity signals. Although approaches based on probability density functions have been used so far, those are not able to explain to what extent the signals' temporal structure impacts the statistical characteristics of the velocity and temperature fluctuations. To tackle this issue, a visibility network analysis is carried out on a field-experimental dataset from a convective atmospheric surface layer flow. Through surrogate data and network-based measures, we demonstrate that the temperature intermittency is related to strong nonlinear dependencies in the temperature signals. Conversely, a competition between linear and nonlinear effects tends to inhibit the temperature-like intermittency behaviour in streamwise and vertical velocities. Based on present findings, new research avenues are likely to be opened up in studying large-scale intermittency in convective turbulence.

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous and mountainous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

Mesoscale-to-Large Eddy Simulation (LES) grid nesting is an important tool for many atmospheric model applications, ranging from wind energy to wildfire spread studies. Different techniques are used in such applications to accelerate the development of turbulence in the LES domain. Here, we explore the impact of a simple and computationally efficient Stochastic Cell Perturbation method (SCPM) to accelerate the generation of turbulence in the Weather Research and Forecasting (WRF) LES model on the Turbulence Kinetic Energy (TKE) budget. In a convective boundary layer, we study the variation of TKE budget terms under the initial conditions of the Scaled Wind Farm Technology (SWiFT) facility located in West Texas. In this study, WRF LES is used with a horizontal grid resolution of 12 m, and is one-way nested within an idealized mesoscale domain. It is crucial to understand how forced perturbation shifts the balance between the terms of the TKE budget. Here, we quantify the shear production, and buoyant production in an unstable case. Since additional production terms are introduced in the SCPM method, we investigate the dissipation term of TKE. In addition, we also study the generation of turbulent transport. Generally, it integrates over height to null in a planar homogeneous case without subsidence, indicating it is positive over some heights and negative over other heights. Furthermore, we also study the variation of the TKE transport term after extending the random perturbation up to a certain height. The findings of this study will provide a better understanding of the contribution of different budget terms in a forced LES simulation.

The vertical turbulent transfer of heat and momentum in the lower atmospheric boundary layer is accom-plished through intermittent sweep, ejection, outward interaction, and inward interaction events associated with turbulent updrafts and downdrafts. These events, collectively referred to as sweep–ejection dynamics, have been studied extensively in forested and nonforested environments and reported in the literature. However, little is known about the sweep–ejection dynamics that occur in response to turbulence regimes induced by wildland fires in forested and nonforested environments. This study attempts to fill some of that knowledge gap through analyses of turbulence data previously collected during three wildland (prescribed) fires that occurred in grassland and forested environments in Texas and New Jersey. Tower-based high-frequency (10 or 20 Hz) three-dimensional wind-velocity and temperature measurements are used to examine fre-quencies of occurrence of sweep, ejection, outward interaction, and inward interaction events and their actual contributions to the mean vertical turbulent fluxes of heat and momentum before, during, and after the passage of fire fronts. The observational results suggest that wildland fires in these environments can substantially change the sweep–ejection dynamics for turbulent heat and momentum fluxes that typically occur when no fires are present, especially the relative contributions of sweeps versus ejections in determining overall heat and momentum fluxes.

Quantifying livelihood vulnerability to wildland fires in the United States is challenging because of the need to systematically integrate multidimensional variables into its analysis. We aim to measure wildfire threats amongst humans and their physical and social environment by devel-oping a framework to calculate the livelihood vulnerability index (LVI) for the top 14 American states most recently exposed to wildfires. The LVI is computed by assessing each state’s contributing factors (exposure, sensitivity, and adaptive capacity) to wildfire events. These contributing factors are determined through a set of indicator variables that are categorized into corresponding groups to produce an LVI framework. The framework is validated by performing a principal component analysis (PCA), ensuring that each selected indicator variable corresponds to the correct contributing factor. Our results indicate that Arizona and New Mexico experience the greatest livelihood vulnerability. In contrast, California, Florida, and Texas experience the least livelihood vulnerabil-ity. While California has one of the highest exposures and sensitivity to wildfires, results indicate that it has a relatively high adaptive capacity, in comparison to the other states, suggesting it has measures in place to withstand these vulnerabilities. These results are critical to wildfire managers, government, policymakers, and research scientists for identifying and providing better resiliency and adaptation measures to support states that are most vulnerable to wildfires.

The characterization of heat and momentum fluxes in wall-bounded turbulence is of paramount importance for a plethora of applications ranging from engineering to Earth sciences. Nevertheless, how the turbulent structures associated with velocity and temperature fluctuations interact to produce the emergent flux signatures has not been evident until now. In this work, we investigate this fundamental issue by studying the switching patterns of intermittently occurring turbulent fluctuations from one state to another, a phenomenon called persistence. We discover that the persistence patterns for heat and momentum fluxes are widely different. Moreover, we uncover power-law scaling and length scales of turbulent motions that cause this behavior. Furthermore, by separating the phases and amplitudes of flux events, we explain the origin and differences between heat and momentum transfer efficiencies in convective turbulence. Our findings provide a new understanding of the connection between flow organization and flux generation mechanisms, two cornerstones of turbulence research.

Momentum and mass exchanges between the atmosphere and forests situated on complex terrain continue to draw significant research attention primarily because of their significance to a plethora of applications. In this paper, we investigated flows behavior on the leeward side of a two-dimensional forested ridge under neutrally stratified conditions using large-eddy simulations (LESs). The goal is to understand how variations in leaf area index (LAI), vertical canopy foliage distributions, and forest edge positions affect mean/turbulent flow statistics, momentum fluxes, and onset of recirculation patterns. Although pressure perturbations are dominated by the hill shape, it is demonstrated here that changes in canopy foliage distribution modulate intensities and patterns of the leeward adverse pressure gradients. Such changes in the adverse pressure gradients alter the mean velocity streamlines including the patterns and magnitudes of the leeward downward mean vertical velocity and the velocity variances and momentum flux in the wake region. While a downwind recirculation zone develops in all cases, the details regarding the incipient location and recirculation zone size vary including positions of the separation and reattachment points. Furthermore, changes in the strength and depth of the zone occur due to canopy-induced changes in adverse pressure gradients, advection, and canopy drag. Because the recirculation zone impacts the local mean advective terms in momentum and scalar exchanges, the simulations here indicate that canopy morphology-induced changes in the leeward flows have significant implications to both measurements and models of biosphere-atmosphere exchange over complex terrain.

Increasing trends in wildfire severity can partly be attributed to fire exclusion in the past century which led to higher fuel accumulation. Mechanical thinning and prescribed burns are effective techniques to manage fuel loads and to establish a higher degree of control over future fire risk, while restoring fire prone landscapes to their natural states of succession. However, given the complexity of interactions between fine scale fuel heterogeneity and wind, it is difficult to assess the success of thinning operations and prescribed burns. The present work addresses this issue systematically by simulating a simple fire line and propagating through a vegetative environment where the midstory has been cleared in different degrees, leading to a canopy with almost no midstory, another with a sparse midstory and another with a dense midstory. The simulations are conducted for these three canopies under two different conditions, where the fuel moisture is high and where it is low. These six sets of simulations show widely different fire behavior, in terms of fire intensity, spread rate and consumption. To understand the physical mechanisms that lead to these differences, detailed analyses are conducted to look at wind patterns, mean flow and turbulent fluxes of momentum and energy. The analyses also lead to improved understanding of processes leading to high intensity crowning behavior in presence of a dense midstory. Moreover, this work highlights the importance of considering fine scale fuel heterogeneity, seasonality, wind effects and the associated fire-canopy-atmosphere interactions while considering prescribed burns and forest management operations.

Thermal plumes are the energy-containing eddy motions that carry heat and momentum in a convective boundary layer. The detailed understanding of their structure is of fundamental interest for a range of applications, from wall-bounded engineering flows to quantifying surface-atmosphere flux exchanges. We address the aspect of Reynolds stress anisotropy associated with the intermittent nature of heat transport in thermal plumes by performing an invariant analysis of the Reynolds stress tensor in an unstable atmospheric surface layer flow, using a field-experimental dataset. Given the intermittent and asymmetric nature of the turbulent heat flux, we formulate this problem in an event-based framework. In this approach, we provide structural descriptions of warm-updraft and cold-downdraft events and investigate the degree of isotropy of the Reynolds stress tensor within these events of different sizes. We discover that only a subset of these events are associated with the least anisotropic turbulence in highly convective conditions. Additionally, intermittent large-heat-flux events are found to contribute substantially to turbulence anisotropy under unstable stratification. Moreover, we find that the sizes related to the maximum value of the degree of isotropy do not correspond to the peak positions of the heat-flux distributions. This is because the vertical velocity fluctuations pertaining to the sizes associated with the maximum heat flux transport a significant amount of streamwise momentum. A preliminary investigation shows that the sizes of the least anisotropic events probably scale with a mixed length scale (, where is the measurement height and is the large-eddy length scale).

Persistence is defined as the probability that the local value of a fluctuating field remains at a particular state for a certain amount of time, before being switched to another state. The concept of persistence has been found to have many diverse practical applications, ranging from non-equilibrium statistical mechanics to financial dynamics to distribution of time scales in turbulent flows and many more. In this study, we carry out a detailed analysis of the statistical characteristics of the persistence probability density functions (PDFs) of velocity and temperature fluctuations in the surface layer of a convective boundary layer using a field-experimental dataset. Our results demonstrate that for the time scales smaller than the integral scales, the persistence PDFs of turbulent velocity and temperature fluctuations display a clear power-law behavior, associated with a self-similar eddy cascading mechanism. Moreover, we also show that the effects of non-Gaussian temperature fluctuations act only at those scales that are larger than the integral scales, where the persistence PDFs deviate from the power-law and drop exponentially. Furthermore, the mean time scales of the negative temperature fluctuation events persisting longer than the integral scales are found to be approximately equal to twice the integral scale in highly convective conditions. However, with stability, this mean time scale gradually decreases to almost being equal to the integral scale in the near-neutral conditions. Contrarily, for the long positive temperature fluctuation events, the mean time scales remain roughly equal to the integral scales, irrespective of stability.

Key message: We have explored the impacts of forest thinning on wildland fire behavior using a process based model. Simulating different degrees of thinning, we found out that forest thinning should be conducted cautiously as there could be a wide range of outcomes depending upon the post-thinning states of fuel availability, fuel connectivity, fuel moisture and micrometeorological features such as wind speed. Context: There are conflicting reports in the literature regarding the effectiveness of forest thinning. Some studies have found that thinning reduces fire severity, while some studies have found that thinning might lead to enhanced fire severity. Aims: Our goal was to evaluate if both of these outcomes are possible post thinning operations and what are the limiting conditions for post thinning fire behavior. Methods: We used a process based model to simulate different degrees of thinning systematically, under two different conditions, where the canopy fuel moisture was unchanged and when the canopy fuel moisture was also depleted post thinning. Both of these scenarios are reported in the literature. Results: We found out that a low degree of thinning can indeed increase fire intensity, especially if the canopy fuel moisture is low. A high degree of thinning was effective in reducing fire intensity. However, thinning also increased rate of spread under some conditions. Interestingly, both intensity and rate of spread were dependent on the competing effects of increased wind speed, fuel loading and canopy fuel moisture. Conclusion: We were able to find the limits of fire behavior post thinning and actual fire behavior is likely to be somewhere in the middle of the theoretical extremes explored in this work. The actual fire behavior post thinning should depend on the site specific conditions which would determine the outcome of the interplay among the aforementioned conditions. The work also highlights that policymakers should be careful about fine scale canopy architectural attributes and micrometeorological aspects when planning fuel treatment operations.

Wildfire behavior is dictated by the complex interaction of numerous physical phenomena including dynamic ambient and fire-induced winds, heat transfer, aerodynamic drag on the wind by the fuel and combustion. These phenomena create complex feedback effects between the fire and its surroundings. In this study, we aim to study the mechanisms by which buoyant flame dynamics along with vortical motions and instabilities control wildfire propagation. Specifically, this study employs a suite of simulations conducted with the physics-based coupled fire-atmosphere behavior model (FIRETEC). The simulations are initialized with a fire line and the fires are allowed to propagate on a grass bed, where the fuel heights and wind conditions are varied systematically. Flow variables are extracted to identify the characteristics of the alternating counter-rotational vortices, called towers and troughs, that drive convective heat transfer and fire spread. These vortices have previously been observed in wildfires and laboratory fires, and have also been observed to arise spontaneously in FIRETEC due to the fundamental physics incorporated in the model. However, these past observations have been qualitative in nature and no quantitative studies can be found in the literature which connected these coherent structures fundamental to fire behavior with the constitutive flow variables. To that end, a variety of state variables are examined in the context of these coherent structures under various wind profile and grass height conditions. Identification of various correlated signatures and fire-atmosphere feedbacks in simulations provides a hypothesis that can be tested in future observational or experimental efforts, potentially assisting experimental design, and can aid in the interpretation of data from in situ detectors.

In this paper, we explore the suitability of upcoming novel computingtechnologies, in particular adiabatic annealing based quantum computers, tosolve fluid dynamics problems that form a critical component of several scienceand engineering applications. We start with simple flows with well-studied flowproperties, and provide a framework to convert such systems to a form amenablefor deployment on such quantum annealers. We analyze the solutions obtainedboth qualitatively and quantitatively as well as the sensitivities of thevarious solution selection schemes on the obtained solution.

We investigate the effects of an isolated meso-γ-scale surface heterogeneity for roughness and albedo on the atmospheric boundary-layer (ABL) height, with a case study at a semi-arid forest surrounded by sparse shrubland (forest area: 28km2, forest length in the main wind direction: 7 km). Doppler lidar and ceilometer measurements at this semi-arid forest show an increase in the ABL height over the forest compared with the shrubland on four out of eight days. The differences in the ABL height between shrubland and forest are explained for all days with a model that assumes a linear growth of the internal boundary layer of the forest through the convective ABL upwind of the forest followed by a square-root growth into the stable free atmosphere. For the environmental conditions that existed during our measurements, the increase in ABL height due to large sensible heat fluxes from the forest (600Wm-2 in summer) is subdued by stable stratification in the free atmosphere above the ABL, or reduced by high wind speeds in the mixed layer.