Turbulent Eddies Research Articles

Tilts of Atmospheric Radar-Scattering Structures Measured by Long-Term Windprofiler Radar Studies

Month-long and seasonally persistent apparent tilts in atmospheric radar scatterers have been measured with a network of six windprofiler radars over periods of two or more years. The method used employs cross-correlations between vertical winds and horizontal winds measured using the radars. It is shown that large-scale apparent tilts that persisted for many weeks and months were not uncommon at many sites, with typical tilts varying from horizontal to ~3–4° from horizontal. The azimuthal and zenithal alignment of the tilts depend on local orography as well as local seasonal atmospheric conditions. It is demonstrated that these apparent tilts are not, in general, true large-scale phenomena, but rather are a manifestation of coordinated motions within turbulent and quasi-specular radar-scattering structures at scales between a few metres and tens of metres, with these structures themselves being defined by larger-scale and longer-term physical processes. Windshear combined with breaking gravity waves seems to be a particularly effective mechanism for producing these tilts, although other possibilities are also discussed. Implications for the interpretation of the nature of turbulent eddies, the accuracy of vertical wind measurements, and the nature of layering and scattering in the real atmosphere, are discussed. A method which allows for accurate measurements of the mean off-horizontal alignment of anisotropic scatterers and turbulent eddies is introduced.

Analytical and Numerical Solutions of Concentration With Deposition Under Unstable Condition

ABSTRACTIn order to study the analytical and numerical solutions with Adomain decomposition of the pollutant's concentration from point source, wind speed and vertical turbulent eddy diffusivity are taken into account as functions of the vertical height above the surface layer power law. The top of the boundary layer of height has an elevated inversion layer that limits the concentration, and there is dry deposition on the ground surface. The pollutant's degradation distance is also estimated. The outcomes of the analytical and numerical solutions were compared with Iodine‐135 measured data under unstable conditions at the Egyptian Atomic Energy Authority. One finds that there is a better agreement between the predicted and observed concentrations than between the numerical concentrations. This study compares the analytical and numerical solutions of the advection‐diffusion equation and data of Iodine‐135 concentrations observed under unstable conditions.

The Dominant Source Mechanism of Infrasound Generation in Powder Snow Avalanches

AbstractPowder snow avalanches (PSAs) radiate infrasound energy, yet the source mechanism remains unclear, limiting hazard monitoring and mitigation with infrasound‐based technologies. Here, we analyze a unique data set from a large PSA to improve the understanding of the source mechanism. Through comparison of cluster activity within the airborne layers of the PSA and the recorded infrasound signal in the frequency domain, we demonstrate that infrasound is mainly generated from particle clusters suspended by turbulent eddies or ejected from the denser basal layer. Further correlating infrasound amplitudes with radar‐derived spatial distributions of these clusters, we reveal a distributed source extending hundreds of meters behind the avalanche front. Additionally, we establish a relationship between infrasound and kinetic energy of suspended particles. These findings deepen our understanding of the complex dynamics of infrasound generation, offering valuable insights for avalanche detection and early warning strategies, and fundamental comprehension of PSA dynamics.

The use of vertical gradients of radar reflectivity factor and radial velocity to diagnose dynamical and microphysical structures in extratropical cyclones: results from IMPACTS

Abstract The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms field campaign comprised three deployments in January and February of 2020, 2022, and 2023. Throughout these deployments, the NASA Earth Resources-2 (ER-2) aircraft conducted 26 research flights, equipped with three vertically pointing radars. These radars sampled the vertical structure of extratropical cyclone clouds at four distinct radar wavelengths, enabling a finer scale analysis of reflectivity and radial velocity structures within extratropical cyclones with a vertical sampling resolution of 26.5 m. In this analysis, we introduce a novel technique utilizing vertical gradients in radial velocity and reflectivity, which proved effective in identifying turbulence, waves, and layers of ascent over 132.5 m layers for all flight legs conducted during the campaign. The spatial scale of 132.5 m was chosen to capture fine-scale variations associated with small-scale turbulent eddies and shear zones in frontal regions. The gradient analysis aided in detecting small scale changes in reflectivity and radial velocity that might have gone unnoticed otherwise. Moreover, the corresponding gradients in reflectivity suggest potential interactions of falling ice crystals with turbulence, waves, and shear layers, possibly influencing the microphysical characteristics and the vertical spatial distribution of falling snow. The observed vertical gradients in radial velocity often exhibited linear, layered patterns, but in some instances displayed wave-like appearances, sloped patterns along frontal boundaries, or magnitude fluctuations. This paper focuses on presenting and detailing the vertical gradient technique to examine winter storms. Future work will involve a comprehensive analysis of these gradients in relation to dual-frequency radar measurements and in situ microphysical characteristics.

Analysis of the transient multiphase structure and motion characteristics of projectiles launched successively

A cavitation flow can greatly impact a vehicle's attitude and stability when exiting water. This paper adopts an improved delayed detached eddy turbulence model and a Schnerr–Sauer cavitation model as well as the volume-of-fluid method and an overlapping grid technique to investigate this effect. In addition, the experimental system of the underwater launch is designed and built independently, which the numerical results are in good agreement with the experimental results. The transient cavitation flow structure and motion characteristics of the projectiles successively launched underwater are studied. When the axial spacing ranges from 0 to 1.0 times the diameter of the projectile, both projectiles are severely affected to various extents in cavitation pattern, vortex structure, and motion characteristics. It is worth noting that the internal cavity of the secondary projectile is disturbed by the wake of the primary projectile, resulting in large-scale fractures and detachment of the internal cavity, but its motion stability is good.

Airborne observations of fast-evolving ocean submesoscale turbulence

Ocean images collected by astronauts onboard the Apollo spacecraft more than 50 years ago revealed a large number of ocean eddies, with a size between 1 and 20 km. Since then, satellite infrared, ocean color, sun glitter and synthetic aperture radar images, with high spatial resolution, have confirmed the ubiquitous presence of these small eddies in all oceans. However, observing the dynamical characteristics and evolution of these eddies has remained challenging. An experiment was recently carried out in the California Current system using the new airborne Doppler Scatterometer (National Aeronautics and Space Administration-Jet Propulsion Laboratory DopplerScatt) instrument that observes surface velocities. Here, with DopplerScatt, we mapped a 30 × 100 km domain over multiple days to unveil numerous 1–20 km ocean eddies, called submesoscale eddies, that evolve over a period of a few hours. The strong interactions between eddies generate horizontal velocity divergence, implying vertical velocities reaching 250 m day−1 at 40 m depth. The velocity field also produces horizontal dispersion of particles over a distance of 50 km within 12 h, which rapidly fills the turbulent eddy field. These observations suggest that submesoscale ocean turbulence may profoundly affect the vertical transport of heat, carbon, and important climatic gases between the atmosphere and the ocean interior, as well as the horizontal dispersion of tracers and particles. As such, submesoscale ocean eddies are a critical element of Earth’s climate system.

Broadening of cloud droplet spectra through eddy hopping: Why did we all have it wrong?

Abstract In situ aircraft observations in adiabatic and close-to-adiabatic cloudy volumes suggest that cloud droplet spectra are often broader than predicted by growth of a droplet population rising from the cloud base. Cloud turbulence has been suggested as one of possible mechanisms for the observed spectral broadening. This paper reviews computational studies of the impact of cloud turbulence on the diffusional growth of cloud droplets in adiabatic cloudy volumes. These studies typically apply direct numerical simulation (DNS) or scaledup DNS approach to represent diffusional growth of cloud droplets embedded within homogeneous isotropic air turbulence. There is also a theory that predicts that the droplet spectral width continuously increases in time because of the individual droplet growth or evaporation within turbulent eddies. This mechanism has been referred to as eddy hopping. This paper expands the discussion in Prabhakaran et al. (J. Atmos. Sci. 2022) and illustrates the fundamental flaw of past computational and theoretical studies. These studies do not consider vertical dispersion of droplet positions that leads to growth of droplets that in the mean move upwards, and to evaporation of those that move downwards. The theoretical prediction comes from confusing spectral broadening with the vertical dispersion of droplet positions when periodic lateral boundaries are used in DNS. Computational examples using a stochastic model mimicking eddy hopping show that droplet spectral width does not continuously increase in time, but it saturates at a small spread. Methodologies for appropriate numerical studies of the adiabatic spectral width evolution in natural clouds are discussed.

Observations and quantification of fog droplet deposition made during the SOFOG3D campaign

AbstractThis paper presents observations collected during the SOFOG3D campaign in southwestern France during 2019–2020, to elucidate the processes involved in the deposition of fog droplets to the surface, a process that is often modelled in Numerical Weather Prediction models, and forms an important component of the water budget within fog. The study considers that three main mechanisms cause deposition: turbulent, whereby water drops are transported to the surface in turbulent eddies; aerodynamic, whereby the mean horizontal wind deposits droplets directly onto surface canopy elements that protrude into the airflow, and gravitational, whereby droplets fall under the action of gravity directly onto the canopy. Results indicate that the gravitational settling is on average a minor component of the deposition, amounting to around 15% of the total figure. The study also identified that this proportion is relatively larger at 18%, when the turbulence intensity levels are low (vertical‐velocity variance <0.003 m2·s−2). Consequently, for greater values of turbulence intensity the proportion is smaller at 12%. All three deposition processes are studied further using a multiple linear regression of terms against observed water deposition rates, in an attempt to evaluate various methods to estimate the deposition. Results indicate that a simple regression of liquid‐water content against observed deposition has some predictive skill, but that a multiple regression including all three terms produces better results with smaller regression errors. A simpler multiple regression that merged turbulent and aerodynamic terms into a single ‘dynamic’ term produced results almost identical to the three‐term multiple regression. Finally, the differences in fog water deposition rates between stable shallow fog and more turbulent, deeper adiabatic fog were assessed and found to be small. Consequences for parametrisation of liquid‐water deposition in fog are discussed.

Severe Convectively Induced Turbulence Hitting a Passenger Aircraft and Its Forecast by the ECMWF IFS Model

AbstractAtmospheric turbulence poses a major risk to aviation. Besides airframe damage, it can cause injuries of passengers and crew when encountered unexpectedly. The Singapore Airlines flight SQ321 was on its way from London to Singapore when severe turbulence was encountered over Myanmar on 21 May 2024. In this study, it is analyzed how well the turbulence was predicted by the turbulent eddy dissipation rate (EDR) forecast index of the ECMWF integrated forecasting system (IFS). It was found that ECMWF IFS was able to predict the convection and associated turbulence 24 hr in advance. The state‐of‐the‐art probabilistic EDR forecasts based on IFS ensemble members predicted probabilities for EDR between 10% and 40% over Myanmar with higher values for shorter lead time (8‐hr forecast). Individual members predicted EDR . Knowledge about the characteristics of convection in the IFS forecasts is required to make proper use of the probabilities determined from the ensemble for such cases.

Effect of pulsation intensity on flow and dispersion characteristics of single-pulsed dual parallel plane jets

The effect of pulsation intensity on flow and dispersion characteristics of single-pulsed dual parallel plane jets was experimentally investigated in this study. A single jet from a pair of dual jets was pulsed by a loudspeaker. The flow evolution processes were examined using the laser-light sheet-assisted smoke flow visualization method. The visual spread of the jet flow was measured using the binary boundary edge detection technique. A hotwire anemometer was used to detect the instantaneous velocities, mean velocities, turbulence intensities, Lagrangian integral time, and length scales. The dispersion capabilities of the jet fluid were evaluated employing the tracer-gas concentration detection technique. Two characteristic flow modes, namely the coherent vortices and vortex breakup, could be classified based on pulsation intensity. At Ip < 1.0, the flow was characterized by coherent vortices, which maintained coherence within one excitation cycle. At Ip > 1.0, vortex breakup occurred, where vortices deformed, lost coherence, and transformed into puff-shaped vortical structures within one excitation cycle. The vortices emerging from the pulsed jet undergo deformation, evolving into puff-shaped vortices, and subsequently fragment into smaller turbulent eddies more quickly than the synchronized vortices from the non-pulsed jet. This leads to significant penetration and velocity fluctuations in the trajectory of the pulsed jet. Consequently, the overall spread width and concentration reduction index of the single-pulsed dual parallel plane jets exceed those of the non-pulsed dual parallel plane jets.

Coupled zone-adaptive turbulence and combustion modeling of turbulent swirling premixed flames

Adaptivity has emerged as a crucial element for capturing the multi-scale dynamics and, therefore, effective turbulent flame simulations. This study explores the theoretical framework of the coupled adaptive turbulence and combustion modeling, in which self-adaptive turbulence eddy simulation (SATES) has been coupled with the zone-adaptive combustion model, the latter one dynamically assigns the laminar finite rate (LFR) model, and the particle-based transported probability density function (TPDF) method. A new length scale, LHybrid, was introduced for the Damköhler (Da) number calculation to ensure consistency between Reynolds-averaged Navier–Stokes and large eddy simulation modes within the SATES framework. The model performance is validated in the swirling burner technical flames (TECFLAM), which produces turbulent premixed flames with intense unsteadiness. The results show that the coupled adaptive simulation accurately reproduces the weak “M” shape flame, demonstrating reliable estimates of turbulence–chemistry interactions in the outer mixing layer. In contrast, the LFR simulation yields a strong M shape flame due to overestimated reaction rates. Quantitatively, both adaptive combustion model and TPDF methods yield a weak bimodal temperature profile and a constant equivalence ratio in the inner recirculation zone, aligning well with experimental data, while LFR overpredicts temperatures, leading to discrepancies in equivalence ratio and species mass fraction. The adaptive combustion model uses only 4.24% of the computational particles needed for TPDF, covering just 0.86% of the total domain, significantly reducing computational cost. Additionally, the new Da-number partitioning criteria based on LHybrid accurately identify regions of strong turbulence–chemistry interaction. It is shown that the adaptive method can converge to the corresponding LFR or TPDF model by adjusting the partitioning criterion parameter, illustrating its potential in balancing computational cost and prediction accuracy in turbulent flames.

Numerical study of turbulent eddy self-interaction in tokamaks with low magnetic shear. Part I: Linear simulations

Abstract This study examines the impact of low and zero magnetic shear, along with rational values of safety factor, on linear mode behavior in tokamak plasmas. We focus on how magnetic field line topology and parallel domain length influence linear mode structures and growth rates as magnetic shear decreases. Our results show that as magnetic shear is reduced to low values, linear modes can transition between different branches, significantly affecting their characteristics. At zero magnetic shear, accurate modeling requires precisely capturing magnetic topology, as small deviations near rational surfaces can greatly impact growth rates.

Numerical study of turbulent eddy self-interaction in tokamaks with low magnetic shear. Part II: Nonlinear simulations

Abstract Using local nonlinear gyrokinetic simulations and building up on linear results from a companion paper (Volčokas 2024 Submitted for publication), we demonstrate that turbulent eddies can extend along magnetic field lines for hundreds of poloidal turns in tokamaks with weak or zero magnetic shear s ^ . We observe that this parallel eddy length scales inversely with magnetic shear and at s ^ = 0 is limited by the thermal speed of electrons v th , e . We examine the consequences of these ‘ultra long’ eddies on turbulent transport, in particular, how field line topology mediates strong parallel self-interaction. Our investigation reveals that, through this process, field line topology can strongly affect transport. It can cause transitions between different turbulent instabilities and in some cases triple the logarithmic gradient needed to drive a given amount of heat flux. We also extensively study a novel ‘eddy squeezing’ effect introduced in Volčokas (2023 Nucl. Fusion 63 014003), which reduces the perpendicular size of eddies and their ability to transport energy, thus representing a novel approach to improve confinement. Finally, we investigate the triggering mechanism of Internal Transport Barriers (ITBs) using low magnetic shear simulations, shedding light on why ITBs are often easier to trigger where the safety factor has a low-order rational value.

Applying the Velocity Gradient Technique in NGC 1333: Comparison with Dust Polarization Observations

Magnetic fields (B-fields) are ubiquitous in the interstellar medium (ISM), and they play an essential role in the formation of molecular clouds and subsequent star formation. However, B-fields in interstellar environments remain challenging to measure, and their properties typically need to be inferred from dust polarization observations over multiple physical scales. In this work, we seek to use a recently proposed approach called the velocity gradient technique (VGT) to study B-fields in star-forming regions and compare the results with dust polarization observations in different wavelengths. The VGT is based on the anisotropic properties of eddies in magnetized turbulence to derive B-field properties in the ISM. We investigate that this technique is synergistic with dust polarimetry when applied to a turbulent diffused medium for the purpose of measuring its magnetization. Specifically, we use the VGT on molecular line data toward the NGC 1333 star-forming region (12CO, 13CO, C18O, and N2H+), and we compare the derived B-field properties with those inferred from 214 and 850 μm dust polarization observations of the region using Stratospheric Observatory for Infrared Astronomy/High-Resolution Airborne Wide-band Camera Plus and James Clerk Maxwell Telescope/POL-2, respectively. We estimate both the inclination angle and the 3D Alfvénic Mach number M A from the molecular line gradients. Crucially, testing this technique on gravitationally bound, dynamic, and turbulent regions, and comparing the results with those obtained from polarization observations at different wavelengths, such as the plane-of-sky field orientation, is an important test on the applicability of the VGT in various density regimes of the ISM. We in general do not find a close correlation between the velocity gradient inferred orientations and the dust inferred magnetic field orientations.

Intermittency of Bubble Deformation in Turbulence.

The deformation of finite-sized bubbles in intense turbulence exhibits complex geometries beyond simple spheroids as the bubbles exchange energy with the surrounding eddies across a wide range of scales. This study investigates deformation via the velocity of the most stretched tip of the deformed bubble in three dimensions, as the tip extension results from the compression of the rest of the interface by surrounding eddies. The results show that the power spectrum based on the tip velocity exhibits a scaling akin to that of the Lagrangian statistics of fluid elements, but decays with a distinct timescale and magnitude modulated by the Weber number based on the bubble size. This indicates that the interfacial energy is primarily siphoned from eddies of similar sizes as the bubble. Moreover, the tip velocity appears much more intermittent than the velocity increment, and its distribution near the extreme tails can be explained by the proposed model that accounts for the fact that small eddies with sufficient energy can contribute to extreme deformation. These findings provide a framework for understanding the energy transfer between deformable objects and multiscale eddies in intense turbulence.

Self-adaptive turbulence eddy simulation of a supersonic cavity-ramp flow

High Reynolds number supersonic wall-bounded turbulent flow is common in the aviation industry. However, accurately predicting this flow remains a long-standing challenge for turbulence modeling, particularly in separation cases. This study presents a numerical investigation of a Mach 2.92 turbulent cavity-ramp flow employing a new hybrid turbulence modeling approach, denoted as the self-adaptive turbulence eddy simulation (SATES) method. The results are compared with experimental data, as well as with outcomes from the conventional Reynolds-averaged Navier–Stokes (RANS) method and the previous delayed detached eddy simulation (DDES). The SATES model demonstrates a satisfactory prediction of time-averaged and fluctuating quantities in the free shear layer, redeveloping boundary layer, and ramp, showing better accuracy than the RANS results. Notably, the SATES results from the medium grid exhibit similarities to the DDES results from the extremely fine grid which is about 26 times compared with the SATES mesh. Furthermore, the significant features of the supersonic reattached flow, including turbulent properties, vortex structures, and unsteadiness characteristics, are analysed in detail, including the Reynolds stresses anisotropy invariant maps, transport process of vorticity, and frequency spectra. This work confirms that accurate numerical predictions of high Reynolds number supersonic separated and reattached flows are achievable using the SATES method with a relatively coarse mesh maintaining an affordable computational cost.

Optimization and parametric analysis of a novel design of Savonius hydrokinetic turbine using artificial neural network

This study focuses on enhancing the efficiency of vertical axis Savonius Hydrokinetic turbines designed for marine applications, historically characterized by a power coefficient below 0.1. Prior efforts aimed at improving rotor performance have primarily involved modifications to blade designs. In this article, a new approach is introduced, incorporating twisted blades inspired by the Archimedes screw turbine. Utilizing a 3D incompressible flow analysis based on the Navier-Stokes equation, this research explores and compares the turbine's effectiveness with varying screw pitches (0.5, 0.75, 1). The system of equations is solved numerically using ANSYS 2020 R2 fluid fluent. The performance assessment involves contrasting each proposed rotor against a pitchless semi-circle rotor. An innovative aspect of this work involves investigating the impact of asymmetry using two different ratios (2:1 and 3:1). Specifically, the lower half of the optimal pitch screw remains constant, while the upper half varies based on these ratios. To understand performance trends, the study employs visualizations of pressure, velocity contours, and streamlines to grasp the flow field and its underlying principles. Turbulent kinetic energy and eddy viscosity are also visualized. The results reveal an 18.25 % improvement in performance with the proposed rotor featuring a pitch screw of 0.5. Notably, the asymmetric rotor with a 2:1 ratio demonstrates the highest performance. According to the ANN, the optimum pitch screw value is determined to be 0.6, achieving a power coefficient of 0.1938. This investigation employs novel design modifications and asymmetrical configurations, offering valuable insights into significantly enhancing the performance of Savonius turbines for marine applications.

Characterization of droplet clusters in a turbulent multiphase gas cloud using a model cough simulator

This study aims to investigate the transport of droplets ejected from an artificial cough simulator, which releases a turbulent puff of droplets into the surrounding air, closely resembling the human coughing process. The focus is on understanding droplet clustering within the multiphase gas cloud across various operating conditions that emulate the wide variation in the spray characteristics in actual human subjects owing to infection severity, age, and gender. Time-resolved particle image velocimetry (PIV) technique was employed to measure the velocity of both droplet and gas phases. It also facilitates the identification and characterization of droplet clusters through Voronoi analysis of the PIV images. The area and length scale of individual droplet clusters were measured, and the degree of droplet clustering was quantified using the clustering index and relative droplet number density within the clusters. Additionally, the interferometric laser imaging for droplet sizing technique was utilized for planar measurement of individual droplet sizes. The range of Stokes number indicated partial to poor response of the droplets to the turbulent eddies. The results reported, for the first time, the presence of droplet clusters in the simulated coughing process. The wide spectrum of cluster size and self-similar evolution of droplet clusters unveil a multi-scale clustering phenomenon, shedding light on the intricate dynamics of the respiratory droplet dispersion process. The study comprehensively investigates the role of injection pressure on droplet clustering and the spatial development of the clusters, revealing some interesting findings, which are discussed.

Thermal stratification prediction in reactor system based on CFD simulations accelerated by a data-driven coarse-grid turbulence model

Thermal stratification in large enclosures is an integral phenomenon to nuclear reactor system safety. Currently, the effective model for thermal stratification utilizes a multi-scale method that integrates 1-D system-level and 3-D CFD code, which offers thermal stratification details while supplying system-level data across various domains. Nonetheless, harmonizing two codes that operate on different spatial and temporal scales presents a significant challenge, with high-resolution CFD simulations requiring substantial computational resources. This study introduced a data-driven coarse-grid turbulence model based on local flow characteristics at a significantly coarser scale, targeting improved efficiency and accuracy in reactor safety analysis concerning thermal stratification. A machine learning framework has been introduced to expedite the RANS-solving process by coupling OpenFOAM and TensorFlow, which entails training a deep neural network with fine-grid CFD-generated data to predict turbulent eddy viscosity. The feasibility of the developed data-driven turbulence model was proven through the SUPERCAVNA experimental facility problem validation.

The Impact of Turbulent Transport Efficiency on Surface Vertical Heat Fluxes in the Arctic Stable Boundary Layer Predicted from Similarity Theory and Machine Learning

Abstract We analyzed 14 days of observations from sonic anemometry and high-resolution fiber-optic distributed sensing collected in the stable boundary layer (SBL). The study sought to evaluate if and under which conditions the sensible heat flux is related to the temperature gradient. Machine learning methods were employed to identify drivers of and model heat fluxes. We found the recently proposed coupling metric Ω defined as the ratio of the buoyancy length scale and measurement height to delineate physically meaningful transport regimes. The regime transition marks the point where static stability, in addition to the vertical turbulence strength, controls the heat transport, which is rather gradual than abrupt. The maximum downward heat flux is reached when one-third of turbulent eddies exceed the opposing buoyancy forces in the SBL. We found evidence that even for large Ω a substantial fraction of the turbulent transport is nonequilibrium. The nondimensional temperature gradient is better explained by variations in Ω than ζ = zL−1 from Monin–Obukhov similarity theory. Its continuous organization with Ω across stabilities suggests that the vertical heat transport always remains coupled to the surface, but its efficiency and the resulting flux vary. Forty-three percent of the total enthalpy is exchanged during conditions of limited transport efficiency in the very SBL despite the small flux magnitude of ≤7 W m−2, which underlines the importance of quantifying the weak surface exchange for polar regions. When predicting sensible heat fluxes using mean quantities from weather stations, the net longwave radiative forcing and the horizontal wind speed are the most important predictors representing stratification and bulk shear. Significance Statement Climate warming is amplified in polar regions, but quantifying heat transfer is complicated since mixing is weak and sporadic. We aim to understand when and why measurements taken in the lowest meters above snow can be used to quantify the surface heat transfer and if common modeling concepts are valid. We found that the measured heat transfer for weak winds and clear skies is connected to the snow surface only to a small degree in 66% of all cases at a much (−65%) reduced magnitude compared to strong wind or cloudy cases. However, 43% of the total heat is exchanged during these conditions and thus must be included in surface heat budgets. Classic modeling concepts systematically underpredicted the exchanged heat budget by 12% across all conditions which limits their utility in polar regions.