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Abstract The transition from moderate to weak turbulence regimes remains a grand challenge for stable boundary layer parameterizations in weather and climate models. In this study, a critical horizontal Froude number (≈0.28) is proposed to characterize such a transition, which corresponds to the development of quasi two‐dimensional pancake vortices. Traditionally defined stability parameters corresponding to the critical horizontal Froude number are estimated and are consistent with values in the literature. The critical horizontal Froude number can recover previously used height‐ and site‐dependent mean wind speed thresholds. These findings offer a way to constrain the validity range of Monin‐Obukhov similarity theory in numerical models for weather and pollutants dispersion. 

Abstract This study analyses the departure of the velocity-variances profiles from their quasi-steady state described by the mixed-layer similarity, using large-eddy simulations with different prescribed shapes and time scales of the surface kinematic heat flux decay. Within the descriptive frames where the time is tracked solely by the forcing time scale (either constant or time-dependent) describing the surface heat flux decay, we find that the normalized velocity-variances profiles from different runs do not collapse while they depart from mixed-layer similarity. As the mixed-layer similarity relies on the assumption that the free-convective boundary layer is in a quasi-equilibrium, we consider the ratios of the forcing time scales to the convective eddy-turnover time scale. We find that the normalized velocity-variances profiles collapse in the only case where the ratio ($$\widetilde{r}$$ $\tilde{r}$) of the time-dependent forcing time scale to the convective eddy-turnover time scale is used for tracking the time, supporting the independence of the departure from the characteristics of the surface heat flux decay. As a consequence of this result, the knowledge of$$\widetilde{r}$$ $\tilde{r}$is sufficient to predict the departure of the velocity variances from their quasi-steady state, irrespective of the shape of the surface heat flux decay. This study highlights the importance of considering both the time-dependent forcing time scale and the convective eddy-turnover time scale for evaluating the response of the free-convective boundary layer to the surface heat flux decay. 

Abstract In very stable boundary layers (VSBL), a “cocktail” of submeso motions routinely result in elevated mean wind speed maxima above the ground, acting as a new source of turbulence generation. This new source of turbulent kinetic energy enhances turbulent mixing and causes mean wind profile distortion (WPD). As a results, this transient distortion in the wind profile adjusts the classical log‐law. Addressing how WPD‐induced turbulence regulates flow structures, turbulent fluxes, and transitions in stability regimes across layers remains a challenge. Eddy covariance data measured at four levels on a 62‐m tower are employed to address these questions. It is shown that the WPD initiates large turbulent eddies that penetrate downward, leading to enhanced vertical mixing and comparable turbulent transport efficiencies across layers. As a consequence, turbulence intensity and fluxes are increased. As the WPD is intensified, turbulent fluxes and turbulent flux transport caused by large eddies are also enhanced, leading to a transition from very stable to weakly stable regimes. Due to the influence of WPD‐induced large eddies, the large‐eddy turbulent Prandtl number does not deviate appreciably from unity and the partitioning between turbulent kinetic and potential energies is linearly related to the gradient Richardson number. 

Abstract We revisit the longstanding problem of grid sensitivity, i.e., the lack of grid convergence in large-eddy simulations (LES) of the stable boundary layer. We use a comprehensive set of LES of the well-known Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study 1 (GABLS1) case with varying grid spacings between 12.5 m and 1 m to investigate several physical processes and numerical features that are possible causes of grid sensitivity. Our results demonstrate that there are two resolution regimes in which grid sensitivity manifests differently. We find that changing the numerical advection schemes and the subgrid-scale models alters the simulation results, but the options tested do not fully address the grid-sensitivity issue. Moreover, sensitivity runs suggest that the surface boundary condition and the interaction of the surface with the near-surface flow, as well as the mixing with the free atmosphere, are unlikely to be the causes of the observed grid sensitivity. One interesting finding is that the grid sensitivity in the fine grid-spacing regime (grid spacings$$\le 2\,\mathrm{m}$$ $\le 2m$) is closely related to the reduction in the energy content of large-scale turbulence, leading to less turbulence kinetic energy and hence lower boundary-layer heights. The present work demonstrates that there is still an urgent need to address this grid-sensitivity issue in order to perform reliable LES of the stable boundary layer. 

Abstract While the signs of the sensitivities of surface temperature (T_s) to land use and land cover change‐induced biophysical changes are relatively well understood, their exact magnitude and how their magnitude depends on the scale characterizing the size of the change remain elusive. In this study, we compare the sensitivities of surface temperature to changes in surface albedo and surface water availability from three analytical/semianalytical models, which are designed for small (<1 km), intermediate (from ∼1 to ∼10 km), and large (>10–20 km) scales. Results suggest that the sensitivities of surface temperature to biophysical changes are scale dependent due to atmospheric feedbacks. Our results demonstrate that it is important to consider the scale and the associated atmospheric feedbacks when quantifying the sensitivities of surface temperature to biophysical changes. 

Abstract Land surface temperature (LST) responds to land‐use/land‐cover change (LULCC), which modifies surface properties that control the surface energy balance (SEB). Quantifying changes in LST due to individual perturbations caused by LULCC is an attribution problem. Most attribution methods are based on the first‐order Taylor series expansion (FOTSE) of a linearized SEB equation. The accuracy of these methods is affected by the use of FOTSE at two places. The first is to linearize the SEB equation and to obtain an analytical solution for LST (the LST model), and the second is to obtain LST changes as the linear sum of concurrent changes in multiple factors (the attribution model). In this study, we systematically assess the importance of non‐linear effects lost in these linearization processes using the second‐order Taylor series expansion (SOTSE). Results show that while the SOTSE LST model outperforms the FOTSE LST model, the order of Taylor series expansion in the LST model does not significantly influence the attribution of LST changes. However, the SOTSE attribution model is considerably more accurate than the FOTSE attribution model, especially when the magnitude of perturbations is large. Results suggest that contributions from higher‐order and cross‐order terms in the attribution model can be as large as 50%. Sensitivity analysis further shows that non‐linear effects associated with changing surface resistance for LULCC scenarios with large perturbations (e.g., deforestation and urbanization) are particularly strong. In conclusion, we recommend using the FOTSE LST model and the SOTSE attribution model. 

Abstract. Accurate air temperature measurements are essential in eddy covariance systems, not only for determining sensible heat flux but also for applying density effect corrections (DECs) to water vapor and CO2 fluxes. However, the influence of wind-induced vibrations of mounting structures on temperature fluctuations remains a subject of investigation. This study examines 30 min average temperature variances and fluxes using eddy covariance systems, combining Campbell Scientific sonic anemometers with closely co-located fine-wire thermocouples alongside LI-COR CO2–H2O gas analyzers at multiple heights above a sagebrush ecosystem. The variances of sonic temperature after humidity corrections (Ts) and sensible heat fluxes derived from Ts are underestimated (e.g., by approximately 5 % for temperature variances and 4 % for sensible heat fluxes at 40.2 m, respectively) as compared with those measured by a fine-wire thermocouple (Tc). Spectral analysis illustrates that these underestimated variances and fluxes are caused by the lower energy levels in the Ts spectra than the Tc spectra in the low-frequency range (natural frequency < 0.02 Hz). These underestimated Ts spectra in the low-frequency range become more pronounced with increasing wind speeds, especially when wind speed exceeds 10 m s−1. Moreover, the underestimated temperature variances and fluxes cause overestimated water vapor and CO2 fluxes through DEC. Our analysis suggests that these underestimations when using Ts are likely due to wind-induced vibrations affecting the tower and mounting arms, altering the time of flight of ultrasonic signals along three sonic measurement paths. This study underscores the importance of further investigations to develop corrections for these errors.