Search for: All records

Large-eddy simulations (LES) above forests and cities typically constrain the simulation domain to the first 10--20\% of the Atmospheric Boundary Layer (ABL), aiming to represent the finer details of the roughness elements and sublayer. These simulations are also commonly driven by a constant pressure gradient term in the streamwise direction and zero stress at the top, resulting in an unrealistic fast decay of the total stress profile. In this study, we investigate five LES setups, including pressure and/or top-shear driven flows with and without the Coriolis force, with the aim of identifying which option best represents turbulence profiles in the atmospheric surface layer (ASL). We show that flows driven solely by pressure not only result in a fast-decaying stress profile, but also in lower velocity variances and higher velocity skewnesses. Top-shear driven flows, on the other hand, better replicate ASL statistics. Overall, we recommend, and provide setup guidance for, simulation designs that include both a large scale pressure forcing and a non-zero stress and scalar flux at the top of the domain, and that also represent the Coriolis force. Such setups retain all the forces used in typical full ABL cases and result in the best match of the profiles of various statistical moments. 

Abstract. Conventional and recently developed approaches for estimating turbulent scalar fluxes under stable atmospheric conditions are evaluated, with a focus on gases for which fast sensors are not readily available. First, the relaxed eddy accumulation (REA) classical approach and a recently proposed mixing length parameterization, labeled A22, are tested against eddy-covariance computations. Using high-frequency measurements collected from two contrasting sites (the frozen tundra near Utqiaġvik, Alaska, and a sparsely vegetated grassland in Wendell, Idaho, during winter), it is shown that the REA and A22 models outperform the conventional Monin–Obukhov similarity theory (MOST) utilized widely to infer fluxes from mean gradients. Second, scenarios where slow trace gas sensors are the only viable option in field measurements are investigated using digital filtering applied to fast-response sensors to simulate their slow-response counterparts. With a filtered scalar signal, the observed filtered eddy-covariance fluxes are referred to here as large-eddy-covariance (LEC) fluxes. A virtual eddy accumulation (VEA) approach, akin to the REA model but not requiring a mechanical apparatus to separate the gas flows, is also formulated and tested. A22 outperforms VEA and LEC in predicting the observed unfiltered (total) eddy-covariance (EC) fluxes; however, VEA can still capture the LEC fluxes well. This finding motivates the introduction of a sensor response time correction into the VEA formulation to offset the effect of sensor filtering on the underestimated net averaged fluxes. The only needed parameter for this correction is the mean velocity at the instrument height, a surrogate of the advective timescale. The VEA approach is very suitable and simple to use with gas sensors of intermediate speed (∼ 0.5 to 1 Hz) and with conventional open- or closed-path setups. 

Abstract The Monin‐Obukhov Similarity Theory (MOST) links turbulent statistics to surface fluxes through universal functions. Here, we investigate its performance over a large lake, where none of its assumptions (flat homogeneous surface) are obviously violated. We probe the connection between the variance budget terms and departure from the nondimensional flux‐variance function for CO₂, water vapor, and temperature. Our results indicate that both the variance storage and its vertical transport affect MOST, and these terms are most significant when small fluxes and near neutral conditions were prevalent. Such conditions are common over lakes and oceans, especially for CO₂, underlining the limitation of using any MOST‐based methods to compute small fluxes. We further show that the relaxed eddy accumulation (REA) method is more robust and less sensitive to storage and transport, adequately reproducing the eddy‐covariance fluxes even for the smallest flux magnitudes. Therefore, we recommend REA over MOST methods for trace‐gas flux estimation. 

Abstract While yearly budgets of CO₂flux (F_c) and evapotranspiration (ET) above vegetation can be readily obtained from eddy‐covariance measurements, the separate quantification of their soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. In this work, we investigate four methods to partition observed total fluxes into soil and plant sources: two new and two existing approaches that are based solely on analysis of conventional high frequency eddy‐covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large‐eddy simulations, which are used to replicate eddy‐covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO₂and water vapor. In addition, best performances for all partitioning methods were found when all four flux components are non‐negligible, and measurements are collected close to the canopy top. Methods relying on the water‐use efficiency (W) perform better whenWis known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO₂and water vapor can be used to infer the reliability of differentWparameterizations. 

Abstract During and after rainfall events, the interaction of precipitation with hot urban pavements leads to hot runoff, and its merger with urban streams can result in an abrupt change in water temperature that can harm aquatic ecosystems. To understand this phenomenon and its relation to land cover and hydrometeorological parameters, we analyzed data spanning two years from 100 sites in the eastern United States. To identify surges, we first isolated temperature jumps of at least 0.5°C over 15 min occurring simultaneously with water flow increase. Surge magnitude was defined as the difference between peak stream temperature and baseflow temperature right before the jump. At least 10 surges were observed in 53 of the studied streams, with some surges exceeding 10°C. Our results demonstrate that the watershed developed area and vegetation fraction are the best descriptors of surge frequency (Spearman correlation of 0.76 and 0.77, respectively). On the other hand, for surge magnitude and peak temperature, the primary drivers are stream discharge and stream temperature immediately before the surge. In general, the more urbanized streams were found to be already warmer than their more “vegetated” counterparts during baseflow conditions, and were also the most affected by temperature surges. Together, these findings suggest the existence of a hydrological urban heat island, here defined as the increase in stream temperature (chronic and/or acute), caused by increased urbanization.