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Land-atmosphere (L-A) interactions encompass the co-evolution of the land surface and overlying planetary boundary layer, primarily during daylight hours. However, many studies have been conducted using monthly or entire-day-mean time series due to the lack of sub-daily data. It has been unclear whether the inclusion of nighttime data alters the assessment of L-A coupling or obscures L-A interactive processes. To address this question, we generate monthly (M), entire-day-mean (E), and daytime-only-mean (D) data based on the ERA5 (5th European Centre for Medium-Range Weather Forecasts reanalysis) product, and evaluate the strength of L-A coupling through two-legged metrics, which partition the impact of the land states on surface fluxes (the land leg) from the impact of surface fluxes on the atmospheric states (the atmospheric leg). Here we show that the spatial patterns of strong L-A coupling regions among the M-, D- and E-based diagnoses can differ by as much as 84.8 %. The signal loss from E- to M-based diagnoses is determined by the memory of local L-A states. The differences between E- and D-based diagnoses can be driven by physical mechanisms or the averaging algorithms. To improve understanding of L-A interactions, we call attention to the urgent need for more high-frequency data from both simulations and observations for relevant diagnoses. Regarding model outputs, two approaches are proposed to resolve the storage dilemma for high-frequency data: (1) integration of L-A metrics within Earth System Models, and (2) producing alternative daily datasets based on different averaging algorithms.

Land–atmosphere (L–A) interactions encompass the co-evolution of the land surface and overlying planetary boundary layer, primarily during daylight hours. However, many studies have been conducted using monthly or entire-day mean time series due to the lack of subdaily data. It is unclear whether the inclusion of nighttime data alters the assessment of L–A coupling or obscures L–A interactive processes. To address this question, we generate monthly (M), entire-day mean (E), and daytime-only mean (D) data based on the ERA5 (5th European Centre for Medium-Range Weather Forecasts reanalysis) product and evaluate the strength of L–A coupling through two-legged metrics, which partition the impact of the land states on surface fluxes (the land leg) from the impact of surface fluxes on the atmospheric states (the atmospheric leg). Here we show that the spatial patterns of strong L–A coupling regions among the M-, D-, and E-based diagnoses can differ by more than 80 %. The signal loss from E- to M-based diagnoses is determined by the memory of local L–A states. The differences between E- and D-based diagnoses can be driven by physical mechanisms or averaging algorithms. To improve understanding of L–A interactions, we call attention to the urgent need for more high-frequency data from both simulations and observations for relevant diagnoses. Regarding model outputs, two approaches are proposed to resolve the storage dilemma for high-frequency data: (1) integration of L–A metrics within Earth system models, and (2) producing alternative daily datasets based on different averaging algorithms.

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 ($t_p$) of momentum flux events from four different quadrants are separately normalized by $\Gamma_{w}$ (integral time scale of the vertical velocity), their distributions ($P(t_p/\Gamma_{w})$) remain height-invariant. This result points to a persistent memory imposed by canopy-induced coherent structures, and to their role as an efficient momentum transport mechanism between the canopy airspace and the region immediately above. Moreover, $P(t_p/\Gamma_{w})$ exhibits a power-law scaling at times $t_{p}, Comment: 33 Pages, 12 figures

The low-wavenumber regime of the spectrum of turbulence commensurate with Townsend’s “attached” eddies is investigated here for the near-neutral atmospheric surface layer (ASL) and the roughness sublayer (RSL) above vegetation canopies. The central thesis corroborates the significance of the imbalance between local production and dissipation of turbulence kinetic energy (TKE) and canopy shear in challenging the classical distance-from-the-wall scaling of canonical turbulent boundary layers. Using five experimental datasets (two vegetation canopy RSL flows, two ASL flows, and one open-channel experiment), this paper explores (i) the existence of a low-wavenumber k−1 scaling law in the (wind) velocity spectra or, equivalently, a logarithmic scaling ln(r) in the velocity structure functions; (ii) phenomenological aspects of these anisotropic scales as a departure from homogeneous and isotropic scales; and (iii) the collapse of experimental data when plotted with different similarity coordinates. The results show that the extent of the k−1 and/or ln(r) scaling for the longitudinal velocity is shorter in the RSL above canopies than in the ASL because of smaller scale separation in the former. Conversely, these scaling laws are absent in the vertical velocity spectra except at large distances from the wall. The analysis reveals that the statistics of the velocity differences Δu and Δw approach a Gaussian-like behavior at large scales and that these eddies are responsible for momentum/energy production corroborated by large positive (negative) excursions in Δu accompanied by negative (positive) ones in Δw. A length scale based on TKE dissipation collapses the velocity structure functions at different heights better than the inertial length scale.

Purpose. To report predictive factors of outcome of conventional epithelium-off corneal crosslinking (CXL) in the treatment of progressive keratoconus. Methods. This is a monocentric observational retrospective study conducted at Eye and Ear International Hospital, Lebanon. All patients with progressive keratoconus who underwent CXL between January 2008 and January 2016, with minimal 3-years follow-up were included. Primary treatment outcomes were maximum keratometry (K max), best-corrected distance visual acuity (CDVA), and failure. Failure was defined as an increase of 1.00 diopters (D) or more in K max and/or an increase of 0.1 logMAR or more in CDVA and conversion to corneal transplantation. Statistical analysis was done to identify predictors of treatment success. Univariate and multivariate analyses were performed to determine the correlations between baseline parameters and outcomes, and an equation for predicting K max and CDVA was created. Results. 156 eyes of 102 patients were enrolled. The mean age was 23.85 ± 6.52 years. Failure occurred in 31 eyes (19.87%). Gender and thinnest pachymetry did not have any impact on postoperative outcomes. Concerning the CDVA outcome, multivariate analysis showed that a better preoperative CDVA was associated with higher improvement in CDVA, and higher baseline K max and higher posterior mean K were associated with a worse outcome CDVA. Regarding postoperative K max, a higher baseline K max, a worse baseline CDVA, and a younger age were associated with less flattening postoperatively. Conclusion. CXL is a safe and effective method in treating progressive keratoconus. However, the clinical benefits can differ among patients, and in our series, a nonnegligible number of cases show a continued progression of their ectasia. Further studies to identify predictors of postoperative progression prior to the procedure could help sort out good responders to treatment.

This paper couples the meteorological Mesoscale Model (MM5) with the non-steady state CALPUFF modelling system in a short range dispersion context to assess regulatory compliance with air quality standards in a coastal urban area with complex terrain. For this purpose, an inventory of CO, NO x , and PM 10 emissions from an industrial complex, highway and quarrying activity was developed using emission factors reported by the US Environmental Protection Agency (USEPA) and the European Environment Agency (EEA). Multiple emission scenarios were then simulated to test the representativeness of the obtained emission factors using statistical analysis of predictions against year-round field measurements. At the validated emission rates, CALPUFF simulations showed an acceptable ability to predict the upper end of observed concentrations and reproduced field measurements at several locations. Statistical analysis revealed that sources are likely to be emitting at conservative estimates (worst-case efficiency of control equipment and fuel quality), with total CO, NO x and PM 10 emissions reaching 913 g s −1 (19% by highway and 81% by industries), 1266 g s −1 (63% by highway and 37% by industries) and 2970 g s −1 (93% by industries and 7% by quarries), respectively.

This paper examines the relative source contribution to ground-level concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), and PM10 (particulate matter with an aerodynamic diameter10 microm) in a coastal urban area due to emissions from an industrial complex with multiple stacks, quarrying activities, and a nearby highway. For this purpose, an inventory of CO, oxide of nitrogen (NO(x)), and PM10 emissions was coupled with the non-steady-state Mesoscale Model 5/California Puff Dispersion Modeling system to simulate individual source contributions under several spatial and temporal scales. As the contribution of a particular source to ground-level concentrations can be evaluated by simulating this single-source emissions or otherwise total emissions except that source, a set of emission sensitivity simulations was designed to examine if CALPUFF maintains a linear relationship between emission rates and predicted concentrations in cases where emitted plumes overlap and chemical transformations are simulated. Source apportionment revealed that ground-level releases (i.e., highway and quarries) extended over large areas dominated the contribution to exposure levels over elevated point sources, despite the fact that cumulative emissions from point sources are higher. Sensitivity analysis indicated that chemical transformations of NO(x) are insignificant, possibly due to short-range plume transport, with CALPUFF exhibiting a linear response to changes in emission rate. The current paper points to the significance of ground-level emissions in contributing to urban air pollution exposure and questions the viability of the prevailing paradigm of point-source emission reduction, especially that the incremental improvement in air quality associated with this common abatement strategy may not accomplish the desirable benefit in terms of lower exposure with costly emissions capping.The application of atmospheric dispersion models for source apportionment helps in identifying major contributors to regional air pollution. In industrial urban areas where multiple sources with different geometry contribute to emissions, ground-level releases extended over large areas such as roads and quarries often dominate the contribution to ground-level air pollution. Industrial emissions released at elevated stack heights may experience significant dilution, resulting in minor contribution to exposure at ground level. In such contexts, emission reduction, which is invariably the abatement strategy targeting industries at a significant investment in control equipment or process change, may result in minimal return on investment in terms of improvement in air quality at sensitive receptors.

The memory timescale that characterizes root-zone soil moisture remains the dominant measure in seasonal forecasts of land-climate interactions. This memory is a quasi-deterministic timescale associated with the losses (e.g. evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however, represents a distribution of time periods where soil moisture resides above or below some prescribed threshold, and is therefore inherently probabilistic. Using multiple soil moisture datasets collected at high resolution (sub-hourly) across different biomes and climates, this paper explores the differences, underlying dynamics, and relative importance of memory and persistence timescales in root-zone soil moisture. A first-order Markov process, commonly used to interpret soil moisture fluctuations derived from climate simulations, is also used as a reference model. Persistence durations of soil moisture below the plant water-stress level (chosen as the threshold), and the temporal spectrum of up- and down-crossings of this threshold, are compared to the memory timescale and spectrum of the full time series, respectively. The results indicate that despite the differences between meteorological drivers, the spectrum of threshold-crossings is similar across sites, and follows a unique relation with that of the full soil moisture series. The distribution of persistence times exhibits an approximate stretched exponential type and reflects a likelihood of exceeding the memory at all sites. However, the rainfall counterpart of these distributions shows that persistence of dry atmospheric periods is less likely at sites with long soil moisture memory. The cluster exponent, a measure of the density of threshold crossings in a time frame, reveals that the clustering tendency in rainfall events (on-off switches) does not translate directly to clustering in soil moisture. This is particularly the case in climates where rainfall and evapotranspiration are out of phase, resulting in less ordered (more independent) persistence in soil moisture than in rainfall.

Connections between the spatial and temporal statistics of turbulent flow, and their possible convergence to ensemble statistics as assumed by the ergodic hypothesis, are explored for passive scalars within a rod canopy. While complete ergodicity is not expected to apply over all the spatial domain within such heterogeneous flows, the fact that canopy turbulence exhibits self-similar characteristics at a given depth within the canopy encourages a discussion on necessary conditions for an ‘operational’ ergodicity framework. Flows between roughness elements such as within canopies exhibit features that distinguish them from their well-studied classical boundary-layer counterparts. These differences are commonly attributed to short-circuiting of the energy cascade and the prevalence of intermittent von Karman vortex streets in the deeper layers of the canopy. Using laser-induced fluorescence measurements at two different depths within a rod canopy situated in a large flume, the spatio-temporal statistical properties and concomitant necessary conditions for ergodicity of passive scalar turbulence statistics are evaluated. First, the integral time and length scales are analyzed and their corresponding maximum values are used to guide the construction of an ensemble of independent realizations from repeated spatio-temporal concentration measurements. As a statistical analysis for an operational ergodicity check, a Kolmogorov–Smirnov test on the distributions of temporal and spatial concentration series against the ensemble was conducted. The outcome of this test reveals that ergodicity is reasonably valid over the entire domain except close to the rod elements where wake-induced inhomogeneities and damped turbulence prevail. The spatial concentration statistics within a grid-cell (square domain formed by four corner rods) appear to be less ergodic than their temporal counterparts, which is not surprising given the periodicity and persistence of von Karman vortices in the flow field. Also, a local advection velocity of dominant eddies is inferred using lagged cross-correlations of scalar concentration time series at different spatial locations. The computed probability density function of this advection velocity agrees well with the laser Doppler anemometry measurements for the same rod canopy.

The inadequacy of conventional gradient-diffusion closure in modeling turbulent heat flux within the convective atmospheric boundary-layer is often alleviated by accounting for nonlocal transport. Such nonlocal effects are a manifestation of the inherent asymmetry in vertical transport in the convective boundary layer, which is in turn associated with third-order moments (skewness and fluxes of fluxes). In this work, the role of these third-order moments in second-order turbulence closure of the sensible heat flux is examined with the goal of reconciling the models to various closure assumptions. Surface layer similarity theory and mixed-layer parametrizations are used here, complemented by LES results when needed. The turbulent heat flux with various closure assumptions of the flux transport term is solved, including both local and nonlocal approaches. We connect to ejection-sweep cycles in the flow field using the GramCharlier cumulant expansion of the joint probability distribution of vertical velocity and potential temperature. In this nonlocal closure, the transport asymmetry models that include the vertical velocity skewness as a correction term to H originate from ejection-sweep events. Vertical inhomogeneity results in a modified-skewness correction to the nonlocal contribution to the heat flux associated with the relative intensity of ejections and sweeps.