Well-mixed Layer Research Articles

Investigation of Vertical Profiles of Particulate Matter and Meteorological Variables up to 2.5 km in Altitude Using a Drone-Based Monitoring System

In this study, a drone-based measurement system equipped with miniaturized optical and condensation particle counters was deployed to investigate the vertical distribution of particulate matter and meteorological variables up to 2.5 km in altitude. Measurements captured at various altitudes demonstrated notable vertical variations in particle concentration and significant correlations with meteorological factors, particularly relative humidity (RH). Near the surface, within a well-mixed boundary layer, particle concentrations remained stable despite RH changes, indicating both anthropogenic and natural influences. At higher altitudes, a clear positive relationship between RH and particle number concentration emerged, particularly for smaller particles, while temperature inversions and distinct wind patterns influenced aerosol dispersion. The unmanned aerial vehicle system’s robust performance, validated against standard meteorological tower data, underscores its potential for high-resolution atmospheric profiling. These insights are crucial for understanding particle behavior in diverse atmospheric layers and have implications for refining air quality monitoring and climate models. Future work should incorporate chemical analysis of aerosols to further expand these findings and assess their environmental impact.

Seasonal variation and fundamental characteristics of baroclinic tides in the Arabian Gulf

In the Arabian Gulf, baroclinic tides significantly impact physical and biological phenomena, shaping the region’s marine ecosystem. This study provides the first high-resolution investigation of the baroclinic tides using the three-dimensional, nonhydrostatic MIT general circulation model (MITgcm). The simulation outputs were validated against data from Oregon State University’s Tidal Inversion Software (OTIS), tidal stations, and mooring observations, showing high agreement and confirming the model’s accuracy. We further examined the characteristics of baroclinic and barotropic tides, identifying four key regions with high-intensity baroclinic tides based on energy budget analysis: 1) the narrow Strait of Hormuz; 2) the strait’s entrance along the trough, including the islands Farur, Siri, Abumusa, and Greater Tunb; 3) the central axial trough area with sea-bottom ridges; and 4) the northern area following a secondary ridge. Most baroclinic tides dissipate quickly due to interactions with complex bottom topography and do not propagate far from their sources. Significant seasonal variation shows that in winter, only the Strait of Hormuz and the area around the four islands showed significant baroclinic tidal energy, likely due to well-mixed upper layer seawater that hinders thermocline disturbances. The strong correlation between the simulation results and satellite images of internal waves suggests that intense baroclinic tides generate internal solitary waves in the Gulf.

How horizontal transport and turbulent mixing impact aerosol particle and precursor concentrations at a background site in the UAE

Abstract. The optical, physical, and chemical properties of aerosol particles have been previously studied in the United Arab Emirates (UAE), but there is still a gap in the knowledge of particle sources and in the horizontal and vertical transport of aerosol particles and their precursors in the area. To investigate how aerosol particle and SO2 concentrations at the surface responded to changes in horizontal and vertical transport, we used data from a 1-year measurement campaign at a background site where local sources of SO2 were expected to be minimal. The measurement campaign provided a combination of in situ measurements at the surface and the boundary layer evolution from vertical and horizontal wind profiles measured by a Doppler lidar. The diurnal structure of the boundary layer in the UAE was very similar from day to day, with a deep, well-mixed boundary layer during the day transitioning to a shallow nocturnal layer, with the maximum boundary layer height usually being reached around 14:00 local time. Both SO2 and nucleation-mode aerosol particle concentrations were elevated for surface winds coming from the east or western sectors. We attribute this to oil refineries located on the eastern and western coasts of the UAE. The concentrations of larger cloud condensation nuclei (CCN)-sized particles and their activation fraction did not show any clear dependence on wind direction, but the CCN number concentration showed some dependence on wind speed, with higher concentrations coinciding with the weakest surface winds. Peaks in SO2 concentrations were also observed despite low surface wind speeds and wind directions unfavourable for transport. However, winds aloft were much stronger, with wind speeds of 10 m s−1 at 1 km common at night and wind directions favourable for transport; surface-measured concentrations increased rapidly once these particular layers started to be entrained into the growing boundary layer, even if the surface wind direction was from a clean sector. These conditions also displayed higher nucleation-mode aerosol particle concentrations, i.e. new particle formation events occurring due to the increase in the gaseous precursor.

Above-cloud concentrations of cloud condensation nuclei help to sustain some Arctic low-level clouds

Abstract. Previous studies have found that low-level Arctic clouds often persist for long periods even in the face of very low surface cloud condensation nuclei (CCN) concentrations. Here, we investigate whether these conditions could occur due to continuous entrainment of aerosol particles from the free troposphere (FT). We use an idealized large eddy simulation (LES) modeling framework, where aerosol concentrations are low in the boundary layer (BL) but increased up to 50× in the free troposphere. We find that the tests with higher tropospheric aerosol concentrations simulated clouds, which persisted for longer and maintained higher liquid water paths (LWPs). This is due to direct entrainment of the tropospheric aerosol into the cloud layer, which results in a precipitation suppression from the increase in cloud droplet number and in stronger cloud-top radiative cooling, which causes stronger circulations maintaining the cloud in the absence of surface forcing. Together, these two responses result in a more well-mixed boundary layer with a top that remains in contact with the tropospheric aerosol reservoir and can maintain entrainment of those aerosol particles. The surface aerosol concentrations, however, remained low in all simulations. The free-tropospheric aerosol concentration necessary to maintain the clouds is consistent with concentrations that are frequently seen in observations.

Vertical Exchange Induced by Mixed Layer Instabilities

Abstract Submesoscale turbulence in the upper ocean consists of fronts, filaments, and vortices that have horizontal scales on the order of 100 m to 10 km. High-resolution numerical simulations have suggested that submesoscale turbulence is associated with strong vertical motion that could substantially enhance the vertical exchange between the thermocline and mixed layer, which may have an impact on marine ecosystems and climate. Theoretical, numerical, and observational work indicates that submesoscale turbulence is energized primarily by baroclinic instability in the mixed layer, which is most vigorous in winter. This study demonstrates how such mixed layer baroclinic instabilities induce vertical exchange by drawing filaments of thermocline water into the mixed layer. A scaling law is proposed for the dependence of the exchange on environmental parameters. Linear stability analysis and nonlinear simulations indicate that the exchange, quantified by how much thermocline water is entrained into the mixed layer, is proportional to the mixed layer depth, is inversely proportional to the Richardson number of the thermocline, and increases with increasing Richardson number of the mixed layer. The results imply that the tracer exchange between the thermocline and mixed layer is more efficient when the mixed layer is thicker, when the mixed layer stratification is stronger, when the lateral buoyancy gradient is stronger, and when the thermocline stratification is weaker. The scaling suggests vigorous exchange between the permanent thermocline and deep mixed layers in winter, especially in mode water formation regions. Significance Statement This study examines how instabilities in the surface layer of the ocean bring interior water up from below. This interior–surface exchange can be important for dissolved gases such as carbon dioxide and oxygen as well as nutrients fueling biological growth in the surface ocean. A scaling law is proposed for the dependence of the exchange on environmental parameters. The results of this study imply that the exchange is particularly strong if the well-mixed surface layer is thick, lateral density gradients are strong (such as at fronts), and the stratification below the surface layer is weak. These theoretical findings can be implemented in boundary layer parameterization schemes in global ocean models and improve our understanding of the marine ecosystem and how the ocean mediates climate change.

Seasonal vertical water vapor distribution at the Mars Phoenix Lander site

Using a combination of orbital and surface observations, we constrain the seasonal vertical distribution of water vapor in the planetary boundary layer in the lowest scale-height of the Martian atmosphere at the Phoenix Mars Lander location (68°N, 234°E). Previous observations have shown significant discrepancies regarding the vapor distribution in the boundary layer, drawing conflicting conclusions as to whether water is uniformly mixed below the cloud condensation height, or whether water is mostly confined in the near surface layer. We conclude that the uniformly well-mixed assumption for water vapor up to the cloud condensation level is not always compatible with observational constraints, particularly when peak near-surface water vapor abundances are observed during Ls = 110°–120°. The uniformly well-mixed assumption leads to an over-estimation of the total water vapor column abundances between Ls = 80°–120°, and an under-estimation of the total water vapor column abundances between Ls = 120°–150°. The overestimation of vapor in the column is particularly evident during peak surface water vapor pressures (∼Ls = 110°–120°), suggesting a concentration of water vapor at the surface that actively participates in subsurface exchange. Using both TECP and column vapor abundance as constraints for the vertical vapor distribution, the maximum height of the well-mixed vapor layer ranges between ∼3.5–13.5 km, all of which falls below the cloud condensation height for the corresponding season. From Ls = 120° to 150°, the maximum height of the well-mixed layer stays fairly consistent at a mean height of ∼7 km. These results are particularly important for providing insight into the seasonal transport of water and the role of regolith-atmospheric exchange.

Machine Learning–Adjusted WRF Forecasts to Support Wind Energy Needs in Black Start Operations

Abstract The push for increased capacity of renewable sources of electricity has led to the growth of wind-power generation, with a need for accurate forecasts of winds at hub height. Forecasts for these levels were uncommon until recently, and that, combined with the nocturnal collapse of the well-mixed boundary layer and daytime growth of the boundary layer through the levels important for energy generation, has contributed to errors in numerical modeling of wind generation resources. The present study explores several machine learning algorithms to both forecast and correct standard WRF Model forecasts of winds and temperature at hub height within wind turbine plants over several different time periods that are critical for the anticipation of potential blackouts and aiding in black start operations on the power grid. It was found that mean square error for day-2 wind forecasts from the WRF Model can be improved by over 90% with the use of a multioutput neural network, and that 60-min forecasts of WRF error, which can then be used to adjust forecasts, can be made with an LSTM with great accuracy. Nowcasting of temperature and wind speed over a 10-min period using an LSTM produced very low error and especially skillful forecasts of maximum and minimum values over the turbine plant area.

Dynamic Subgrid Turbulence Modeling for Shallow Cumulus Convection Simulations beyond LES Resolutions

Abstract A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC Cloud (MONC) model using two averaging flavors, along Lagrangian pathlines and local moving averages. The dynamic approaches were compared against the conventional Smagorinsky–Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The simulations spanned from the LES to the near-gray-zone and gray-zone resolutions and revealed the adaptability of the dynamic model across the scales and different stability regimes. The dynamic model can produce a scale- and stability-dependent profile of the subfilter turbulence length scale across the chosen resolution range. At gray-zone resolutions the adaptive length scales can better represent the early precloud boundary layer leading to temperature and moisture profiles closer to the LES compared to the standard Smagorinsky. As a result, the initialization and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the standard Smagorinsky produces a less well-mixed boundary layer, which fails to ventilate moisture from the boundary layer, resulting in the delayed spinup of the cloud layer. Moreover, strong downgradient diffusion controls the turbulent transport of scalars in the cloud layer. However, the dynamic approaches rely on the resolved field to account for nonlocal transports, leading to overenergetic structures when the boundary layer is fully developed and the Lagrangian model is used. Introducing the local averaging version of the model or adopting a new Lagrangian time scale provides stronger dissipation without significantly affecting model behavior.

Mixing across stable density interfaces in forced stratified turbulence

Understanding how turbulence enhances irreversible scalar mixing in density-stratified fluids is a central problem in geophysical fluid dynamics. While isotropic overturning regions are commonly the focus of mixing analyses, we here investigate whether significant mixing may arise in anisotropic statically stable regions of the flow. Focusing on a single forced direct numerical simulation of stratified turbulence, we analyse spatial correlations between the vertical density gradient $\partial \rho /\partial z$ and the dissipation rates of kinetic energy $\epsilon$ and scalar variance $\chi$ , the latter quantifying scalar mixing. The domain is characterized by relatively well-mixed density layers separated by sharp stable interfaces that are correlated with high vertical shear. While static instability is most prevalent within the mixed layers, much of the scalar mixing is localized to the intervening interfaces, a phenomenon not apparent if considering local static instability or $\epsilon$ alone. While the majority of the domain is characterized by the canonical flux coefficient $\varGamma \equiv \chi /\epsilon =0.2$ , often assumed in ocean mixing parametrizations, extreme values of $\chi$ within the statically stable interfaces, associated with elevated $\varGamma$ , strongly skew the bulk statistics. Our findings suggest that current parametrizations of turbulent mixing may be biased by undersampling, such that the most common, but not necessarily the most significant, mixing events are overweighted. Having focused here on a single simulation of stratified turbulence, it is hoped that our results motivate a broader investigation into the role played by stable density interfaces in mixing, across a wider range of parameters and forcing schemes representative of ocean turbulence.

Subsurface Bacterioplankton Structure and Diversity in the Strongly-Stratified Water Columns within the Equatorial Eastern Indian Ocean.

The consequences of climate change may directly or indirectly impact the marine biosphere. Although ocean stratification has been recognized as one of the crucial consequences of ocean warming, its impacts on several critical aspects of marine microbes remain largely unknown in the Indian Ocean. Here, we investigate the effects of water stratification, in both surface and subsurface layers, on hydrogeographic parameters and bacterioplankton diversity within the equatorial eastern Indian Ocean (EIO). Strong stratification in the upper 200 m of equatorial EIO was detected with evidential low primary productivity. The vertical bacterioplankton diversity of the whole water columns displayed noticeable variation, with lower diversity occurring in the surface layer than in the subsurface layers. Horizontal heterogeneity of bacterioplankton communities was also in the well-mixed layer among different stations. SAR11 and Prochlorococcus displayed uncharacteristic low abundance in the surface water. Some amplicon sequence variants (ASVs) were identified as potential biomarkers for their specific depths in strongly-stratified water columns. Thus, barriers resulting from stratification are proposed to function as an 'ASV filter' to regulate the vertical bacterioplankton community diversity along the water columns. Overall, our results suggest that the effects of stratification on the structure and diversity of bacterioplankton can extend up to the bathypelagic zone in the strongly-stratified waters of the equatorial EIO. This study provides the first insight into the effect of stratification on the subsurface microbial communities in the equatorial eastern Indian Ocean.

A downcore increase in time averaging is the null expectation from the transit of death assemblages through a mixed layer

AbstractUnderstanding how time averaging changes during burial is essential for using Holocene and Anthropocene cores to analyze ecosystem change, given the many ways in which time averaging affects biodiversity measures. Here, we use transition-rate matrices to explore how the extent of time averaging changes downcore as shells transit through a taphonomically complex mixed layer into permanently buried historical layers: this is a null model, without any temporal changes in rates of sedimentation or bioturbation, to contrast with downcore patterns that might be produced by human activity. Assuming stochastic burial and exhumation movements of shells between increments within the mixed layer and stochastic disintegration within increments, we find that almost all combinations of net sedimentation, mixing, and disintegration produce a downcore increase in time averaging (interquartile range [IQR] of shell ages), this trend is typically associated with a decrease in kurtosis and skewness and by a shift from right-skewed to symmetrical age distributions. A downcore increase in time averaging is thus the null expectation wherever bioturbation generates an internally structured mixed layer (i.e., a surface, well-mixed layer is underlain by an incompletely mixed layer): under these conditions, shells are mixed throughout the entire mixed layer at a slower rate than they are buried below it by sedimentation. This downcore trend created by mixing is further amplified by the downcore decline in disintegration rate. We find that transition-rate matrices accurately reproduce the downcore changes in IQR, skewness, and kurtosis observed in bivalve assemblages from the southern California shelf. The right-skewed shell age-frequency distributions typical of surface death assemblages—the focus of most actualistic research—might be fossilized under exceptional conditions of episodic anoxia or sudden burial. However, such right-skewed assemblages will typically not survive transit through the surface mixed layer into subsurface historical layers: they are geologically transient. The deep-time fossil record will be dominated instead by the more time-averaged assemblages with weakly skewed age distributions that form in the lower parts of the mixed layer.

ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application

Abstract. This paper provides a description of ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model. This framework can be used to study the atmospheric boundary layer, surface layer, or the exchange of gases, moisture, heat, and momentum between the land surface and the lower atmosphere. The general aim of the framework is to allow the assimilation of various streams of observations (fluxes, mixing ratios at multiple heights, etc.) to estimate model parameters, thereby obtaining a physical model that is consistent with a diverse set of observations. The framework allows the retrieval of parameters in an objective manner and enables the estimation of information that is difficult to obtain directly by observations, for example, free tropospheric mixing ratios or stomatal conductances. Furthermore, it allows the estimation of possible biases in observations. Modelling the carbon cycle at the ecosystem level is one of the main intended fields of application. The physical model around which the framework is constructed is relatively simple yet contains the core physics to simulate the essentials of a well-mixed boundary layer and of the land–atmosphere exchange. The model includes an explicit description of the atmospheric surface layer, a region where scalars show relatively large gradients with height. An important challenge is the strong non-linearity of the model, which complicates the estimation of the best parameter values. The constructed adjoint of the tangent linear model can be used to mitigate this challenge. The adjoint allows for an analytical gradient of the objective cost function, which is used for minimisation of this function. An implemented Monte Carlo way of running ICLASS can further help to handle non-linearity and provides posterior statistics on the estimated parameters. The paper provides a technical description of the framework, includes a validation of the adjoint code, in addition to tests for the full inverse modelling framework, and a successful example application for a grassland in the Netherlands.

Development and long-term evolution of density staircases in stirred stratified turbulence

Stirring a stably stratified fluid can lead to the formation of a system of well-mixed layers separated by sharp interfaces. We present a one-dimensional mixing-length model for layering, and investigate trends in the solutions to late times. Over time, layers drift and merge together on an inverse logarithmic timescale.

Aerosol characterisation in the subtropical eastern North Atlantic region using long-term AERONET measurements

Abstract. A comprehensive characterisation of atmospheric aerosols in the subtropical eastern North Atlantic has been carried out using long-term ground-based Aerosol Robotic NETwork (AERONET) photometric observations over the period 2005–2020 from a unique network made up of four stations strategically located from sea level to 3555 m on the island of Tenerife. This site can be considered a sentinel for the passage of airmasses going to Europe from Africa, and therefore the aerosol characterisation performed here adds important information for analysing their evolution during their path toward Northern Europe. Two of these stations (Santa Cruz de Tenerife – SCO – at sea level and La Laguna – LLO – at 580 m a.s.l.) are located within the marine atmospheric boundary layer (MABL), and the other two (Izaña – IZO – at 2373 m a.s.l. and Teide Peak – TPO – at 3555 m a.s.l.) are high mountain stations within the free troposphere (FT). Monthly climatology of the aerosol optical depth (AOD), Ångström exponent (AE), aerosol concentration, size distribution and aerosol optical properties has been obtained for the MABL and FT. Measurements that are quite consistent across the four sites have been used to categorise the main atmospheric scenarios, and these measurements confirm an alternation between predominant background conditions and predominant dust-loaded Saharan air mass conditions caused by seasonal dust transport over the subtropical North Atlantic. Background conditions prevail in the MABL and FT for most of the year, while dust-laden conditions dominate in July and August. The MABL under background conditions appears as a well-mixed layer with a low aerosol concentration (the volume concentration, VolCon, ranges from 0.02 ± 0.01 to 0.04 ± 0.02 µm3 µm−2), a predominance of coarse-mode marine aerosols (the effective radius, Reff, changes from 1.60 ± 0.19 to 1.91 ± 0.34 µm), and a volume contribution of the fine-mode fraction Vf/Vt <0.35. The clean FT is characterised by remarkably low aerosol loading and a predominant impact of fine-mode aerosols throughout the year (Vf/Vt has a maximum value of 0.93 ± 0.13), with an average Reff of 0.16 ± 0.02 µm. However, under dust-laden conditions and mainly in summer, we observe a predominance of coarse-mode aerosols with maximum VolCon values of 0.26 ± 0.23 µm3 µm−2 for the MABL and 0.16 ± 0.12 (0.06 ± 0.05) µm3 µm−2 for IZO (TPO), and a similar and quite consistent fine-mode fraction of 0.12 ± 0.03 in the vertical within the MABL and FT. Similarities in micro-physical and optical intensive aerosol properties confirm that the Saharan Air Layer (SAL) is a well-mixed layer in terms of the particulate composition. An estimation of the difference in the aerosol loading in the 1 km layer between IZO and TPO (in terms of VolCon and AOD) is performed in this study, and this shows that aerosol loading at IZO is double that at TPO, but they have similar fine-mode fractions, effective radii and intensive optical properties. The long-term trend analysis at SCO shows a significant negative trend in the fine-mode AOD between 2005 and 2020 (−1.8 ± 0.5) × 10−5 yr−1, which might be linked to the large reduction in oil-refining SO2 emissions from the SCO refinery in 2012.

Analysis of MONARC and ACTIVATE Airborne Aerosol Data for Aerosol-Cloud Interaction Investigations: Efficacy of Stairstepping Flight Legs for Airborne In Situ Sampling

A challenging aspect of conducting airborne in situ observations of the atmosphere is how to optimize flight plans for specific objectives and constraints associated with weather and flight restrictions. For aerosol-cloud interaction research, two recent campaigns utilized a “stairstepping” approach whereby an aircraft conducts level legs at various altitudes while moving forward with each subsequent leg: the 2019 MONterey Aerosol Research Campaign (MONARC) over the northeast Pacific and the 2020–2022 Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) over the northwest Atlantic. We examine the homogeneity of several atmospheric variables both vertically and horizontally in the marine boundary layer with a focus on the sub-cloud environment. In well-mixed boundary layers, there was generally good horizontal and vertical homogeneity in potential temperature, winds, water vapor mixing ratio, various trace gases, and many aerosol variables. Selected aerosol variables exhibited the most variability owing to sensitivity to humidity and near-cloud conditions (supermicrometer aerosol concentrations), coastal pollution gradients (e.g., organic aerosol mass), and small spatial scale phenomena such as new particle formation (aerosol number concentration for particles with diameter >3 nm). Illustrative cases are described when stairstepping can pose issues requiring extra caution for data analysis: (i) poor vertical mixing and layers decoupled from those below; (ii) multiple cloud layers; (iii) fluctuating cloud base/top and boundary layer top heights; and (iv) horizontal variability across specific features leading to sharp gradients such as right near coastlines and over the Gulf Stream with strong sea surface temperature changes. Results from this study provide a guide both for future studies aiming to examine these mission datasets and for designing new airborne campaigns.

Framework to Extract Extreme Phytoplankton Bloom Events with Remote Sensing Datasets: A Case Study

The chlorophyll-a concentration (CHL) is an essential climate variable. Extremes of CHL events directly reflect the condition of marine ecosystems. Here, we applied the statistical framework for defining marine heatwaves to study the extremes of winter CHL blooms off the Luzon Strait (termed as LZB), northeastern South China Sea (SCS), from a set of remote sensing data. The application was enabled by a recent gap-free CHL dataset, the SCSDCT data. We present the basic properties and the long-term trends of these LZB events, which had become fewer but stronger in recent years. We further statistically analyze the LZB events’ controlling factors, including the submesoscale activity quantified by a heterogeneous index or surface temperature gradients. It was revealed that the submesoscale activity was also a vital modulating factor of the bloom events in addition to the well-understood wind and upwelling controls. This modulation can be explained by the stratification introduced by submesoscale mixed-layer instabilities. In the winter, the intensified winter monsoon provides a background front and well-mixed upper layer with replenished nutrients. During the wind relaxation, submesoscale baroclinic instabilities developed, leading to rapid stratification and scattered submesoscale fronts. Such a scenario is favorable for the winter blooms. For the first time, this study identifies the bloom events in a typical marginal sea and highlights the linkage between these events and submesoscale activity. Furthermore, the method used to identify extreme blooms opens up the possibility for understanding trends of multiple marine extreme events under climate change.

Well-Mixed Boundary Layer–Top Entrainment Instability: Hydrodynamic Analysis

Abstract The present study shows by a linear hydrodynamic stability analysis that an unstable mixed-layer deep circulation can be generated in the dry convective well-mixed layer by the entrainment from the top. The newly identified instability arises under the two competing processes induced by the top entrainment: the destabilization by generating thermal perturbations and the damping by mechanical mixing. The former and the latter, respectively, dominate over the other in the limits of large and small scales. As a result, the instability is realized at the horizontal scales larger than the order of the mixed-layer depth (ca. 1 km), and the time scale for the growth is about 1 day. This study has been motivated from a question of whether the cloud-top entrainment instability (CTEI) can induce a transition of the stratocumulus-topped well-mixed boundary layer into trade cumulus. The present study intends to extend the previous studies based on the local parcel analyses to a full analysis based on the hydrodynamics. Unfortunately, being based on a dry formulation, the present result does not apply directly to the CTEI problem. Especially, the evaporative cooling is totally neglected. Nevertheless, the present result can still be applied to moist systems, to some extent, by redefining certain terms in the formulation.

Dispersal of hydrogen in the retina – a three-layer model

Two simple mathematical models of advection and diffusion of hydrogen within the retina are discussed. The work is motivated by the hydrogen clearance technique, which is used to estimate blood flow in the retina. The first model assumes that the retina consists of three, well-mixed layers with different thickness, and the second is a two-dimensional model consisting of three regions that represent the layers in the retina. Diffusion between the layers and leakage through the outer edges are considered. Solutions to the governing equations are obtained by employing Fourier series and finite difference methods for the two models, respectively. The effect of important parameters on the hydrogen concentration is examined and discussed. The results contribute to understanding the dispersal of hydrogen in the retina and in particular the effect of flow in the vascular retina. It is shown that the predominant features of the process are captured by the simpler model. doi: https://doi.org/10.1017/S1446181122000050

Warm and moist air intrusions into the winter Arctic: a Lagrangian view on the near-surface energy budgets

Abstract. In this study, warm and moist air intrusions (WaMAIs) over the Arctic Ocean sectors of Barents Sea, Kara Sea, Laptev Sea, East Siberian Sea, Chukchi Sea, and Beaufort Sea in 40 recent winters (from 1979 to 2018) are identified from the ERA5 reanalysis using both Eulerian and Lagrangian views. The analysis shows that WaMAIs, fueled by Arctic blocking, cause a relative surface warming and hence a sea-ice reduction by exerting positive anomalies of net thermal irradiances and turbulent fluxes on the surface. Over Arctic Ocean sectors with land-locked sea ice in winter, such as Laptev Sea, East Siberian Sea, Chukchi Sea, and Beaufort Sea, the total surface energy-budget is dominated by net thermal irradiance. From a Lagrangian perspective, total water path (TWP) increases linearly with the downstream distance from the sea-ice edge over the completely ice-covered sectors, inducing almost linearly increasing net thermal irradiance and total surface energy-budget. However, over the Barents Sea, with an open ocean to the south, total net surface energy-budget is dominated by the surface turbulent flux. With the energy in the warm-and-moist air continuously transported to the surface, net surface turbulent flux gradually decreases with distance, especially within the first 2∘ north of the ice edge, inducing a decreasing but still positive total surface energy-budget. The boundary-layer energy-budget patterns over the Barents Sea can be categorized into three classes: radiation-dominated, turbulence-dominated, and turbulence-dominated with cold dome, comprising about 52 %, 40 %, and 8 % of all WaMAIs, respectively. Statistically, turbulence-dominated cases with or without cold dome occur along with 1 order of magnitude larger large-scale subsidence than the radiation-dominated cases. For the turbulence-dominated category, larger turbulent fluxes are exerted to the surface, probably because of stronger wind shear. In radiation-dominated WaMAIs, stratocumulus develops more strongly and triggers intensive cloud-top radiative cooling and related buoyant mixing that extends from cloud top to the surface, inducing a thicker well-mixed layer under the cloud. With the existence of cold dome, fewer liquid water clouds were formed, and less or even negative turbulent fluxes could reach the surface.

A Time-Varying Model for Predicting Formaldehyde Emission Rates in Homes.

Recent studies have succeeded in relating emissions of various volatile organic compounds to material mass diffusion transfer using detailed empirical characteristics of each of the individual emitting materials. While significant, the resulting models are often scenario specific and/or require a host of individual component parameters to estimate emission rates. This study developed an approach to estimate aggregated emissions rates based on a wide number of field measurements. We used a multi-parameter regression model based on previous mass transfer models to predict formaldehyde emission rate for a whole dwelling using field-measured, time-resolved formaldehyde concentrations, air exchange rates, and indoor environmental parameters in 63 California single-family houses built between 2011 and 2017. The resulting model provides time-varying formaldehyde emission rates, normalized by floor area, for each study home, assuming a well-mixed mass balance transport model of the home, and a well-mixed layer transport model of indoor surfaces. The surface layer model asserts an equilibrium concentration within the surface layer of the emitted materials that is a function of temperature and RH; the dwelling ventilation rate serves as a surrogate for indoor concentration. We also developed a more generic emission model that is suitable for broad prediction of emission for a population of buildings. This model is also based on measurements aggregated from 27 homes from the same study. We showed that errors in predicting household formaldehyde concentrations using this approach were substantially less than those using a traditional constant emission rate model, despite requiring less unique building information.