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Characterizing aerosol chemical composition in response to meteorological changes and atmospheric chemistry is important to gain insights into new particle formation mechanisms. A BAECC (Biogenic Aerosols – Effects on Clouds and Climate) campaign was conducted during the spring 2014 at the SMEAR II station (Station for Measuring Forest Ecosystem–Aerosol Relations) in Finland. The particles were characterized by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). A PBL (planetary boundary layer) dilution model was developed to assist interpreting the measurement results. Right before nucleation events, the mass concentrations of organic and sulfate aerosol species were both decreased rapidly along with the growth of PBL heights. However, the mass fraction of sulfate aerosol of the total aerosol mass was increased, in contrast to a decrease for the organic mass fraction. Meanwhile, an increase in LVOOA (low-volatility oxygenated organic aerosol) mass fraction of the total organic mass was observed, in distinct comparison to a reduction of SVOOA (semi-volatile OOA) mass fraction. Our results demonstrate that, at the beginning of nucleation events, the observed sulfate aerosol mass was mainly driven by vertical turbulent mixing of sulfate-rich aerosols between the residual layer and the newly formed boundary layer, while the condensation of sulfuric acid (SA) played a minor role in interpreting the measured sulfate mass concentration. For the measured organic aerosols, their temporal profiles were mainly driven by dilution from PBL development, organic aerosol mixing in different boundary layers and/or partitioning of organic vapors, but accurate measurements of organic vapor concentrations and characterization on the spatial aerosol chemical composition are required. In general, the observed aerosol particles by AMS are subjected to joint effects of PBL dilution, atmospheric chemistry and aerosol mixing in different boundary layers. During aerosol growth periods in the nighttime, the mass concentrations of organic aerosols and organic nitrate aerosols were both increased. The increase in SVOOA mass correlated well with the calculated increase in condensed HOMs' (highly oxygenated organic molecules) mass. To our knowledge, our results are the first atmospheric observations showing a connection between increase in SVOOA and condensed HOMs during the nighttime.

We investigate the representation of convective transport of atmospheric compounds by boundary layer clouds. We focus on three key parameterizations that, when combined, express this transport: the area fraction of transporting clouds, the upward velocity in the cloud cores and the chemical concentrations at cloud base. The first two parameterizations combined represent the kinematic mass flux by clouds. To investigate the key parameterizations under a wide range of conditions, we use large-eddy simulation model data for 10 meteorological situations, characterized by either shallow cumulus or stratocumulus clouds. The parameterizations have not been previously tested with such large data sets. In the analysis, we show that the parameterization of the area fraction of clouds currently used in mixed-layer models is affected by boundary layer dynamics. Therefore, we (i) simplify the independent variable used for this parameterization, Q1, by considering the variability in moisture rather than in the saturation deficit and update the parameters in the parameterization to account for this simplification. We (ii) next demonstrate that the independent variable has to be evaluated locally to capture cloud presence. Furthermore, we (iii) show that the area fraction of transporting clouds is not represented by the parameterization for the total cloud area fraction, as is currently assumed in literature. To capture cloud transport, a novel active cloud area fraction parameterization is proposed. Subsequently, the scaling of the upward velocity in cloud cores by the Deardorff convective velocity scale and the parameterization for the concentration of atmospheric reactants at cloud base from literature are verified and improved by analysing six shallow cumulus cases. For the latter, we additionally discuss how the parameterization is affected by wind conditions. This study contributes to a more accurate estimation of convective transport, which occurs at sub-grid scales.

Formic acid (HCOOH) is one of the most abundant acids in the atmosphere, with an important influence on precipitation chemistry and acidity. Here we employ a chemical transport model (GEOS-Chem CTM) to interpret recent airborne and ground-based measurements over the US Southeast in terms of the constraints they provide on HCOOH sources and sinks. Summertime boundary layer concentrations average several parts-per-billion, 2–3× larger than can be explained based on known production and loss pathways. This indicates one or more large missing HCOOH sources, and suggests either a key gap in current understanding of hydrocarbon oxidation or a large, unidentified, direct flux of HCOOH. Model-measurement comparisons implicate biogenic sources (e.g., isoprene oxidation) as the predominant HCOOH source. Resolving the unexplained boundary layer concentrations based (i) solely on isoprene oxidation would require a 3× increase in the model HCOOH yield, or (ii) solely on direct HCOOH emissions would require approximately a 25× increase in its biogenic flux. However, neither of these can explain the high HCOOH amounts seen in anthropogenic air masses and in the free troposphere. The overall indication is of a large biogenic source combined with ubiquitous chemical production of HCOOH across a range of precursors. Laboratory work is needed to better quantify the rates and mechanisms of carboxylic acid production from isoprene and other prevalent organics. Stabilized Criegee intermediates (SCIs) provide a large model source of HCOOH, while acetaldehyde tautomerization accounts for ~ 15% of the simulated global burden. Because carboxylic acids also react with SCIs and catalyze the reverse tautomerization reaction, HCOOH buffers against its own production by both of these pathways. Based on recent laboratory results, reaction between CH3O2 and OH could provide a major source of atmospheric HCOOH; however, including this chemistry degrades the model simulation of CH3OOH and NOx : CH3OOH. Developing better constraints on SCI and RO2 + OH chemistry is a high priority for future work. The model neither captures the large diurnal amplitude in HCOOH seen in surface air, nor its inverted vertical gradient at night. This implies a substantial bias in our current representation of deposition as modulated by boundary layer dynamics, and may indicate an HCOOH sink underestimate and thus an even larger missing source. A more robust treatment of surface deposition is a key need for improving simulations of HCOOH and related trace gases, and our understanding of their budgets.

Sea surface temperature (SST) is characterized by abundant warm and cold structures that influence the overlying atmospheric boundary layer dynamics through two different mechanisms. First, turbulence and large eddies in the lower troposphere are affected by atmospheric stability, which can be modified by local SST, resulting in enhanced vertical mixing and larger surface winds over warmer waters. Second, the thermodynamic adjustment of air density to the underlying SST structures and the subsequent changes in atmospheric pressure drive secondary circulations. This paper aims to disentangle the effects of these processes and explore the environmental conditions that favor them. Two main environmental variables are considered: the large-scale air–sea temperature difference (proxy for stability) and wind speed. Using 5 years of daily reanalyses data, we investigate the 10-m wind response to SST structures. Based on linear regression between wind divergence and SST derivatives, we show that both mechanisms operate over a large spectrum of conditions. Ten-meter wind divergence is strongly impacted by the local SST via its effect on vertical mixing for midwind regimes in slightly unstable to near-neutral conditions, whereas the secondary circulation is important in two distinct regimes: low wind speed with a slightly unstable air column and high background wind speed with a very unstable air column. The first regime is explained by the prolonged Lagrangian time that the air parcel stays over an SST structure while the second one is related to strong heat fluxes at the air–sea interface, which greatly modify the marine atmospheric boundary layer properties. Location and frequency of the environmentally favorable conditions are discussed, as well as the response in low-cloud cover and rainfall.

Nighttime ozone in the lower boundary layer regulates atmospheric chemistry and surface ozone air quality, but our understanding of its vertical structure and impact is largely limited by the extreme sparsity of direct measurements. Here we present 3-year (2017–2019) measurements of ozone in the lower boundary layer (up to 500 m) from the Canton Tower in Guangzhou, the core megacity in South China, and interpret the measurements with a 1-month high-resolution chemical simulation from the Community Multiscale Air Quality (CMAQ) model. Measurements are available at 10, 118, 168, and 488 m, with the highest (488 m) measurement platform higher than the typical height of the nighttime stable boundary layer that allows direct measurements of ozone in the nighttime residual layer (RL). We find that ozone increases with altitude in the lower boundary layer throughout the day, with a vertical ozone gradient between the 10 and 488 m heights (ΔO3/ΔH10–488 m) of 3.6–6.4 ppbv hm−1 in nighttime and 4.4–5.8 ppbv hm−1 in daytime. We identify a high ozone residual ratio, defined as the ratio of ozone concentration averaged over nighttime to that in the afternoon (14:00–17:00 LT), of 69 %–90 % in January, April, and October, remarkably higher than that in the other three layers (29 %–51 %). Ozone in the afternoon convective mixing layer provides the source of ozone in the RL, and strong temperature inversion facilitates the ability of RL to store ozone from the daytime convective mixing layer. The tower-based measurement also indicates that the nighttime surface Ox (Ox= O3+NO2) level can be an effective indicator of RL ozone if direct measurement is not available. We further find significant influences of nocturnal RL ozone on both the nighttime and the following day's daytime surface ozone air quality. During the surface nighttime ozone enhancement (NOE) event, we observe a significant decrease in ozone and an increase in NO2 and CO at the 488 m height, in contrast to their changes at the surface, a typical feature of enhanced vertical mixing. The enhanced vertical mixing leads to an NOE event by introducing ozone-rich and NOx-poor air into the RL to enter the nighttime stable boundary layer. The CMAQ model simulations also demonstrate an enhanced positive contribution of vertical diffusion (ΔVDIF) to ozone at the 10 and 118 m heights and a negative contribution at the 168 and 488 m heights during the NOE event. We also observe a strong correlation between nighttime RL ozone and the following day's surface maximum daily 8 h average (MDA8) ozone. This is tied to enhanced vertical mixing with the collapse of nighttime RL and the development of a convective mixing layer, which is supported by the CMAQ diagnosis of the ozone budget, suggesting that the mixing of ozone-rich air from nighttime RL downward to the surface via the entrainment is an important mechanism for aggravating ozone pollution the following day. We find that the bias in CMAQ-simulated surface MDA8 ozone the following day shows a strong correlation coefficient (r= 0.74) with the bias in nighttime ozone in the RL, highlighting the necessity to correct air quality model bias in the nighttime RL ozone for accurate prediction of daytime ozone. Our study thus highlights the value of long-term tower-based measurements for understanding the coupling between nighttime ozone in the RL, surface ozone air quality, and boundary layer dynamics.

Existing CO2 emissions reported by city inventories usually lag in real-time by a year or more and are prone to large uncertainties. This study responds to the growing need for timely and precise estimation of urban CO2 emissions to support present and future mitigation measures and policies. We focus on the Paris metropolitan area, the largest urban region in the European Union and the city with the densest atmospheric CO2 observation network in Europe. We performed long-term atmospheric inversions to quantify the citywide CO2 emissions, i.e., fossil fuel as well as biogenic sources and sinks, over 6 years (2016–2021) using a Bayesian inverse modeling system. Our inversion framework benefits from a novel near-real-time hourly fossil fuel CO2 emission inventory (Origins.earth) at 1 km spatial resolution. In addition to the mid-afternoon observations, we attempt to assimilate morning CO2 concentrations based on the ability of the Weather Research and Forecasting model with Chemistry (WRF-Chem) transport model to simulate atmospheric boundary layer dynamics constrained by observed layer heights. Our results show a long-term decreasing trend of around 2 % ± 0.6 % per year in annual CO2 emissions over the Paris region. The impact of the COVID-19 pandemic led to a 13 % ± 1 % reduction in annual fossil fuel CO2 emissions in 2020 with respect to 2019. Subsequently, annual emissions increased by 5.2 % ± 14.2 % from 32.6 ± 2.2 MtCO2 in 2020 to 34.3 ± 2.3 MtCO2 in 2021. Based on a combination of up-to-date inventories, high-resolution atmospheric modeling and high-precision observations, our current capacity can deliver near-real-time CO2 emission estimates at the city scale in less than a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.

Weakly stratified layers over sloping topography can support a submesoscale baroclinic instability mode, a bottom boundary layer counterpart to surface mixed layer instabilities. The instability results from the release of available potential energy, which can be generated because of the observed bottom intensification of turbulent mixing in the deep ocean, or the Ekman adjustment of a current on a slope. Linear stability analysis suggests that the growth rates of bottom boundary layer baroclinic instabilities can be comparable to those of the surface mixed layer mode and are relatively insensitive to topographic slope angle, implying the instability is robust and potentially active in many areas of the global oceans. The solutions of two separate one-dimensional theories of the bottom boundary layer are both demonstrated to be linearly unstable to baroclinic instability, and results from an example nonlinear simulation are shown. Implications of these findings for understanding bottom boundary layer dynamics and processes are discussed.

Understanding atmospheric processes is essential for improving weather forecasts and models, but in continental regions the effects of dynamical mixing and frontal events on the chemical composition of the planetary boundary layer (PBL) remain poorly characterized. This study connects meteorological and chemical PBL processes during summer rain in Central and Southern rural Germany, focusing on two events: a warm front in a high-pressure system and a cold front following a convergence line.

Parameterization of submarine melting represents a large source of uncertainty in modeling ice sheet response to climate change. Here we present in situ observations of melt at near‐vertical ice faces using a novel instrument platform mounted rigidly to icebergs. We investigate boundary layer dynamics controlling melt across 31 measurement periods that span a range of momentum and thermal forcing (1–12 cm/s flows and 3–10 K). While melt generally scales with velocity and temperature, we find substantially enhanced melt linked with unsteady forcing. Several implementations of the three‐equation melt parameterization show melt can be predicted within a factor of 2 if the model is evaluated with peak near‐boundary velocities and flows are quasi‐steady. However, if flows are unsteady or the model is evaluated with low‐resolution velocities, melt is underpredicted by 2–75×.$75\\times .$We conclude that understanding the detailed character of near‐boundary flows is critical for submarine melt predictions. Plain Language Summary Glaciers are outlets for the world's ice to flow and melt into the ocean as fresh water. Despite the importance of understanding how glaciers melt and where that water goes, our knowledge of the environment where the glacier meets the ocean is limited due to the challenges of working under actively calving ice cliffs. To address this gap, we developed a remotely deployed instrument that measures melt rate and ocean speed and temperature along near‐vertical, underwater ice faces. In this study, we present results from the initial set of deployments at the sides of icebergs in southeast Alaska. We find that the flows along icebergs can vary rapidly, and that this may enhance melt rates. Furthermore, this enhanced melt rate is not captured by the standard melt models, resulting in a significant underprediction of melt. Therefore, accurate melt rate predictions at glaciers and icebergs require a realistic representation of both ocean characteristics and enhanced melt rate due to rapidly varying flows. Key Points Ice‐ocean boundary layer forcing varies on short timescales; flow unsteadiness appears to enhance melt rate Observed flows violate steady shear assumptions of ice‐ocean models, which underpredict observed melt by a factor of 2–75 Melt models exhibit increased skill when evaluated with instantaneous, highly‐resolved boundary layer conditions

The diurnal variations of surface and air temperature are closely related, but their different responses to evaporative conditions can inform us about land–atmosphere interactions. Here, we evaluate the responses of the diurnal ranges in surface (ΔTs ) and air (ΔTa ) temperature to evaporative fraction at 160 FLUXNET sites and in the ERA5 reanalysis. We show that the sensitivity of Ts to evaporative fraction depends on vegetation type, whereas Ta does not. On days with low evaporative fraction, Ts in FLUXNET is enhanced by up to ~20 K (~30 K in ERA5) in short vegetation, but only by up to ~10 K (~10 K in ERA5) in forests. Note that Ta responds rather similarly to evaporative fraction irrespective of vegetation type (~5 K in FLUXNET, ~10 K in ERA5). We find a systematic bias in ERA5’s ΔT response to evaporative conditions, showing a stronger sensitivity to evaporative fraction than in FLUXNET. We then demonstrate with a simple atmospheric boundary layer (SABL) model that the weak response of Ta to evaporative fraction can be explained by greater boundary layer growth under dry conditions, which increases the heat storage capacity and reduces the response of air temperature to evaporative fraction. Additionally, using a simplified surface energy balance (SSEB) model we show that Ts mainly responds to solar radiation, evaporative fraction, and aerodynamic conductance. We conclude that the dominant patterns of diurnal temperature variations can be explained by fundamental physical concepts, which should help us to better understand the main controls of land–atmosphere interactions.