JGR–Atmospheres

Over the past decades, various experimental and numerical model studies have indicated cooling trend in the mesosphere and lower thermosphere (MLT), while the magnitude of the trend varies noticeably. Previous studies using the lidar observations derived the temperature trends and solar responses solely from the traditional nocturnal measurements. While these archived results are more or less in agreement with modeling studies, one of the main uncertainties in these studies is the potential biases induced by the trends of the diurnal tide forced in the lower atmosphere, and that of the in situ exothermal reactions involving the photolysis. In the MLT, the diurnal tide has significant seasonal variations, considerable amplitude and is one of the dominant dynamic sources. However, its potential effects in the trend studies have rarely been discussed. In this paper, we present and compare the long-term temperature trends in the upper mesosphere utilizing the daily mean and nightly mean temperature profiles measured by a Sodium (Na) Doppler lidar at midlatitude. The system was operating routinely in full diurnal cycles between 2002 and 2017, obtaining a unique multi-year temperature data set. A customized multi-linear regression (MLR) model is applied to determine the linear trends and the other fitting parameters, such as ENSO and solar F10.7 responses in the upper mesosphere. This study indicates the daily mean cooling trend between 84 and 98 km is larger than that of nightly mean trend by ∼−1 K/decade, while differences in the solar response are within the fitting uncertainties.

We use measurements of trace gases from the Microwave Limb Sounder and polar stratospheric clouds (PSCs) from the Cloud-Aerosol Lidar with Orthogonal Polarization to investigate how the extraordinary stratospheric water vapor enhancement from the 2022 Hunga eruption affected polar processing during the 2023 Antarctic winter. Although the dynamical characteristics of the vortex itself were generally unexceptional, the excess moisture initially raised PSC formation threshold temperatures above typical values. Cold conditions, especially in early July, prompted ice PSC formation and unusually severe irreversible dehydration at higher levels (500–700 K), while atypical hydration occurred at lower levels (380–460 K). Heterogeneous chemical processing was more extensive, both vertically (up to 750–800 K) and temporally (earlier in the season), than in prior Antarctic winters. The resultant HCl depletion and ClO enhancement redefined their previously observed ranges at and above 600 K. Albeit unmatched in the satellite record, the early-winter upper-level chlorine activation was insufficient to induce substantial ozone loss. Chlorine activation, denitrification, and dehydration processes ran to completion by July/August, with trace gas evolution mostly following the climatological mean thereafter, but with chlorine deactivation starting slightly later than usual. While cumulative ozone losses at 410–550 K were relatively large, probably because of the delayed chlorine deactivation, they were not unprecedented. Thus, ozone depletion was unremarkable throughout the lower stratosphere. Although Hunga enhanced PSC formation and chemical processing in early winter, saturation of lower stratospheric denitrification, dehydration, and chlorine activation (as is typical in the Antarctic) prevented an exceptionally severe ozone hole in 2023.

Hydration of the stratosphere by tropopause-overshooting convection has received increasing interest due to the extreme concentrations of water vapor that can result and, ultimately, the climate warming potential such hydration provides. Previous work has recognized the importance of numerous dynamic and physical processes that control stratospheric water vapor delivery by convection. This study leverages recent comprehensive observations from the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign to determine the frequency at which each process operates during real events. Specifically, a well-established analysis technique known as tracer-tracer correlation is applied to DCOTSS observations of ozone, water vapor, and potential temperature to identify the occurrence of known processes. It is found that approximately half of convectively-driven stratospheric hydration samples show no indication of significant air mass transport and mixing, emphasizing the importance of ice sublimation to stratospheric water vapor delivery. Furthermore, the temperature of the upper troposphere and lower stratosphere environment and/or overshoot appears to be a commonly active constraint, since the approximate maximum possible water vapor concentration that can be reached in an air mass is limited to the saturation mixing ratio when ice is present. Finally, little evidence of relationships between dynamic and physical processes and their spatial distribution was found, implying that stratospheric water vapor delivery by convection is likely facilitated by a complex collection of processes in each overshooting event.

Methane (CH4) is the second most abundant greenhouse gas and affects the Earth's radiative balance. In some regions, the methane burden and budget are still not well understood due to the lack of in situ observations, especially vertical profile observations. Here, we present the first high-resolution aircraft-based tropospheric vertical profiles of CH4 across the Indian subcontinent. Observations show significant variability, with the largest variability seen in the Indo-Gangetic Plain (IGP) during post-monsoon (September). The IGP also shows the highest concentrations and a peak in the boundary layer. By contrast, observations over western India show lower variability, especially during the Asian Summer Monsoon (ASM) (July). During ASM, when CH4 emissions peak, the vertical updraft of CH4 and other tracers is observed, leading to a peak between 4 and 5 km. During winter, the peak occurs in the boundary layer, and a decrease with altitude is observed. Model simulations slightly overestimate CH4 at the surface during some seasons but underestimate it at higher altitudes during all seasons. Integrated over the observed column, model simulations slightly underpredict CH4 (0.5%–3.1%) during all seasons. Calculations made using the observed CO/CH4 enhancement ratios show that in addition to anthropogenic fossil fuel emissions, other sources, such as rice cultivation and wetlands, need to be considered to reproduce the observed CH4 concentrations.

Proteinaceous matter (PrM) is a substantial component of bioaerosols. Although numerous studies have examined the characteristics and sources of PrM in the atmosphere, its interactions with atmospheric oxidants remain uncertain. A 1-year observation of PrM characteristics in PM2.5 was performed in both urban Nanchang (eastern China) and suburban Guiyang (southwestern China), respectively. Glycine was the dominant free amino acid (FAA) species in urban Nanchang. In contrast, proline dominated both total free amino acids (FAAs) and total combined amino acids (CAAs) in suburban Guiyang. We found that oxidative degradation can significantly promote the release of FAAs, especially glycine, from CAAs in Nanchang. The controlled experiment on protein oxidation by hydroxyl radical suggested that the contribution of free glycine to the total FAA fraction tended to increase during the oxidative degradation of CAAs, supporting the predominance of glycine in FAAs in Nanchang and most previous observations. The composition of FAAs was mainly influenced by primary sources in suburban Guiyang with weak atmospheric degradation of PrM. These results suggest that the degradation of aerosol PrM by atmospheric oxidants can be responsible for the difference in FAA composition between the biosphere and the atmosphere, and also imply that the oxidative degradation of aerosol PrM may be a potential source of secondary organic nitrogen compounds in aerosols. Thus, this study can improve the current understanding of the composition characteristics of PrM in the biosphere and the atmosphere, as well as the liquid phase reactions of proteinaceous compounds with atmospheric oxidants.

Modeling atmospheric black carbon (BC) aerosol optical properties remains largely uncertain due to their complex mixing states, nonsphericity, and heterogeneity of coating distribution. Although there exist numerical models with realistic BC morphologies, these models are mostly limited to particle-scale studies and have not been coupled to large-scale atmospheric or climate models. In this study, a multidimensional parameterization scheme is developed by an accurate numerical algorithm for BC optical property calculation in global climate models, by incorporating their mixing state and nonspherical structure as well as heterogeneous coating distribution. The scheme was coupled and tested with the Community Atmosphere Model version 6 (CAM6) by a weighted averaging algorithm for individual particles and integration for particle ensembles. The simulation results indicate that BC morphology has a limited influence on the aerosol absorption cross section (C abs), and the differences in C abs between irregularly coated fractal aggregates and ideal core-shell spherical (CS) counterparts are ∼3% on average. However, the relative positions between the BC core and coating parts may introduce C abs variations of up to 69% as compared with the CS results. The BC mixing state introduce ∼20% relative variations in the global average aerosol absorption optical depth, which is comparable to that of heterogeneity of coating distribution and three times greater than that of particle nonsphericity. Furthermore, the normalized mean biases of modeled single scattering coalbedo (1−SSA, i.e., the ratio of absorption to extinction) compared to those observed in BC-rich regions are reduced by 20%∼80% when applying our new parameterization in CAM6.

The Bay of Bengal summer monsoon (BOBSM) is the most prominent branch of the Asian summer monsoon system, which exhibits complex interannual variability. While previous studies have focused on the onset conditions of the BOBSM, less attention has been paid to the retreat of the BOBSM. In this study, we propose an index to measure BOBSM retreat, based on the mean zonal wind field at 850 hPa during the summer-to-winter monsoon transitions. By analyzing the climatic characteristics and interannual variability of the BOBSM retreat using this index, we find that BOBSM retreat exhibits significant interannual variability, which is closely related to the occurrence of Indian Ocean Dipole (IOD) events. Statistically, when a positive IOD event takes place in the boreal autumn season, the retreat of the summer monsoon occurs earlier correspondingly. Conversely, the retreat is delayed when a negative IOD event occurs.

The source of dust in the global atmosphere is an important factor to better understand the role of dust aerosols in the climate system. However, it is a difficult task to attribute the airborne dust over the remote land and ocean regions to their origins since dust from various sources are mixed during long-range transport. Recently, a multi-model experiment, namely the AeroCom-III Dust Source Attribution (DUSA), has been conducted to estimate the relative contribution of dust in various locations from different sources with tagged simulations from seven participating global models. The BASE run and a series of runs with nine tagged regions were made to estimate the contribution of dust emitted in East- and West-Africa, Middle East, Central- and East-Asia, North America, the Southern Hemisphere, and the prominent dust hot spots of the Bodélé and Taklimakan Deserts. The models generally agree in large scale mean dust distributions, however models show large diversity in dust source attribution. The inter-model differences are significant with the global model dust diversity in 30%–50%, but the differences in regional and seasonal scales are even larger. The multi-model analysis estimates that North Africa contributes 60% of global atmospheric dust loading, followed by Middle East and Central Asia sources (24%). Southern hemispheric sources account for 10% of global dust loading, however it contributes more than 70% of dust over the Southern Hemisphere. The study provides quantitative estimates of the impact of dust emitted from different source regions on the globe and various receptor regions including remote land, ocean, and the polar regions synthesized from the seven models.

Despite their essential role in the high-latitude climate, the representation of mixed-phase clouds is still a challenge for Global Climate Models (GCMs)'s cloud schemes. In this study we propose a methodology for robustly assessing Arctic mixed-phase cloud properties in a climate model using airborne measurements. We leverage data collected during the RALI-THINICE airborne campaign that took place near Svalbard in August 2022 to evaluate the simulation of mid-level clouds associated with Arctic cyclones. Simulations are carried out with the new limited-area configuration of the ICOLMDZ model which combines the recent icosahedral dynamical core DYNAMICO and the physics of LMDZ, the atmospheric component of the IPSL-CM Earth System Model. Airborne radar and microphysical probes measurements are then used to evaluate the simulated clouds. A comparison method has been set-up to guarantee as much as possible the spatiotemporal co-location between observed and simulated cloud fields. We mostly focus on the representation of ice and liquid in-cloud contents and on their vertical distribution. Results show that the model overestimates the amount of cloud condensates and exhibits a poor cloud phase spatial distribution, with too much liquid water far from cloud top and too much ice close to it. The downward gradual increase in snowfall flux is also not captured by the model. This in-depth model evaluation thereby pinpoints priorities for further improvements in the ICOLMDZ cloud scheme.

Secondary air pollution, especially ozone (O3) and secondary aerosols, are emerging air quality challenges confronting China. Nitrous acid (HONO), as the predominant source of hydroxyl radicals (OH), are acknowledged to be essential for secondary pollution. However, HONO concentrations are usually underestimated by current air quality models due to the inadequate representations of its sources. In the present study, we revised the Weather Research and Forecasting & Chemistry (WRF-Chem) model by incorporating additional HONO sources, including primary emissions, photo-/dark oxidation of NOx, heterogeneous uptake of NO2 on surfaces, and nitrate photolysis. By combining in-situ measurements in the Yangtze River Delta (YRD) region, we found the improved model show much better performance on HONO simulation and is capable of reproducing observed high concentrations. The source-oriented method is employed to quantitatively understand the relative importance of various processes, which showed that heterogeneous NO2 uptake on the ground surface was the major contributor to HONO formation in urban areas. Comparatively, photo-oxidation of NOx is a main contributor in rural areas. The introduction of multiple sources of HONO led to an apparent increase in OH and hydroperoxyl (HO2) radicals. The promoted HO2 levels further increased diurnal O3 concentration by 4.5–12.9 ppb, while secondary inorganic and organic concentrations were also increased by 14%–32% during a typical secondary pollution event. The improved description of HONO emission and formation in the model substantially narrowed the gaps between simulations and observations, highlighting the great importance in understanding and numerical representations of HONO in secondary pollution study.

High-latitudinal mixed-phase clouds significantly affect Earth's radiative balance. Observations of cloud and radiative properties from two field campaigns in the Southern Ocean and Antarctica were compared with two global climate model simulations. A cyclone compositing method was used to quantify “dynamics-cloud-radiation” relationships relative to the extratropical cyclone centers. Observations show larger asymmetry in cloud and radiative properties between western and eastern sectors at McMurdo compared with Macquarie Island. Most observed quantities at McMurdo are higher in the western (i.e., post-frontal) than the eastern (frontal) sector, including cloud fraction, liquid water path (LWP), net surface shortwave and longwave radiation (SW and LW), except for ice water path (IWP) being higher in the eastern sector. The two models were found to overestimate cloud fraction and LWP at Macquarie Island but underestimate them at McMurdo Station. IWP is consistently underestimated at both locations, both sectors, and in all seasons. Biases of cloud fraction, LWP, and IWP are negatively correlated with SW biases and positively correlated with LW biases. The persistent negative IWP biases may have become one of the leading causes of radiative biases over the high southern latitudes, after correcting the underestimation of supercooled liquid water in the older model versions. By examining multi-scale factors from cloud microphysics to synoptic dynamics, this work will help increase the fidelity of climate simulations in this remote region.

The influence of northern polar vortex in the stratosphere (SPV) in December-January on Asia's surface air temperature (SAT) in February has been examined using reanalysis data sets and a barotropic model. An out-of-phase interannual linkage between the SPV in December-January and SAT in February during 1979–2022 has been observed, that is, a strong (weak) SPV corresponds to a cooling (warming) over Asia. Approximately 25% of the SAT over Asia in February can be explained by the SPV in December-January. This relationship between the SPV and SAT is independent of the Arctic Oscillation. The influence of the SPV on SAT over Asia cannot be solely explained by radiative processes, but is instead related to circulation anomalies in the troposphere. A stronger SPV tends to result in negative geopotential height anomalies with cyclonic circulation over Asia. The SPV-related geopotential height over Asia is accompanied by a weakened teleconnection pattern between the North Atlantic and Asia, with three centers from the northeastern Atlantic-eastern Europe-Asia, and fewer stationary waves propagated from North Atlantic into Asia. These anomalous circulation patterns and anomalous northerly wind over Central Asia in February are beneficial to the colder air transportation from the higher latitudes to Asia, facilitating a surface cooling over Asia. Our results shed light on the interannual linkage between SPV and SAT over Asia, suggesting that the SPV in December-January could be considered as a new predicator of SAT in February over Asia.

Water-soluble organic carbon (WSOC) deposited in ambient snowpack play key roles in regional carbon cycle and surface energy budget, but the impacts of photo-induced processes on its optical and chemical properties are poorly understood yet. In this study, melted samples of the seasonal snow collected from northern Xinjiang, northwestern China, were exposed to ultraviolet (UV) radiation to investigate the photolytic transformations of WSOC. Molecular characteristics and chemical composition of WSOC and its brown carbon (BrC) constituents were investigated using high-performance liquid chromatography interfaced with a photodiode array detector and a high-resolution mass spectrometer. Upon illumination, formation of nitrogen- and sulfur-containing species with high molecular weight was observed in snow samples influenced by soil- and plant-derived organics. In contrast, the representative sample collected from remote region showed the lowest molecular diversity and photolytic reactivity among all samples, in which no identified BrC chromophores decomposed upon illumination. Approximately 65% of chromophores in urban samples endured UV irradiation. However, most of BrC composed of phenolic/lignin-derived compounds and flavonoids disappeared in the illuminated samples containing WSOC from soil- and plant-related sources. Effects of the photochemical degradation of WSOC on the potential modulation of snow albedo were estimated. Apparent half-lives of WSOC estimated as albedo reduction in 300–400 nm indicated 0.1–0.4 atmospheric equivalent days, which are shorter than typical photolysis half-lives of ambient biomass smoke aerosol. This study provides new insights into the roles of WSOC in snow photochemistry and snow surface energy balance.

Nitrogen dioxide (NO2) is an atmospheric pollutant emitted from anthropogenic and natural sources. Human exposure to high NO2 concentrations causes cardiovascular and respiratory illnesses. The Environmental Protection Agency operates ground monitors across the U.S. which take hourly measurements of NO2 concentrations, providing precise measurements for assessing human pollution exposure but with sparse spatial distribution. Satellite-based instruments capture NO2 amounts through the atmospheric column with global coverage at regular spatial resolution, but do not directly measure surface NO2. This study compares regression methods using satellite NO2 data from the TROPospheric Ozone Monitoring Instrument (TROPOMI) to estimate annual surface NO2 concentrations in varying geographic and land use settings across the continental U.S. We then apply the best-performing regression models to estimate surface NO2 at 0.01° by 0.01° resolution, and we term this estimate as quasi-NO2 (qNO2). qNO2 agrees best with measurements at suburban sites (cross-validation (CV) R 2 = 0.72) and away from major roads (CV R 2 = 0.75). Among U.S. regions, qNO2 agrees best with measurements in the Midwest (CV R 2 = 0.89) and agrees least in the Southwest (CV R 2 = 0.65). To account for the non-Gaussian distribution of TROPOMI NO2, we apply data transforms, with the Anscombe transform yielding highest agreement across the continental U.S. (CV R 2 = 0.77). The interpretability, minimal computational cost, and health relevance of qNO2 facilitates use of satellite data in a wide range of air quality applications.

The light absorption enhancement (Eabs) of black carbon (BC) coated with non-BC materials is crucial in the assessment of radiative forcing, yet its evolution during photochemical aging of plumes from biomass burning, the globe's largest source of BC, remains poorly understood. In this study, plumes from open burning of corn straw were introduced into a smog chamber to explore the evolution of Eabs during photochemical aging. The light absorption of BC was measured with and without coating materials by using a thermodenuder, while the size distributions of aerosols and composition of BC coating materials were also monitored. Eabs was found to increase initially, and then decrease with an overall downward trend. The lensing effect dominated in Eabs at 520 nm, with an estimated contribution percentages of 47.5%–94.5%, which is far greater than light absorption of coated brown carbon (BrC). The effects of thickening and chemical composition changes of the coating materials on Eabs were evaluated through comparing measured Eabs with that calculated by the Mie theory. After OH exposure of 1 × 1010 molecules cm−3 s, the thickening of coating materials led to an Eabs increase by 3.2% ± 1.6%, while the chemical composition changes or photobleaching induced an Eabs decrease by 4.7% ± 0.6%. Simple forcing estimates indicate that coated BC aerosols exhibit warming effects that were reduced after aging. The oxidation of light-absorbing CxHy compounds, such as polycyclic aromatic hydrocarbons (PAHs), to CxHyO and CxHyO>1 compounds in coating materials may be responsible for the photobleaching of coated BrC.

Rain-on-snow (ROS) events occur when rain falls on snowpack and can have substantial ecological and social impacts. During ROS events, liquid water in the snowpack can decrease the surface albedo, which contributes to the positive snow-albedo feedback and further accelerates snowmelt. In a warming climate, the frequency and spatial coverage of ROS events are projected to increase in the high-latitude regions, especially in northern Alaska. Multi-year ground observations at two northern Alaska sites are utilized to evaluate 59 ROS events from 2012 to 2022. Results show that ROS events lead to dramatic snow albedo changes with a mean decline of −0.04 per day, which is considerably larger than the multi-year mean of −0.005 in May and −0.008 in June. A snow albedo model is used to simulate the daily snow albedo changes due to snowpack liquid water content. The simulated impact of liquid water content accounts for only 10% of the observed snow albedo changes. In addition, composite synoptic conditions from reanalysis products reveal different moisture sources for ROS events. ROS events in May are associated with anomalous high pressure systems over the site and meridional transport of warm and moist air from lower latitudes. While the June synoptic conditions for ROS events show little deviation from the climatological mean and suggest local moisture contributions. ROS events in June show comparable snow albedo changes as in May despite the difference in moisture sources, which implies a prolonged impact of ROS events on rapid snow deterioration during late spring.

No abstract is available for this article.

The shortwave cloud radiative effect (SWCRE) is important for the Arctic surface radiation budget and is a major source of inter-model spread in simulating Arctic climate. To better understand the individual contributions of various radiative processes to changes in SWCRE, we extend the existing Approximate Partial Radiative Perturbation (APRP) method by adding the absorptivity for the upward beam, considering differences in reflectivity between upward and downward beams, and analyzing the cloud masking effect resulting from changes in surface albedo. Using data from CMIP model experiments, the study decomposes the SWCRE over the Arctic surface and analyzes inter-model differences in quadrupled CO2 simulations. The study accounts for the influence of surface albedo, cloud amount, and cloud microphysics in the response of SWCRE to Arctic warming. In the sunlit season, CMIP models exhibit a strong, negative SWCRE with a large inter-model spread. Arctic clouds dampen the surface albedo feedback by reflecting incoming solar radiation and further decrease the shortwave radiation reflected by surface, a fraction of which is scattered back to the surface by clouds. Specifically, this accounts for the majority of the inter-model spread in SWCRE. In addition, increased (decreased) cloud amount and cloud liquid water reduce (increase) incoming shortwave fluxes at the surface, but they are found to be not critical to the Arctic surface radiation budget and its inter-model variation. Overall, the extended APRP method offers a useful tool for analyzing the complex interactions between clouds and radiative processes, accurately decomposes the individual SWCRE responses at the Arctic surface.

To better understand and improve the prediction of the seasonal surface temperature (TS) across the United States, we employed convolutional neural network (CNN) models trained on the Community Earth System Model Version 2 Large Ensemble (CESM2 LENS). We used lagged sea surface temperatures (SST) over the tropical Pacific region, containing the information of the El Niño Southern Oscillation (ENSO), as input for the CNN models. ENSO is the principal driver of variability in seasonal US surface temperatures (TSUS) and employing CNN models allows for spatiotemporal aspects of ENSO to be analyzed to make seasonal TSUS predictions. For predicting TSUS, the CNN models exhibited significantly improved skill over standard statistical multilinear regression (MLR) models and dynamical forecasts across most regions in the US, for lead times ranging from 1 to 6 months. Furthermore, we employed the CNN models to predict seasonal TSUS during extreme ENSO events. For these events, the CNN models outperformed the MLR models in predicting the effects on seasonal TSUS, suggesting that the CNN models are able to capture the ENSO-TSUS teleconnection more effectively. Results from a heatmap analysis demonstrate that the CNN models utilize spatial features of ENSO rather than solely the magnitude of the ENSO events, indicating that the improved skill of seasonal TSUS is due to analyzing spatial variation in ENSO events. The proposed CNN model demonstrates a promising improvement in prediction skill compared to existing methods, suggesting a potential path forward for enhancing TSUS forecast skill from subseasonal to seasonal timescales.

We investigate the absolute momentum flux (AMF) and vertical wind variance ρw′2‾ $\left(\rho \overline{{w}^{\prime 2}}\right)$ of gravity waves (GWs) along with intermittencies in the upper troposphere and lower stratosphere (UTLS) during 2017–2022 using the Middle Atmosphere Alomar Radar System at Andøya, Norway (69.30°N, 16.04°E). We categorized the AMF and ρw′2‾ $\rho \overline{{w}^{\prime 2}}$ into different period ranges (30 min–2 hr, 2–6 hr, 6–13 hr, 13 hr–1 day, and 30 min–1 day) to study the significance of short- and long-period waves. The selection of these period bands was based on the boundary conditions of the available spectra: 30 min (Nyquist frequency), 13 hr (inertial period), and 1 day (based on our interest in maximum long-period oscillations). Through the investigation of the AMF and ρw′2‾ $\rho \overline{{w}^{\prime 2}}$, we wish to determine in detail the GW characteristics at northern polar latitudes. Furthermore, it is crucial to assess the intermittency as it considerably influences and alters the GW attributes. Our novel results indicate for both AMF and ρw′2‾ $\rho \overline{{w}^{\prime 2}}$: (a) seasonal variation with minima during summer (May–September); (b) higher magnitude in the upper troposphere (<9.00 km) than the lower stratosphere; (c) short-period components (30 min–2 hr, 2–6 hr) are more intermittent in the entire UTLS; and (d) the long-period components (6–13 hr, 13 hr–1 day) demonstrate lower (higher) intermittency in the upper troposphere (lower stratosphere) in summer implying a plausible wave-filtering mechanism.