Journal of Geophysical Research: Atmospheres最新文献

Black carbon (BC) from maritime emissions plays a critical role by influencing radiation, cloud processes, and atmospheric dynamics in the marine atmosphere. These impacts depend on BC concentration and mixing state with other aerosol components. However, in situ observations of BC over oceans remain scarce, and the influence of the marine environment on the evolution of BC mixing state is not well understood. Here, we present shipborne measurements aboard the research sailing yacht S/Y Eugen Seibold during 10 Atlantic Ocean cruises. The data set spans 1,120 of measurement hours from near-coastal regions to remote ocean areas. In oceanic regions extending from tens to thousands of kilometers offshore, 1-min averaged BC concentrations were typically around 100 ng m⁻³, suggesting a well-mixed marine background. Despite the relatively small variability in BC mass concentrations, the mixing state of BC exhibits substantial differences between nearshore and remote oceanic regions. High number fractions (>50%) of BC particles without core-shell morphologies, characterized by BC externally attached to non-BC materials, were observed in near-coastal regions and decreased to ∼20% in remote oceanic regions. In ship-impacted regions, small freshly emitted BC particles tend to coagulate with other aerosol particles and forming non-core-shell attached structures, while high relative humidity (RH > 85%) tends to promote the formation of thick coatings. Our results provide new insights into climate-relevant properties and underscore the importance of coagulation and hygroscopic processing for the mixing state of BC in the marine atmosphere.

Air pollution in India is complex due to the multitude of sources and varying topography, rendering the interplay between meteorology and emission sources significant. To address this challenge, this work presents an integrated methodology for PM_2.5 source apportionment in Bhopal, central India, combining dispersion-normalized positive matrix factorization (DN-PMF) with a machine-learning interpretability approach using Random Forest and SHAP (RF-SHAP). DN-PMF improves conventional source identification by incorporating air dilution effects, yielding refined source contributions for nine factors in Bhopal. Seasonal factor contributions peaked during periods with a lower boundary layer height, such as secondary sulfate during the winter season (21.3 μg m⁻³, 31.7%). The COVID-19 lockdowns, a quasi-natural emissions reduction experiment, led to a decrease in aerosol contributions from industrial, residential and traffic-related sources. However, during this period, crop residue burning was exposed as a major anthropogenic contributor, which together with unfavorable meteorology resulted in increased mean PM_2.5 (50.6 ± 24.3 μg m⁻³) during the lockdowns compared to the reference period (36.7 ± 9.7 μg m⁻³). Using RF-SHAP the influence of meteorology and emission sources in driving secondary inorganic aerosol formation was examined. Secondary nitrate and residential fuel were identified as key contributors to exceedances of the Indian National Ambient Air Quality Standards (60 μg m⁻³, 24-hr average) at the study site. Integrating DN-PMF with RF-SHAP (driver analysis) enhanced source attribution by linking source contributions with their driving factors, establishing a framework for assessing pollution dynamics. This framework can help strengthen improved air quality initiatives in India, including the national Smart Cities Mission.

Abnormally elevated ozone (O₃) is observed during compound heatwave and drought (CHWD), posing severe environmental and socioeconomic threats. Response of O₃ to CHWD is complicated by the vegetation-atmosphere feedbacks through influencing biogenic emissions and stomatal deposition. Here, we employed a regional meteorology-chemistry-vegetation coupled model, integrated with optimized drought emission algorithm and interactive dry deposition scheme, to investigate the vegetation-atmosphere feedbacks and their effects on O₃ pollution during CHWD. Analysis shows that CHWD have intensified in the northern hemisphere, with more frequent occurrence, stronger intensity and longer duration compared to the average climatology. Unusually elevated O₃ levels and exceedance frequency by more than 20% compared to normal conditions were observed during CHWD in the United States, western Europe and China. Model results indicate that heatwaves and droughts jointly lead to 10%–24% increase of summertime biogenic volatile organic compound emissions in vegetated regions, except in the severely drought-affected areas. Furthermore, extremely hot and dry conditions induce stomatal closure and suppress plant growth, inhibiting O₃ stomatal removal by water-stressed vegetation. It is estimated that such intricate vegetation-atmosphere feedbacks substantially exacerbate O₃ pollution during CHWD, with equal importance to that of increased photochemical rates. Our findings offer a novel perspective on the interactions between climate, vegetation, and chemistry regarding compound extreme weather events.

Ice cores from Mt. Logan, the second highest peak in North America located in the St. Elias mountains in southwest Yukon, Canada, have provided conflicting accumulation records, thus the hydroclimate response to changing atmospheric conditions in the highest elevation regions is not well constrained. Here, we present the accumulation record from the new 325 m Mt. Logan ice core drilled at 5,334 m asl on the summit plateau in May 2022. Multi-parameter annual layer counting, confirmed with radionuclide and volcanic tephra measurements, extends to 1911 CE, associated with a depth of 257 m. The thinning-corrected annual accumulation record reveals an average rate of 3.0 m water equivalent per year (m weq a⁻¹) from 1912 to 2020 CE, greater than six times higher than the previous estimate of ∼0.41 m weq a⁻¹ from the 2002 Mt. Logan Prospector Russell Col core. Correlation analysis between the annual accumulation record and regional climate data sets (e.g., Japanese 55-year Reanalysis, weather stations) reveal a strong positive relationship with warm-season total precipitable water and temperature. Thus, we suggest interdecadal precipitation variability on Mt. Logan is at least partially driven by warm-season atmospheric water vapor loading, potentially related to atmospheric temperature responses associated with the warm-season Alaska Blocking Index. Further, the record reveals a statistically significant increase in accumulation of 0.13 m weq per decade since 1970. These results reveal a drastically different Mt. Logan ice core record and provide a new warm-season perspective on drivers of high-elevation accumulation variability in the North Pacific.

Katabatic storms in southeastern Greenland are fierce, density-driven, downslope wind events with substantial implications for the local and downstream weather conditions and climate. This study presents a detailed assessment of their representation across three generations of global reanalysis products (ERA5, ERA-Interim, and ERA40) from the European Centre for Medium-Range Weather Forecasts, paired with a hierarchy of simulations at different grid resolutions with the Community Earth System Model version 2 (CESM2). Using the high-resolution (2.5-km resolution) Copernicus Arctic Regional Reanalysis (CARRA) as a benchmark, we find that the global reanalysis data sets systematically underestimate wind speeds (around 30% in ERA5 and 50% in ERA-Interim and ERA40) and fail to capture key structural features of these regional storms. Similar deficiencies are observed in CESM2 simulations when using standard latitude-longitude grids at 1–2$��°�$ horizontal resolutions, which is a common model configuration used in recent iterations of the Coupled Model Intercomparison Projects. Variable-resolution configurations in CESM2 with enhanced representation of the Greenland topography demonstrate a marked improvement in capturing the strength and structure of these regional storms. Sensitivity simulations further confirm that steeper ice-sheet margins (better resolved at higher spatial resolution) are crucial for accurately representing katabatic acceleration. These findings underscore the importance of spatial resolution and realistic topographic representation in simulating local climate extremes. Accurately capturing such events is vital not only for understanding modern climate dynamics on and around the polar ice sheets, but likely also for simulating realistic ice sheet/Earth system interactions in glacial climates of the past.

Launched in April 2023, the Tropospheric Emissions: Monitoring of Pollution (TEMPO), instrument provides for the first time hourly measurements of atmospheric pollutants over most of North America at high spatial resolution (∼2 × 4.75 km²). This evaluation of TEMPO's first year demonstrates the capability of total formaldehyde column retrievals (ΩHCHO, version 3) at different locations, seasons, and meteorological conditions. The ΩHCHO product is assessed using 36 ground-based Pandora direct-sun measurements from Pandonia Global Network (PGN) as a reference data set. The 36 PGN sites were chosen for consistency in direct-sun and sky-scan measurement modes. In the first year of operation (Aug 2023–Sep 2024), TEMPO ΩHCHO exhibits moderate to strong agreement at PGN sites in both measurement modes (R² = 0.63 to 0.85). TEMPO shows a negligible bias of −2 ± 20% at lower ΩHCHO (<1.0 × 10¹⁶ molecule cm⁻²) and a larger underestimation of −22 ± 5% at higher ΩHCHO (>1.5 × 10¹⁶ molecule cm⁻²). TEMPO clearly captures the seasonal variability of ΩHCHO, with summer values being greatest and winter, spring, and fall values being lower by − 62%, − 45%, and − 29%, respectively. TEMPO shows no consistent bias at any time of day with excellent agreement with Pandora for different meteorological conditions. For all hourly differences between TEMPO and Pandora, 96% fall within 1 × 10¹⁶ molecules cm⁻². TEMPO provides almost 50% more days with at least one observation compared to observations taken only at 1 p.m., from typical polar-orbiting satellites. These findings confirm the high quality of TEMPO's ΩHCHO measurements under a wide variety of conditions and show great promise for future scientific applications.

The subtropical westerly jet (SWJ), a fundamental element of the midlatitude atmospheric circulation that greatly impacts global weather and climate, exhibits multiple centers with relatively high wind speed on the hemispheric scale. It manifests pronounced spatial heterogeneity when these jet centers experience asynchronous variations. However, previous researches about this heterogeneity are still limited. This study examines the long-term variability of the spatial heterogeneity of SWJ during boreal summer (July–August) over recent 40 years, particular for the decadal changes. Three centers with high wind speed along SWJ, respectively located over Atlantic, West Asia and East Asia (short for ATJ, WAJ and EAJ) exhibit marked spatial heterogeneity in their temporal evolution. Both of ATJ and WAJ demonstrate the equatorward shifts, while EAJ shows poleward shift. This zonal heterogeneity is particularly pronounced on the decadal time scale, with all three centers have phase transitions in their meridional displacements around 1998. The decadal changes in the atmospheric circulation before and after 1998 encompass the circulation anomalies caused by the individual meridional displacements of the three jet centers. Meanwhile, the combined circulation anomalies caused by these jet centers closely match the decadal change of the atmospheric circulation. This provides compelling evidence for a strong dynamical connection between the atmospheric circulation and the heterogeneous variation of SWJ. The phase transitions of the Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation, combined with the rapid retreat of Arctic sea ice, influence the decadal changes in the spatial heterogeneity of SWJ by modulating the meridional temperature gradient.

Atmospheric rivers (ARs) are long bands of strong horizontal water vapor transport responsible for over 90% of total integrated vapor transport (IVT) in extratropical and polar regions. Using a 12-year record (2010–2022) of ground-based remote sensing, radiosonde, snow stake, and reanalysis data from Summit Station, Greenland, we quantify the impacts of 41 AR events on snowfall, clouds, and the atmospheric state. Although ARs occur 0.97% of all times and 2.68% of snowing times, they contribute 5.8% to total snowfall, enhance snowfall rates by 80%, and double daily snowfall accumulation relative to general snowing conditions. AR events increase near-surface and atmospheric profile temperatures by over 7°C up to 350 hPa and increase specific humidity by 66%, deepen clouds and increase radar reflectivity. While ARs contribute only a modest fraction to total accumulation in central Greenland, they consistently produce clouds and snowfall and create an environment that enables enhanced snow particle growth processes typically not observed in an area characterized by cold, dry conditions.

Ammonia (NH₃) is an important alkaline gas, mainly emitted from agricultural activities, playing an important role in global nitrogen cycle and surface ecosystems. Chemical transport models and emission inventories are widely used to study the emission, transport, and chemical transformation of NH₃. However, traditional static inventories consider emissions as unidirectional, overlooking interactions between NH₃ emissions and other ecosystems, especially land surface processes linked to emissions. In this study, we achieved bidirectional NH₃ exchange between land surface and atmospheric chemistry models by developing WRF-CN-Chem, a model integrating the Noah-MP land surface model with carbon-nitrogen dynamics (Noah-MP-CN) and the Weather Research and Forecasting model with atmospheric chemistry (WRF-Chem). Compared with the static Multi-resolution Emission Inventory for China, the dynamic bidirectional model exhibits higher spatiotemporal resolution and demonstrated a stronger temporal correlation with satellite observations. WRF-CN-Chem model estimated 7.88 TgN NH₃ emission in year 2020 in eastern China. Additionally, we incorporated the atmospheric nitrogen deposition, simulated by the “Online” experiment, into the soil ammonium pool. Our findings revealed an increase of 2.25 TgC yr⁻¹ in land net primary productivity (NPP) in eastern China attributable to the increased nitrogen deposition. By incorporating bidirectional NH₃ exchange between land surface and atmosphere chemistry models, this study enhances the simulation of dynamic ammonia emissions and improves understanding of atmospheric nitrogen deposition processes. Furthermore, linking these processes to land NPP provides valuable insights for sustainable land management and pollution mitigation strategies, helping address the environmental impacts of excessive fertilization.

Floods often cause substantial losses worldwide, and skillful flood predictions are critical to water management and disaster relief. However, the overlooking of surface water flow in the land surface models (LSMs) leads to the defect of flood simulation and prediction. In this study, a quasi-3D LSM, incorporated with the overland flow, has been driven by downscaled numerical weather prediction (NWP) to establish a high-resolution flood prediction system. Compared to the Sentinel-1 imagery, the quasi-3D LSM reasonably depicts the distributions of deluged regions and surface runoff for an unprecedented flood event over North China in July-August 2023. The surface lateral flow redistributes soil moisture, resulting in wetter valleys and drier ridgelines. In addition, the results show that the downscaled precipitation prediction is skillful at a lead time of 3.5 days, while the reliable flood prediction can be expected with a lead time of up to 6 days, especially in low-lying regions. Our work highlights that reliable flood prediction can be achieved through integrating the high-resolution quasi-3D LSM and the NWP, which is crucial for disaster prevention and reduction.