Journal of Geophysical Research: Atmospheres最新文献

Atmospheric hydrogen peroxide (H₂O₂) is a critical oxidant that influences atmospheric chemistry, playing a pivotal role in the cycling of hydroperoxyl (HO₂) and hydroxyl (OH) radicals, ozone (O₃) formation, and sulfate aerosol production. However, the current understanding of its concentration level, sources and atmospheric effects are still poor. This study investigates the drivers of elevated H₂O₂ concentrations during autumn in Beijing using comprehensive field observations from October to November 2021. The averaged H₂O₂ concentration in the urban boundary layer of Beijing is 0.26 ± 0.03 ppb, peaking at 16:00. By integrating Random Forest Regression and relative incremental reactivity analysis, we systematically examine the influence of meteorological factors, trace gases, and photochemical reactions on H₂O₂ concentrations. The result showed the significant contributions of temperature (T) and photochemical processes to H₂O₂ production, while identifying key inhibitors such as nitrogen monoxide (NO). Additionally, we explore the role of H₂O₂ in sulfate formation during haze pollution episodes, finding that although H₂O₂-mediated oxidation contributes to sulfate production, it is not the dominant pathway during the campaign. These findings underscore the complex interplay between meteorological factors, trace gases, and multiphase reactions in regulating H₂O₂ concentrations and cycling, providing valuable insights into the dynamics of atmospheric oxidation processes and offer guidance for mitigating air quality issues in urban boundary layer.

Mixed-phase clouds modulate the water and energy cycles of high-latitude regions, yet their liquid-ice phase partitioning has long been poorly simulated in climate models. Here, simulations of Arctic mixed-phase clouds by the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) are assessed against large-eddy simulations, satellite data, and ground-based observations during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment field campaign. SCREAM simulates nearly completely frozen clouds, which is attributed largely to the unreasonably strong Wegener–Bergeron–Findeisen (WBF) process that converts liquid to ice excessively and partly to the early over-abundant ice production at cold temperatures from a temperature-deterministic deposition ice nucleation scheme. Assuming no subgrid variation for the WBF process in the original formulation particularly conflicts with the instantaneous saturation adjustment assumption in the condensation scheme that assumes subgrid variability, leading to exaggerated WBF process rates. A proposed simple physically-based improvement on the treatment of subgrid cloud overlap substantially increases supercooled liquid water content and notably improves cloud-top phase partitioning, aligning better with observations. Improvement of supercooled liquid water content also converges with increasing horizontal resolution. The deposition ice nucleation scheme is found responsible for a falsely-produced ice cloud aloft that is not observed, biasing the simulated cloud radiative effects and top-of-atmosphere radiative fluxes. This study identifies key deficiencies in cloud parameterizations that continue to challenge convection-permitting models.

Droughts of different durations affect water resources and ecosystems in distinct ways. Human activities have been confirmed to contribute to the increased occurrence of droughts; however, the dependence of these impacts on the durations of drought, and whether they differ between drylands and humid regions, remains insufficiently understood. This study investigates the human influence on droughts of different durations using the Standardized Precipitation Evapotranspiration Index (SPEI), derived from multi-source observations and four sets of Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model simulations. The results show that human activities cause an intensification of long-term droughts, particularly in drylands. This is primarily attributed to rising greenhouse gas (GHG) emissions, with both GHGs and aerosols exerting stronger impacts on droughts in drylands than in humid regions, though aerosols partly offset the intensifying effect. GHGs contribute to more extreme multi-year droughts over drylands by amplifying temperature-induced water demand, whereas aerosols reduce drought occurrence in drylands by enhancing precipitation, in contrast to their precipitation-suppressing effects in humid areas in the past decades.

Over recent decades, North African dust storms have undergone marked variability, reflecting complex interactions between regional climate processes and environmental change. Using four decades (1984–2023) of visibility-based observational records, we examine regional and seasonal trends in dust storm frequency across the Sahel and the Sahara, capturing their distinct dust dynamics. Results reveal a significant decline in dust activity in both regions, most pronounced during pre-monsoon (MAM) and monsoon (JJA) seasons in the Sahel, and during post-monsoon (SON) and dry season (DJF) in the Sahara. Integrating surface observations with local meteorology (precipitation, surface wind speed, vegetation) and climate indices (AMO, NAO, MEI), we find the Atlantic Multidecadal Oscillation (AMO) as the primary driver, with region-specific effects: in the Sahel, AMO-driven warming and rainfall increase vegetation, suppressing dust; in the Sahara, AMO intensifies the Saharan Heat Low (SHL) and elevates temperatures, modulating dust through atmospheric stability and wind patterns. Local meteorology further differentiates responses, with precipitation and Leaf Area Index (LAI) dominating dust variability in the Sahel, while SHL strength and surface winds are most influential in the Sahara. By explicitly separating the Sahel and Sahara and integrating multiple drivers, this study provides a more spatially resolved understanding of dust–climate link and suggests continued declines in North African dust storm activity under future warming. These findings offer critical constraints for improving dust emission projections in climate models.

We investigate the 1D reflectance distribution of shallow cumulus as a function of cloud size, using high-spatial-resolution observations from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Reflectance transects through clouds are compared between Inner Mongolia and Tropical Ocean. The reflectance shows varying degrees of shadowing–illumination effects, depending on transect direction. Perpendicular to the solar azimuth (cross-sun direction), where shadowing–illumination effects are minimal, the reflectance follows a symmetric, bell-shaped decrease from the cloud center to the cloud edge and into the transition zone or radiative halo. The peak reflectance is located slightly off-center for larger clouds, which can be explained by the competition between radiative smoothing and sharpening. Reflectance steadily increases with cloud size in both regions; however, Inner Mongolia clouds are significantly brighter and have larger cloud top height variations for the same chord length (cloud diameter). The size and height of continental clouds also systematically increase with surface temperature, indicating more vigorous convection over warm, dry land characterized by high Bowen ratio. In the halo region, reflectance increases by 20%–25% above its clear-sky value within one chord length of the cloud edge, the brightness enhancement showing little variation with cloud size. The chord-length normalized size of the halo steadily decreases with cloud size, as the absolute halo size does not scale linearly with cloud size. This observation, consistent with large-eddy simulations of the moist buffer around shallow cumulus, suggests that the processes responsible for halo formation have size-independent length scales.

Climate change exacerbates hydroclimatic extremes, yet predicting risks for vulnerable Indo-Pacific populations remains limited by overlooked storm-climate linkages. The Indian Ocean dipole (IOD) and El Niño-Southern Oscillation (ENSO) govern regional droughts, floods, and heat waves. While IOD and ENSO typically synchronize (e.g., positive IOD with El Niño), several positive IODs (pIODs) occur independently or even cooccur with La Niña—events that defy conventional modes and trigger mismatches in forecasts. Current theories predominantly attribute this phase mismatch phenomenon to internal forcing within the Indian Ocean, lacking robust identification of external forcing mechanisms—a critical gap that undermines the reliability of predictive frameworks. Here, we show that active western North Pacific (WNP) tropical cyclones (TCs) induce maritime continent subsidence, triggering anomalous easterly winds and sea surface cooling in the eastern tropical Indian Ocean, thus generating independent pIODs. Our findings identify a critical external forcing mechanism for the ENSO-IOD phase discrepancy, filling a pivotal knowledge gap in current theoretical frameworks. By quantifying TCs' role as synoptic-scale triggers of interannual extremes, we provide a basis for disaster agencies to integrate real-time TC activity into early warning systems.

The collection of dust aerosols (0.1–10 $��\mu �$m) by near-surface obstacles is one of the important processes in atmospheric aerosol dry deposition. However, existing understanding of this process remains limited. For example, most current deposition models assume complete deposition or describe the collection process through empirical models, making it difficult to accurately predict the concentration distribution of dust particles within the near-surface collection layer. In this study, the effects of turbulence around obstacles are considered to improve an existing numerical model for simulating aerosol particle deposition in rough surface environments. The modified numerical model is validated through wind tunnel experiments. Subsequently, the particle collection process on an isolated cylindrical obstacle placed on the ground is investigated using numerical simulations. The effects of different wind conditions, particle properties, and obstacle sizes on the collection process are analyzed. Finally, a fitted relationship between the Stokes number and collection efficiency is proposed. The results show that inertial impaction and interception jointly dominate particle deposition on the windward side of the isolated obstacle, while turbulence-induced impaction governs deposition on the leeward side. Therefore, parameters that affect particle inertia and the turbulent flow around the obstacle have a more significant impact on the particle deposition process. The simulation results agree well with existing experimental data and exhibit lower data dispersion, demonstrating that the numerical model developed in this study can effectively describe the collection of particles by near-surface obstacles. This provides a solid basis for improving atmospheric particle deposition models.

Accurate representation of CO₂ transport is important for reliable flux inversions with global inversion systems. Previous studies have revealed systematic discrepancies between two widely used global transport models, GEOS-Chem and TM5, in simulated CO₂ distributions at mid-latitudes. However, the causes of these discrepancies and potential transport biases in the models remain unclear without constraints of intensive measurements. Here, we drive GEOS-Chem and TM5 with identical surface CO₂ fluxes and perform simulations with and without parameterized convection. By comparing the simulated spatial-temporal distributions of [CO₂] to intensive aircraft and tower measurements collected by the Atmospheric Carbon Transport (ACT)-America project and NOAA's airborne profiling and tower networks across four seasons, we identify potential transport biases in both models over North America. Model discrepancies in vertical transport produce seasonal-mean planetary boundary layer (PBL)–free-troposphere [CO₂] differences of up to ∼4 ppm and PBL height differences of ∼100–400 m. In summer, GEOS-Chem underestimates transport through moist convection but overestimates PBL mixing depth, whereas TM5 exhibits more realistic total vertical mixing (moist convection and PBL depth). In spring and winter, TM5 underestimates PBL mixing while potentially overestimating mixing through moist convection, whereas GEOS-Chem more accurately represents vertical mixing. These transport biases are likely to contribute to discrepancies in the meridional gradient of zonal-mean [CO₂] and propagate into differences in posterior flux estimates from the OCO-2 Model Intercomparison Project inversions using the two transport models over North America. Expanded vertically resolved [CO₂] measurements beyond North America can further advance the current understanding of transport uncertainties at larger spatial scales.

This sequel study continues to develop a strategic framework for the global Planetary Boundary Layer Height (PBLH) analysis and monitoring using the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System (GEOS) data assimilation (DA) system. The framework supports the assessment of PBLH from multiple observing systems, including radiosonde, Global Navigation Satellite System-Radio Occultation (GNSS-RO), spaceborne lidars: Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Cloud-Aerosol Transport System (CATS), ground-based lidar: NASA Micro-Pulse Lidar Network (MPLNET), and ground-based radar: networks of radar wind profilers (GRWP), using either consistent or inconsistent PBLH definitions from the GEOS model. A comprehensive evaluation over a 27-day period (23 August –18 September 2015) is performed to quantify the PBLH Observation minus Forecast bias and Root Mean Square Deviation across data types. Although radiosonde, GNSS-RO, and GRWP PBLH are assessed using consistent model definitions, lidar-based PBLH is compared using inconsistent ones due to current model limitations. The results underscore the importance of using physically and instrumentally consistent model PBLH with corresponding PBLH observations. They further demonstrate that robust quality control and thinning procedures tailored to each observation type are critical, particularly when model definition and PBLH observations are inconsistent. The results also highlight notable discrepancies among two space-based lidar PBLH data sets, especially over the ocean, which the implementation of corresponding lidar-based model PBLH and advanced PBLH retrieval algorithms are expected to reduce. The developed framework enables a robust evaluation of current and future PBLH data sets and serves as a foundation for an effective assimilation strategy.

Temperature and air humidity are critical environmental factors regulating photosynthesis and biogenic volatile organic compound (BVOC) emissions from plants, which influence air quality and climate change. While previous research has demonstrated the impacts of temperature on photosynthesis and BVOCs, the effects of humidity and the combined effects of temperature and humidity remain understudied. Here we discuss the discrete and synergistic impacts of temperature and humidity on ponderosa pine trees. We used a portable photosynthesis system coupled to a proton-transfer-reaction mass spectrometer to quantify leaf-level changes in photosynthesis, stomatal conductance, and emissions as a function of both temperature and humidity. Results demonstrate that all BVOC emissions investigated increased with temperature, regardless of humidity, in agreement with literature. To our knowledge, we present the first direct observation of temperature-dependent methyl vinyl ketone and methacrolein emissions from ponderosa pines. We find that elevated humidity enhances the baseline emissions of many BVOCs. Increasing relative humidity from 30% to 50% resulted in basal emission rates increasing between 1.7-fold for sesquiterpenes and 2.9-fold for 2-methyl-3-buten-2-ol. Our results may help explain field observations where BVOC emissions are decoupled from temperature under some conditions, and we clearly illustrate the need for further investigations on BVOC humidity sensitivity over larger (e.g., ecosystem) scales and on other plant species to improve chemical transport model predictions.