JGR–Atmospheres

Utilizing the Open Integrated Forecasting System, the responses of Ural blocking (UB) to different stratospheric warming scenarios are investigated. Numerical results show that stratospheric warming with moderate strength in minor patterns prolongs the UB duration and enhances its intensity, while strong stratospheric warming in minor patterns tends to shorten its duration and weaken its intensity, even leading to the collapse of the UB events. Further diagnosis reveals that the planetary wave activity flux propagates downward from the stratosphere to the troposphere after stratospheric warming. Moreover, the convergence of planetary wave activity flux is a key factor for UB enhancement and maintenance. In addition, the weakened meridional temperature gradients, decelerated zonal westerly winds, and a reduced meridional potential vorticity gradient (PVy) result in UB enhancement in response to stratospheric warming with moderate strength. As stratospheric warming strengthens, planetary wave activity flux diverges, westerly winds in the tropospheric mid-latitudes accelerate and the PVy in the Ural sector enlarges, which further weakens UB. Regarding the stratospheric perturbations in major patterns, they have similar influences on UB events, that is, UB enhances with moderate stratospheric warming and weakens with strong warming. However, the strengthened warming would trigger UB re-enhancement, which is closely associated with anomalous activities of tropospheric synoptic-scale waves induced by stratospheric perturbations. These results reveal UB events respond differently to stratospheric warming with various intensities and patterns in the short term, which makes a contribution to understanding stratosphere-troposphere coupling.

Nonlinearities and asymmetries of El Niño Southern Oscillation (ENSO) stratospheric pathway to the North Atlantic and Europe are examined in large ensembles conducted with fully coupled climate models during wintertime. The analysis is centered on historical experiments of the Max Planck Institute Grand Ensemble (MPI-GE, 95 members) and expanded to six other ensembles of more limited size. In MPI-GE, significant responses are obtained for each ENSO phase and three different intensities (weak, moderate and strong). Overall, linear relationships are found for either El Niño or La Niña key diagnostics that characterize the pathway. These relationships are generally weaker for the cold La Niña than for the warm El Niño so that asymmetries between them develop as the events intensify. Specifically for strong events, the extra-tropical North Pacific and stratospheric responses are asymmetric, with larger responses for El Niño. In addition, the stratospheric asymmetry in strong events seems to contribute to the asymmetry in strong events in the North Atlantic—Europe response in the troposphere in late winter. The extra-tropical North Pacific response shows general agreement between MPI-GE and the other large ensembles. However, this agreement is not as large when other parts of the pathway are compared. Relatively high inter-model response spread confirms the typical model uncertainty found when examining atmospheric circulation responses which include the stratosphere in state-of-the-art climate models.

Because of the potential similarities of the climate in the mid-Pliocene to the projected conditions in the near future, studying mid-Pliocene dryland aridity can advance our future projections. In this study, we used climate modeling to investigate mid-Pliocene dryland aridity. Our results indicated that, in the mid-Pliocene compared to the preindustrial period, the simulated dryland was substantially less arid in North Africa, the Arabian Peninsula, Australia and Central Asia and more arid in North and South America and Southern Africa. The combined topography, vegetation and lakes (TVL) and atmospheric CO2 concentrations markedly modified this large-scale dryland aridity, mainly by modulating precipitation and potential evapotranspiration, respectively. Moreover, the dryland aridity during the mid-Pliocene varied under different orbital parameter intervals, mainly through precipitation changes. Our results show the important effect of vegetation on dryland aridity in a previous warm period and imply the potential effect of vegetation on future dryland aridity.

Aerosols play a key role in polar climate, and are affected by long-range transport from the mid-latitudes, both in the Arctic and Antarctic. This work investigates poleward extreme transport events of aerosols, referred to as polar aerosol atmospheric rivers (p-AAR), leveraging the concept of atmospheric rivers (AR) which signal extreme transport of moisture. Using reanalysis data, we build a detection catalog of p-AARs for black carbon, dust, sea salt and organic carbon aerosols, for the period 1980–2022. First, we describe the detection algorithm, discuss its sensitivity, and evaluate its validity. Then, we present several extreme transport case studies, in the Arctic and in the Antarctic, illustrating the complementarity between ARs and p-AARs. Despite similarities in transport pathways during co-occurring AR/p-AAR events, vertical profiles differ depending on the species, and large-scale transport patterns show that moisture and aerosols do not necessarily originate from the same areas. The complementarity between AR and p-AAR is also evidenced by their long-term characteristics in terms of spatial distribution, seasonality and trends. p-AAR detection, as a complement to AR, can have several important applications for better understanding polar climate and its connections to the mid-latitudes.

Arctic clouds are sensitive to atmospheric particles since these are sometimes in such low concentrations that clouds cannot always form under supersaturated water vapor conditions. This is especially true in the late summer, when aerosol concentrations are generally very low in the high Arctic. The environment changes rapidly around freeze-up as the open waters close and snow starts accumulating on ice. We investigated droplet formation during eight significant fog events in the central Arctic Ocean, north of 80°, from August 12 to 19 September 2018 during the Arctic Ocean 2018 expedition onboard the icebreaker Oden. Calculated hygroscopicity parameters (κ) for the entire study were very high (up to κ = 0.85 ± 0.13), notably after freeze-up, suggesting that atmospheric particles were very cloud condensation nuclei (CCN)-active. At least one of the events showed that surface clouds were able to form and persist for at least a couple hours at aerosol concentrations less than 10 cm−3, which was previously suggested to be the minimum for cloud formation. Among these events that were considered limited in CCN, effective radii were generally larger than in the high CCN cases. In some of the fog events, droplet residuals particles did not reactivate under supersaturations up to 0.95%, suggesting either in-droplet reactions decreased hygroscopicity, or an ambient supersaturation above 1%. These results provide insight into droplet formation during the clean late-summer and fall of the high Arctic with limited influence from continental sources.

Volcanic ash clouds are carefully monitored as they present a significant hazard to humans and aircraft. The primary tool for forecasting the transport of ash from a volcano is dispersion modeling. These models make a number of assumptions about the size, sphericity and density of the ash particles. Few studies have measured the density of ash particles or explored the impact that the assumption of ash density might have on the settling dynamics of ash particles. In this paper, the raw apparent density of 23 samples taken from 15 volcanoes are measured with gas pycnometry, and a negative linear relationship is found between the density and the silica content. For the basaltic ash samples, densities were measured for different particle sizes, showing that the density is approximately constant for particles smaller than 100 μm, beyond which it decreases with size. While this supports the current dispersion model used by the London Volcanic Ash Advisory Centre (VAAC), where the density is held at a constant (2.3 g cm−3), inputting the measured densities into a numerical simulation of settling velocity reveals a primary effect from the silica content changing this constant. The VAAC density overestimates ash removal times by up to 18%. These density variations, including those varying with size beyond 100 μm, also impact short-range particle-size distribution measurements and satellite retrievals of ash.

We investigate the benefit of assimilating high spatial-temporal resolution nitrogen dioxide (NO2) measurements from a geostationary (GEO) instrument such as Tropospheric Emissions: Monitoring of Pollution (TEMPO) versus a low-earth orbit (LEO) platform like TROPOspheric Monitoring Instrument (TROPOMI) on the inverse modeling of nitrogen oxides (NOx) emissions. We generated synthetic TEMPO and TROPOMI NO2 measurements based on emissions from the COVID-19 lockdown period. Starting with emissions levels prior to the lockdown, we use the Weather Research and Forecasting Model coupled with Chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) to assimilate these pseudo-observations in Observing System Simulation Experiments to adjust NOx emissions and quantify how well the assimilation of TEMPO versus TROPOMI measurements recovers the lockdown-induced emissions changes. We find that NOx emission biases can be ameliorated using half as many simulation days when assimilating GEO observations, and the estimated NOx emissions in 23 out of 29 major urban regions in the US are more accurate. The root mean square error and coefficient of determination of posterior NOx emissions are reduced by 12.5%–41.5% and 1.5%–17.1%, respectively, across different regions. We conduct sensitivity experiments that use different data assimilation (DA) configurations to assimilate synthetic GEO observations. Results demonstrate that the temporal width of the DA window introduces −10% to −20% biases in the emissions inversion and constraining both NOx concentrations and emissions simultaneously yields the most accurate NOx emissions estimates. Our work serves as a valuable reference on how to appropriately assimilate GEO observations for constraining NOx emissions in future studies.

Poor air quality is often experienced in densely populated areas located alongside large rivers. The presence of a river valley can modify local meteorology, potentially interfering with the formation of air pollutants such as PM2.5. However, the mechanisms behind PM2.5 formation in river valleys and its impacts on surrounding regions remain poorly understood. This study investigates the formation mechanisms of PM2.5 in the Nanjing reach of the Yangtze River, considering its complex terrain and anthropogenic emissions, through numerical simulation. Simulated results revealed higher PM2.5 concentrations along the Yangtze River compared to the average concentrations in Nanjing, primarily driven by elevated nitrate level. Factors such as higher humidity, wind speed, ageostrophic wind field, and shallow boundary layer were identified as key contributors to the increased PM2.5 concentrations along the river. Our study demonstrates significant impact of local thermal circulations on PM2.5 formation, resulting from the interaction between the large water body of the Yangtze River and the urban area. This phenomenon was confirmed through sensitivity experiments, which showed attenuated local thermal circulations in the absence of the Yangtze River. Source apportionment and process analysis results confirm the dominant roles of local thermal circulation related horizontal and vertical advections, with diurnal fluctuations, in shaping PM2.5 variations along the river. Inorganic chemistry processes also played a non-negligible role, particularly during polluted conditions. Local thermal circulations in river valleys are crucial for PM2.5 formation, highlighting the need for comprehensive strategies to tackle air pollution in similar regions.

Supercooled liquid clouds are ubiquitous over the Southern Ocean (SO), even to temperatures below −20°C, and comprise a large fraction of the marine boundary layer (MBL) clouds. Earth system models and reanalysis products have struggled to reproduce the observed cloud phase distribution and occurrence of cloud ice in the region. Recent simulations found the microphysical representation of ice nucleation and growth has a large impact on these properties, however, measurements of SO ice nucleating particles (INPs) to validate simulations are sparse. This study presents measurements of INPs from simultaneous aircraft and ship campaigns conducted over the SO in austral summer 2018, which include the first in situ observations in and above cloud in the region. Our results confirm recent observations that INP concentrations are uniformly lower than measurements made in the late 1960s. While INP concentrations below and above cloud are similar, higher ice nucleation efficiency above cloud supports model simulations that the dominant INP composition varies with height. Model parameterizations based solely on aerosol properties capture the mean relationship between INP concentration and temperature but not the observed variability, which is likely related to the only modest correlations observed between INPs and environmental or aerosol metrics. Including wind speed in addition to activation temperature in a marine INP parameterization reduces bias but does not explain the large range of observed INP concentrations. Direct and indirect inference of marine INP size suggests MBL INPs, at least during Austral summer, are dominated by particles with diameters smaller than 500 nm.

We observed two Terrestrial Gamma-ray Flashes (TGFs) in Uchinada, Japan associated with negative cloud-to-ground lightning strokes exactly 1 year apart on 18 December 2020 and 2021. The events were remarkable for their lateral distance from the associated strokes—each about 5 km away from the detector site. Not only was that lateral distance remarkable on its own for a ground based detection, but the low-altitude profile of winter thunderstorms in Japan would suggest the detections occurred at unprecedented nadir angles—73.3° off axis for the 2020 event with the standard assumption of a vertically oriented TGF. Unsurprisingly, Monte Carlo simulations of the straightforward interpretation of these events yield fluences 2 orders of magnitude lower than observed data. We investigate a variety of ways to attempt to resolve the contradiction between expected and observed behavior.