JGR–Atmospheres

This manuscript investigates the impact of land-surface heterogeneity on atmospheric processes by comparing 92 large-eddy simulation cases over the Southern Great Plains, leveraging high-resolution spatially heterogeneous and homogeneous land-surface fields. Utilizing the HydroBlocks land-surface model for detailed surface data and the Weather Research and Forecasting model for atmospheric simulations, this study emphasizes the significant role land-surface details play in atmospheric dynamics, particularly in cloud formation and boundary-layer development. The analysis focuses on the comparison of turbulent kinetic energy and liquid water path between heterogeneous and homogeneous surface conditions, revealing a strong correlation between surface heterogeneity and enhanced atmospheric activity. Furthermore, the study underscores that the most influential land-surface characteristics on the atmosphere are encapsulated within the largest spatial scales, suggesting a potential simplification for incorporating sub-grid scale land-surface features into global models. The findings advocate for a more formal coupling between the sub-grid land and atmosphere in Earth system models to improve the accuracy of weather and climate predictions, particularly for processes such as cloud formation and boundary-layer dynamics that are sensitive to surface conditions. This work lays foundational insights for future parameterization schemes in global models, highlighting the importance of land-surface details on atmospheric modeling.

Deep tropical oceanic convection (TOC) is a prevailing component of the tropical atmosphere and plays a significant role in modulating global weather and climate. Despite its importance, prediction challenges remain, partly attributed to a lack of understanding of how TOC relates to its near-storm environments. Prior studies suggest location-dependent relationships between TOC structure and associated environments, necessitating targeted regional studies. The NASA 2017 Convective Processes Experiment (CPEX) and 2021 CPEX—Aerosols & Winds (CPEX-AW) field campaigns collected high-resolution measurements of convective storms and their environments in the Gulf of Mexico, Caribbean, and western Atlantic basins, providing a rare opportunity to investigate near-storm environmental relationships with 3-D TOC structure where in situ non-tropical cyclone-related deep TOC research is comparatively lacking. Collocated CPEX and CPEX-AW airborne observations from the multi-wavelength Airborne Precipitation Radar, Doppler Aerosol Wind Lidar, and dropsondes revealed large near-storm environmental variability across TOC of similar convective type (i.e., isolated, organized) and within individual convective systems. However, trends still emerged amongst the large environmental variability. Horizontal TOC structure was most consistently linked to planetary boundary layer and mid-tropospheric near-storm environments, with organized TOC being associated with generally greater relative humidity (RH) and vertical speed shear than isolated TOC. TOC intensity was linked to upper tropospheric (i.e., above melting level) near-storm environments, with isolated TOC intensity most consistently associated with upper tropospheric CAPE and organized TOC intensity associated with upper tropospheric RH. Mesoscale low-level convergence was also linked to greater organized TOC intensity, motivating further research using these unique data sets.

Odhisa, a state of India, bore the disastrous consequences of two consequent Tropical Cyclones (TCs), TC 04B and TC 05B (Odisha 1999 supercyclone), which formed over the Bay of Bengal and experienced landfall in October 1999, with a time gap of fewer than two weeks, over the same region. It is suggested that the first TC, TC 04B, provided an “ocean-like situation” over the coastal land region, thus delivering the appropriate land conditions that would facilitate the intensification of the following second tropical cyclone, TC 05B; a clear illustration of the “Brown Ocean effect.” Two Weather Research Forecasting (WRF) simulations were conducted, with the control and experimental runs differing solely in the following aspect: the initial cyclonic vortex corresponding to the first TC at the initial time was removed in the experimental run, whereas it was retained in the control run. Both simulations were analyzed to reveal the “Brown Ocean Effect” role. The experimental run result indicates that the minimum central sea level pressure of the second TC was 35 hPa higher than the second TC simulation in the control run. The heavy rainfall associated with TC 04B led to increased soil moisture conditions, providing the second TC (TC 05B) with the necessary conditions for its intensification by the “Brown Ocean Effect.” The results of this study appear to strongly suggest that the “Brown Ocean Effect” could provide one of the main reasons for the extraordinary intensities associated with the 1999 Odisha supercyclone.

Ammonia (NH3) from animal feeding operations (AFOs) is an important source of reactive nitrogen in the US, but despite its ramifications for air quality and ecosystem health, its near-source evolution remains understudied. To this end, Phase I of the Transport and Transformation of Ammonia (TRANS2Am) field campaign was conducted in the northeastern Colorado Front Range in summer 2021 and characterized atmospheric composition downwind of AFOs during 10 research flights. Airborne measurements of NH3, nitric acid (HNO3), and a suite of water-soluble aerosol species collected onboard the University of Wyoming King Air research aircraft present an opportunity to investigate the sensitivity of particulate matter (PM) formation to AFO emissions. We couple the observations with thermodynamic modeling to predict the seasonality of ammonium nitrate (NH4NO3) formation. We find that during TRANS2Am northeastern Colorado is consistently in the NH3-rich and HNO3-limited NH4NO3 formation regime. Further investigation using the Extended Aerosol Inorganics Model reveals that summertime temperatures (mean: 23°C) of northeastern Colorado, especially near the surface, inhibit NH4NO3 formation despite high NH3 concentrations (max: ≤114 ppbv). Finally, we model spring/autumn and winter conditions to explore the seasonality of NH4NO3 formation and find that cooler temperatures could support substantially more NH4NO3 formation. Whereas NH4NO3 only exceeds 1 μg m−3 ∼10% of the time in summer, modeled NH4NO3 would exceed 1 μg m−3 61% (88%) of the time in spring/autumn (winter), with a 10°C (20°C) temperature decrease relative to the campaign.

No abstract is available for this article.

Perchlorate in the environment originates from both natural and anthropogenic sources. A previous study of a 300-year Greenland ice core perchlorate record found that anthropogenic impact on environmental perchlorate became significant starting around 1980, while natural formation is the only significant source of environmental perchlorate prior to that. The study also found increased perchlorate deposition in the Arctic following certain volcanic eruptions and suggested that at least some volcanic eruptions could enhance natural perchlorate production. Here we compare the perchlorate record with the volcanic record from sulfate in the same Greenland ice core and find that only stratospheric eruptions—large eruptions injecting volcanic substances directly into the stratosphere—enhance perchlorate production. No contribution to naturally formed perchlorate is detected from non-stratospheric eruptions. The high-resolution ice core perchlorate data are used to quantify contributions from volcanic eruptions, non-volcanic natural processes, as well as from human activities during different periods. For the location in the Arctic in the perchlorate Pre-Anthropogenic Era (1701–1979), the magnitude (0.26 μg m−2 yr−1 on average) of perchlorate produced during sporadic stratospheric eruptions is comparable to that (0.23 μg m−2 yr−1) produced by non-volcanic natural processes. In the Anthropogenic Era (1980–2006), the magnitude of both the volcanic and non-volcanic natural perchlorate production is similar to the enhancement (0.29 μg m−2 yr−1) by human activities.

Previous studies have suggested possible connections between the decreasing Arctic sea-ice and long-duration (>5 days, LD) cold weather events in Eurasia and North America. Here we document the occurrences of weather regimes in winter by their durations, based on the empirical orthogonal function analyses of the daily geopotential height fields at 500 hPa (z500) for the months of November–March 1979–2019. Significant changes in the occurrence frequency and persistence of Ural ridge (UR) and weak stratospheric polar vortex (PV) were found between winters following high and low autumn sea-ice covers (SIC) in the Barents and Kara seas. It is shown that a strengthening of the UR is accompanied with a weakening of the PV, and a weak PV favors Greenland ridge (GR). Cold spells in East Asia persist for 5 more days after an LDUR. Cold spells from Canada to the U.S. occur 2–5 days after an LD Ural trough (UT) and are associated with a z500 anomaly dipole centered over Alaska (+) and Hudson Bay (−). Cold spells in the eastern U.S. occur 1–4 days after an LDGR due to circulations resembling the Pacific-North America pattern. Increased occurrences of UR in winter are associated with a decreased eastward propagation of synoptic waves from the North Atlantic to Japan and the North Pacific.

In this study, the Extreme Hourly Precipitation Areas (EHPAs) of three extreme levels (i.e., between the 95th and 99th percentiles, between the 99th and 99.9th percentiles, beyond the 99.9th percentile) in the Pearl River Delta over South China are identified; then the related events and associated Convective Cores (CCs) are tracked, and their macro-and-microphysical characteristics are analyzed using multi-year dual-polarization radar observations. Results show that >90% of EHPAs are smaller than 10 km2, and 65%–75% of EHPA events last only one hour. They tend to be more localized and persist longer with increasing hourly-precipitation extremity. The EHPAs overlap with the CCs during 50%–64% of the EHPAs' life span. Their occurrence frequencies are nearly quadrupled after the monsoon onset over South China Sea (SCS), with a major (secondary) peak at about 1400 LST (0600 LST) in the diurnal variations. The CCs are non-linear shaped with about 65% being meso-γ-scale and embedded within mostly meso-β or α-scale 20 dBZ regions. The CCs generally contain active warm-rain processes and about 70% possess moderate-to-intense mixed-phase microphysical processes. The ratios of ice water path to liquid water path are about 0.37, and coalescence dominates (about 68%) the liquid-phase processes. The average size of raindrop is slightly larger than the “maritime-like” regime and the average concentration is much higher than the “continental-like” regime. These CCs' characteristics roughly resemble those of the convection producing extreme instantaneous precipitation, except for a larger horizontal scale and less evident variations with the increasing hourly-precipitation extremity.

The question of stratospheric aerosol type following the Raikoke eruption is revisited. Raman lidar measurements suggest the aerosols are predominately smoke, while Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) results indicate the aerosols are predominately sulfate aerosols. The suggested mechanism of smoke particles self-lofting into the stratosphere is inconsistent with observations in 2020, when more severe Siberian fires failed to invoke a response even vaguely similar to 2019. A side-by side comparison of the Sarychev and Raikoke eruptions invalidates model calculations that suggest sulfate aerosols should be at levels too low to explain the observed aerosol loading. Structure in infrared absorption spectra provides conclusive evidence of composition, a unique fingerprint for identifying aerosol type. Such information cannot be misinterpreted so long as there is sufficient resolution and spectral coverage. ACE-FTS infrared aerosol spectra often have an order of magnitude stronger absorption than that of background sulfate aerosols. These spectra can be accurately reproduced by laboratory measured sulfate aerosol spectroscopic information, providing unambiguous identification of the aerosols as sulfate. Visual inspection of thousands of infrared aerosol spectra from the period following the Raikoke eruption indicates the aerosols in the lower stratosphere are predominately sulfate, with no indication of smoke. The lidar study's identification of the aerosols as smoke was based primarily on observed lidar ratios that were more consistent with a material that absorbed significantly at the lidar wavelengths, inconsistent with expectations for sulfate aerosols. However, this could indicate the presence of a substance dissolved in the sulfate aerosols absorbing at those wavelengths rather than smoke particles.

Based on satellite observations in the Arctic stratosphere at latitudes from 61° to 66°N in the second half of 2019, Boone et al. (2022, https://doi.org/10.1029/2022jd036600) provide the impression that the aerosol in the upper troposphere and lower stratosphere (UTLS) over the entire Arctic consisted of sulfate aerosol originating from the Raikoke volcanic eruption in the summer of 2019. Here, we show that this was most probably not the case and the aerosol layering conditions were much more complex. By combining the stratospheric aerosol typing results of Boone et al. (2022, https://doi.org/10.1029/2022jd036600) with lidar observations at 85°–86°N of Ohneiser et al. (2021, https://doi.org/10.5194/acp-21-15783-2021) of a dominating wildfire smoke layer in the UTLS height range, we demonstrate that the Arctic UTLS aerosol most likely consisted of Siberian wildfire smoke in the lower part and sulfate aerosol in the upper part of the aerosol layer which extended from 7 to 19 km height and was well observable until May 2020. The smoke- and sulfate-related aerosol optical thickness (AOT) fractions were about 0.7–0.8 and 0.2–0.3, respectively, according to our analysis. The sulfate AOT is in good agreement with model-based predictions of the Raikoke sulfate AOT.

Fungal aerosols, as significant biocomponents of inhalable particulate matter, encompass a variety of allergens and pathogens. However, comprehensive knowledge regarding their composition, sources, and opportunistic pathogens present in severe air pollution remains limited. In this study, PM2.5 samples were collected from January to March 2018 in a northern Chinese city, during the winter heating and spring sandstorm seasons. The fungal community characteristics within three distinct haze and haze-dust composite pollution were examined. The concentration of fungal aerosols was found to be significantly higher in dust samples. This was evidenced by a strong positive correlation with Ca2+, temperature, and wind speed (p < 0.05). Human and animal pathogens, such as Candida, were more prevalent in haze samples. Conversely, allergens and plant pathogens, like Alternaria, were found in higher concentration in dust samples. The primary ecological function shifted from being saprophytic to becoming human-animal pathogenic or plant-animal pathogenic. This shift was observed from non-pollution, haze, to haze-dust composite pollution. The dispersion of fungal aerosols was influenced by factors such as dust events and meteorological conditions, including increased temperature and wind speed. In the spring dust episodes, dust-related pollutants, such as soil Ca2+ and PM10, accounted for 51.39% of the variation in the fungal community. This research explored the dynamics of fungal communities, potential pathogens, and factors influencing fungal communities in regional air pollution. The insights garnered from this research provide a robust foundation for subsequent human health exposure assessments.

The formation of secondary organic aerosol (SOA) is inextricably linked to the photo-oxidation of aromatic hydrocarbons. However, models still exhibit biases in representing SOA mass and chemical composition. We implemented a box model coupled with a near-explicit photochemical mechanism, the Master Chemical Mechanism (MCMv3.3.1), to simulate a series of chamber studies and assess model biases in simulating SOA from representative monocyclic aromatic hydrocarbons, that is, toluene and three xylene isomers (TX SOA). The box model underpredicted SOA yields of toluene and xylenes by 4.7%–100%, which could be improved by adjusting the saturation vapor pressure (SVP) of their oxidation products. After updating the SVP values, the mass concentration of TX SOA in the Yangtze River Delta region during summer doubled, and there was also an approximate 3% enhancement in the total SOA. Compared to a lumped mechanism used for simulating TX SOA, MCM predicted comparable mass concentrations but exhibited different volatility distributions and oxidation states.

The capabilities of assimilating the all-sky Fengyun-4A Advanced Geostationary Radiation Imager (AGRI) infrared radiances (IR) are completed by including hydrometers in the observation operator, its adjoint, and tangent linear model. This allows the three-dimensional variational data assimilation model to include cloud-precipitation information from infrared IR observations. Advanced as the all-sky data assimilation methodologies are, the assimilation of cloudy scene IR radiances for tropical cyclone (TC) systems has not led to consistently better results, especially for the intensity of TCs. This work explores the effects of all-sky AGRI radiance assimilation on a Super Typhoon In-Fa (2106) during its stage experiencing abnormal changes in the intensity and the track. It is shown that the all-sky assimilation of AGRI two channels 9–10 brings no obviously better TC forecasts than the all-sky AGRI single-channel assimilation does. Besides, the O − B (observation minus background) bias was corrected to be even larger with the variational bias correction method for the pixels with relatively lower or higher cloud impact. This indicates that traditional bias correction schemes with linear fitting functions are suboptimal if the relations between the predictor and O − B biases are non-linear. When the conventional observation and IR radiances are assimilated in two steps, the wind in the inner-core region is better described to properly capture the changes in the typhoon intensity. Generally, the analyses and forecasts of Typhoon In-Fa from experiments with the all-sky IR observations are enhanced compared to those with only the clear-sky IR observations.

Observational evidence has shown that the Earth's tropics have widened since 1980. However, climate models underestimate the observed tropical expansion rate, with a large spread among individual models. The proposal of internal variability to account for model–observation differences is hindered by the limited availability of sufficient realizations from models in the Coupled Model Intercomparison Project (CMIP), restricting the accuracy of quantitative contribution estimation. The emergence of a single model initial-condition large ensemble provides a new opportunity to quantify the role of internal variability. Here, using large-ensemble simulations from two individual models complemented with CMIP Phase 6 (CMIP6) simulations, we show evidence that the recent widening of the tropics is mainly caused by internal variability related to the Interdecadal Pacific Oscillation (IPO). The positive-to-negative phase transition of the IPO from 1980 to 2014 reduced the meridional tropospheric temperature gradient, resulting in poleward shifts in tropical edges. After adjusting the IPO trends simulated by individual realizations to ensure consistency with the observations, the IPO phase transition can account for at least 73% (66%) of the observed tropical expansion rate in the Northern Hemisphere based on the metric of the meridional stream function (surface zonal wind). The IPO is also essential for shaping tropical expansion-related precipitation changes. Our results underscore the significance of considering internal variability when explaining model–observation differences and understanding intermodel uncertainty.

Atmospheric gravity waves (GWs) impact the circulation and variability of the atmosphere. Sub-grid scale GWs, which are too small to be resolved, are parameterized in weather and climate models. However, some models are now available at resolutions at which these waves become resolved and it is important to test whether these models do this correctly. In this study, a GW resolving run of the European Center for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), run with a 1.4 km average grid spacing (TCo7999 resolution), is compared to observations from the Atmospheric Infrared Sounder (AIRS) instrument, on NASA's Aqua satellite, to test how well the model resolves GWs that AIRS can observe. In this analysis, nighttime data are used from the first 10 days of November 2018 over part of Asia and surrounding regions. The IFS run is resampled with AIRS's observational filter using two different methods for comparison. The ECMWF ERA5 reanalysis is also resampled as AIRS, to allow for comparison of how the high resolution IFS run resolves GWs compared to a lower resolution model that uses GW drag parametrizations. Wave properties are found in AIRS and the resampled models using a multi-dimensional S-Transform method. Orographic GWs can be seen in similar locations at similar times in all three data sets. However, wave amplitudes and momentum fluxes in the resampled IFS run are found to be significantly lower than in the observations. This could be a result of horizontal and vertical wavelengths in the IFS run being underestimated.

Pollen can serve as an effective ice-nuclei (IN), altering cloud microphysical and radiative properties, thus precipitation and cloud life cycles. Here, a nationwide pollen emission inventory with a horizontal resolution of 5 km was established based on a parameterization scheme of mass balance of pollen grain fluxes surrounding the plant crowns, and using satellite observational data sets (including leaf area index and fractional vegetation cover) as well as pollen emission rates. The potential emission is then implemented in RegCM-pollen model which treated pollen as aerosol tracers. Besides, pollen-IN parameterization schemes were incorporated in RegCM-pollen to simulate the interactions between pollen and ice clouds. Investigations show that the mean annual pollen emission in China is 2.65 × 107 grains m−2 yr−1, mainly distributed in the south and northeast of China. The IN magnitude is mainly determined by a combination of temperature and pollen concentration. Notably, an increasing number concentration of pollen grains produces opposite effects in Southern China (SC) and Northern China (NC). The weakened upward motion and vertical transport of water vapor in NC made ice clouds hardly form, resulting in cloud forcing (CF) of +0.86 W/m2. In contrast, it generates a CF of −0.84 W/m2 in SC mainly owing to expanded cloud cover. The changes in shortwave radiative forcing is more significant compared to longwave radiative forcing in the two regions. At the surface, the net radiative forcing in NC is +0.74 W/m2, while it is a −0.51 W/m2 in SC. Among them, downward shortwave radiative forcing is approximately twice that of upward longwave radiative forcing in SC and 1.4 times in NC. Surface temperature shows rising over NC, ranging from 0.05 to 0.25 K. In SC, it is primarily decreasing by −0.12 to −0.03 K. The pollen-IN effect also causes a decline of precipitation in NC (−0.17 mm/day) and a rise in SC (0.09 mm/day). Our results suggest that the pollen effect on ice clouds is complex, yet significant in understanding its impact on radiation and climate of the atmosphere.

The eruption of Hunga in January 2022 injected a large amount of water into the stratosphere. Satellite measurements from Aura Microwave Limb Sounder (MLS) show that this water vapor (H2O) has now spread throughout the stratosphere and into the lower mesosphere, resulting in an increase of >1 ppmv throughout most of this region. Measurements from three ground-based Water Vapor Millimeter Wave Spectrometer (WVMS) instruments and MLS are in good agreement, and show that in 2023 there was more H2O in the lower mesosphere than at any time since the WVMS measurements began in the 1990's. At Table Mountain, California all WVMS H2O measurements at 54 km since June 2023, and all of the measurements from Mauna Loa, Hawaii, since the resumption of measurements in September 2023, show larger mixing ratios than any previous measurements. At 70 km several recent WVMS retrievals since September 2023 show the largest anomalies ever measured. The MLS measurements show that maximum H2O anomalies over the 2004–2023 record have occurred throughout almost all of the stratosphere and lower mesosphere since the eruption. As of November 2023, almost all of the ∼140 Tg of water originally injected into the stratosphere by the Hunga eruption remains in the middle atmosphere at pressures below 83 hPa (altitudes above ∼17 km). The eruption occurred during a period when stratospheric H2O was already slightly elevated above the 2004–2021 MLS average, and the November 2023 anomaly of ∼160 Tg represents ∼15% of the total mass of H2O in this region.

This study explores the impact of coupling cumulus and planetary boundary layer (PBL) parameterizations on diurnal precipitation forecasting during the plum rainy season in Jiangsu Province, China, using a double grid-nesting approach. Results show that coherent coupling of cumulus (only in the 15 km grid outer domain [O]) and PBL parameterizations leads to improved forecasting of diurnal variations in the morning, afternoon, and the evening. Increasing the frequency of the Kain-Fritsch (KF) cumulus scheme in [O] enhances subgrid precipitation while reducing grid-scale precipitation, resulting in a more accurate representation of daytime convective activities and a reduction in over-forecasting of evening valley and early-morning precipitation. Additionally, coupling a suitable PBL scheme mitigates the overpredicted afternoon peak by facilitating turbulent mixing to penetrate higher altitudes with a thicker layer, thereby reducing instability energy accumulation. A higher KF frequency in [O] retains less low tropospheric moisture, reducing moisture convergence into the 1 km grid inner domain [I] and decreasing overpredicted daytime precipitation in [I]. Various PBL schemes produce distinct vertical distributions of turbulent moisture and heat transport, impacting convection and precipitation in [I] resolved by cloud microphysics processes. The coherent coupling of these parameterizations maintains a balanced supply of convective energy and water vapor, significantly improving diurnal precipitation forecasts in [I]. Isolating these parameterizations between nested grids may undermine this improvement.

Mass loss of the Greenland Ice Sheet (GrIS) plays a major role in the global sea level rise. The west coast of the GrIS has contributed 1,000 Gt of the 4,488 Gt GrIS mass loss between 2002 and 2021, making it a hotspot for GrIS mass loss. Surface melting is driven by changes in the radiative budget at the surface, which are modulated by clouds. Previous works have shown the impact of North Atlantic transport for influencing cloudiness over the GrIS. Here we used space-based lidar cloud profile observations to show that a polar low circulation promotes the presence of low clouds over the GrIS west coast that warm radiatively the GrIS surface during the melt season. Polar low circulation transports moisture and low clouds from the sea to the west of Greenland up over the GrIS west coast through the melt season. The concomitance of the increasing presence of low cloud in fall over the Baffin Sea due to seasonal sea-ice retreat and a maximum occurrence of Polar low circulation in September results in a maximum of low cloud fraction (∼14% at 2.5 km above sea level) over the GrIS west coast in September. These low clouds warm radiatively the GrIS west coast surface up to 80 W/m2 locally. This warming contributes to an average increase of 10 W/m2 of cloud surface warming in September compared to July on the GrIS west coast. Overall, this study suggests that regional atmospheric processes independent from North Atlantic transport may also influence the GrIS melt.

The Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA's Terra satellite observed the Hunga Tonga—Hunga Ha'apai (HTHH) 15 January eruption plume on eight occasions between 15 and 23 January 2022. From the MISR multi-angle, multi-spectral imagery we retrieve aerosol plume height geometrically, along with plume-level motion vectors, and derive radiometrically constraints on particle effective size, shape, and light-absorption properties. Parts of two downwind aerosol layers were observed in different places and times, one concentrated in the upper troposphere (11–18 km ASL), and a mid-stratosphere layer ∼23–30+ km ASL. After the initial day (1/15), the retrievals identified only spherical, non-light-absorbing particles, typical of volcanic sulfate/water particles. The near-tropopause plume particles show constant, medium-small (several tenths of a micron) effective size over 4 days. The mid-stratosphere particles were consistently smaller, but retrieved effective particle size increased between 1/17 and 1/23, though they might have decreased slightly on 1/22. As a vast amount of water was also injected into the stratosphere by this eruption, models predicted relatively rapid sulfate particle growth from the modest amounts of SO2 gas injected by the eruption to high altitudes along with the water (Zhu et al., 2022, https://doi.org/10.5194/acp-22-10267-2022). MISR observations up to 10 days after the eruption are consistent with these model predictions. The possible decrease in stratospheric particle size after initial growth was likely caused by evaporation, as the plume mixed with drier, ambient air. Particles in the lower-elevation plume observed on 1/15 were larger than all the downwind aerosols and contained significant non-spherical (likely ash) particles.