Stratosphere-troposphere exchange (STE) plays a crucial role in Earth's climate; however, the significance of small-scale processes such as midlatitude convection to global STE remains understudied. Midlatitude tropopause-overshooting convection is especially important to climate because it can enhance stratospheric water vapor, which has its greatest radiative forcing sensitivity in the extratropical lower stratosphere. Thus, it is essential to understand what factors influence the strength and prevalence of overshooting storms and associated STE. The U.S. Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign during 2021 and 2022 was the first large-scale airborne primarily focused on sampling stratospheric impacts from overshooting convection. Our research utilizes the extensive DCOTSS data set in combination with radar, satellite, and environmental observations to investigate relationships between observed stratosphere composition change and storm and environmental characteristics. Our results demonstrate greater magnitudes of STE for above-anvil cirrus plume (AACP)-producing storms and mesoscale convective systems (MCSs). In addition, the most extreme enhancements in water vapor and other tropospheric gases occur where the tropopause height is low and the depth of overshooting is high, especially for AACP-producing storms. We also investigate the impact of storm and environmental characteristics on pathways for hydration (air mass transport and mixing vs. ice sublimation), finding that they also modulate the frequencies of each process at different altitudes. Namely, mixing is found to be most prevalent in AACP-producing storms and MCSs, which can help explain transport differences between water vapor and other gases.

Overshooting storms are convective systems with updrafts that penetrate through the tropopause into the overlying stratosphere. These storms can rapidly transport a wide variety of chemical species and aerosols from the boundary layer and free troposphere directly to the stratosphere. The central plains of the U.S. and the Sierra Madre Occidental of Mexico are two of the global hotspots for overshooting convection. While the existence of these storms has been known for several decades, the amount of tropospheric air, including water vapor, trace gases, and aerosols, transported across the tropopause is poorly understood, as is their impact on the dynamics, chemistry, and radiative balance of the stratosphere. Climate models suggest that as Earth’s climate continues to warm, overshooting convection over the U.S. may increase, potentially causing changes to stratospheric composition and transport. To address these scientific questions, the NASA ER-2 high-altitude research aircraft flew 31 missions during the summers of 2021 and 2022 to make observations of the outflow from overshooting storms in the stratosphere over North America and the eastern Pacific Ocean as part of the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) project. The ER-2 carried a payload of 12 instruments to measure meteorological parameters, water and its isotopologues, trace gases, and aerosol properties. Ozone, water vapor, and aerosol sondes were also launched on balloons during the field deployments. This paper describes the science goals of the DCOTSS project, the aircraft measurement strategy, the data produced by the project, and highlights of science results to date.

Abstract In September 2022, National Aeronautics and Space Administration (NASA) conducted the Convective Processes Experiment–Cabo Verde (CPEX-CV) campaign over the data-sparse eastern Atlantic Ocean. Over this region, CPEX-CV collected a suite of dense observations to aid in the study of convective systems. Tropical Storm (TS) Hermine formed in late September and had an unusual northward trajectory. Hermine was sampled by two consecutive research flights prior to becoming a TS, which provided an opportunity to improve Hermine’s forecast via data assimilation and verify model forecasts. With an improved forecast after assimilating CPEX-CV observations, model data are used to study the processes controlling Hermine’s evolution more accurately. Two experiments were conducted. One experiment assimilated CPEX-CV observations (WCPEX), while the other did not (WoCPEX). Compared to WoCPEX, the assimilation of CPEX-CV observations in the WCPEX analysis produced a stronger Saharan air layer, more intense dry-air intrusion, more easterly wind bias corrections, and a stronger midlevel circulation within pre-Hermine. Forecasts show that the strengthening of pre-Hermine into a TS in WoCPEX was delayed by 12 h due to the large vertical tilt of the vortex and weak midlevel vorticity; it also had a westward track bias. Compared to WoCPEX, in WCPEX, while convection near pre-Hermine was weaker at early forecast times due to a more intense dry-air intrusion, stronger, more organized midlevel vorticity and better vertical alignment of the vortex improved the intensity and track forecast. Additional sensitivity tests revealed that assimilating only CPEX-CV remote sensing observations improved Hermine’s forecast nearly as much as assimilating all CPEX-CV observations. Significance Statement In September 2022, NASA conducted a field campaign whose goal was to collect meteorological observations over the data-sparse eastern Atlantic Ocean. Field observations of Tropical Storm Hermine, which occurred during the campaign, were used in a weather forecast model to assess the effects of the observations on Hermine’s forecast. The modeling results showed that the additional observations from the field campaign improved the forecast of both the track and the strength of Hermine. The modeling results also showed that with the additional observations, the processes that contributed to Hermine’s formation were better represented.

Automated satellite-based methods that pinpoint storms most likely to be severe are valuable for weather and climate analysis, especially in regions with insufficient ground-based radar coverage. Severe storms generate two distinct patterns discernible in satellite imagery, referred to as overshooting tops (OTs) and above-anvil cirrus plumes (AACPs). This paper introduces an open-source OT and AACP detection method that is included in a recent NASA software release. The analysis involved testing 18 satellite and numerical weather reanalysis model input combinations and three semantic segmentation frameworks (U-Net, MultiResUnet, and AttentionUnet) to determine the optimal configura-tion for detecting these storm signatures. Manual labeling of OTs and AACPs across seven severe storm outbreaks provided a truth dataset for model training and validation, with the MultiResUnet model demonstrating superior performance. Radar echo-top heights were analyzed for six additional cases across different seasons and regions of the United States to further test OT detection models. The OT detection models generally performed better when using the 10.3-mm channel in combination with shortwave channels. The best OT detection model detected over 75% of OTs with very few incorrect detections. For AACPs, training the model using confident plume labels, that honed in on warm anomalies near an OT, improved detection performance relative to models trained using all plume labels. Confident plume-trained models skillfully detect AACP occurrences but were unable to capture full plume spatial extent. The 10.3 and 12.3-10.3-mm difference was identified as the optimal input combination for detecting AACPs. Overall, this software holds promise for enhancing severe storm forecasting and advancing weather and climate research applications.

Hailstorms exhibit distinct signatures in spaceborne remote sensing datasets, namely, overshooting cloud tops (OTs) in infrared (IR) imagery or large brightness temperature depressions in passive-microwave radiometer (MWR) imagery. Approaches that leverage these signatures are prone to several issues, e.g., nonuniform beamfilling in MWR datasets or insensitivity to processes below cloud top in IR imagery. Upwelling MWR can also be scattered to extremely low brightness temperatures by high concentrations of graupel-sized ice scatterers. To address this, we investigate Aqua IR, and MWR observations paired with ground-based radar maximum expected size of hail (MESH), and reanalysis environmental parameters over the continental United States. We observe that storms with low (<250 K) 19-GHz brightness temperatures tend to exhibit larger, deeper OTs and a decreasing probability of large MESH with very low (<180 K) 37-GHz brightness temperature. To capture the complex MWR, IR, and environmental parameter interactions, we train a deep neural network (DNN) to estimate severe hail likelihood for a given suite of Aqua observations and reanalysis variables. Leveraging these datasets in combination produces a critical success index of 0.593 and a Heidke skill score of 0.401. The satellite observation analysis and performance assessment using the DNN suggest the relationships between likelihood of large hail (vs smaller hail/graupel) and satellite parameters are complex and nonlinear. The analysis suggests that passive-microwave channels with shorter wavelengths (<1 cm) are vulnerable to scattering from smaller particles, and that hail retrievals mistakenly flag these occurrences as hail, thereby pointing to error sources in previously documented climatologies. Significance Statement Satellites provide the most uniform way to map the distribution of severe weather like hail: They can observe across the globe and provide data in otherwise unreachable locations, like remote areas or over the ocean. For decades, satellite datasets have been used to estimate the global climatology of hail. Two of the most prominent datasets used are infrared (IR) cloud-top products and passive-microwave radiometer (MWR). These approaches are standard but suffer from biases, and this can result in hail being overestimated in the tropics. In this paper, we explore some of those issues to understand where the satellite datasets’ vulnerabilities are and how we might use them together to produce a more accurate result. The relationships we discover turn out to be very complex, so we explore a deep neural network machine learning model to quantify the performance of IR and MWR datasets in detecting likely severe hail over the United States.

This study uses high-resolution airborne data from the NASA Convective Process Experiments-Cabo Verde field campaign to examine the effects of synoptic conditions on mesoscale convective systems (MCSs) over the western coastal waters of West Africa. African easterly waves (AEWs) are the dominant source of synoptic variability over the region, but their influences on coastal areas remain unclear. This study compares airborne data from 2 days with contrasting synoptic conditions and MCS evolution over the coastal water. On one day, large MCSs with high rain rates persisted over the coastal water when the AEW trough was near the coastline. The flow modulation by the AEW strengthened the near-surface onshore flow and warmed and moistened the boundary layer over the coastal water. These combined effects increased the equivalent potential temperature of inflow air into the coastal MCSs, likely supporting their development. On the other day, an AEW was absent or weak, and coastal MCSs remained small and short lived without the effects of the AEW. The observed modulation of the coastal atmosphere and MCSs by AEWs during the field campaign is analogous to the historical relationship of AEW and coastal MCSs obtained by satellite and reanalysis data. Although not represented by the two field campaign cases, the historical analysis suggests the enhancement of coastal vertical wind shear by AEWs can also intensify coastal MCSs. These results highlight the importance of synoptic modulation in understanding the variability and mechanism of coastal MCSs, which differ from those over land or open ocean.

Convective storms over South America and Australia are among the most intense worldwide (e.g., Zipser 2006). However, they are less researched compared to US and Europe. This study analyses the thunderstorm climatology over South America and Australia based on over 20 years of overshooting cloud top (OT) satellite detections (Khlopenkov et al. 2021). These OTs serve as robust, horizontally homogeneous indicators of strong updrafts and hence intense thunderstorms. Furthermore, we focus on the frequency of severe storms and hail by using ERA5 Reanalysis data to exclude OTs in unfavorable environments (e.g., Punge et al. 2023).The resulting climatologies of intense thunderstorms and hail are largely consistent with existing literature, showing strong thunderstorm activity in tropical regions but more severe (e.g., hail-producing) storms in south-central South America and southeast Australia. Some notable details will also be discussed, such as the discrepancy with observational hotspots near the coast in South America and a surprisingly strong signal over northwest Australia. Furthermore, regarding a climate change signal, preliminary analysis indicates no significant trend for South America. However, the multi-year variations are strongly linked to the El Ninjo-Southern Oscillation (ENSO).

One objective of NASA's Convective Processes Experiments Aerosols and Winds (CPEX-AW, 2021) and Cabo Verde (CPEX-CV, 2022) was to assess the impact of high-spatiotemporal-resolution airborne observations on the understanding and prediction of tropical Atlantic convective systems. This study investigates the effects of assimilating observations simultaneously from two airborne lidar systems, Doppler Aerosol Wind (DAWN) lidar winds and High Altitude Lidar Observatory (HALO) water vapor profiles, as well as dropsonde profiles on short-range precipitation forecasts associated with four African easterly waves (AEWs) during CPEX-AW and CPEX-CV. Observations are assimilated into the Weather Research and Forecasting (WRF) Model using the NCEP Gridpoint Statistical Interpolation analysis system (GSI)-based three-dimensional ensemble-variational hybrid data assimilation (3DEnVAR) system. Forecasts are evaluated against Airborne Precipitation Radar (APR)-3 observations and satellite-derived precipitation datasets. Results show that assimilating DAWN winds improves forecasts of the African easterly jet (AEJ) and AEW steering flow, refining precipitation placement. DAWN assimilation also weakens low-level convergence and upper-level divergence, thereby reducing moisture convergence and suppressing spurious simulated precipitation under observed clear skies. HALO water vapor assimilation achieves similar improvements by reducing low-level moisture and total precipitable water. Additionally, DAWN wind assimilation adjusts divergence near cloud tops and enhances precipitation forecasts in observed cloudy skies. The joint assimilation of DAWN winds and HALO water vapor combines these benefits. Dropsonde profiles provide valuable in-cloud data that enhance convective system forecasts but can introduce uncertainties due to their sparse and drifting nature. These drawbacks are effectively mitigated when dropsonde data are jointly assimilated with DAWN winds and HALO water vapor, underscoring the advantages of integrated airborne data assimilation.

This study quantifies the air volume injected into the stratosphere by overshooting convection detected by GOES‐16/17 geostationary infrared imagery and NOAA NEXRAD precipitation echo top during the 2021 and 2022 Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) missions. This analysis addresses a key DCOTSS science question, namely “How much tropospheric air and water is irreversibly injected into the stratosphere by convection?” A novel method for defining individual storms or a cluster of adjacent storms as objects and tracking them throughout their lifetime facilitates the analysis. Overshooting convection injected 3.92 × 10 6 – 5.36 × 10 6 km 3 of air into the stratosphere in 2021 and 9.59 × 10 6 – 1.06 × 10 7 km 3 in 2022 over the North American study domain with GOES being higher than GridRad during both years. GOES overshooting detections were more uncertain due to difficulty differentiating updrafts from adjacent broad areas of cold outflow. Overshooting volume from the top 10 storm objects each year contributed 37%–52% of the total domain‐wide volume. Total object‐lifetime volume from these events ranged from ∼1.3 × 10 5 to 7.9 × 10 5 km 3 for GOES and ∼8.7 × 10 4 to 8.0 × 10 5 km 3 for GridRad. Overshooting seldom exceeded 5% of the total anvil area, and most often occupied <1%, demonstrating that very small regions within convection are responsible for impacting stratosphere composition. Despite differences in overshooting characteristics, airmasses initiated from GOES and NEXRAD overshooting and advected forward in time by reanalysis model winds had similar spatial and vertical distributions, indicating that geostationary satellite data could be used to study the long‐range transport of overshooting airmasses.

Recent field campaigns, observational studies, and modeling work have demonstrated that extratropical tropopause-overshooting convection has a substantial and previously underestimated impact on stratospheric water vapor concentrations. This necessitates improved understanding of how tropopause-overshooting convection will respond to a warming climate. A growing body of research indicates that environments conducive to severe thunderstorms will occur more often and be increasingly unstable in the future, but no study has examined how this may be related to increased overshooting. To rectify this, this study leverages an existing pseudo-global warming (PGW) experiment to evaluate potential future changes in tropopause-overshooting convection over North America. We examine two 10-yr simulations consisting of 1) a retrospective period (2003-12) forced by ERA-Interim initial and boundary conditions (the control simulation) and 2) the same retrospective period with CMIP5 ensemble-mean high-end emission scenario climate changes added to the initial and boundary conditions (the PGW simulation). Tropopause-overshooting convection in the control simulation is validated against observed overshoots from both ground-based radar observations in the United States and GOES observations over North America. The model is shown to effectively simulate the observed regional distribution, annual cycle, and diurnal cycle of tropopause-overshooting convection. In the PGW simulation, tropopause-overshooting convection is found to increase more than 250% across the model domain, and the projected seasonal period of frequent tropopause-overshooting convection is shown to extend into late summer. Additionally, tropopause-overshooting convection with extreme tropopause-relative heights (>4 km) is more frequent in a warmed climate scenario.

Above anvil cirrus plumes (AACPs) form atop deep convective storm anvils. Storms containing AACPs are closely associated with surface severe weather. AACPs often reside in the lower stratosphere, and their microphysics are thought to be characterized by smaller ice particles with increased reflectance in shortwave infrared (SWIR) satellite imagery. This study aimed to determine which SWIR channels exhibit the strongest unique signatures over AACP lifetimes, assess how NEXRAD GridRad radar-derived fields associated with severe weather relate to AACP presence and evolution, and take steps toward a red-green-blue (RGB) recipe to identify AACPs. AACPs and non-plume anvil regions were labeled and analyzed using 5-min resolution Geostationary Operational Environmental Satellites (GOES)-16 Advanced Baseline Imager observations for five storms between 2019 and 2021. Considered were 0.64, 1.37, 1.6, 2.24, 3.9 mu m reflectances, and 10.3 mu m brightness temperatures (BTs). Results show: (a) higher median reflectance of accumulated AACPs in the 0.64, 1.37, and 2.24 mu m channels compared to non-plumes, (b) the 60-79 degrees solar zenith angle bin contained the most data, corresponded with an afternoon peak in storm intensity, and contained a large plume to non-plume pixel ratio, (c) increased lower stratosphere water vapor associated with AACPs impacted the 1.37 mu m reflectance, leading to smaller, more reflective cloud ice particles than non-plume regions, (d) GridRad radar 10- and 40-dBZ echo heights and column maximum reflectivity (CMR) show AACPs coinciding with a secondary maximum in CMR, and (e) an RGB combining 1.37 mu m, 0.64 mu m + 3.9 mu m reflectance, and 10.3 mu m BT visually revealed AACPs.

The challenges associated with reliably observing and simulating hazardous hailstorms call for new approaches that combine information from different available sources, such as remote sensing instruments, observations, or numerical modelling, to improve understanding of where and when severe hail most often occurs. In this work, a proxy for hail frequency is developed by combining overshooting cloud top (OT) detections from the Meteosat Second Generation (MSG) weather satellite with convection-permitting High rEsolution ReAnalysis over Italy (SPHERA) reanalysis predictors describing hail-favourable environmental conditions. Atmospheric properties associated with ground-based reports from the European Severe Weather Database (ESWD) are considered to define specific criteria for data filtering. Five convection-related parameters from reanalysis data quantifying key ingredients for hailstorm occurrence enter the filter: most unstable convective available potential energy (CAPE), K index, surface lifted index, deep-layer shear, and freezing-level height. A hail frequency estimate over the extended summer season (April–October) in south-central Europe is presented for a test period of 5 years (2016–2020). OT-derived hail frequency peaks at around 15:00 UTC in June–July over the pre-Alpine regions and the northern Adriatic Sea. The hail proxy statistically matches with ∼63 % of confirmed ESWD reports, which is roughly 23 % more than the previous estimate over Europe coupling deterministic satellite detections with coarser global reanalysis ambient conditions. The separation of hail events according to their severity highlights the enhanced appropriateness of the method for large-hail-producing hailstorms (with hailstone diameters ≥ 3 cm). Further, signatures for missed small-hail occurrences are identified, which are characterized by lower instability and organization and warmer cloud top temperatures.

The NASA Convective Processes Experiment - Cabo Verde (CPEX-CV) field campaign took place in September 2022 out of Sal Island, Cabo Verde. A unique payload aboard the NASA DC-8 aircraft equipped with advanced remote sensing and in situ instrumentation, in conjunction with radiosonde launches and satellite observations, allowed CPEX-CV to target the coupling between atmospheric dynamics, marine boundary layer properties, convection, and the dust-laden Saharan Air Layer in the data-sparse tropical East Atlantic region. CPEX-CV provided measurements of African Easterly Wave environments, diurnal cycle impacts on convective lifecycle, and several Saharan dust outbreaks, including the highest dust optical depth observed by the DC-8 interacting with what would become Tropical Storm Hermine. Preliminary results from CPEX-CV underscore the positive impact of dedicated tropical East Atlantic observations on downstream forecast skill, including sampling environmental forcings impacting the development of several non-developing and developing convective systems such as Hurricanes Fiona and Ian. Combined airborne radar, lidar, and radiometer measurements uniquely provide near-storm environments associated with convection on various spatiotemporal scales and, with in situ observations, insights into controls on Saharan dust properties with transport. The DC-8 also collaborated with the European Space Agency to perform coordinated validation flights under the Aeolus spaceborne wind lidar and over the Mindelo ground site, highlighting the enhanced sampling potential through partnership opportunities. CPEX-CV engaged in professional development through dedicated team building exercises that equipped the team with a cohesive approach for targeting CPEX-CV science objectives and promoted active participation of scientists across all career stages.

The objective of this study is to understand rainfall processes over tropical islands by identifying synoptic conditions that influence fl uence the diurnal cycle of rainfall over western Puerto Rico. Summer rainfall over Puerto Rico is dominated by its afternoon peak, yet there is large variability in its behavior that remains challenging to predict. We use radiosonde and airborne data collected through the NASA Convective Processes Experiment Aerosols and Winds (CPEX-AW) fi eld campaign (August-September 2021) to achieve our objective, in addition to the network of surface station data over the island. We fi nd that the background wind speed and humidity have strong influences fl uences on afternoon rainfall through different mechanisms. A stronger background wind inhibits afternoon rainfall likely by reducing land-sea thermal contrast and weakening sea-breeze convergence over the island. At the same time, an inversion layer often forms with a stronger background wind that further inhibits deep convection. When the background wind is weak and sea breezes are prominent, afternoon rainfall increases exclusively over the island, while limited rainfall appears over the surrounding ocean. However, enhanced rainfall still occurs over the island with weak sea breezes if humidity is high, accompanied by enhanced rainfall over the surrounding ocean due to the offshore movement and development of convective storms. The sources of variability in background wind and humidity are mostly independent, resulting in a wide range of synoptic conditions and associated effects on the island rainfall. This expanded understanding of the mechanisms causing variability of diurnal rainfall can lead to improved forecasts over Puerto Rico and other tropical islands.

A new airborne coherent Doppler Wind Lidar (DWL) instrument has been implemented leveraging NASA's development of the 2-micron Wind-Space Pathfinder (Wind-SP) lidar transceiver. A technology development project, WindSP refined and demonstrated numerous components required for a coherent-detection space wind lidar instrument. Aerosol Wind Profiler (AWP) transitioned this transceiver into an airborne wind lidar capable of providing full 3-D wind vector retrievals. AWP operates with laser pulse energy and repetition rate combination required for high spatial and vertical resolution wind profiling from space. Operation from aircraft platforms will yield very strong signal return required for detailed process studies at <2 km spatial and <100 m vertical resolution under most conditions. AWP will serve as NASA's wind calibration and validation instrument for future space-based wind observations over the coming decades, while also providing data supporting space wind lidar simulation studies. The AWP instrument is introduced and preliminary results from recent AWP demonstration flights are presented.

We investigate the formation mechanism of a tropopause cirrus cloud layer observed during the Balloon measurement campaigns of the Asian Tropopause Aerosol Layer (BATAL) over Hyderabad (17.47 degrees N, 78.58 degrees E), India, on 23 August 2017. Simultaneous measurements from a backscatter sonde and an optical particle counter on board a balloon flight revealed the presence of a subvisible cirrus cloud layer (optical thickness similar to 0.025) at the cold-point tropopause (temperature similar to -86.4 degrees C, altitude similar to 17.9 km). Ice crystals in this layer are smaller than 50 mu m with a layer mean ice crystal number concentration of about 46.79 L-1. Simultaneous backscatter and extinction coefficient measurements allowed us to estimate the range-resolved extinction to backscatter coefficient ratio (lidar ratio) inside this layer with a layer mean value of about 32.18 +/- 6.73 sr, which is in good agreement with earlier reported values at similar cirrus cloud temperatures. The formation mechanism responsible for this tropopause cirrus is investigated using a combination of three-dimensional back trajectories, satellite observations, and ERA5 reanalysis data. Satellite observations revealed that the overshooting convection associated with a category 3 typhoon, Hato, which hit Macau and Hong Kong on 23 August 2017, injected ice into the lower stratosphere. This caused a hydration patch that followed the Asian summer monsoon anticyclone to subsequently move towards Hyderabad. The presence of tropopause cirrus cloud layers in the cold temperature anomalies and updrafts along the back trajectories suggested the role of typhoon-induced waves in their formation. This case study highlights the role of typhoons in influencing the formation of tropopause cirrus clouds through stratospheric hydration and waves.

Abstract On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water‐rich plume at least 58 km high. Using a combination of satellite‐ and ground‐based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min−1) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co‐located with an internal gravity wave traveling >80 m s−1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high‐current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 109 kg s−1), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma‐water interaction at the submarine vent.

Abstract Water vapor's contribution to Earth's radiative forcing is most sensitive to changes in its lower stratosphere concentration. One recognized pathway for rapid increases in stratospheric water vapor is tropopause‐overshooting convection. Since this pathway has been rarely sampled, the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field project focused on obtaining in situ observations of stratospheric air recently affected by convection over the United States. This study reports on the extreme altitudes to which convective hydration was observed. The data show that the overworld stratosphere is routinely hydrated by convection and that past documented records of stratospheric heights of convective hydration were exceeded during several DCOTSS flights. The most extreme event sampled is highlighted, for which stratospheric water vapor was increased by up to 26% at an altitude of 19.25 km, a potential temperature of 463 K, and an ozone mixing ratio >1500 ppbv.

The eruption of the submarine Hunga Tonga Hunga Hapaii volcano on 15 January 2022 was associated with a powerful blast that injected sulfur and water to altitudes up to 58 km. In this study, we combine the data from various satellite instruments (MLS, OMPS-LP, CALIOP, SAGE III, Aeolus, COSMIC-2, ACE-FTS, GOES, Himawari), ground-based lidars at various locations, meteorological radiosoundings as well as model simulation using CLaMS chemistry-transport model to investigate the evolution of the stratospheric moisture and sulfate aerosol plume at a wide range of scales—from minutes and kilometres to monthly and planetary scale. We show that due to extreme altitude reach of the eruption, the volcanic plume has circumnavigated the Earth in only one week and dispersed nearly pole-to-pole in three months. The observations provide evidence for an unprecedented increase in the global stratospheric water mass by 13% as compared to climatological levels. As there are no efficient sinks of water vapour in the stratosphere, this perturbation is expected to persist several years. The eruption has also led to a 5-fold increase in the stratospheric aerosol load, the highest in the last three decades yet factor of 6 smaller than the previous major eruption of Mt Pinatubo in 1991.The unique nature and magnitude of the global stratospheric perturbation by the Hunga eruption ranks it among the most remarkable climatic events in the modern observation era. Given the expected longevity of the stratospheric humidity perturbation, the Hunga eruption can be said to have initiated a new era in stratospheric gaseous chemistry and particle microphysics with a wide range of potential long-lasting repercussions for the global stratospheric composition and dynamics. The eruption has thus provided a unique natural testbed, lending itself to studies of climate sensitivity to strong change in both stratospheric gaseous and particulate composition.Spanning more than one year, the satellite and ground-based observations available to-date enable the first accurate assessment of the annual-scale stratospheric aftermath of the Hunga Tonga eruption, uncovering its climate-altering capacity.