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The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) field campaign provides accurate data for aerosol characterization and trace gas profiles, and establishes knowledge of the relationships between aerosols and water. The dropsonde dataset provides an in situ characterization of the vertical thermodynamic structure of the atmosphere during 165 research flights by NASA Langley's King Air research aircraft between February 2020 and June 2022 and four test flights between December 2019 and November 2021. The research flights covered the western North Atlantic region, off the coast of the Eastern United States and around Bermuda and covered all seasons. The dropsonde profiles provide observations of temperature, pressure, relative humidity, and horizontal and vertical winds between the surface and about 9 km. 801 dropsondes were released, of which 796 were processed and 788 provide complete profiles of all parameters between the flight level and the surface with normal parachute performance. Here, we describe the dataset, the processing of the measurements, general statistics, and applications of this rich dataset., (© 2023. The Author(s).)

The eruption of the Hunga Tonga-Hunga Ha'apai volcano on 15 January 2022 offered a good opportunity to explore the early impacts of tropical volcanic eruptions on stratospheric composition. Balloon-borne observations near Réunion Island revealed the unprecedented amount of water vapor injected by the volcano. The enhanced stratospheric humidity, radiative cooling, and expanded aerosol surface area in the volcanic plume created the ideal conditions for swift ozone depletion of 5% in the tropical stratosphere in just 1 week. The decrease in hydrogen chloride by 0.4 parts per million by volume (ppbv) and the increase in chlorine monoxide by 0.4 ppbv provided compelling evidence for chlorine activation within the volcanic plume. This study enhances our understanding of the effect of this unusual volcanic eruption on stratospheric chemistry and provides insights into possible chemistry changes that may occur in a changing climate.

Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.

Large volcanic eruptions, although rare events, can influence the chemistry and the dynamics of the stratosphere for several years after the eruption. Here we show that the eruption of the submarine volcano Hunga Tonga-Hunga Ha'apai on 15 January 2022 injected at least 50 teragrams of water vapor directly into the stratosphere. This event raised the amount of water vapor in the developing stratospheric plume by several orders of magnitude and possibly increased the amount of global stratospheric water vapor by more than 5%. This extraordinary eruption may have initiated an atmospheric response different from that of previous well-studied large volcanic eruptions.

In this study, an overview of two years of research findings concerning the 2022 Hunga Tonga–Hunga Ha'apai (HTHH) volcanic eruption in the stratospheric environment is provided, focusing on water vapor, aerosols, and ozone. Additionally, the potential impacts of these changes on aviation equipment materials are discussed. The HTHH volcanic eruption released a large amount of particles (e.g., ash and ice) and gases (e.g., H2O, SO2, and HCl), significantly affecting the redistribution of stratospheric water vapor and aerosols. Stratospheric water vapor increased by approximately 140–150 Tg (8–10%), with a concentration peak observed in the height range of 22.2–27 km (38–17 hPa). Satellite measurements indicate that the HTHH volcano injected approximately 0.2–0.5 Tg of sulfur dioxide into the stratosphere, which was partially converted into sulfate aerosols. In-situ observations revealed that the volcanic aerosols exhibit hygroscopic characteristics, with particle sizes ranging from 0.22–0.42 μm under background conditions to 0.42–1.27 μm. The moist stratospheric conditions increased the aerosol surface area, inducing heterogeneous chlorine chemical reactions on the aerosol surface, resulting in stratospheric ozone depletion in the HTHH plume within one week. In addition, atmospheric disturbances and ionospheric disruptions triggered by volcanic eruptions may adversely affect aircraft and communication systems. Further research is required to understand the evolution of volcanic aerosols and the impact of volcanic activity on aviation equipment materials. [ABSTRACT FROM AUTHOR]

The main goal of this paper is to validate the total water vapour column (TWVC) measured by the Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensor and generated using the GOME Data Processor (GDP) retrieval algorithm developed by the German Aerospace Centre (DLR). For this purpose, spatially and temporally collocated TWVC data from highly accurate sounding measurements for the period January 2009-May 2014 at six sites are used. These balloon-borne data are provided by the GCOS Reference Upper-Air Network (GRUAN). The correlation between GOME-2 and sounding TWVC data is reasonably good (determination coefficient, R2, of 0.89) when all available radiosondes (1400) are employed in the intercomparison. When cloud-free cases (544) are selected by means of the satellite cloud fraction (CF<5 %), the correlation exhibits a remarkable improvement (R2 ∼0.95). Nevertheless, the analysis of the relative differences between GOME-2 and GRUAN data shows a mean absolute bias error (weighted with the combined uncertainty derived from the estimated errors of both data sets) of 15% for all-sky conditions (9% for cloud-free cases). These results evidence a notable bias in the satellite TWVC data against the reference balloon-borne measurements, partially related to the cloudy conditions during the satellite overpass. The detailed analysis of the influence of cloud properties - CF, cloud top albedo (CTA) and cloud top pressure (CTP) - on the satellitesounding differences reveals, as expected, a large effect of clouds in the GOME-2 TWVC data. For instance, the relative differences exhibit a large negative dependence on CTA, varying from -6 to -23% when CTA rises from 0.3 to 0.8. Furthermore, the satellite-sounding TWVC differences show a strong dependence on the satellite solar zenith angle (SZA) for values above 50°. Hence the smallest relative differences found in this satellite-sounding comparison are achieved for those cloud-free cases with satellite SZA below 50°. Finally, the relative differences also show a negative dependence on the reference TWVC values, e.g. changing from C10% (TWVC below 10 mm) to -10% (TWVC above 40 mm) when cloud-free conditions with SZA below 50° are selected. Overall, relative differences within +10% with respect to reference sounding data for a large range of TWVC values can be considered as a good result for satellite retrievals. [ABSTRACT FROM AUTHOR]

Ozonesonde data from November 2013 to April 2015 over Kunming, China are used to verify ozone and temperature profile retrievals from two spaceborne instruments, the version 4.2 product from the Microwave Limb Sounder (MLS) on the NASA Aura satellite and the version 6.0 product from the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite. We calculated and compared the ozone effective height H eff and effective temperature T eff , which are two important parameters in ground-based total ozone retrieval through the use of various profile datasets. This is used to verify the accuracy of the operative values (H eff(0)  = 23 km, T eff(0)  = -46.3 °C (or -45 °C)) from the World Meteorological Organization. The results show that the deviation of MLS and AIRS ozone profiles from ozone sounding data has significant oscillation and scatter in the upper troposphere and lower stratosphere. The average difference of MLS at 82.5 hPa is (80.5 ± 65.1) %, and that of AIRS at 70 and 100 hPa are (105.6 ± 74.9) % and (107.0 ± 67.8) %, respectively. The two satellite temperature profiles have differences within ±3 °C and can effectively describe the vertical distribution and variation of temperature. When calculating the H eff and T eff , upper stratospheric data missing from the sounding data must be filled in by the satellite profile data; otherwise the calculated results will show large errors of 3.2 km and 3.3 °C. The H eff and T eff at Kunming are respectively 24.36 to 25.51 km and -48.3 to -43.6 °C. The operational H eff and T eff used at Kunming ozone observation station clearly do not conform to the actual situation and must be corrected., (Copyright © 2019. Published by Elsevier B.V.)

The GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) data processing for the Vaisala RS92 radiosonde was developed to meet the criteria for reference measurements. These criteria stipulate the collection of metadata, the use of well-documented correction algorithms, and estimates of the measurement uncertainty. An important and novel aspect of the GRUAN processing is that the uncertainty estimates are vertically resolved. This paper describes the algorithms that are applied in version 2 of the GRUAN processing to correct for systematic errors in radiosonde measurements of pressure, temperature, humidity, and wind, as well as how the uncertainties related to these error sources are derived. Currently, the RS92 is launched on a regular basis at 13 out of 15 GRUAN sites. An additional GRUAN requirement for performing reference measurements with the RS92 is that the manufacturerprescribed procedure for the radiosonde's preparation, i.e. heated reconditioning of the sensors and recalibration during ground check, is followed. In the GRUAN processing however, the recalibration of the humidity sensors that is applied during ground check is removed. For the dominant error source, solar radiation, laboratory experiments were performed to investigate and model its effect on the RS92's temperature and humidity measurements. GRUAN uncertainty estimates are 0.15K for night-time temperature measurements and approximately 0.6K at 25 km during daytime. The other uncertainty estimates are up to 6% relative humidity for humidity, 10-50m for geopotential height, 0.6 hPa for pressure, 0.4-1ms–1 for wind speed, and 1° for wind direction. Daytime temperature profiles for GRUAN and Vaisala processing are comparable and consistent within the estimated uncertainty. GRUAN daytime humidity profiles are up to 15% moister than Vaisala processed profiles, of which two-thirds is due to the radiation dry bias correction and onethird is due to an additional calibration correction. Redundant measurements with frost point hygrometers (CFH and NOAA FPH) show that GRUAN-processed RS92 humidity profiles and frost point data agree within 15% in the troposphere. No systematic biases occur, apart from a 5% dry bias for GRUAN data around –40 °C at night. [ABSTRACT FROM AUTHOR]

Large areas of synoptic-scale ice PSCs (Polar Stratospheric Clouds) distinguished the Arctic winter 2009/2010 from other years and revealed unprecedented evidence of water redistribution in the stratosphere. A unique snapshot of water vapor repartitioning into ice particles was observed under extremely cold Arctic conditions with temperatures around 183K. Balloon-borne, aircraft and satellite-based measurements suggest that synoptic-scale ice PSCs and concurrent reductions and enhancements in water vapor are tightly linked with the observed de- and rehydration signatures, respectively. In a companion paper (Part 1), water vapor and aerosol backscatter measurements from the RECONCILE (Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions) and LAPBIAT-II (Lapland Atmosphere-Biosphere Facility) field campaigns have been analyzed in detail. This paper uses a column version of the Zurich Optical and Microphysical box Model (ZOMM) including newly developed NAT (Nitric Acid Trihy-drate) and ice nucleation parameterizations. Particle sedimentation is calculated in order to simulate the vertical redistribution of chemical species such as water and nitric acid. Accounting for small-scale temperature fluctuations along the trajectory is essential to reach agreement between simulated optical cloud properties and observations. Whereas modeling only homogeneous nucleation causes the formation of ice clouds with particle radii too small to explain the measured vertical redistribution of water, we show that the use of recently developed heterogeneous ice nucleation parameterizations allows the model to quantitatively reproduce the observed signatures of de- and rehydration. [ABSTRACT FROM AUTHOR]

Reprocessed ozonesonde data from eight SHADOZ (Southern Hemisphere ADditional OZonesondes) sites have been used to derive the first analysis of uncertainty estimates for both profile and total column ozone (TCO). The ozone uncertainty is a composite of the uncertainties of the individual terms in the ozone partial pressure (P O3 ) equation, those being the ozone sensor current, background current, internal pump temperature, pump efficiency factors, conversion efficiency, and flow-rate. Overall, P O3 uncertainties (ΔP O3 ) are within 15% and peak around the tropopause (15±3km) where ozone is a minimum and ΔP O3 approaches the measured signal. The uncertainty in the background and sensor currents dominate the overall ΔP O3 in the troposphere including the tropopause region, while the uncertainties in the conversion efficiency and flow-rate dominate in the stratosphere. Seasonally, ΔP O3 is generally a maximum in the March-May, with the exception of SHADOZ sites in Asia, for which the highest ΔP O3 occurs in September-February. As a first approach, we calculate sonde TCO uncertainty (ΔTCO) by integrating the profile ΔP O3 and adding the ozone residual uncertainty, derived from the McPeters and Labow [2012] 1-σ ozone mixing ratios. Overall, ΔTCO are within ±15 DU, representing ~5-6% of the TCO. TOMS and OMI satellite overpasses are generally within the sonde ΔTCO. However, there is a discontinuity between TOMS v8.6 (1998-2004/09) and OMI (2004/10-2016) TCO on the order of 10DU that accounts for the significant 16DU overall difference observed between sonde and TOMS. By comparison, the sonde-OMI absolute difference for the eight stations is only ~4DU.