Status and Extension of the Geant4-DNA Dielectric Models for Application to Electron Transport

The development of accurate physics models that enable track structure simulations of electrons in liquid water medium over a wide energy range, from the eV to the MeV scale, is a subject of continuous efforts due to its importance (among other things) in theoretical studies of radiation quality for application in radiotherapy and radiation protection. A few years ago, the Geant4-DNA very low-energy extension of the Geant4 Monte Carlo code had offered to users an improved set of physics models for discrete electron transport below 10 keV. In this work we present refinements to this model set and its extension to energies up to 1 MeV. Preliminary comparisons against the existing Geant4-DNA physics models with respect to total and differential ionization cross sections of electrons in liquid water are reported and discussed.

Modelling SO₂ conversion into sulphates in the mid-troposphere with a 3D chemistry-transport model: the case of Mount Etna's eruption on April 12, 2012

Volcanic activity is an important source of atmospheric sulphur dioxide (SO2), which, after conversion into sulphuric acid, induces impacts on, among others, rain acidity, human health, meteorology and the radiative balance of the atmosphere. This work focuses on the conversion of SO2 into sulphates (, S(+VI)) in the mid-tropospheric volcanic plume emitted by the explosive eruption of Mount Etna (Italy) on Apr. 12, 2012, using the CHIMERE chemistry-transport model. Since volcanic plume location and composition depend on several often poorly constrained parameters, using a chemistry-transport model allows us to study the sensitivity of SO2 oxidation to multiple aspects such as volcanic water emissions, transition metal emissions, plume diffusion and plume altitude. Our results show that in the mid-troposphere, two pathways contribute to sulphate production, the oxidation of SO2 by OH in the gaseous phase (70 %), and the aqueous oxidation by O2 catalyzed by Mn2+ and Fe3+ ions (25 %). The oxidation in aqueous phase is the faster process, but in the mid-troposphere, liquid water is scarce, therefore the relative share of gaseous oxidation can be important. After one day in the mid-troposphere, about 0.5 % of the volcanic SO2 was converted to sulphates through the gaseous process. Because of the nonlinear dependency of the kinetics in the aqueous phase to the amount of volcanic water emitted and on the availability of transition metals in the aqueous phase, several experiments have been designed to determine the prominence of different parameters. Our simulations show that during the short time that liquid water remains in the plume, around 0.4 % of sulphates manage to quickly enter the liquid phase. Sensitivity tests regarding the advection scheme have shown that this scheme must be chosen wisely, as dispersion will impact both oxidation pathways explained above.

Understanding the Extratropical Liquid Water Path Feedback in Mixed-Phase Clouds with an Idealized Global Climate Model

A negative shortwave cloud feedback associated with higher extratropical liquid water content in mixed-phase clouds is a common feature of global warming simulations, and multiple mechanisms have been hypothesized. A set of process-level experiments performed with an idealized global climate model (a dynamical core with passive water and cloud tracers and full Rotstayn-Klein single-moment microphysics) show that the common picture of the liquid water path (LWP) feedback in mixed-phase clouds being controlled by the amount of ice susceptible to phase change is not robust. Dynamic condensate processes—rather than static phase partitioning—directly change with warming, with varied impacts on liquid and ice amounts. Here, three principal mechanisms are responsible for the LWP response, namely higher adiabatic cloud water content, weaker liquid-to-ice conversion through the Bergeron-Findeisen process, and faster melting of ice and snow to rain. Only melting is accompanied by a substantial loss of ice, while the adiabatic cloud water content increase gives rise to a net increase in ice water path (IWP) such that total cloud water also increases without an accompanying decrease in precipitation efficiency. Perturbed parameter experiments with a wide range of climatological LWP and IWP demonstrate a strong dependence of the LWP feedback on the climatological LWP and independence from the climatological IWP and supercooled liquid fraction. This idealized setup allows for a clean isolation of mechanisms and paints a more nuanced picture of the extratropical mixed-phase cloud water feedback than simple phase change.

Mapping liquid water content in snow at the millimeter scale: an intercomparison of mixed-phase optical property models using hyperspectral imaging and in situ measurements

It is well understood that the distribution and quantity of liquid water in snow is relevant for snow hydrology and avalanche forecasting, yet detecting and quantifying liquid water in snow remains a challenge from the micro- to the macro-scale. Using near-infrared (NIR) spectral reflectance measurements, previous case studies have demonstrated the capability to retrieve surface liquid water content (LWC) of wet snow by leveraging shifts in the complex refractive index between ice and water. However, different models to represent mixed-phase optical properties have been proposed, including (1) internally mixed ice and water spheres, (2) internally mixed water-coated ice spheres, and (3) externally mixed interstitial ice and water spheres. Here, from within a controlled laboratory environment, we determined the optimal mixed-phase optical property model for simulating wet snow reflectance using a combination of NIR hyperspectral imaging, radiative transfer simulations (Discrete Ordinate Radiative Transfer model, DISORT), and an independent dielectric LWC measurement (SLF Snow Sensor). Maps of LWC were produced by finding the lowest residual between measured reflectance and simulated reflectance in spectral libraries, generated for each model with varying LWC and grain size, and assessed against the in situ LWC sensor. Our results show that the externally mixed model performed the best, retrieving LWC with an uncertainty of ∼1 %, while the simultaneously retrieved grain size better represented wet snow relative to the established scaled band area method. Furthermore, the LWC retrieval method was demonstrated in the field by imaging a snowpit sidewall during melt conditions and mapping LWC distribution in unprecedented detail, allowing for visualization of pooling water and flow features.

Water vapor in cold and clean atmosphere: a 3-year data set in the boundary layer of Dome C, East Antarctic Plateau

The air at the surface of the high Antarctic Plateau is very cold, dry and clean. In such conditions the atmospheric moisture can significantly deviate from thermodynamic equilibrium conditions, and supersaturation with respect to ice can occur. Most conventional humidity sensors for meteorological applications cannot report supersaturation in this environment. A simple approach for measuring supersaturation using conventional instruments, one being operated in a heated airflow, is presented. Since 2018, this instrumental setup was deployed at 3 levels in the lower ~40 m above the surface at Dome C on the high Antarctic Plateau. The 3-year 2018–2020 record (Genthon et al. 2021) is presented and analyzed for features such as the frequency of supersaturation with respect to ice, diurnal and seasonal variability, and vertical distribution. As supercooled liquid water droplets are frequently observed in clouds at the temperatures met on the high Antarctic Plateau, the distribution of relative humidity with respect to liquid water at Dome C is also discussed. It is suggested that, while not strictly mimicking the conditions of the high troposphere, the surface atmosphere on the Antarctic Plateau is a convenient natural laboratory to test parametrizations of cold microphysics predominantly developed to handle the genesis of high tropospheric clouds. Data are distributed on the PANGAEA data repository at https://doi.pangaea.de/10.1594/PANGAEA.939425 (Genthon et al., 2021).