Abstract
We observed five clusters of upper-level compact intracloud discharges (CIDs) moving positive charge up over land and over water in Florida. The clusters each contained 3 to 6 CIDs, and the overall cluster duration ranged from 27 to 58 s. On average, the CIDs in a given cluster occurred 11 s apart and were separated by a 3D distance of about 1.5 km. All the clustered CIDs were located above the tropopause and were likely associated with convective surges that penetrated the stratosphere. The average periodicity of CID occurrence within a cluster (every 11 s) was comparable to the periodicity at which the average cluster area is expected to be bombarded by ≥1016 eV cosmic-ray particles (every 5 s). Each of such energetic particles gives rise to a cosmic ray shower (CRS) and, in the presence of sufficiently strong electric field over a sufficiently large distance, to a relativistic runaway electron avalanche (RREA). We infer that each of our upper-level CIDs is likely to be caused by a CRS-RREA traversing, at nearly the speed of light, the electrified overshooting convective surge and triggering, within a few microseconds, a multitude of streamer flashes along its path, over a distance of the order of hundreds of meters (as per the mechanism recently proposed for lightning initiation by Kostinskiy et al., 2020, https://doi.org/10.1029/2020JD033191). The upper-level CID clustering was likely made possible by the recurring action of energetic cosmic rays and the rapid recovery of the negative screening charge layer at stratospheric altitudes.
Abstract
This study examines marine boundary layer cloud regime transition during a cold air outbreak (CAO) over the Norwegian Sea, simulated by a global storm-resolving model (GSRM) known as the Simple Cloud-Resolving Energy Exascale Earth System Model Atmosphere Model (SCREAM). By selecting observational references based on a combination of large-scale conditions rather than strict time-matched comparisons, this study finds that SCREAM qualitatively captures the CAO cloud transition, including boundary layer growth, cloud mesoscale structure, and phase partitioning. SCREAM also accurately locates the greatest ice and liquid in the mesoscale updrafts, however, underestimates supercooled liquid water in cumulus clouds. The model evaluation approach adopted by this study takes advantages of the existing computational-expensive global simulations of GSRM and the available observations to understand model performance and can be applied to assessments of other cloud regimes in different regions. Such practice provides valuable guidance on the future effort to correct and improve biased model behaviors.
Abstract
The Southern Ocean regulates atmospheric CO2 and Earth's climate as a critical region for air-sea gas exchange, delicately poised between being a CO2 source and sink. Here, we estimate how long a water mass has remained isolated from the atmosphere and utilize 14C/12C ratios (Δ14C) to trace the pathway and escape route of carbon sequestered in the deep ocean through the mixed layer to the atmosphere. The position of our core at the northern margin of the Southern Indian Ocean, tracks latitudinal shifts of the Southern Ocean frontal zones across the deglaciation. Our results suggest an expanded glacial Antarctic region trapped CO2, whereas deglacial expansion of the subantarctic permitted ventilation of the trapped CO2, contributing to a rapid atmospheric CO2 rise. We identify frontal positions as a key factor balancing CO2 outgassing versus sequestration in a region currently responsible for nearly half of global ocean CO2 uptake.
Abstract
The January 2022 eruption of Hunga Tonga-Hunga Ha'apai (HTHH) injected a huge amount (∼150 Tg) of water vapor (H2O) into the stratosphere, along with small amount of SO2. An off-line 3-D chemical transport model (CTM) successfully reproduces the spread of the injected H2O through October 2023 as observed by the Microwave Limb Sounder. Dehydration in the 2023 Antarctic polar vortex caused the first substantial (∼20 Tg) removal of HTHH H2O from the stratosphere. The CTM indicates that this process will dominate removal of HTHH H2O for the coming years, giving an overall e-folding timescale of 4 years; around 25 Tg of the injected H2O is predicted to still remain in the stratosphere by 2030. Following relatively low Antarctic column ozone in midwinter 2023 due to transport effects, additional springtime depletion due to H2O-related chemistry was small and maximized at the vortex edge (10 DU in column).
Abstract
We examined the possible factors affecting the spatial distribution of very low frequency earthquakes and tremors in the shallow megathrust of Nankai Trough (<30 km) using a dense network of prestack depth migrated profiles at the frontal wedge. Geometrical parameters examined were decollement roughness, taper angle, and underthrust thickness. Physical properties such as effective basal friction (μb) and pore pressure ratio (λ*) were calculated from the taper angle and p-wave velocity. Regions of low λ* (0.39 ± 0.08) and smooth decollement showed no slow earthquake activity. In contrast, high activity of slow earthquakes was observed in areas with a rough decollement due to the presence of subducted seamounts or bathymetric highs. The low taper angle (3.8°) off Muroto where slow earthquakes also occur translates to a wide zone of low μb (0.21 ± 0.06) and high λ* (0.66 ± 0.06). However, our results also show that slow earthquakes don't always occur in areas with high λ*.
Abstract
The Southern Ocean's eddy response to changing climate remains unclear, with observations suggesting non-monotonic changes in eddy kinetic energy (EKE) across scales. Here simulations reappear that smaller-mesoscale EKE is suppressed while larger-mesoscale EKE increases with strengthened winds. This change was linked to scale-wise changes in the kinetic energy cycle, where a sensitive balance between the dominant mesoscale energy sinks—inverse KE cascade, and source—baroclinic energization. Such balance induced a strong (weak) mesoscale suppression in the flat (ridge) channel. Mechanistically, this mesoscale suppression is attributed to stronger zonal jets weakening smaller mesoscale eddies and promoting larger-scale waves. These EKE multiscale changes lead to multiscale changes in meridional and vertical eddy transport, which can be parameterized using a scale-dependent diffusivity linked to the EKE spectrum. This multiscale eddy response may have significant implications for understanding and modeling the Southern Ocean eddy activity and transport under a changing climate.
Abstract
Diagnosing land-atmosphere fluxes of carbon-dioxide (CO2) and methane (CH4) is essential for evaluating carbon-climate feedbacks. Greenhouse gas satellite missions aim to fill data gaps in regions like the humid tropics but obtain very few valid measurements due to cloud contamination. We examined data yields from the Orbiting Carbon Observatory alongside Sentinel-2 cloud statistics. We find that the main contribution to low data yields are frequent shallow cumulus clouds. In the Amazon, the success rate in obtaining valid measurements vary from 0.1% to 1.0%. By far the lowest yields occur in the wet season, consistent with Sentinel-2 cloud patterns. We find that increasing the spatial resolution of observations to ∼200 m would increase yields by 2–3 orders of magnitude and allow regular measurements in the wet season. Thus, the key to effective tropical greenhouse gas observations lies in regularly acquiring high-spatial resolution data.
Abstract
FY-3E plays a vital role in the meteorological global earth observing system. Precipitable water vapor (PWV) is an essential parameter for the water cycle and global climate change. Here, we carry out the PWV retrieval using the MERSI-LL sensor onboard the FY-3E satellite for the first time. The retrieval accuracy under different cloudage conditions is validated by the extra PWV from ground-based GNSS and spaceborne occultation. For the results against ground-based GNSS, the total accuracy shows an RMSE of 2.69–3.36 mm as the clouds increase, and correlation coefficients higher than 0.95. The spatial accuracy distribution indicates that inland stations have higher accuracy than the coast and island stations. As for the results against spaceborne occultation, the verification accuracy varies with the spatial pairing distance, showing poor accuracy in the low latitude area. This study can provide an essential reference for the community to understand the current water vapor inversion performance of MERSI-LL.
Abstract
Earthquakes and tsunamis can trigger acoustic and gravity waves that could reach the ionosphere, generating electron density disturbances, known as traveling ionospheric disturbances. These perturbations can be investigated as variations in ionospheric total electron content (TEC) estimated through global navigation satellite systems (GNSS) receivers. The VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm is a well-known real-time tool for estimating TEC variations. In this context, the high amount of data allows the exploration of a VARION-based machine learning classification approach for TEC perturbation detection. For this purpose, we analyzed the 2015 Illapel earthquake and tsunami for its strength and high impact. We use the VARION-generated observations (i.e., dsTEC/dt) provided by 115 GNSS stations as input features for the machine learning algorithms, namely, Random Forest and XGBoost. We manually label time frames of TEC perturbations as the target variable. We consider two elevation cut-off time series, namely, 15° and 25°, to which we apply the classifier. XGBoost with a 15° elevation cut-off dsTEC/dt time series reaches the best performance, achieving an F1 score of 0.77, recall of 0.74, and precision of 0.80 on the test data. Furthermore, XGBoost presents an average difference between the labeled and predicted middle epochs of TEC perturbation of 75 s. Finally, the model could be seamlessly integrated into a real-time early warning system, due to its low computational time. This work demonstrates high-probability TEC signature detection by machine learning for earthquakes and tsunamis, that can be used to enhance tsunami early warning systems.
Supershear crack propagation in snow slab avalanche release: new insights from numerical simulations and field measurements
Grégoire Bobillier, Bertil Trottet, Bastian Bergfeld, Ron Simenhois, Alec van Herwijnen, Jürg Schweizer, and Johan Gaume
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-70,2024
Preprint under review for NHESS (discussion: open, 0 comments)
Our study focuses on the initiation process of snow slab avalanches. By combining experimental data and numerical simulations, we show that on gentle slopes, a crack forms and propagates due to compression fracture within a weak layer, and on steep slopes, the crack velocity can increase dramatically after about 5 meters due to a fracture mode transition (compression to shear). Understanding these dynamics represents an essential additional piece in the dry-snow slab avalanche formation puzzle.
Researchers at Aston University have found differences between experienced Ordnance Survey (OS) mapmakers and novices in the way that they interpret aerial images for mapmaking, which could lead to improved training processes for new recruits. The findings are published in the Journal of Vision.
Tectonically active mountains play an important role in the natural CO2 regulation of the atmosphere. Competing processes take place here: At Earth's surface, erosion drives weathering processes that absorb or release CO2, depending on the type of rock. At depth, the heating and melting of carbonate rock leads to the outgassing of CO2 at the surface.
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, 2024
We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, 2024
Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Black carbon (BC) is the result of incomplete combustion of fossil fuels and biomass, with strong light absorption. It is second only to carbon dioxide as a climate-forcing factor for atmospheric warming. Deposition of BC on snow and ice surfaces reduces albedo, accelerates glacier and snow cover melting, and alters hydrological processes and water resources in the region.
New research finds that modern weather models can accurately predict satellite movements due to the energy emitted and reflected by the Earth. In addition to weather prediction, weather models can also help understand and predict how satellites respond to weather events, such as storms.
Investigation of cirrus cloud properties in the tropical tropopause layer using high-altitude limb-scanning near-IR spectroscopy during NASA-ATTREX
Santo Fedele Colosimo, Nathaniel Brockway, Vijay Natraj, Robert Spurr, Klaus Pfeilsticker, Lisa Scalone, Max Spolaor, Sarah Woods, and Jochen Stutz
Atmos. Meas. Tech., 17, 2367–2385, https://doi.org/10.5194/amt-17-2367-2024, 2024
Cirrus clouds are poorly understood components of the climate system, in part due to the challenge of observing thin, sub-visible ice clouds. We address this issue with a new observational approach that uses the remote sensing of near-infrared ice water absorption features from a high-altitude aircraft. We describe the underlying principle of this approach and present a new procedure to retrieve ice concentration in cirrus clouds. Our retrievals compare well with in situ observations.
Identifying the seeding signature in cloud particles from hydrometeor residuals
Mahen Konwar, Benjamin Werden, Edward C. Fortner, Sudarsan Bera, Mercy Varghese, Subharthi Chowdhuri, Kurt Hibert, Philip Croteau, John Jayne, Manjula Canagaratna, Neelam Malap, Sandeep Jayakumar, Shivsai A. Dixit, Palani Murugavel, Duncan Axisa, Darrel Baumgardner, Peter F. DeCarlo, Doug R. Worsnop, and Thara Prabhakaran
Atmos. Meas. Tech., 17, 2387–2400, https://doi.org/10.5194/amt-17-2387-2024, 2024
In a warm cloud seeding experiment hygroscopic particles are released to alter cloud processes to induce early raindrops. During the Cloud–Aerosol Interaction and Precipitation Enhancement Experiment, airborne mini aerosol mass spectrometers analyse the particles on which clouds form. The seeded clouds showed higher concentrations of chlorine and potassium, the oxidizing agents of flares. Small cloud droplet concentrations increased, and seeding particles were detected in deep cloud depths.
Before climate change really got going, eastern Australia's flash floods tended to concentrate on our coastal regions, east of the Great Dividing Range.
Earthquakes and landslides are famously difficult to predict and prepare for. By studying a miniature version of the ground in the lab, scientists at the UvA Institute of Physics have demonstrated how these events can be triggered by a small external shock wave. Bring a flotation device: it involves the ground briefly turning into a liquid.
