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Abstract

Infrared (IR) luminosity of lightning channel in the 3–5 μm range usually persisted throughout the entire interstroke interval, which is in contrast to the simultaneously recorded visible (0.4–0.8 μm) luminosity that always decayed to an undetectable level prior to a subsequent return stroke pulse. A longer visible luminosity period at the end of flash tended to be associated with a longer IR afterglow period following the decay of visible luminosity (and by inference current) to an undetectable level. At the end of flash, the IR luminosity persisted up to about 1 s, and the median IR afterglow duration was a factor of 10 longer than the median visible luminosity duration. The IR luminosity often exhibited a hump when the visible luminosity was monotonically decaying or undetectable, with the corresponding channel temperature being likely around 3400 K.

Abstract

An accurate solar wind (SW) speed model is important for space weather predictions, catastrophic event warnings, and other issues concerning SW—magnetosphere interaction. In this work, we construct a model based on convolutional neural network (CNN) and Potential Field Source Surface (PFSS) magnetic field maps, considering a SW source surface of R SS = 2.5R⊙, aiming to predict the SW speed at the Lagrange-1 (L1) point of the Sun-Earth system. The input of our model consists of four PFSS magnetic field maps at R SS, which are three, four, five, and six days before the target epoch. Reduced maps are used to promote the model's efficiency. We use the Global Oscillation Network Group (GONG) photospheric magnetograms and the potential field extrapolation model to generate PFSS magnetic field maps at the source surface. The model provides predictions of the quasi-continuous test data set, which is generated by randomly assigning 120 data segments that are individually continuous in time, with an averaged correlation coefficient (CC) of 0.53 ± 0.07 and a root mean square error (RMSE) of 80.8 ± 4.8 km/s in an eight-fold validation training scheme with the time resolution of the data as small as one hour. The model also has the potential to forecast high speed streams of the SW, which can be quantified with a general threat score of 0.39.

Abstract

A coronal mass ejection erupted from the Sun on 21 April 2023 and created a G4 geomagnetic storm on 23 April. NASA's global-scale observations of the limb and disk (GOLD) imager observed bright equatorial ionization anomaly (EIA) crests at ∼25° Mlat, ∼11° poleward from their average locations, computed by averaging the EIA crests during the previous geomagnetic quiet days (18–22 April) between ∼15°W and 5°W Glon. Reversed C-shape equatorial plasma bubbles (EPBs) were observed reaching ∼±36° Mlat (∼40°N and ∼30°S Glat) with apex altitudes ∼4,000 km and large westward tilts of ∼52°. Using GOLD's observations EPBs zonal motions are derived. It is observed that the EPBs zonal velocities are eastward near the equator and westward at mid-latitudes. Model-predicted prompt penetration electric fields indicate that they may have affected the postsunset pre-reversal enhancement at equatorial latitudes. Zonal ion drifts from a defense meteorological satellite program satellite suggest that westward neutral winds and perturbed westward ion drifts over mid-latitudes contributed to the observed latitudinal shear in zonal drifts.

Abstract

Atmospheric aerosols not only cause severe haze pollution, but also affect climate through changes in cloud properties. However, during the haze pollution, aerosol-cloud interactions are not well understood due to a lack of in situ observations. In this study, we conducted simultaneous observations of cloud droplet and particle number size distribution, together with supporting atmospheric parameters, from ground to cloud base in East China using a high-payload tethered airship. We found that high concentrations of aerosols and cloud condensation nuclei were constrained below cloud, leading to the pronounced “Twomey effect” near the cloud base. The cloud inhibited the pollutants dispersion by reducing surface heat flux and thus deteriorated the near-surface haze pollution. Satellite retrievals matched well with the in situ observations for low stratus clouds, while were insufficient to quantify aerosol-cloud interactions for other cases. Our results highlight the importance to combine in situ vertical and satellite observations to quantify the aerosol-cloud interactions.

Abstract

Freezing temperature parameterization significantly impacts the heat balance at sea-ice bottom and, consequently, the simulated sea-ice thickness. Here, the single-column model ICEPACK was used to investigate the impact of the freezing temperature parameterization on the simulated sea-ice thermodynamic growth during the MOSAiC expedition from October 2019 to September 2020. It is shown that large model errors exist with the standard parameterization and that different formulations for calculating the freezing temperature impact the simulated sea-ice thickness significantly. Considering the winter mixed layer temperature, a modified parameterization of the freezing point temperature based on Mushy scheme was developed. The mean absolute error (ratio) of simulating sea-ice thickness for all buoys reduces from 7.4 cm (4.9%) with the “Millero” scheme, which performs the best among the existing schemes in the ICEPACK model, to 4.2 cm (2.9%) with the new developed scheme.

Abstract

The Emirates Mars Ultraviolet Spectrometer (EMUS), aboard the Emirates Mars Mission (EMM), has been conducting observations of ultraviolet emissions within the Martian exosphere. Taking advantage of the distinctive orbit of the EMM around Mars, EMUS utilizes a dedicated strafe observation strategy to scan the illuminated Martian exosphere at tangential altitudes ranging from 130 to over 20,000 km. To distinguish between emissions of Martian origin and those from the interplanetary background, EMUS conducts specialized background observations by looking away from the planet. This approach has allowed us to investigate the radial and seasonal variations in Martian coronal emission features at H Lyman-α, β and γ wavelengths. Our analysis supports the previous studies indicating that Martian exospheric hydrogen Lyman emission brightness attains its highest levels around the southern summer solstice and reaches its lowest levels when Mars is near aphelion. Additionally, a secondary peak emission at all altitudes is observed after perihelion during Martian Year (MY) 36, which can be attributed to a Class C dust storm. Our study establishes a strong correlation between solar flux and coronal brightness for these emissions, highlighting the impact of solar activity on the visibility of Martian corona. In addition, we have examined interannual variability and found that emission intensities in MY 37 surpassed those in MY 36, primarily due to increased solar activity. These observations help to understand potential seasonal patterns of exospheric hydrogen, which is driven by underlying mechanisms in the lower atmosphere and solar activity, eventually suggesting an impact on water loss in the Martian atmosphere.

Abstract

Quasi 16-day waves (Q16DWs) are a prominent and recurrent phenomenon in the middle atmosphere, typically observed over winter mid and high latitudes. This study investigates the intense Q16DW event during the 2018–2019 Northern Hemisphere (NH) winter, and explores its propagation in the middle atmosphere and its notable influence on the E-region ionosphere. Long-term geopotential height estimates of Aura Microwave Limb Sounder (MLS) reveal that the wave activity under consideration exhibited the largest amplitudes in the mesosphere for past 16 years. An analysis of wind data obtained from medium frequency (MF) and meteor radars, as well as from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis, reveals the presence of a westward-propagating Q16DW with zonal wavenumber 1 exhibiting notable asymmetry about the equator, with the majority of the wave activity being confined to the NH. The prominently large amplitudes and vertical wavelengths of the wave suggest potential for the wave propagation to extend deep into the E-region ionosphere. Swarm satellite observations reveal concurrent ∼16-day oscillations in the eastward component of the geomagnetic field at low latitudes. These oscillations can be attributed to the periodic variations in interhemispheric field-aligned currents (IHFACs). The ∼16-day oscillations in the IHFACs are likely a consequence of asymmetric wind-dynamo action, which is directly or indirectly associated with the Q16DW. These findings suggest that planetary waves originating in the middle atmosphere can cause interhemispheric coupling in the ionosphere.

Abstract

Interplanetary (IP) shocks are one of the dominant solar wind structures that can significantly impact the Geospace when impinge on the Earth's magnetosphere. IP shocks severely distort the magnetosphere and induce dramatic changes in the magnetospheric currents, often leading to large disturbances in the geomagnetic field. Sudden enhancements in the solar wind dynamic pressure (P Dyn) during IP shocks cause enhanced high-latitude convection electric fields which penetrate promptly to equatorial latitudes. In response, the equatorial electrojet (EEJ) current exhibits sharp changes of magnitudes primarily controlled by the change in P Dyn and the local time. In this paper, we further investigated the influence of shock impact angle on the EEJ response to a large number (306) of IP shocks that occurred during 2001–2021. The results consistently show that the EEJ exhibits a heightened response to the shocks that head-on impact the magnetosphere (frontal shocks) than those with inclined impact (inclined shocks). The greater EEJ response during the frontal shocks could be due to a more intensified high-latitude convection electric field resulting from the symmetric compression of the magnetosphere. Finally, an existing empirical relation involving P Dyn and local time is improved by including the effects of impact angle, which can quantitatively better predict the EEJ response to IP shocks.

DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, 2024
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.

Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-73,2024
Preprint under review for GMD (discussion: open, 0 comments)
Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.

Abstract

The orographic effect on the spatial structure of precipitation is a fundamental problem in hydrometeorology that still requires a better understanding of the physical processes involved in the emergence of rainfall patterns and their complex statistical structure. In tropical regions, where meteorological measurements are notoriously sparse and data quality control is often poor or missing, the study of precipitation modeling and prediction is challenging. This research aims to show an innovative approach based on a random cascade downscaling method to generate high-resolution precipitation products from coarse-scale precipitation products. This approach also includes a topographic enhancement function for describing the altitudinal variability of precipitation and a numerical diffusion filter to lessen the blockiness problem of random cascades. The suggested approach was applied to analyze some long-term precipitation statistics in the metropolitan area of Mexico City. The model result agrees closely with the temporal statistics of the selected precipitation products and reflects complex orographic constraints. The proposed downscaling approach becomes an alternative to expensive computational methods and allows urban hydrology applications and analysis of small watersheds to incorporate the effects of complex orography.

Abstract

Fog processing has a significant impact on sulfur chemistry in the atmosphere. This study analyzed three winter fog events in Hong Kong using single-particle aerosol mass spectrometry (SPAMS) and a Monitor for AeRosols and GAses in ambient air (MARGA). Black carbon (BC)-related carbonaceous particles with substantial sulfate amounts comprised the largest particle number fraction (56.7%). Sulfate mass concentration decreased during fog due to the cloud's effective scavenging, but fog processing notably promoted sulfate formation at the single-particle level (average peak area increases of 31.2%). Hydroxymethanesulfonate (HMS), an important S(IV) compound and fog tracer, was identified accounting for up to 12% by particle number fraction. Although pH showed a positive correlation (r = 0.53–0.69) with HMS particles in each fog scenario, a negative overall correlation (r = −0.51) was observed. Further analysis revealed that the higher aerosol acidity (pH 0.65–3.11), promoted Fe dissolution, leading to 49% of HMS particles being mixed with Fe, which potentially facilitated sulfate formation via the Fenton reaction. Additionally, around 40% of HMS-Fe particles are mixed with oxalate, thereby warranting further attention for their potential to cause more intricate sulfur oxidation processes. This study reveals the initial identification of a high mixed-state of HMS-Fe, which could potentially serve as a crucial avenue for the formation of sulfate on individual particulate matter. Considering the persistent augmentation of aerosol acidity in the Asian region, this phenomenon necessitates further investigation and attention.

Abstract

Land management can moderate or intensify the impacts of a warming atmosphere. Since the early 1980s, nearly 116,000 km2 of cropland that was once held in fallow during the summer is now planted in the northern North American Great Plains. To simulate the impacts of this substantial land cover change on regional climate processes, convection-permitting model experiments using the Weather Research and Forecasting model were performed to simulate modern and historical amounts of summer fallow. The control simulation was extensively validated using multiple observational data products as well as eddy covariance tower observations. Results of these simulations show that the transition from summer fallow to modern land cover led to ∼1.5°C cooler temperatures and decreased vapor pressure deficit by ∼0.15 kPa during the growing season across the study region, which is consistent with observed cooling trends. The cooler and wetter land surface with vegetation led to a shallower planetary boundary layer and lower lifted condensation level, creating conditions more conducive to convective cloud formation and precipitation. Our model simulations however show little widespread evidence of land surface changes effects on precipitation. The observed precipitation increase in this region is more likely related to increased moisture transport by way of the Great Plains Low Level Jet as revealed by the ERA5 reanalysis. Our results demonstrate that land cover change is consistent with observed regional cooling in the northern North American Great Plains but changes in precipitation cannot be explained by land management alone.

Abstract

In this study, we have determined the single-crystal elasticity of clinohumite [Mg8.85Ti0.19Si3.93O16(OH1.11F0.89)] using Brillouin measurement up to 21 GPa at 300 K and 1 bar at 750 K, respectively. The elasticity of clinohumite was determined to be K S0 = 126.2(3) GPa, G 0 = 79.7(2) GPa with pressure derivatives K S′ = 4.2(1), G′ = 1.3(1), pressure derivatives ∂K S/∂T = −0.024(1) GPa/K, and ∂G/∂T = −0.011(1) GPa/K). We comprehensively examined the effects of varying H2O, fluorine content and thermal states, on the velocity and density structures of the subducted harzburgite layer. Assuming a typical H2O content of 2 wt.% within harzburgite, our modeling has shown that hydrous harzburgite with clinohumite as the decomposition product of serpentine along a hot slab geotherm even has the V P and V S 0.4–0.8(6)% greater than it dry counterpart at 250–380 km depth. Yet in the top transition zone, the addition of H2O and F can effectively lower the sound velocities and density. The F-bearing hydrous harzburgite has the V P and V S 1.1(5)–1.3(3)% lower than its dry counterpart, and only 0.6(5)% and 2.3(5)% greater than the pyrolitic mantle. Along cold slab geotherm, phase A will replace clinohumite as the dominant hydrous phase in the harzburgite, the V P and V S are 4.8(5)–5.3(3)% and 5.9(5)–6.0(3)% greater than the pyrolitic mantle in the upper mantle. In the top transition zone, the difference is approximately 3% in V P and 5% in V S. Our results provide crucial experimental evidence for future assessments of the seismic signals of subducted slabs with different hydrous minerals and thermal states.

Abstract

Precipitation changes in northern China are projected to increase in the Coupled Model Inter-comparison Project Phase 6 (CMIP6) multi-model ensemble. However, these projections are accompanied by notable inter-model uncertainty, and the sources of this uncertainty remain largely unexplored. By analyzing 30 CMIP6 models, this research explores the source of inter-model uncertainty in projected precipitation change and reveals the fundamental mechanism driving uncertainty spread. Following the empirical orthogonal function of inter-model projected precipitation change, the leading mode displays a seesaw spatial pattern between northwest and north China. This phenomenon predominantly stems from the inter-model divergence of projected sea surface temperature (SST) warming in the North Atlantic. Further scrutinizing the ocean mixed layer heat budget, we discover that the combined effect of surface sensible heat flux, net surface shortwave radiation flux, and ocean heat transport convergence influences heat flux and SST change of North Atlantic. The multi-model projections indicate that localized increases in solar radiation and heat convergence warm sea surface, raising SST and initiating convective motion. This convective motion subsequently transforms the 200 hPa teleconnection wave train, leading to an anti-phase pattern over northern China. This wave pattern modulates total cloud cover percentage, influences surface upward latent heat flux, and adjusts the top of atmosphere outgoing longwave radiation, collectively resulting in the seesaw pattern. Our study underscores the pivotal role of inter-model disparities in North Atlantic SST warming projection, which is a primary driver of precipitation uncertainty in northern China. These insights offer an essential foundation for refining and diminishing inter-model uncertainty.

Abstract

This study focuses on the causes for the generation of equatorial plasma bubbles (EPBs) over the Indian subcontinent and their correlation with atmospheric-ionospheric disturbances resulting from the eruption of the Tonga volcano on 15 January 2022. Concurrent ionosonde observations obtained from Tirunelveli (8.67°N, 77.81°E) and Prayagraj (25.41°N, 81.93°E) show the presence of spread-F traces in ionograms. Notably, the EPBs are also accompanied by plasma blobs (PBs), with their pronounced occurrence during midnight at Prayagraj and Tirunelveli. Analysis of in situ electron density observations obtained from the Swarm B and C satellites reveals substantial plasma density depletions associated with EPBs. An intriguing observation is the intensification of Pre-Reversal Enhancement (PRE) immediately preceding the onset of spread-F at Tirunelveli due to enhanced eastward F region zonal winds by Tonga Volcano, as seen in the satellite observations. Furthermore, the isofrequency analysis from Tirunelveli shows the presence of gravity wave-like oscillations in the equatorial F-region over India. The investigation of Total Electron Content (TEC) obtained from a Pseudo Random Number (PRN)-14 over Indian longitudes suggests the presence of two dominant modes of Traveling Ionospheric Disturbances (TIDs) with speeds ∼452 m/s and ∼406 m/s having periods in the range of ∼65–75 min. These observations reaffirm that volcano triggered atmospheric/ionospheric disturbances can propagate long distances for several hours and can provide necessary seeding conditions for the generation of EPBs.

Review article: Research progress on influencing factors, data, and methods for early identification of landslide hazards
Heng Lu, Zhengli Yang, Kai Song, Zhijie Zhang, Chao Liu, Ruihua Nie, Lei Ma, Wanchang Zhang, Gang Fan, Chen Chen, and Min Zhang
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-68,2024
Preprint under review for NHESS (discussion: open, 2 comments)
1. Sort out the characteristics, functions, links, and application scope of various measuring tools. 2. Bibliometric analysis of early identification methods for landslide hazards. 3. Review the influencing factors of landslides and summarize data links and application literature. 4. Focused on analyzing 5 early landslide identification methods. 5. In-depth exploration of the internal connections of literature and future development directions.

How can seismo-volcanic catalogues be improved or created using robust neural networks through weakly supervised approaches?
Manuel Titos, Carmen Benítez, Milad Kowsari, and Jesús M. Ibáñez
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-102,2024
Preprint under review for NHESS (discussion: open, 0 comments)
Developing seismo-volcanic monitoring tools is crucial for Volcanic Observatories. Our study reviews current methods using Transfer Learning techniques and finds that while these systems identify nearly 90 % of seismic events, they miss other important volcanic data due to the catalogue-learning bias. We propose a weakly supervised technique to reduce bias and uncover new volcanic information. This method can improve existing databases and create new ones efficiently using machine learning.

Observations of traveling ionospheric disturbances driven by gravity waves from sources in the upper and lower atmosphere
Paul Prikryl, David R. Themens, Jaroslav Chum, Shibaji Chakraborty, Robert G. Gillies, and James M. Weygand
Ann. Geophys. Discuss., https//doi.org/10.5194/angeo-2024-6,2024
Preprint under review for ANGEO (discussion: open, 3 comments)
Travelling ionospheric disturbances are plasma density fluctuations usually driven by atmospheric gravity waves in the neutral atmosphere. The aim of this study is to attribute multi-instrument observations of travelling ionospheric disturbances to gravity waves generated in the upper atmosphere at high latitudes or gravity waves generated by tropospheric weather systems at mid latitudes.

Abstract

The intense electron-scale current structures (ECSs) with the current density J ≥ 30 nA/m2 are often observed in the Plasma Sheet (PS) during high-speed bulk flows. Using MMS observations we have analyzed 41 earthward and 37 tailward flow intervals and found 452 and 754 ECSs distributed over the PS region, respectively. Almost all ECSs are generated by high-speed electron beams. The duration of ECSs is ≤1 s, and many of them have a half-thickness L ≤ a few ρ e (ρ e is the gyroradius of thermal electrons). In such thin ECSs electrons become demagnetized and experience the dynamics like that observed in the electron diffusion region. Strong nonideal electric fields (E’) associated with violation of frozen-in condition for electrons are observed in the ECSs. This results in the intense energy conversion with J·E’ up to hundreds pW/m3. The major part of the dissipating energy is transferred to electron heating and acceleration. We suggest that the ECSs are manifestations of kinetic-scale turbulence driven by the high-speed ion bulk flows. The inductive electric fields generated by the growing magnetic fluctuations accelerate electron beams which, in turn, generate the ECSs. The ECSs thinning during their evolution, probably, stops for L ≤ a few ρ e . Further thinning leads to development of kinetic instability causing the current disruption and strong electric field generation. The last accelerates new electron beams which generate new ECSs in other locations. Thus, the life cycles of the ECSs contribute to energy cascade in turbulent plasma at electron kinetic scales.