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Abstract

In July and August 2022, the Yangtze River basin (YRB) experienced its hottest summer since 1961. The SINTEX-F2 seasonal prediction system initialized in early May predicted the hotter-than-normal summer due to its successful prediction of central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the tropical West Pacific-East Indian Ocean (TWP_EIO). The common SST forcing explains only about 26% to the heatwave strength, while the internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land-air interaction account for approximately 65%, based on the analysis of 108 ensemble members. These factors have collectively increased the maximum temperature over the YRB through the enhancement and westward expansion of western North Pacific subtropical high. Our findings quantify the relative contributions of external forcing and internal variations to the unprecedented hot event, offering insights into its forming mechanism and potential predictability.

Abstract

Currently, there is no clear understanding of the comprehensive set of variables that controls fluxes of relativistic electrons within the outer radiation belt. Herein, the methodology based on causal inference is applied for identification of factors that control fluxes of relativistic electrons in the outer belt. The patterns of interactions between the solar wind, geomagnetic activity and belt electrons have been investigated. We found a significant information transfer from solar wind, geomagnetic activity and fluxes of very low energy electrons (54 keV), into fluxes of relativistic (470 keV) and ultra-relativistic (2.23 MeV) electrons. We present evidence of a direct causal relationship from relativistic into ultra-relativistic electrons, which points to a local acceleration mechanism for electrons energization. It is demonstrated that the observed information transfer from low energy electrons at 54 keV into energetic electrons at 470 keV is due to the presence of common external drivers such as substorm activity.

Abstract

Using NASA's Global-scale Observations of the Limb and Disk (GOLD) imager, we report nightside ionospheric changes during the G5 super geomagnetic storm of 10 and 11 May 2024. Specifically, the nightside southern crest of the Equatorial Ionization Anomaly (EIA) was observed to merge with the aurora near the southern tip of South America. During the storm, the EIA southern crest was seen moving poleward as fast as 450 m/s. Furthermore, the aurora extended to mid-latitudes reaching the southern tips of Africa and South America. The poleward shift of the equatorial ionospheric structure and equatorward motion of the aurora means there was no mid-latitude ionosphere in this region. These observations offer unique insights into the ionospheric response to extreme geomagnetic disturbances, highlighting the complex interplay between solar activity and Earth's upper atmosphere.

Multi-decadal atmospheric carbon dioxide measurements in Hungary, central Europe
László Haszpra
Atmos. Meas. Tech., 17, 4629–4647, https://doi.org/10.5194/amt-17-4629-2024, 2024
The paper evaluates a 30-year-long atmospheric CO2 data series from a mid-continental central European site, Hegyhátsál (HUN). It presents the site-specific features observed in the long-term evolution of the atmospheric CO2 concentration. Since the measurement data are widely used in atmospheric inverse models and budget calculations all around the world, the paper provides potentially valuable information for model tuning and interpretation of the model results.

Negative Differential Resistance, Instability, and Critical Transition in Lightning Leader
Xueqiang Gou, Chao Xin, Liwen Xu, Ping Yuan, Yijun Zhang, and Mingli Cheng
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2024-15,2024
Preprint under review for NPG (discussion: open, 0 comments)
Our research examines lightning's complex behavior by studying changes in its electrical pathways under different conditions. We found that lightning channels switch between stable and unstable states based on their length and surrounding electric fields. This helps explain why lightning often reactivates after a brief pause and offers new insights into these processes. Our findings could improve lightning prediction and protection, benefiting scientific understanding and public safety.

Science, Volume 385, Issue 6709, August 2024.

Science, Volume 385, Issue 6709, August 2024.

Science, Volume 385, Issue 6709, August 2024.

Science, Volume 385, Issue 6709, August 2024.

Science, Volume 385, Issue 6709, August 2024.

Performance evaluation of an online monitor based on X-ray fluorescence for detecting elemental concentrations in ambient particulate matter
Ivonne Trebs, Céline Lett, Andreas Krein, Erika Matsumoto Kawaguchi, and Jürgen Junk
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-134,2024
Preprint under review for AMT (discussion: open, 0 comments)
This study explores the effectiveness of the Horiba PX-375 monitor for analyzing the elemental composition of airborne particulate matter (PM). Understanding this composition of PM is important for identifying its sources, assessing potential health risks, and developing strategies to reduce air pollution. The PX-375 monitor proved to be a valuable tool for ongoing air quality monitoring studies and could be particularly useful as pollution levels and sources change in the future.

HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, 2024
Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.

Risk-informed representative earthquake scenarios for Valparaíso and Viña del Mar, Chile
Hugo Rosero-Velásquez, Mauricio Monsalve, Juan Camilo Gómez Zapata, Elisa Ferrario, Alan Poulos, Juan Carlos de la Llera, and Daniel Straub
Nat. Hazards Earth Syst. Sci., 24, 2667–2687, https://doi.org/10.5194/nhess-24-2667-2024, 2024
Seismic risk management uses reference earthquake scenarios, but the criteria for selecting them do not always consider consequences for exposed assets. Hence, we adopt a definition of representative scenarios associated with a return period and loss level to select such scenarios among a large set of possible earthquakes. We identify the scenarios for the residential-building stock and power supply in Valparaíso and Viña del Mar, Chile. The selected scenarios depend on the exposed assets.

The effect of slab touchdown on anticrack arrest in propagation saw tests
Philipp L. Rosendahl, Johannes Schneider, Grégoire Bobillier, Florian Rheinschmidt, Bastian Bergfeld, Alec van Herwijnen, and Philipp Weißgraeber
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-122,2024
Preprint under review for NHESS (discussion: open, 0 comments)
Our research investigates the role of anticracks in snowpacks and their impact on avalanche formation, focusing on anticracks due to weak layer collapse. We discovered that slab touchdown on the snow below the weak layer decreases the energy available for crack propagation, potentially leading to a stop of crack propagation. This underscores the importance of mechanical interactions in snowpack stability. Our work offers new insights for enhancing avalanche prediction and mitigation strategies.

Abstract

The earliest Asian summer monsoon onset (SMO) occurs in the Bay of Bengal (BoB), heralding the coming of the rainy season. In late April or early May, the strong sea surface temperature (SST) diurnal variation accompanied by ocean surface warming triggers the SMO. However, this observed diurnal cycle intensity cannot be reasonably simulated by state-of-the-art climate models, resulting in a spurious delayed SMO. To address this issue, the SST diurnal cycle parameterized by a diagnostic sublayer scheme was incorporated into a climate model named FIO-ESM v2.0. The large diurnal amplitude of SST contributes to surface warming and changes atmospheric circulation. Consequently, the high-pressure anomaly at high levels and an inverted trough at low levels promote more convective activity, triggering an earlier SMO. Our findings improve the ability of climate models in simulating the evolution of the Asian monsoon system.

Abstract

Powerful lightning strikes generate broadband electromagnetic signals. At Extremely Low Frequencies (ELF), the signal partly leaks into the ionosphere and produces whistlers that can be detected by satellites. Indeed, the satellites of the European Space Agency (ESA) Swarm Earth Explorer mission can detect those signals during 250 Hz burst-mode acquisition campaigns of their Absolute Scalar Magnetometers (ASM). The dispersion of these whistlers depends on their propagation path and the distribution of ionization in the ionosphere crossed along that path. In this paper, we introduce a technique to derive a new measure of ionosphere electron content, the Total square-Root Electron Content (TREC), using the arrival times of two frequencies of the whistler signal. We validate this approach by using data from ionosondes and from in situ measurements of the electron density at Swarm location. This technique brings new opportunities for sounding the ionosphere in regions poorly observed by other techniques.

Abstract

The tropical arm of Atlantic Multidecadal Variability (AMV) influences climate worldwide, yet the mechanisms generating it remain unclear. Here, we examine experiments with sea surface temperature (SST)-restoring in the extratropical North Atlantic in multiple models and use mixed-layer heat budgets to elucidate the important mechanisms. Our results demonstrate that the tropical AMV is driven by wind-mixed-layer-SST feedback. The evolution has two phases with tropical AMV SST anomalies growing from April to October and decaying from November to March. The amplitude of the growth phase surpasses that of the decay phase, resulting in overall tropical Atlantic warming during positive AMV phases. During summer, positive SST anomalies in the extratropics weaken the trade winds, resulting in a shallower mixed-layer with reduced heat capacity. Subsequent absorption of climatological shortwave radiation in this shallower mixed-layer then causes SSTs to warm, generating the tropical AMV. Importantly, anomalous surface heat-fluxes make modest contributions to tropical AMV in these experiments.

Abstract

In this work, we present a metastable helium lidar system for the measurements of metastable helium He(23S) density in the thermosphere and lower exosphere. This lidar system consists of a high power 1,083 nm pulsed laser, a 1 m aperture laser beam expander, six 1 m aperture receiving telescopes and a superconducting nanowire single-photon detector (SNSPD). This system realizes metastable helium density detection up to 1,000 km. Daily rapid variation of metastable helium density within several hours was measured with a height resolution of 50 km for the first time. It demonstrates the capability of ground-based lidar for continuous height-resolved detection of the atmospheric metastable helium in the height range of 200–1,000 km. This is a promising tool to help study the coupling of neutral and ionized atmosphere in this height range and further providing observation basis for space weather prediction.

Abstract

The closure of an ancient ocean basin via oceanic arc-continent collision has two subduction styles with opposite polarities, which may proceed via subduction polarity reversal (SPR) or a subduction zone jump (SZJ). Interpreting the geometry or kinematic evolution of ancient collisional zones, especially the original subduction polarity, can be challenging. Here we used 2D thermo-mechanical modeling to investigate the dynamic evolution process of SPR versus SZJ. Our modeling predicts different structural, topographic, magmatic, and basin histories for SPR and SZJ, which can be compared against, and help interpret, the geologic record past sites of oceanic closure during collisional orogens. Our results match geologic observations of past collisions in Kamchatka, eastern Russia, and the Banda Arc, eastern Indonesia, and thus our results can help effectively decode the evolutionary history of past arc-continent collisions.

Abstract

To better understand and improve the prediction of the seasonal surface temperature (TS) across the United States, we employed convolutional neural network (CNN) models trained on the Community Earth System Model Version 2 Large Ensemble (CESM2 LENS). We used lagged sea surface temperatures (SST) over the tropical Pacific region, containing the information of the El Niño Southern Oscillation (ENSO), as input for the CNN models. ENSO is the principal driver of variability in seasonal US surface temperatures (TSUS) and employing CNN models allows for spatiotemporal aspects of ENSO to be analyzed to make seasonal TSUS predictions. For predicting TSUS, the CNN models exhibited significantly improved skill over standard statistical multilinear regression (MLR) models and dynamical forecasts across most regions in the US, for lead times ranging from 1 to 6 months. Furthermore, we employed the CNN models to predict seasonal TSUS during extreme ENSO events. For these events, the CNN models outperformed the MLR models in predicting the effects on seasonal TSUS, suggesting that the CNN models are able to capture the ENSO-TSUS teleconnection more effectively. Results from a heatmap analysis demonstrate that the CNN models utilize spatial features of ENSO rather than solely the magnitude of the ENSO events, indicating that the improved skill of seasonal TSUS is due to analyzing spatial variation in ENSO events. The proposed CNN model demonstrates a promising improvement in prediction skill compared to existing methods, suggesting a potential path forward for enhancing TSUS forecast skill from subseasonal to seasonal timescales.