Geophysical Research Letters

Plain Language Summary When solid grains are compressed against each other in an aqueous environment, minerals at the grain‐to‐grain contact dissolve more easily because of the higher stress. This process is known as pressure solution, which involves dissolution reactions and diffusive solute transport. We have developed an analytical model with fully coupled reaction and diffusion processes. Our model can recover the analytical solutions in the literature that are developed for reaction‐dominant and diffusion‐dominant scenarios. The proposed model is also validated against independent numerical simulations. After validation, we employ the model in experimental measurement, where the measured data is interpreted more accurately compared to previous models.

We investigate the impacts of meltwater from Antarctic Ice Sheet (AIS) mass loss on New Zealand climate in a state‐of‐the‐art global climate model. We conduct simulations with additional meltwater from AIS mass loss for both the historical period and a high‐emissions future scenario. The ocean surface to the southeast of New Zealand cools, with the largest change in winter and spring. The additional meltwater results in a northward shift of the oceanic sub‐tropical front near New Zealand, which partially offsets the projected southward shift of this front in a warming climate. Wintertime surface westerly winds to the south of New Zealand also increase with the addition of the meltwater. The magnitude of the impact of Antarctic meltwater is uncertain due to the wide spread in estimates of Antarctic mass imbalance, but has important implications for future projections for New Zealand climate.

Plain Language Summary The El Niño–Southern Oscillation (ENSO) is a climate phenomenon that exerts global environmental and socioeconomic effects. Understanding and extending the predictability of ENSO is one of the most important issues in climate science. The North Pacific Victoria mode (VM) has been demonstrated as a precursor signal for ENSO events in observations and models, which may potentially improve ENSO prediction. However, some studies suggest that the VM can increase the prediction uncertainty of ENSO through air‐sea coupling processes, which may limit ENSO prediction skill. To address the controversy, this study employed the signal‐to‐noise ratio method to evaluate the contribution of the VM to ENSO predictability in forecast models. The results show that the VM can increase the potential predictability of ENSO, suggesting that the VM primarily acts as a signal in ENSO prediction. The accurate simulation of the robust relationship between the VM and ENSO is essential to improve ENSO predictability and prediction in forecast models.

Due to the wide range of processes impacting the sea surface height (SSH) on daily‐to‐interannual timescales, SSH forecasts are hampered by numerous sources of uncertainty. While statistical‐dynamical methods like Linear Inverse Modeling have been successful at making forecasts, they often rely on assumptions that can be hard to satisfy given the nonlinear dynamics of the climate. Here, we train convolutional autoencoders with a dynamical propagator in the latent space to generate forecasts of SSH anomalies. Learning a nonlinear dimensionality reduction and the prediction timestepping together results in a propagator that produces better predictions for daily‐ and monthly‐averaged SSH in the North Pacific and Atlantic than if the dimensionality reduction and dynamics are learned separately. The reconstruction skill of the model highlights regions in which better representation results in improved predictions: in particular, the tropics for North Pacific daily SSH predictions and the Caribbean Current for the North Atlantic.

Chemical cycling drives the production and loss of many important atmospheric constituents. The speed of atmospheric chemical cycling is a particularly valuable indicator for characterizing and measuring the effects of such cycles on oxidant chemistry, air quality, and climate. Here, we apply graph theoretical methods to explicitly quantify and analyze the characteristic timescales of gas‐phase chemical cycles in the troposphere and stratosphere, as simulated by the GEOS‐Chem chemical mechanism. We identify all two‐, three‐, and four‐reaction cycles in the mechanism and calculate a characteristic timescale for each individual cycle. We find that the speed of chemical cycling varies by orders of magnitude at any given location but tends to be faster in urban‐ and biogenically‐dominated chemical regions, and slower during the night. We further quantify the fraction of cycling that contains a rate‐determining step, and explicitly demonstrate the large potential for mechanisms to recycle oxidants like OH.

Plain Language Summary Lakes and ponds are key indicators of the Arctic's vulnerability to rapid warming. Their presence influences the water cycle, wildlife habitat, permafrost temperatures, and the balance between carbon storage and release to the atmosphere. Scientists expect permafrost thaw to cause lake area to decline over time, representing a major shift in the landscape with consequences for ecosystems, water resources, and carbon cycling. The extent of lake drainage across the northern permafrost zone remains unclear, especially given recent studies that have found both increasing and decreasing lake area. Here, we demonstrate that differences in glacial history and geology can explain many of the conflicting trends reported in these previous studies. We show that thawing permafrost tends to reduce lake area in regions without past glaciation. However, in regions shaped by glaciers, lake areas can slightly increase with permafrost thaw. To do this, we use the new the Alaska Lake and Pond Occurrence Data set, which maps over 800,000 lakes and ponds and their seasonal fluctuations in unprecedented detail. We discuss potential mechanisms for long‐term landscape evolution to influence modern lake responses to permafrost thaw. Finally, we use our results to improve projections of future changes to lake area across Alaska.

Plain Language Summary Evaporation plays a key role in the transfer of water and energy from Earth's surface to the atmosphere. Although the physical processes that govern it are well‐understood, much less is known about its extremes. In this study, a statistical framework is introduced which defines its extremes as individual events with a beginning and an ending. By applying this methodological approach over Czechia, we can see that ExEvEs tend to form clusters of heightened evaporation lasting several days. In summer, these events are linked to sunny, dry conditions, while in winter, they are driven by wet weather and longwave radiation. Since 1981, the frequency and intensity of ExEvEs in Czechia have risen sharply, much more dramatically than overall evaporation. This increase has significant effects on the amount and speed of water exchange between land and atmosphere. The proposed framework provides a systematic way to identify, study, and understand evaporation extremes, shedding light on their causes, effects, and seasonal patterns.

Juno performed close flybys of the innermost Galilean moon, Io, in December 2023 (I57) and February 2024 (I58). During these flybys, the radio link connecting the Juno spacecraft to Earth observing stations of NASA's Deep Space Network (DSN) propagated through the Alfvén wing, a magnetospheric feature in which plasma is produced between Io and Jupiter. The radio link is sensitive to the elevated electron densities in the Alfvén wing. A direct measurement of the total electron content was made by a linear combination of Juno's X‐band and Ka‐band downlink frequencies. Two different approaches were used in inverting the measurements into electron densities which assume different electron density distributions within the Alfvén wing. The maximum electron densities estimated in the Alfvén wing were 20,500–27,000 cm⁻³ on I57, in the northern Alfvén wing, and 15,300–31,000 cm⁻³ on I58, in the southern Alfvén wing.

Plain Language Summary Quantifying the dispersion coefficient is one of the most fundamental aspects of transport in porous materials with direct application in energy storage/recovery, or pollutant/nutrient transport in subsurface media. Dispersion arises from the availability of variable flow paths, resulting in a spectrum of transient times that solute particles can experience for transport through porous media. Porous media are often heterogeneous structures with irregular flow paths, making the prediction of solute spreading challenging. In nature, a common phenomenon that impacts the geometry of media is erosion. We analyze solute spreading under single‐phase conditions in media with different degree/type of erosion. We found a non‐monotonic erosion‐dispersion relation. Depending on the transport regime, our investigation shows that erosion can either enhance solute spreading (for diffusion‐dominated transport) or limit it (for advection‐dominated transport). While mechanical erosion through particle migration creates media with a multi‐modal variation in pore size distribution, chemical erosion, which involves particle shrinkage, primarily widens pore spaces without significantly altering the initial pore size distribution. These findings mark a crucial advancement in predicting the fate of injected or released solute species into natural porous media, particularly in the context of ongoing changes in pore space properties driven by erosion.

Plain Language Summary Seismic events in the shallow subsurface can be caused by industrial activities, such as pumping operations in geothermal power plants. In recent years, it has been recognized that brief pauses in geothermal production are associated with increased seismicity, a phenomenon that was rarely reported before. The San Emidio geothermal field in Nevada, USA is a natural experiment site to study this phenomenon. In April 2022, a planned power plant shutdown at San Emidio was monitored using dense seismic and hydrologic instrumentation, providing an excellent opportunity to understand its underlying mechanisms. Using data from the dense seismic array with state‐of‐the‐art seismic detection, location, and tomography techniques, we developed a microseismic event catalog with high‐precision event locations and a high‐resolution three‐dimensional P‐wave seismic velocity model. Our results, combined with hydrologic data, support the hypothesis that the cessation of production rapidly increased fluid pressures along pre‐existing fault zones, activating critically stressed fault patches and fractures and producing microseismicity.

Plain Language Summary Humid heat extremes, characterized by high wet bulb temperature (Tw), pose health risks even to young, healthy individuals. While strong El Niño events are known to affect extreme Tw days, the impact of different El Niño types (Central Pacific and Eastern Pacific) has not been well studied. Using historical data and future climate projections, we examined how these El Niño types affect the frequency and spatial extent of dangerous Tw. Our analysis shows that under future warming, Eastern Pacific and Central Pacific El Niño events drive distinctly different, regionally varying patterns of dangerous Tw, yet both significantly increase the affected population and area impacted by humid heat extremes at all global warming levels. Even at low global warming levels, during El Niño events, the population exposed to dangerous Tw is expected to be equal to that exposed regularly when the mean warming is more than four times higher. This highlights the need to consider El Niño diversity in assessing the additional heat stress in heavily populated regions as the planet warms and approaches the critical threshold of heat stress.

Plain Language Summary We study how ocean heat transport (OHT) influences the atmospheric circulation in the major western boundary currents (WBCs) of both hemispheres, including the Gulf Stream, Kuroshio‐Oyashio Extension, Brazil‐Malvinas Confluence, and Agulhas Currents. We find that the heating due to anomalous ocean heat transport causes air to rise on the equatorward side of the largest surface heating in all WBC regions. The regions of rising air are also associated with more intense convective precipitation. The effect is strongest in the Northern Hemisphere (NH) where the atmospheric response extends to the upper troposphere, leading to significant heating and atmospheric circulation anomalies aloft. The findings highlight the robustness of the atmospheric response to ocean dynamical processes in the western boundary currents, although differences in the hemispheric responses are noteworthy. In the NH WBCs, the atmospheric response to OHT anomalies is balanced primarily through vertical air movement, whereas in the Southern Hemisphere, the response is balanced primarily by low‐level horizontal temperature advection.

Plain Language Summary The new Surface Water and Ocean Topography (SWOT) mission is the first satellite altimeter to observe changes in the height of the sea surface over broad swaths at high resolution. To obtain high accuracy measurements various corrections are needed for the raw radar measurements. One of the required corrections accounts for the water vapor in the atmosphere which delays the radar signal. Although SWOT sea surface measurements are at high resolution, the correction available for the water vapor in the atmosphere is at a lower resolution, which could possibly affect interpretation of SWOT observations. Here we use a high‐resolution atmospheric model and a set of GNSS buoys to investigate the variations of atmospheric water vapor over shorter distances in Australian coastal waters. We find that the variation is higher than the SWOT error budget and that a higher‐resolution correction for moisture in the atmosphere is often needed to ensure the correct interpretation of SWOT observations.

The Southern Ocean plays a vital role in global CO2 uptake, but the magnitude and even the sign of the flux remain uncertain, and the influence of phytoplankton phenology is underexplored. This study focuses on the West Antarctic Peninsula, a region experiencing rapid climate change, to examine shifts in seasonal carbon uptake. Using 20 years of in situ air‐sea CO2 flux and satellite‐derived Chlorophyll‐a, we observe that the seasonal cycles of both air‐sea CO2 flux and Chlorophyll‐a intensify poleward. The amplitude of the seasonal cycle of the non‐thermal component of surface ocean pCO2 increases with increasing latitude, while the amplitude of the thermal component remains relatively stable. Pronounced biological uptake occurs over the shelf in austral summer despite reduced CO2 solubility in warmer waters, which typically limits carbon uptake through physical processes. These findings underscore the prominence of biological mechanisms in regulating carbon fluxes in this rapidly changing region.

We present consecutive observations of Flux Transfer Events (FTEs) on 10 November 2020, using MMS, THEMIS and Cluster spacecraft located at different magnetopause locations. Two typical scale FTE signatures are successively observed by low‐latitude THEMIS, mid‐latitude MMS and high latitude Cluster, reflecting their global spatial scale characteristics. Multi‐spacecraft observation also revealed the complete 3‐D structure of the FTEs, with azimuthal extended section, magnetosheath and magnetospheric arm. The simultaneous existence of different magnetic field line topologies during the FTEs indicates the generation mechanism of multiple X‐line reconnection. Successive observations with intervals of several minutes revealed some evolutionary features of FTEs, including an increase in size and flux, and disappearance of the magnetic dip region on both sides. Our observations give a complete 3‐D picture of FTEs on a global scale, which can improve our understanding of the transient magnetic reconnection and solar wind‐magnetosphere interaction at the magnetopause.

Black carbon (BC) is considered as an important contributor to the Himalayan glaciers melt in the past few decades. However, the long‐term source apportionment of BC remains unclear. Here we present the first radiocarbon (¹⁴C)‐based annual variation of BC source apportionment in an ice core spanning the period of 1959–2012 drilled from the Southeastern Tibetan Plateau, a receptor site of South Asia outflow. We find fossil fuel combustion is a major contribution (73% ± 5%), yet the biomass burning fraction (ƒbiomass) has grown from 24% ± 4% to 30% ± 4% since 1990. Intriguingly, we further find the ƒbiomass demonstrating a robust correlation with South Asian wildfires linked to climate oscillations. Thus, for mitigating BC impacts on Himalayan glaciers, South Asia's transition from fossil fuels to clean energy is a more efficient and urgent strategy than reducing residential biomass burning.

Knowledge about orientation of falling snow is still poorly documented with field measurements despite its importance, for example, in the interpretation of remote sensing data. This study investigates the orientation of snow hydrometeors using data from a Multi‐Angle Snowflake Camera. We explore the impact of different observational setups (sheltered vs. unsheltered), wind speed, hydrometeor type, and axis ratio on the orientation distributions. Numerical simulations are used to select the best orientation estimator and to understand the reason behind contrasting results reported in past literature. We find that previously reported non‐zero median orientations are likely artifacts due to averaging absolute values of orientations from the three individual cameras. Observed orientations generally follow a symmetrical distribution around 0° ${}^{\circ}$, with broader distributions observed at unsheltered sites and/or high wind conditions. Observed distributions may vary significantly from those assumed in previous studies, highlighting the need for further research on hydrometeor orientations under varying environmental conditions.

Plain Language Summary Seismic ruptures—that initiate rapid slip along tectonic faults during earthquakes—are known to propagate with two different styles; either as crack‐like ruptures, analogous to fracture in brittle materials, or as pulse‐like ruptures, where the motion of the fault resembles the crawling of a caterpillar. The reason why some seismic ruptures are predominantly pulse‐like is a central question in earthquake science that impacts our understanding of how faults operate, of how seismic ruptures move and arrest and, thereby, of what controls the size of an earthquake and the hazard that it poses. The difficulty in answering these questions often ties to the complexity of the processes involved during seismic ruptures and the limited ways to observe them at several kilometers depth. This work proposes a generic model, with a minimal number of parameters, to study and predict the style of seismic ruptures. The domain near tectonic faults often comprises densely fractured rocks, and our generic model illuminates how the reduction of stiffness in this damaged region directly impacts the seismic rupture style. Our model also predicts that slip direction could be reversed in the wake of a pulse‐like rupture, a process that can create additional damage.

Plain Language Summary The South Slope of the Himalayas (SSH), known for its unique biodiversity and complex role in climate regulation, is undergoing noticeable changes in vegetation due to climate change. Due to diverse climatic environments and abrupt elevational variations, this region has different vegetation zones. However, there remains a gap in comprehensive studies addressing these changes. To fill this gap comprehensively, we utilized Normalized Vegetation Difference Index (NDVI) from 2000 to 2022 to analyze variations in naturally vegetated surface across the elevation and their correlation with climate. Our results revealed a significant increase in vegetation greenness across SSH and subregions (except Eastern Himalaya (EH)). The relative change rate (RCR) of NDVI indicated stronger vegetation growth at higher elevations from ∼2,600 to ∼5,000 m, followed by a decline in all subregions. Interestingly, further analyses revealed a warming induced vegetation growth in highland areas across the region, while lowland region faced heat stress in the Central Himalay (CH), and Western Himalaya (WH). Conversely, precipitation promoted vegetation in the middle‐elevated areas, although EH faced waterlogging stress. These contrasting responses, patterns, and trends in vegetation changes in the Himalayas highlight the need for a comprehensive understanding of specific spatial variations when devising climate change adaptation strategies.

Plain Language Summary Precipitation loss plays a major role in removing ions from the ring current and is a key reason why the ring current decays quickly during geomagnetic storms. Understanding the evolution of proton precipitation loss is critical to better understanding the ring current dynamics. Recent observations show the development of a notable reduction in phase space density (PSD) radial profiles, called deepening PSD minima, indicating fast local precipitation loss potentially caused by wave‐induced scattering. In this study, we present a comprehensive analysis of the evolution of ring current protons in Earth's inner magnetosphere, specifically focusing on these deepening PSD minima. Using >6 years of observations from the Van Allen Probes, we show that the overall occurrence rates of proton deepening PSD minimum peaks at ∼3%, mainly located at ∼4.5–5.0 Earth radii. The occurrence rate increases with increasing levels of geomagnetic/solar wind conditions. Theoretical calculations indicate that these protons with deepening PSD minima can resonate with electromagnetic ion cyclotron (EMIC) waves, a major type of plasma waves in Earth's magnetosphere. As a result, our study suggests that EMIC waves are the likely cause of the deepening PSD minima and contribute to the fast local loss of ring current protons.

Plain Language Summary The Younger Dryas (YD) cold event is thought to have been triggered by a weakening of the Atlantic Meridional Overturning Circulation, driven by an influx of freshwater into the North Atlantic Deep Water formation region. Determining the source, timing, and magnitude of this freshwater input is critical for understanding the associated climate change. In this study, we analyzed the hydrogen isotopic composition of various lipids in a sediment core from the Canadian Beaufort Sea to investigate these hydrological changes. Our results show that terrestrial leaf wax lipids and microalgae lipids recorded distinct freshwater signals during the YD, allowing for a better constraint on the source and magnitude of this freshening. Using an established empirical relationship between lipid hydrogen isotopes and sea surface salinity, we estimated that surface waters in the Canadian Beaufort Sea experienced a substantial salinity reduction of approximately 15–24 during the YD. This significant decrease was likely caused by a combination of a freshwater outburst and the Laurentide Ice Sheet (LIS) melting water discharge. Following the LIS retreat, the δ²Hlipid indicates that the region likely experienced a shift toward a drier climate during the mid‐to‐late Holocene (∼8–0 cal. kyr BP).

This study examines the impact of the 10 May 2024, geomagnetic storm on the Mexican power grid, utilizing geomagnetically induced currents (GIC), measurements and regional magnetic field data recorded by the Laboratorio Nacional de Clima Espacial. Significant GIC were observed at three different locations within the grid. The observations were complemented with estimates for the Mexican power grid provided by a numerical model developed in late 2022. Our findings suggest that the GIC can pose a potential threat to low‐latitude power grids during extreme geomagnetic disturbances. Furthermore, the model demonstrates its potential to forecast the grid response during these events, providing critical insight into the behavior of the electrical grid during extreme space weather events.

Plain Language Summary As a sophisticated monitoring tool, weather radar occupies a pivotal position in convective nowcasting. While numerous contemporary deep learning approaches predominantly concentrate on refining network architectures using radar reflectivity as the sole input, the impact of atmospheric physical information on nowcasting remains underexplored. To incorporate the contextual backdrop of atmospheric states in nowcasting, we devise a comprehensive deep learning framework that integrates atmospheric variables across multiple levels. To enhance generalization, we employ a transfer learning strategy to extract generalized spatialtemporal features. Rather than emphasizing a specific network design, we underscore the advantages of harnessing multi‐source data and the decision mechanism of the model. By fusing atmospheric variables and radar reflectivity, and adopting a pre‐training and fine‐tuning approach, we achieve more reliable and resilient nowcasting. Overall, our successful implementation of transfer learning within this multi‐modal model offers promising insights for advancing the field of nowcasting.

Plain Language Summary A major ocean current system called the Atlantic meridional overturning circulation (AMOC) is slowing down. The AMOC plays a crucial role in regulating Earth's climate by distributing heat across the globe. While computer models suggest that the melting of Arctic sea‐ice, caused by human activities, is leading to this slowdown, there hasn't been conclusive observational evidence to confirm this link. In our study, we provide such evidence that the reduction of Arctic sea‐ice, especially during the summer months, is causing the SST fingerprint of AMOC to weaken. We analyzed data from the past century and found that this effect was particularly strong between the 1950s and 1980s, a period known for significant changes in ocean salinity called the Great Salinity Anomaly. Using advanced analytical methods, we showed that decreases in sea‐ice lead to changes in the AMOC‐SST, but with a delay of one to three decades. Our findings are important because they confirm the link between human‐induced sea‐ice loss and changes in major ocean currents. This enhances our understanding of climatic forcing factors and helps inform policy decisions aimed at mitigating these effects.

Plain Language Summary Electromagnetic ion cyclotron (EMIC) waves, with frequencies ranging from 0.1 to 5 Hz, are commonly found in Earth's magnetosphere. These waves can be detected in the outer dayside magnetosphere, where the interaction between Earth's magnetic field and the solar wind causes the magnetic field lines to compress. EMIC waves can be generated at points where the magnetic field strength becomes minimum in each magnetic field line, meaning the magnetic latitude of the source location can vary for each L‐shell. We conducted a full‐wave simulation of EMIC waves in the outer dayside magnetosphere using the Petra‐M code, incorporating a non‐dipole compressed magnetic field. Our results indicated that the direction of wave energy flow from the source varies; thus, based on a satellite's location, it can detect wave energy flowing either parallel or antiparallel to the magnetic field, which is consistent with satellite observations. We also show that EMIC waves generated in the northern hemisphere can reach both the north and the south Polar Regions. However, the wave power reaching the northern hemisphere is significantly stronger than that which reaches the southern hemisphere.