GRL

Archimedean spirals are common in various fields such as biology, engineering, astronomy, and space physics. Here we report the discovery of patterns resembling the general Archimedean spirals in particle distributions in the Earth radiation belt. Our analytic theory and numerical simulations demonstrate that electrons with initially asymmetric spatial distributions form such spirals in the inner magnetosphere, where particles at smaller radial distances move more slowly in angular velocity. These spirals result in time-varying peaks and valleys in particle fluxes, referred to as “zebra stripes,” which are well consistent with Van Allen Probes measurements. Although the initial asymmetric distribution may be seeded by the electric field in the magnetosphere, the spiral formation does not require them. Furthermore, we show that, due to the same fundamental motion of charged particles in regions dominated by dipole fields, this spiral phenomenon may also appear in the proton distributions, as well as in planetary magnetospheres.

Meteor radar observations provide wind data ranging from 80 to 100 km altitude, while the Michaelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) onboard the Ionospheric Connection Explorer satellite offers wind data above 90 km altitude. This study aims to generate wind profiles in the mesosphere and lower thermosphere by combining the winds derived from meteor radar and MIGHTI observations over the Korean Peninsula from January 2020 to December 2021. The wind profiles derived from the two instruments are continuous at night, but they show discrepancies during the day. The atomic oxygen 557.7 nm (green line) emission intensity measured by MIGHTI peaks at approximately 100 km during the day and 94 km at night. The vertical gradient of the airglow volume emission rate is more pronounced during the day. These differences can cause day-night differences in the MIGHTI wind retrieval accuracy, potentially leading to discrepancies during the day.

Super-coarse dust particles (diameters >10 μm) are evidenced to be more abundant in the atmosphere than model estimates and contribute significantly to the dust climate impacts. Since super-coarse dust accounts for less dust extinction in the visible-to-near-infrared (VIS-NIR) than in the thermal infrared (TIR) spectral regime, they are suspected to be underestimated by remote sensing instruments operates only in VIS-NIR, including Aerosol Robotic Networks (AERONET), a widely used data set for dust model validation. In this study, we perform a radiative closure assessment using the AERONET-retrieved size distribution in comparison with the collocated Atmospheric Infrared Sounder (AIRS) TIR observations with comprehensive uncertainty analysis. The consistently warm bias in the comparisons suggests a potential underestimation of super-coarse dust in the AERONET retrievals due to the limited VIS-NIR sensitivity. An extra super-coarse mode included in the AERONET-retrieved size distribution helps improve the TIR closure without deteriorating the retrieval accuracy in the VIS-NIR.

This study leveraged a Lagrangian framework to examine the evolution of stratocumulus clouds under cold and warm advections (CADV and WADV) in the Community Earth System Model 2 (CESM2) against observations. We found that CESM2 simulates a too rapid decline in low-cloud fraction (LCF) and cloud liquid water path (CLWP) under CADV conditions, while it better aligns closely with observed LCF under WADV conditions but overestimates the increase in CLWP. Employing an explainable machine learning approach, we found that too rapid decreases in LCF and CLWP under CADV conditions are related to overestimated drying effects induced by sea surface temperature, whereas the substantial increase in CLWP under WADV conditions is associated with the overestimated moistening effects due to free-tropospheric moisture and surface winds. Our findings suggest that overestimated drying effects of sea surface temperature on cloud properties might be one of crucial causes for the high equilibrium climate sensitivity in CESM2.

Plasmaspheric hiss waves are important to shape the Earth’s electron radiation belt. These waves are commonly envisioned to have a long lifetime which allows them to permeate the global plasmasphere from a spatially restricted source. However, this hypothesis has not been experimentally confirmed yet, because of the challenging observational requirements in terms of location and timing. With wave and particle measurements from five magnetospheric satellites and detailed modeling, we present the first report of long lifetime (∼42 s) hiss rays in the substorm-disturbed plasmasphere. The low-frequency hiss waves are found to originate from the middle piece of the plasmaspheric plume, bounce between two hemispheres, and eventually drift into the plasmaspheric core. These hiss rays can travel through ∼3 hr magnetic local time and ∼4 magnetic shell. Such a long-time and large-scale permeation of hiss rays could benefit from the ducting process by plasmaspheric field-aligned density irregularities.

The long half-life of 129I makes it useful for dating marine sediments aged 2–90 Ma. However, the lack of initial value dating hinders its application for dating terrestrial sediments. A large scatter of 129I/127I in prenuclear terrestrial samples has been reported; however, the key influencing factors remain unclear. This study presented iodine isotope data from three Argentine Entisol profiles and developed an iodine-source model to determine the influence of the source on iodine isotopic composition. The temporal patterns demonstrated clear climate modulations in natural terrestrial iodine isotopes over the last ∼15 Kyr. The model identified rock weathering as a major source of iodine in continental sediments. Higher 129I/127I ratios at mid-high latitudes arise from weak geomagnetic shielding of cosmic rays and thus a high production rate, implying limited meridional diffusion of atmospheric iodine. These findings reveal that environmental factors are significant for constraining the initial value of terrestrial 129I.

Tibetan Plateau (TP) has experienced a slowdown of the vegetation greening since the late 1990s. This structural change (i.e., greening) along with canopy physiology (i.e., potential photosynthetic productivity) regulates vegetation gross primary productivity (GPP). However, it remains unclear how the joint regulation influences the trend of alpine GPP under climate change. Here, we validate a universal productivity model against flux-based and satellite-derived observations at TP and diagnose the long-term climatic impacts on GPP via canopy physiology and structure. We found an increasing but weakening trend of GPP after 1998. About 3/4 of this slowdown was attributed to the slowing greening after 1998, which was caused by the fact that the stress of atmospheric aridity and reduced benefits of warming overwhelmed the positive effects of CO2 fertilization and radiation enhancement. This study highlights the coupling between canopy structure and productivity for the long-term period.

Atmospheric blocking is a large-amplitude, quasi-stationary, and long-lasting flow regime in the extratropics. To understand the physical processes governing the occurrence of atmospheric blocking, we identify that the positive phase of Baroclinic Annular Mode (BAM) increases the occurrence of blocking events in the Southern Hemisphere atmosphere. As BAM can translate to regional scales, we identify an enhanced zonal flux of wave activity and reduced dispersiveness associated with high BAM states that are dynamically conducive to the occurrence of atmospheric blocking. Blocking frequency in the high BAM state almost doubles as compared to the climatology, and the enhanced occurrence of blocks is most significant within BAM-associated wave packets. This finding suggests BAM can be employed as a new source of predictability for atmospheric blocking.

Using data from the NASA Soil Moisture Active/Passive mission, Koster et al. (2023, https://doi.org/10.1038/s41467-023-39318-3) conclude that, for medium-scale basins in the contiguous United States, a quarter of interannual variability in springtime streamflow is explained by interannual anomalies in late-fall soil moisture. This lagged relationship can be leveraged for seasonal hydrologic forecasting, but only if effectively captured by existing prediction models. Here, we extend the analysis in Koster et al. (2023, https://doi.org/10.1038/s41467-023-39318-3) to diagnose systematic errors present in the United States National Water Model (NWM). Results demonstrate that the NWM tends to underestimate both the trans-winter temporal memory of 0–1 m soil moisture as well as the correlation between 0 and 1 m soil moisture and streamflow—thereby reducing the NWM's ability to leverage vertically averaged soil moisture as a source of hydrologic predictability.

The effects of atmospheric thermal structure on the surface energy flux are poorly understood over the Arctic sea-ice surface. Here, we explore the mechanism of sensible heat exchange under different types of thermal structures over the Arctic sea-ice surface by using data collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition. The quadrant analysis indicates that strong surface temperature inversions below 100 m enhance non-local effects on the positive (upward) sensible heat flux (w′θ′‾ $\overline{{w}^{\prime }{\theta }^{\prime }}$) through entrainment of large eddies from the convective boundary layer aloft. However, strong surface inversions restrict the contributions of large eddies to the negative (downward) w′θ′‾ $\overline{{w}^{\prime }{\theta }^{\prime }}$ due to intensified surface stability. By inspecting the existing parameterization schemes, we found that the European Center for Medium-Range Weather Forecasts Integrated Forecasting System scheme fails to predict the impacts of non-local processes on the positive w′θ′‾ $\overline{{w}^{\prime }{\theta }^{\prime }}$, and an adjustment term to correct the bias of parameterized w′θ′‾ $\overline{{w}^{\prime }{\theta }^{\prime }}$ is proposed.

Accurate precipitation simulations for various climate scenarios are critical for understanding and predicting the impacts of climate change. This study employs a Cycle-generative adversarial network (CycleGAN) to improve global 3-hr-average precipitation fields predicted by a coarse grid (200 km) atmospheric model across a range of climates, morphing them to match their statistical properties with those of reference fine-grid (25 km) simulations. We evaluate its performance on both the target climates and an independent ramped-SST simulation. The translated precipitation fields remove most of the biases simulated by the coarse-grid model in the mean precipitation climatology, the cumulative distribution function of 3-hourly precipitation, and the diurnal cycle of precipitation over land. These results highlight the potential of CycleGAN as a powerful tool for bias correction in climate change simulations, paving the way for more reliable predictions of precipitation patterns across a wide range of climates.

Extreme melt and rainfall events can induce temporary acceleration of Greenland Ice Sheet motion, leading to increased advection of ice to lower elevations where melt rates are higher. In a warmer climate, these events are likely to become more frequent. In September 2022, seasonally unprecedented air temperatures caused multiple melt events over the Greenland Ice Sheet, generating the highest melt rates of the year. The scale and timing of the largest event overwhelmed the subglacial drainage system, enhancing basal sliding and increasing ice velocities by up to ∼240% relative to pre-event velocities. However, ice motion returned rapidly to pre-event levels, and the speed-ups caused a regional increase in annual ice discharge of only ∼2% compared to when the effects of the speed-ups were excluded. Therefore, although late melt-season events are forecast to become more frequent and drive significant runoff, their impact on net mass loss via ice discharge is minimal.

While some previous studies examined the contribution of Eastern Pacific (EP) hurricanes toward precipitation in the arid Southwest US (SWUS), their potential to influence wildfires in that region has not been explored. Here we show, using observations and simulations from the Energy Exascale Earth System Model (E3SM), that recurving EP hurricanes modulate the wildfire environment in the SWUS by increasing precipitation and soil moisture, and reducing the vapor pressure deficit. This is especially the case during late season months of September–October when the likelihood of storms to recurve and make landfall increases. Further, analysis of burnt area observations reveals that for the months of September–October, recurving EP hurricanes may significantly reduce the prevalence of wildfires in the SWUS. Finally, E3SM simulations indicate that late season EP hurricanes have been on the decline, with important implications for wildfires in the SWUS.

This letter uses simultaneous observations from Magnetosphere Multiscale (MMS) and Time History of Events and Macroscale Interactions during Substorms (THEMIS) to address the dynamics of the magnetopause and magnetosheath boundary layers during the main phase of a storm during which the interplanetary magnetic field (IMF) reverses from south to north. Near the dawn terminator, MMS observes two boundary layers comprising open and closed field lines and containing energetic electrons and ring current oxygen. Some closed field line regions exhibit sunward convection, presenting an avenue to replenish dayside magnetic flux lost during the storm. Meanwhile, THEMIS observes two boundary layers in the pre-noon sector which strongly resemble those observed at the flank by MMS. Observations from the three THEMIS spacecraft indicate the boundary layers are still evolving several hours after the IMF has turned northward. These observations advance our knowledge of the dynamic magnetopause and magnetosheath boundary layers under the combined effects of an ongoing storm and changing IMF.

ENSO's atmospheric teleconnections drive anomalous North Pacific sea surface temperatures through changes in surface heat fluxes (“the atmospheric bridge”). Previous research focusing on the bridge as a seasonal phenomenon did not consider how ENSO-related changes in synoptic variability might also impact surface turbulent heat fluxes (STHF). In this study, we find that while well over half of ENSO's impact on STHF occurs on low-frequency (>8 days) time scales, up to 20% of its impact arises on high-frequency (<8 days) time scales, through changes in the covariance between surface wind speed and air-sea enthalpy difference that typically warms the ocean south of the storm track. During El Niño, the North Pacific storm track and its attendant sea surface warming shift southward, reducing warming of the central North Pacific ocean and thereby enhancing the bridge signal there. Additionally, changes in the bulk formula coefficients between ENSO phases drive STHF differences (5%–10%).

The close relationship between the Indian Ocean Basin mode (IOBM) and summer precipitation in Central Asia (CA) has been documented in several studies. Nonetheless, this relationship has weakened since the 1990s and varies with the Atlantic Multi-decadal Oscillation (AMO) phase transition. During the cold phase of the AMO (1970–1998), precipitation in CA was significantly positively correlated with the IOBM. Conversely, during the warm phase of the AMO (1999–2019), this correlation became insignificant. The decrease in the interannual variation in the IOBM resulted in the weakening of the atmospheric heat source variation over the North Indian continent and the south-north movement of the subtropical westerly jet (SWJ). Along with the southerly SWJ, the IOBM exhibited only a weak positive correlation with precipitation in southern CA after the 1990s. This remarkable contrast in the impact of IOBM during different phases of the AMO offers intriguing possibilities for improving climate prediction in CA.

Accurately representing the ocean carbon cycle in Earth System Models (ESMs) is essential to understanding the oceanic CO2 sink evolution under CO2 emissions and global warming. A key uncertainty arises from the ESM's inability to explicitly represent mesoscale eddies. To address this limitation, we conduct eddy-resolving experiments of CO2 uptake under global warming in an idealized mid-latitude ocean model. In comparison with similar experiments at coarser resolution, we show that the CO2 sink is 34% larger in the eddy-resolving experiments. 80% of the increase stems from a more efficient anthropogenic CO2 uptake due to a stronger Meridional Overturning circulation (MOC). The remainder results from a weaker reduction in CO2 uptake associated to a weaker MOC decline under global warming. Although being only a fraction of the overall response to climate change, these results emphasize the importance of an accurate representation of small-scale ocean processes to better constrain the CO2 sink.

Electromagnetic ion cyclotron (EMIC) waves are known to exhibit frequency chirping occasionally, contributing to the rapid acceleration and precipitation of energetic particles in the magnetosphere. However, the chirping mechanism of EMIC waves remains elusive. In this work, a phenomenological model of whistler mode chorus waves named the Trap-Release-Amplify (TaRA) model is applied to EMIC waves. Based on the proposed model, we explain how the chirping of EMIC waves occurs, and give predictions on their frequency chirping rates. For the first time, we relate the frequency chirping rate of EMIC waves to both the wave amplitude and the background magnetic field inhomogeneity. Direct observational evidence is provided to validate the model using previously published events of chirping EMIC waves. Our results not only provide a new model for EMIC wave frequency chirping, but more importantly, they indicate the potential wide applicability of the underlying principles of TaRA model.

Heterogeneous chemical cycles of pyrogenic nitrogen and halides influence tropospheric ozone and affect the stratosphere during extreme Pyrocumulonimbus (PyroCB) events. We report field-derived N2O5 uptake coefficients, γ(N2O5), and ClNO2 yields, φ(ClNO2), from two aircraft campaigns observing fresh smoke in the lower and mid troposphere and processed/aged smoke in the upper troposphere and lower stratosphere (UTLS). Derived φ(ClNO2) varied across the full 0–1 range but was typically <0.5 and smallest in a PyroCB (<0.05). Derived γ(N2O5) was low in agricultural smoke (0.2–3.6 × 10−3), extremely low in mid-tropospheric wildfire smoke (0.1 × 10−3), but larger in PyroCB processed smoke (0.7–5.0 × 10−3). Aged biomass burning aerosol in the UTLS had a higher γ(N2O5) of 17 × 10−3 that increased with sulfate and liquid water, but that was 1–2 orders of magnitude lower than values for aqueous sulfuric aerosol used in stratospheric models.

Enhanced continental phosphorus input into the ocean has been suggested as a potential trigger for the transient oxygenation events during the mid-Proterozoic; however, the response of phosphorus cycling to these marine oxygenations remains unclear. Here, we report the changes in phosphorus cycling associated with a ∼1.7 Ga transient oxygenation. Abundant authigenic aluminum phosphate–sulfate mineral svanbergite (SrAl3(PO4) (SO4) (OH)6; 8.02 ± 4.92 wt%) is identified within the ∼1.7 Ga Yunmengshan ironstones from the Xiong'er Basin, North China and other contemporaneous basins. This observation provides new evidence to support the suggestion that early diagenetic aluminum phosphate-sulfate minerals could have represented a critical sink of marine phosphorus during the Proterozoic. We suggest that atmospheric oxygenation and concomitant changes in porewater redox chemistry may have enhanced the formation of early diagenetic phosphates, leading to a negative feedback on the oceanic phosphorus reservoir and atmospheric oxygen levels.