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Vegetation responses to rising atmospheric CO2 levels can significantly affect water availability (defined as precipitation minus evapotranspiration (ET)). While this effect has long been recognized and assessed for the mean state, its influence on interannual variability, which is more closely associated with extreme events, has yet to be comprehensively quantified. In this study, our primary focus is to evaluate the impacts of ET by plant physiology (denoted as ET Phy ) on the mean and interannual variability of water availability under elevated CO2 using multiple CO2 sensitivity experiments from the coupled model intercomparison project phase 6. We show that the contribution of vegetation physiological effects to the mean water availability varies among regions, while it consistently contributes to variability by about 33%. Considering CO2 physiological effects alone, ET Phy exerts a more significant influence on the mean state than on variability, particularly in humid regions. Consequently, ET Phy contributes less than 5% to the variability of water availability in humid regions under rising CO2, whereas it accounts for about 20% of the mean state. This distinction could be attributed to the different mechanisms governing the mean and variability of ET Phy . Specifically, evaporation from CO2 physiological forcing is the most critical contributor to the variability of ET Phy in most regions while showing minimal impacts on the mean state. Our findings identify the divergent effects of ET Phy on the mean state and interannual variability of water availability under elevated CO2, as important in future climate projections.

We investigated the effects of the propagation path and site amplification of shallow tremors along the Nankai Trough. Using far-field S-wave propagation from intraslab earthquake data, the amplification factors at the DONET stations were 5–40 times against an inland outcrop rock site. Thick (∼5 km) sedimentary layers with V S of 0.6–2 km/s beneath DONET stations have been confirmed by seismological studies. To investigate the effects of thick sedimentary layers, we synthesized seismograms of shallow tremors and intraslab earthquakes at seafloor stations. The ratios of the maximum amplitudes from the synthetic intraslab seismograms between models with and without thick sedimentary layers were 1–2. This means that thin lower-velocity (<0.6 km/s) sediments just below the stations primarily control the estimated large amplifications. Conversely, at near-source (≤20 km) distances, 1-order amplifications of seismic energies for a shallow tremor source can occur due to thick sedimentary layers. Multiple S-wave reflections between the seafloor and plate interface are contaminated in tremor envelopes; consequently, seismic energy and duration are overestimated. If a shallow tremor occurs within underthrust sediments, the overestimation becomes stronger because of the invalid rigidity assumptions around the source region. After 1-order corrections of seismic energies of shallow tremors along the Nankai Trough, the scaled energies of seismic slow earthquakes were 10−10–10−9 irrespective of the region and source depth. Hence, the physical mechanisms governing seismic slow earthquakes can be the same, irrespective of the region and source depth.

We use neural networks and large climate model ensembles to explore predictability of internal variability in sea surface temperature (SST) anomalies on interannual (1–3 years) and decadal (1–5 and 3–7 years) timescales. We find that neural networks can skillfully predict SST anomalies at these lead times, especially in the North Atlantic, North Pacific, Tropical Pacific, Tropical Atlantic and Southern Ocean. The spatial patterns of SST predictability vary across the nine climate models studied. The neural networks identify “windows of opportunity” where future SST anomalies can be predicted with more certainty. Neural networks trained on climate models also make skillful SST predictions in reconstructed observations, although the skill varies depending on which climate model the network was trained. Our results highlight that neural networks can identify predictable internal variability within existing climate data sets and show important differences in how well patterns of SST predictability in climate models translate to the real world.

The electric fields of subauroral polarization streams (SAPS) have been suggested to affect energetic charged particles' dynamics in the inner magnetosphere, though their role on radiation belt electrons has never been properly quantified. A moderate geomagnetic storm on 2015-09-07 caused the deep injection of 10–100s of keV electrons in Earth's inner magnetosphere to low L* (L* < 4). Using a 2-D test particle tracer, we present the effects of electric fields given by the Volland-Stern model, a SAPS (Goldstein et al., 2005, https://doi.org/10.1029/2005ja011135) model, and a modified SAPS model on the energetic electron deep injections. The modified SAPS model reflects the SAPS electric field observations by the Van Allen Probes and is supported by Defense Meteorological Satellite Program observations. Simulations suggest that the SAPS electric field pushes 10–20 MeV/G electrons Earthward to L* ∼ 2.7 in 2.5 hr, much deeper compared to the Volland-Stern electric field.

Thicker snow cover in permafrost areas causes deeper active layers and thaw subsidence, which alter local hydrology and may amplify the loss of soil carbon. However, the potential for changes in snow cover and surface runoff to mobilize permafrost carbon remains poorly quantified. In this study, we show that a snow fence experiment on High-Arctic Svalbard inadvertently led to surface subsidence through warming, and extensive downstream erosion due to increased surface runoff. Within a decade of artificially raised snow depths, several ice wedges collapsed, forming a 50 m long and 1.5 m deep thermo-erosion gully in the landscape. We estimate that 1.1–3.3 tons C may have eroded, and that the gully is a hotspot for processing of mobilized aquatic carbon. Our results show that interactions among snow, runoff and permafrost thaw form an important driver of soil carbon loss, highlighting the need for improved model representation.

A too-weak eddy feedback in models has been proposed to explain the signal-to-noise paradox in seasonal-to-decadal forecasts of the winter Northern Hemisphere. We show that the “eddy feedback parameter” (EFP) used in previous studies is sensitive to sampling and multidecadal variability. When these uncertainties are accounted for, the EFP diagnosed from CMIP6 historical simulations generally falls within the reanalysis uncertainty. We find the EFP is not independent of the sampled North Atlantic Oscillation (NAO). Within the same dataset, a sample containing larger NAO variability will show a larger EFP, suggesting that the link between eddy feedbacks and the signal-to-noise paradox could be due to sampling effects with the EFP. An alternative measure of eddy feedback, the barotropic energy generation rate, is less sensitive to sampling errors and delineates CMIP6 models that have weak, strong, or unbiased eddy feedbacks, but shows little relation to NAO variability.

We use multi-year observations of cross-track winds (u) from the CHAllenging Minisatellite Payload (CHAMP) and the Gravity Field and Steady State Ocean Circulation Explorer (GOCE) to calculate third-order structure functions in the thermosphere as a function of horizontal separation (s). They are computed using the mean (〈δu 3〉) and the median 〈δu3〉med $\left({\langle \delta {u}^{3}\rangle }_{\text{med}}\right)$ and implemented over non-polar satellite paths in both hemispheres. On height averages, 〈δu 3〉 is shown to scale with s 2 for s ≃ 80–1,000 km, in agreement with equivalent estimates in the lower atmosphere from aircraft observations. Conversely, 〈δu3〉med ${\langle \delta {u}^{3}\rangle }_{\text{med}}$ follows an s 3 power law for almost the whole s range, consistent with the two-dimensional turbulence scaling law for a direct enstrophy cascade. These scaling laws appear independent of winds in distinct atmospheric regions. Furthermore, the functions are predominantly positive, indicating a preferential cyclonic motion for the wind.

Elevated duct (EleD) is an abnormal atmospheric refraction structure with a suspended trapped layer. The precise and highly resolved elevated duct-height-based data (EleDH) is crucial for radio communication systems, especially in electromagnetic wave path loss prediction and EleDH-producing systems. However, producing high-resolution EleDH is challenging because of the massive details in the EleDH data. Direct and high-time refinement procedures mostly lead to unrealistic outcomes. The study provides a Dense-Linear convolutional neural network (DLCNN)-based EleDH refinement technique based on the development of statistical downscaling and super-resolution technologies. Additionally, the stack approach is used, and the refining order is taken into consideration to ensure precision in high-time refinement and provide reliable outcomes. To demonstrate the strength of DLCNN in capturing complex internal characteristics of EleDH, a new EleD data set is first funded, which only contains the duct height. From this data set, we use the duct height as the core refinement of the EleD's trapped layer and the thickness of the trapped layer to ensure reliable duct height. Seven super-resolution models are utilized for fair comparisons. The experimental results prove that the DLCNN has the highest refinement performance; also, it obtained excellent generalization capacity, where the minimum and maximum obtained Accuracy(20%), MAE, and RMSE were 85.22% ∓ 88.30%, 36.09 ∓ 45.97 and 8.68 ∓ 10.14, respectively. High-resolution EleDH improves path loss prediction, where the minimum and maximum obtained bias were 2.37 ∓ 9.51 dB.

We use multiple instruments data to investigate the behavior of the equatorial and low-latitude ionosphere during the geomagnetically active and quiet period of November 1–6, 2021. In this context, total electron content (TEC) data obtained from the Global Positioning System (GPS) receivers in the equatorial and low-latitude regions of Asia, Africa, and America are used to assess variations in plasma density during the storm. The storm-time ionization levels were found to vary significantly in the crests of the Equatorial Ionization Anomaly (EIA) region over the 3 longitudes. The Rate of Change TEC Index (ROTI) derived from GPS receiver measurements, is used to study the equatorial/low-latitude ionospheric plasma irregularities at various longitudes under geomagnetically quiet and disturbed conditions. Observations showed longitudinal variations in the ionospheric irregularities under both quiet and disturbed conditions. Some days exhibit a decrease in the strength of the midnight plasma irregularities toward the East, that is, the irregularities are more pronounced in West America, less common in East America, and almost non-existent in Africa and Asia. Our investigations show this storm prevented the occurrence of plasma irregularities at the equatorial/low-latitude region in the American sector during the night following the main phase. In general, no significant storm effects were observed at the target locations in Africa and Asia. The existence of westward Prompt Penetration Electric Field (PPEF) and the Equatorial Electrojet (EEJ) during the main phase, from midnight to noon, is clearly related with the constriction of plasma diffusion and the consequent suppression of plasma irregularities. Thus, the longitudinal dependence for the generation of midnight plasma irregularities during this storm is mainly influenced by local time occurrence of maximum ring current, and the ionospheric electric fields.

The mid-lithosphere discontinuity (MLD), identified by a sharp velocity drop at ∼70–100 km depths within the cratonic lithosphere is key to comprehending the chemical composition and thermal structure of the cratonic lithosphere. The MLD is widely accepted to be caused by composition anomalies, such as hydrous minerals, which show low velocities and high electrical conductivities. However, noticeable high-electrical conductivity anomalies have not been detected in the most cratonic lithosphere. Dolomite has an electrical conductivity similar to olivine and can be originated by carbonatitic melts trapped at ∼80–140 km depths. Here we investigated the elasticity of dolomite under mantle conditions using ab initio calculations and found dolomite exhibits significantly lower velocities than the primary minerals in the lithospheric mantle. Therefore, the dolomite enrichment might provide a good explanation for the observed velocity drop of the MLD in cratonic regions where no high-conductivity anomaly has been detected, such as the northern Slave craton.

The empirical rate- and state-dependent friction law is widely used to explain the frictional resistance of rocks. However, the constitutive parameters vary with temperature and sliding velocity, preventing extrapolation of laboratory results to natural conditions. Here, we explain the frictional properties of natural gouge from the San Andreas Fault, Alpine Fault, and the Nankai Trough from room temperature to ∼300°C for a wide range of slip-rates with constant constitutive parameters by invoking the competition between two healing mechanisms with different thermodynamic properties. A transition from velocity-strengthening to velocity-weakening at steady-state can be attained either by decreasing the slip-rate or by increasing temperature. Our study provides a framework to understand the physics underlying the slip-rate and state dependence of friction and the dependence of frictional properties on ambient physical conditions.

Amplification of sea surface temperature (SST) seasonality in response to global warming is a robust feature in climate model projections but season-dependent regional disparities in this amplification and the associated mechanisms are not well addressed. Here, by analyzing large ensemble simulations using Community Earth System Model version 2, we investigate detailed spatiotemporal characteristics of the amplification of SST seasonality focusing on the North Pacific and North Atlantic, where robust changes are projected to emerge around 2050 under SSP3-7.0 scenario. Our results indicate that atmosphere-ocean coupled processes shape regional changes in SST seasonality differently between warm (MAMJJAS) and cold seasons (ONDJF). During the warm season, the projected warming tendency is mainly due to increased net surface heat flux and weakening of vertical mixing. On the other hand, in the cold season, the projected cooling tendency is driven by strengthened vertical mixing over the North Pacific associated with the northward shift of storm tracks but weakened horizontal advection and mixing due to changes in ocean currents over the North Atlantic.

Compound wind and precipitation extremes (CWPEs) can severely impact natural and socioeconomic systems. However, our understanding of CWPE future changes, drivers, and uncertainties under a warmer climate is limited. Here, by analyzing the event both on oceans and landmasses via state-of-the-art climate model simulations, we reveal a poleward shift of CWPE occurrences by the late 21st century, with notable increases at latitudes exceeding 50° in both hemispheres and decreases in the subtropics around 25°. CWPE intensification occurs across approximately 90% of global landmasses, and is most pronounced under a high-emission scenario. Most changes in CWPE frequency and intensity (about 70% and 80%, respectively) stem from changes in precipitation extremes. We further identify large uncertainties in CWPE changes, which can be understood at the regional level by considering climate model differences in trends of CWPE drivers. These results provide insights into understanding CWPE changes under a warmer climate, aiding robust regional adaptation strategy development.

Forecasts of tropical cyclone (TC) tornadoes are less skillful than their non-TC counterparts at all lead times. The development of a convection-allowing regional ensemble, known as the Warn-on-Forecast System (WoFS), may help improve short-fused TC tornado forecasts. As a first step, this study investigates the fidelity of convective-scale kinematic and thermodynamic environments to a preliminary set of soundings from WoFS forecasts for comparison with radiosondes for selected 2020 landfalling TCs. Our study shows reasonable agreement between TC convective-scale kinematic environments in WoFS versus observed soundings at all forecast lead times. Nonetheless, WoFS is biased toward weaker than observed TC-relative radial winds, and stronger than observed near-surface tangential winds with weaker winds aloft, during the forecast. Analysis of storm-relative helicity (SRH) shows that WoFS underestimates extreme observed values. Convective-scale thermodynamic environments are well simulated for both temperature and dewpoint at all lead times. However, WoFS is biased moister with steeper lapse rates compared to observations during the forecast. Both CAPE and, to a lesser extent, 0–3-km CAPE distributions are narrower in WoFS than in radiosondes, with an underestimation of higher CAPE values. Together, these results suggest that WoFS may have utility for forecasting convective-scale environments in landfalling TCs with lead times of several hours.

The dominant fraction of anthropogenic volatile organic compound (VOC) emissions shifted from transportation fuels to volatile chemical products (VCP) in Los Angeles (LA) in 2010. This shift in VOC composition raises the question about the importance of VCP emissions for ozone (O3) formation. In this study, O3 chemistry during the CalNex 2010 was modeled using the Master Chemical Mechanism (MCM) version 3.3.1 and a detailed representation of VCP emissions based on measurements combined with inventory estimates. The model calculations indicate that VCP emissions contributed to 23% of the mean daily maximum 8-hr average O3 (DMA8 O3) during the O3 episodes. The simulated OH reactivity, including the contribution from VCP emissions, aligns with observations. Additionally, this framework was employed using four lumped mechanisms with simplified representations of emissions and chemistry. RACM2-VCP showed the closest agreement with MCM, with a slight 4% increase in average DMA8 O3 (65 ± 13 ppb), whereas RACM2 (58 ± 13 ppb) and SAPRC07B (59 ± 14 ppb) exhibited slightly lower levels. CB6r2, however, recorded reduced concentrations (37 ± 10 ppb). Although emissions of O3 precursors have declined in LA since 2010, O3 levels have not decreased significantly. Model results ascribed this trend to the rapid reduction in NOX emissions. Moreover, given the impact of COVID-19, an analysis of 2020 reveals a shift to a NOX-limited O3 formation regime in LA, thereby diminishing the influence of VCPs. This study provides new insights into the impact of VCP emissions on O3 pollution from an in-depth photochemical perspective.

Eighteen lightning flash rate parameterization schemes (FRPSs) were investigated in a Weather Research and Forecasting model coupled with chemistry cloud-resolved simulation of the 29–30 May 2012 supercell storm system observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. Most of the observed storm's meteorological conditions were well represented when the model simulation included both convective damping and lightning data assimilation techniques. Newly-developed FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The schemes are based on relationships between lightning and various kinematic, structural, and microphysical thunderstorm characteristics (e.g., cloud top height, hydrometeors, reflectivity, and vertical velocity) available in the model. The results suggest the model-simulated graupel and snow/ice hydrometeors require scaling factors to more closely represent proxy observations. The model-simulated lightning flash trends and total flashes generated by each scheme over the simulation period are compared with observations from the central Oklahoma Lightning Mapping Array. For this supercell system, 13 of the 18 schemes overpredicted flashes by >100% with the group of FRPSs based on storm kinematics and structure (particularly updraft volume) performing slightly better than the hydrometeor-based schemes. During the storm's first 4 hr, the upward cloud ice flux FRPS, which is based on the combination of vertical velocity and hydrometeors, well represents the observed total flashes and flash rate trend; while, the updraft volume scheme well represents the observed flash rate peak and subsequent sharp decline in flash rate.

Understanding the impacts of high-resolution ocean model provides valuable insights for future research. However, the outcomes of sea surface state changes in both the tropics and mid-latitudes remain unclear, and initialized seasonal forecasts have not been studied extensively. This study investigates the impact of ocean model resolution with the first long-term hindcast experiment of an eddy-resolving (0.1°) ocean model used for global seasonal forecasting. We show that using the high-resolution ocean model significantly changes boreal winter jet streams in the atmosphere, based on the comparison of 30-year hindcasts with ocean resolutions ranging from 1° to 0.1° for the Japan Meteorological Agency/Meteorological Research Institute Coupled Prediction System version 3. In boreal winters, the cold sea surface bias in the equatorial Pacific is significantly reduced, leading to an equatorward shift in the intertropical convergence zone (ITCZ) and enhanced convective activity in the western equatorial Pacific. The subtropical jet shifts equatorward due to the ITCZ shift and the weakening of equatorward propagation of mid-latitude atmospheric eddies. The enhanced convective activity in the tropics has a remote influence in the mid-latitudes, significantly reducing the upward eddy propagation of zonal wavenumber 1. Sea surface warm-up in the mid-latitudes partially cancels the reduction impact by enhancing the zonal wavenumber 2. Overall, the polar night jet accelerates due to the reduced supply of eddy forcing.

A cloud-resolved storm and chemistry simulation of a severe convective system in Oklahoma constrained by anvil aircraft observations of NO x was used to estimate the mean production of NO x per flash in this storm. An upward ice flux scheme was used to parameterize flash rates in the model. Model lightning was also constrained by observed lightning flash types and the altitude distribution of flash channel segments. The best estimate of mean NO x production by lightning in this storm was 80–110 mol per flash, which is smaller than many other literature estimates. This result is likely due to the storm having been a high flash rate event in which flash extents were relatively small. Over the evolution of this storm a moderate negative correlation was found between the total flash rate and flash extent and energy per flash. A longer-term simulation at 36-km horizontal resolution with parameterized convection was used to simulate the downwind transport and chemistry of the anvil outflow from the same storm. Convective transport of low-ozone air from the boundary layer decreased ozone in the anvil outflow by up to 20–40 ppbv compared with the initial conditions, which contained stratospheric influence. Photochemical ozone production in the lightning-NO x enhanced convective plume proceeded at a rate of 10–11 ppbv per day in the 9–11 km outflow layer over the 24-hr period of downwind transport to the Southern Appalachians. Photochemical production plays a large role in the restoration of upper tropospheric ozone following deep convection.

Recent research has described a ‘moist margin’ in the tropics, defined through a total column water vapor (TCWV) value of 48 kg m−2, that encloses most of the rainfall over the tropical oceans. Diagnosing the moist margin in the ERA5 reanalysis reveals that it varies particularly on synoptic time scales, which this study aims to quantify. We define ‘wet and dry perturbation’ objects based on the margin's movement relative to its seasonal climatology. These perturbations are associated with a variety of synoptic weather systems. Wet (dry) perturbations produce substantially more (less) rainfall compared to the seasonal average, confirming the clear link between moisture and precipitation. On synoptic scales we suggest that mid-tropospheric humidity plays a key role in creating these perturbations, while sea surface temperatures (SSTs) are relatively unimportant.

The present study investigates wavenumber-4 (wave-4) structure in the longitude variation of zonal and meridional winds observed by the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) instrument onboard the Ionospheric Connection Explorer (ICON) satellite. The amplitude of the wave-4 pattern in meridional wind displays semi-annual variation with equinoctial maxima whereas its seasonal variation in zonal wind shows maxima during August–October at the equatorial and low latitudes. The wave-4 longitude variation maximizes at lower thermospheric heights (below 130 km) in zonal and meridional winds. It is considered primarily driven by the non-migrating eastward propagating diurnal tide with zonal wavenumber-3 (DE3) in the zonal wind. However, the amplitude of DE3 tide in the meridional wind does not show any enhancement during September–October. The seasonal variations of the wave-4 amplitude and the DE3 tide are not similar in the zonal and meridional winds. The migrating ter-diurnal tide (TW3) exhibits significant amplitudes during March–April and September–November in the meridional wind. In addition, the latitude variation of non-migrating TE1 tide shows maximum amplitude during September–October. These results suggest that the non-linear interaction between the TW3 and TE1 tides can serve as a potential source for the wave-4 longitude variation in the meridional wind at lower thermospheric altitudes.