GRL

Knowledge of aerosol radiative effects in the Tibetan Plateau (TP) is limited due to the lack of reliable aerosol optical properties, especially the single scattering albedo (SSA). We firstly reported in situ measurement of SSA in Lhasa using a cavity enhanced albedometer (CEA) at λ = 532 nm from 22nd May to 11th June 2021. Unexpected strong aerosol absorbing ability was observed with an average SSA of 0.69. Based on spectral absorptions measured by Aethalometer (AE33), black carbon (BC) was found to be the dominated absorbing species, accounting for about 83% at λ = 370 nm, followed by primary and secondary brown carbon (BrCpri and BrCsec). The average direct aerosol radiative forcing at the top of atmosphere (DARFTOA) was 2.83 W/m2, indicating aerosol warming effect on the Earth-atmosphere system. Even though aerosol loading is low, aerosol heating effect plays a significant role on TP warming due to strong absorbing ability.

Temperature inversion (TI) constitutes a crucial component in the physicochemical processes of the lower troposphere, but disentangling human contributions to its generation from complex environmental factors poses significant challenges. We leveraged the unique natural experiment prompted by the coronavirus disease 2019 (COVID-19) pandemic to estimate changes in TI incidence and temperature difference (∆T) caused by the economic shutdown in the first half of 2020 across 500 major cities worldwide. We found that ∆T declined by 2.5% and TI incidence declined by 18.2% compared to 2016–2019, exhibiting spatial-temporal heterogeneity and pronounced declines in cities with higher levels of economic development and emission reduction. Moreover, we demonstrated that fine particulate matter (PM2.5) may serve as a mediating pathway through which human activities influence air thermal properties, and climate categories modulate this mediating effect. Our analysis provides empirical evidence of human influence on the vertical thermal structure of the atmosphere.

Clustering extreme weather events are concurrent or consecutive occurrences of disastrous weather in multiple regions, resulting in cumulative impacts. Here we discovered a significant increasing trend in clustering extreme precipitation events over the Indo-Pacific rim over the past four decades. This trend can be largely attributable to the increasing frequency of the Rossby wave response, including the circum-Pacific and cross-Pacific patterns due to Rossby wave activity propagation, and the Pacific anticyclone pattern due to Rossby wave breaking. The three patterns show remarkable disparity in seasonality, persistence, and hydrological impacts. They can increase the occurrences of most severe precipitation by up to 5, 8, and 25 times, respectively. The Indian Summer Monsoon heat sources and La Niña are identified as key drivers, and the mid-latitude jet streams are modulators contributing to the events. Our findings suggest that specific Rossby wave patterns may influence the potential evolution of future clustering extremes.

Theoretical analysis has revealed a specific resonance that shares the same condition as Landau resonance, but instead involves wave electromagnetic fields rather than traditionally electrostatic fields. While this resonance, referred to as electromagnetic Landau resonance due to its properties, is considered significant for magnetospheric dynamics, rare reports or evaluations based on observations have been made thus far. Here, we present an event detected by the Magnetospheric Multiscale mission near the dayside magnetopause. During this event, ∼748-eV protons are observed to be in resonance with a wave. Detailed data analysis demonstrates the resonant velocity closely matches the wave's parallel phase speed, which, combined with the significant work done by wave perpendicular electric field, confirms this interaction as electromagnetic Landau resonance. Further investigation indicates these protons are being secularly accelerated within this resonance. Consequently, our observations provide the first empirical evidence supporting the previously suggested theoretical importance of the electromagnetic Landau resonance.

As droughts propagate both in time and space, their impacts increase because of changes in drought properties. Because temporal and spatial drought propagation are mostly studied separately, it is yet unknown how drought spatial extent and connectedness change as droughts propagate though the hydrological cycle from precipitation to streamflow and groundwater. Here, we use a large-sample dataset of 70 catchments in Central Europe to study the propagation of local and spatial drought characteristics. We show that drought propagation leads to longer, later, and fewer droughts with larger spatial extents. 75% of the precipitation droughts propagate to P-ET, among these 20% propagate further to streamflow and 10% to groundwater. Of the streamflow droughts, 40% propagate to groundwater. Drought extent and dependence increase during drought propagation along the drought propagation pathway from precipitation to streamflow thanks to synchronizing effects of the land-surface but decreases again for groundwater because of sub-surface heterogeneity.

A severe hailstorm that occurred in Spain on 30 August 2022, caused material and human damage, including one fatality due to giant hailstones up to 12 cm in diameter. By applying a pseudo-global warming approach, here we evaluate how a simultaneous marine heatwave (and anthropogenic climate change) affected a unique environment conductive to such giant hailstones. The main results show that the supercell development was influenced by an unprecedented amount of convective available energy, with significant contributions from thermodynamic factors. Numerical simulations where the marine heatwave is not present show a notable reduction in the hail-favorable environments, related mainly to modifications in thermodynamic environment. Our simulations also indicate that the environment in a preindustrial-like climate would be less favorable for convective hazards and thus the hailstorm event would likely not have been as severe as the observed one, being possible to perform a novel attribution of such kind.

Characterizing and understanding the changes in the flow regimes of rivers have been challenging. Existing global river network data sets are not updated and can only identify rivers wider than 30 m. We propose a novel automated method to map river networks on a monthly basin scale for the first time at 10-m resolution using Sentinel-1 Synthetic Aperture Radar, Sentinel-2 multispectral images, and the AW3D30 Digital Surface Model. This method achieved an overall accuracy of 95.8%. The total length of the Yellow River network produced is 40,280 km, approximately 3.2 times that of the Global River Widths from Landsat (GRWL) database, more effectively covering small and medium rivers. The monthly river geometry revealed a positive correlation between river network area and precipitation. This study is expected to provide a cost-effective alternative to accurately mapping global river networks and advance our understanding of the changes and drivers of river systems.

Turbulence in clouds is known to enhance particle collision rates, as widely demonstrated for warm rain formation. A similar impact on ice growth processes is expected but a solid observational basis is missing. A statistical analysis of a 15-month data set of cloud radar observations allows for the first time to quantify the impact of turbulence on ice aggregation and riming in Arctic low-level mixed-phase clouds. Increasing eddy dissipation rate (EDR), from below 10−4 to above 10−3 m2 s−3, yields larger ice aggregates, and higher particle concentration, likely caused by increasing fragmentation. In conditions more favorable to riming, higher EDR is associated with dramatically higher particle fall velocities (by up to 125%), under similar liquid water paths, indicative of markedly higher degrees of riming. Our findings thus reveal the key role of turbulence for cold precipitation formation, and highlight the need for an improved understanding of turbulence-hydrometeor interactions in cold clouds.

This study develops an unstructured mesh generation tool for land surface modeling using a multi-scale hexagon discrete mesh. The tool can automatically determine the required mesh resolution for different regions based on multi-objective criteria such as elevation, slope, land cover, and land use. The refined unstructured meshes demonstrate significant enhancement in the representation of spatial heterogeneity. The tool is coupled with the Common Land Model (CoLM) to enable land surface simulations using unstructured meshes. Evaluations focused on runoff, river discharge, and inundation indicate improved model performance compared to traditional structured mesh-based CoLM simulations under the same computational cost constraints. This tool provides new capabilities for more efficiently capturing localized land surface processes and extreme events.

Heavy cold ions at Mars are gravitationally bound to the planet unless some process provides energy to them. Observations show that cold (<20 eV) and dense (∼>1 cm−3) O+/O2 + ions with bulk velocities equal to energies ∼1 keV can reach deep into the nightside Martian magnetosheath. These ions are co-located with a change of the sign of the sunward component of the magnetic field. This magnetic field topology implies the persistence of a localized planetary ions escape channel associated with draped magnetic field lines that are convecting tailward. The observed ion populations propagate approximately in the same direction as surrounding magnetosheath flow and are likely to be almost unheated ionospheric ions from low altitudes. The paper discusses planetary ion energization via Hall electric field originated from ions and electron separation associated with magnetic field curvature.

The baroclinic component of the sea surface height, referred to as steric height, is governed by geostrophically balanced motions and unbalanced internal waves, and thus is an essential indicator of ocean interior dynamics. Using yearlong measurements from a mooring array, we assess the distribution of upper-ocean steric height across frequencies and spatial scales of O (1–20 km) in the northeast Atlantic. Temporal decomposition indicates that the two largest contributors to steric height variance are large-scale atmospheric forcing (32.8%) and mesoscale eddies (34.1%), followed by submesoscale motions (15.2%), semidiurnal internal tides (8%), super-tidal variability (6.1%) and near-inertial motions (3.8%). Structure function diagnostics further reveal the seasonality and scale dependence of steric height variance. In winter, steric height is dominated by balanced motions across all resolved scales, whereas in summer, unbalanced internal waves become the leading-order contributor to steric height at scales of O (1 km).

Whether tectonic strain from the early stage India-Asia collision has synchronously affected the far-field margin of the Tibetan Plateau is crucial for understanding plateau deformation and growth processes. However, direct evidence for early far-field deformation remains scarce. Utilizing illite K-Ar dating of three fault gouge samples, we established the faulting history of the Leibo fault zone (LFZ) at the southeastern margin of the Tibetan Plateau (SEMTP). Consistent authigenic illite ages of 52 ± 2, 54 ± 12 and 55 ± 6 Ma suggest the reactivated thrust faulting of the LFZ in the Early Cenozoic. Positioned ∼700 km east of the collisional boundary and at the intersection of three blocks with distinct lithospheric rheology in strength/viscosity, this event suggests a quasi-synchronous far-field tectonic response in the SEMTP to the India-Asia collision.

Extreme flood events have regional differences in their generating mechanisms due to the complex interaction of different climate and catchment processes. This study aims to examine the capability of climate drivers to capture year-to-year variability in global flood extremes. Here, we use a statistical attribution approach to model seasonal and annual maximum daily discharge for 7,886 stations worldwide, using season- and basin-averaged precipitation and temperature as predictors. The results show robust performance of our seasonal climate-informed models in describing the inter-annual variability in seasonal and annual maximum discharges regardless of the geographical region, climate type, basin size, degree of regulation, and impervious area. The developed models enable the assessment of the sensitivity of flood discharge to precipitation and temperature changes, indicating their potential to reliably project changes in the magnitude of flood extremes.

Climate models suffer from longstanding precipitation biases, much of which has been attributed to their atmospheric component owing to unrealistic parameterizations. Here we investigate precipitation biases in 37 Atmospheric Model Intercomparison Project Phase 6 (AMIP6) models, focusing on the Indo-Pacific region during boreal summer. These models remain plagued by considerable precipitation biases, especially over regions of strong precipitation. In particular, 22 models overestimate the Asian-Pacific monsoon precipitation, while 28 models underestimate the southern Indian Ocean Intertropical Convergence Zone precipitation. The inter-model spread in summer precipitation is decomposed into Empirical Orthogonal Functions (EOFs). The leading EOF mode features an anomalous anticyclone circulation spanning the Indo-northwest Pacific oceans, which we show is energized by barotropic conversion from the confluence of the background monsoonal westerlies and trade-wind easterlies. Our results suggest precipitation biases in atmospheric models, though caused by unrealistic parameterizations, are organized by dynamical feedbacks of the mean flow.

To improve the forecast accuracy of numerical weather prediction, it is essential to obtain better initial conditions by combining simulations and available observations via data assimilation. It has been known that a part of observations degrade the forecast accuracy. Detecting and discarding such detrimental observations via proactive quality control (PQC) could improve the forecast accuracy. However, conventional methods for diagnosing observation impacts require future observations as a reference state and PQC cannot be real-time in general. This study proposes using machine learning (ML) trained by a time series of analyses to obtain a reference state without future observations and enable real-time ML-based PQC. This study presents proof-of-concept using a low-dimensional dynamical system. The results indicate that ML-based and model-based estimates of observation impacts are generally consistent. Furthermore, ML-based real-time PQC successfully improves the forecast accuracy compared to a baseline experiment without PQC.

The South Asian summer monsoon strongly modulates regional temperature and humidity. While extreme dry heat peaks in the pre-monsoon season, recent literature suggests that extreme humid heat can continue to build throughout the monsoon season. Here we explore the influence of monsoon onset and subseasonal precipitation variability on the occurrence of extreme wet bulb temperatures (Tw) across South Asia. We find that extreme Tw events often occur on rainy days during the monsoon season. However, the influence of precipitation on Tw varies with the background climatology of surface specific humidity. In climatologically drier areas, positive Tw anomalies tend to occur when precipitation increases due to either early onset or wet spells during the monsoon. In contrast, in climatologically humid areas, positive Tw anomalies occur during periods of suppressed precipitation, including both delayed onset and dry spells during the monsoon.

Seismic surveys along subduction zones have identified anomalously high ratio of P- to S-wave velocity (V P /V S ) in the subducting oceanic crust that are possibly due to the presence of pore water. Such interpretations postulate that the pore structure is homogeneous at the scale of the seismic wavelength. Here we present the first statistical evidence of a heterogeneous pore structure in oceanic crust at scales larger than laboratory samples. The spatial correlation of measured bulk density profiles of the crustal section of the Samail ophiolite suggests that the pore structure is heterogeneous at scales smaller than ∼1 m. Wave-induced fluid flow cannot follow the loading during the seismic wave propagation at this estimated heterogeneity, which implies that fluid-filled microscopic pores and cracks have a limited impact on the observed high V P /V S anomalies in the subducting oceanic crust. Large-scale cracks may therefore play an important role in shaping these anomalies.

Radial diffusion (RD) induced by ULF waves can contribute to particle acceleration and scattering. Past global simulations that incorporate RD often use dipole magnetic fields, which could not realistically reveal the role of RD. To better understand the effects of RD and identify whether a background magnetic field model matters in understanding the ring current dynamics in response to RD, we simulate a storm event with different magnetic configurations using a global kinetic ring current model. Results indicate that RD can effectively diffuse protons of hundreds of keV to inner regions (L ∼ 3.5), especially in recovery phase. Comparisons with in-situ observations demonstrate that simulations with TS05 overall capture both the intensity and variations of proton fluxes with the aid of RD, whereas that with a dipole field significantly overestimates low-L region fluxes. This study implies adopting realistic magnetic fields is important for correctly interpreting the role of RD.

Taking advantage of a large ensemble of Convection Permitting-Regional Climate Models on a pan-Alpine domain and of an object-oriented dedicated analysis, this study aims to investigate future changes in high-impact fall Mediterranean Heavy Precipitation Events at high warming levels. We identify a robust multi-model agreement for an increased frequency from central Italy to the northern Balkans combined with a substantial extension of the affected areas, for a dominant influence of the driving Global Climate Models for projecting changes in the frequency, and for an increase in intensity, area, volume and severity over the French Mediterranean. However, large quantitative uncertainties persist despite the use of convection-permitting models, with no clear agreement in frequency changes over southeastern France and a large range of plausible changes in events' properties, including for the most intense events. Model diversity and international coordination are still needed to provide policy-relevant climate information regarding precipitation extremes.

Induced seismicity represents a negative drawback during subsurface exploitation for geothermal energy production. Understanding the triggering mechanisms of induced earthquakes can help implement effective seismic hazard mitigation actions. Among the triggering mechanisms, the pore fluid pressure is of primary importance. Here we provide a static picture of the excess pore fluid pressure at the hypocenters of a seismic sequence induced at the deep geothermal field in St. Gallen, Switzerland, in July 2013. We find that in addition to the Coulomb static stress change, fluids play a key role in promoting the sequence. The estimated excess pore fluid pressure for approximately half of the earthquakes is higher than the injection pressure necessary during the well control phase to fight the unexpected gas kick, that accidently occurred during field operations when a trap of overpressured gas was broken.