Extreme precipitation events associated with atmospheric rivers (ARs) trigger floods, landslides, and avalanches that threaten lives and livelihoods in Southeast Alaska. Six rural and indigenous communities (Hoonah, Klukwan, Skagway, Yakutat, Craig, and Kasaan) identified specific needs regarding these hazards and joined the Southeast Alaska Coastlines and People (CoPe) Kutí­ Hub to address the shared challenge of understanding and predicting these events. This study presents a climatology (1980–2019) of synoptic, mesoscale, and local meteorological characteristics of ARs and heavy precipitation across this region. High-amplitude upper-level patterns across the northeastern Pacific Ocean favor ARs reaching Southeast Alaska, where moisture is orographically lifted, resulting in heavy precipitation. In the six communities, ARs occur 8–15 days per month, yet only 9 AR days per year account for up to 75–90% of precipitation extremes. Furthermore, 79–95% of days with extreme precipitation have > 75th percentile integrated water vapor transport (IVT), demonstrating the strong relationship between IVT and extreme precipitation. This study also highlights the relationship between IVT direction and complex coastal topography in determining precipitation extremes. For example, in Klukwan and Skagway, 80–90% of extreme ARs have south-southwesterly or south-southeasterly IVT. Coastal communities like Yakutat experience higher IVT and precipitation overall, and although southeasterly IVT is more common, extreme precipitation events are most common with southwesterly IVT. Collaboration with the National Weather Service in Juneau, Alaska will lead to improved situational awareness, forecasts, and Impact Decision Support Services to remote communities, saving lives and property in a region vulnerable to the impacts of climate change.

We use teleseismic data from the Jammu and Kashmir Seismological NETwork, to perform P-wave receiver function spatial and common-conversion-point (CCP) stacks, and joint inversion with Rayleigh-wave group-velocity dispersion, to construct 3D Vs model of the Jammu and Kashmir (J&K) Himalaya. 2D-CCP and Vs profiles reveal increasing crustal thickness from the foreland-to-hinterland, and an under-thrust Indian crust beneath J&K. The Moho positive impedance-contrast boundary is at ∼45 km depth beneath Sub-Himalaya and deepens to ∼70 km beneath Higher-to-Tethyan Himalaya, with an overall gentle NE dip. The Main Himalayan Thurst (MHT) forms a low velocity layer (LVL) with negative impedance contrast, and has a flat–ramp geometry. The flat segment is beneath Sub-to-Lesser Himalaya at 6–10 km depth, and dips ∼4◦. The mid-crustal (frontal) ramp is beneath Kishtwar Higher-Himalaya and Zanskar Ranges at 10–16 km depth, and dips ∼13–17◦. Significant along-arc variation in crustal structure is observed between east (Kishtwar) and west (Kashmir Valley) segments. Beneath the Kishtwar Window we image a Lesser Himalayan duplex (LHD) bound between MHT sole-thrust and MCT roof-thrust. LHD horses dip at high angle to the bounding structures and are illuminated by moderate seismicity. Beneath the Pir-Panjal Ranges and Kashmir Valley, the underthrust crust is ∼10 km thicker, has higher crustal Vs , and a shallower flat MHT at ∼10 km depth. The westward shallowing of the MHT occurs through a lateral ramp beneath Kishtwar Himalaya. Aftershocks of the 2013 Kishtwar earthquake concentrate on the MHT frontal and lateral ramp intersection, and possibly marks the down-dip locked-to-creep transition.

Numerical simulations of seismic cycles with rate-, state-, and temperature-dependent friction explain the various modes of seismic and aseismic ruptures in the brittle section of the lithosphere. However, the effects of viscoelastic flow in the ductile layers remain challenging to incorporate due to the wide range of length scales involved, from extremely localized within fault zones to widely distributed in the lower crust and asthenosphere. Here, we describe simulations of seismic cycles in a viscoelastic half-space using the integral method that combines discrete surface and volume elements to capture the coupling between brittle and ductile deformation. Viscoelastic flow is captured by cuboidal and tetrahedral volume elements within rectilinear and curvilinear meshes, respectively. The model resolves all phases of the seismic cycle under the radiation-damping approximation, including the nucleation and propagation of earthquake ruptures, but also the viscoelastic relaxation that follows in the ductile layers. We illustrate the approach in three dimensions with numerical simulations of seismic cycles on finite strike-slip and thrust faults overlying a viscoelastic lower crust with linear and nonlinear rheology. In two-dimensional models of subduction zones with the in-plane strain approximation, the ductile regions are meshed with triangle volume elements. The use of Green's functions only requires the discretization of the actively deforming region, resulting in a relatively small mesh. We provide open-source software implementing the method with parallel computing in a distributed architecture. The approach allows increasingly realistic representations of the lithosphere-asthenosphere system with nonlinear constitutive laws in structurally complex tectonic settings.

We devised a new data analysis technique to identify the threat level of solar active regions by processing a combined data set of magnetic field parameters and flaring activity. The data set is composed of two elements: a reduced factorization of SHARP parameters of the active regions, and information about the flaring activity at the time of measurement of the SHARP parameters. Machine learning is used to reduce the data and to subsequently classify the active regions. For this classification we used both supervised and unsupervised methods. The following processing steps are applied to reduce and enhance the SHARP data: outlier detection, redundancy elimination with common factor analysis, addition of sparsity with autoencoders, and construction of a balanced data set with under- and over-sampling. The supervised method, K-nearest neighbors, produces very good results on the strong X- and M-flares, with TSS scores of respectively 0.94 and 0.75. As unsupervised methods we used clustering models, K-means and Gaussian Mixture Models. We find that both techniques are able to distinguish non-flaring and flaring active regions. Moreover, K-means is able to distinguish C-/M-flaring active regions from X-flaring active regions. For processing purposes an unsupervised method is more useful, since the type of flare will not be available. Therefore, we conclude that K-means provides the most promising results.

Global Ionosphere Thermosphere Model (GITM) results have been compared with measurements from Global-scale Observations of the Limb and Disk (GOLD) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). For the first time, GOLD-derived exospheric temperature and column-integrated O/N$_2$ ratio measurements have been used to validate GITM model results. We examine two geomagnetic storm events for which we drive GITM with space weather conditions to understand how well the model reproduces the thermospheric responses to geomagnetic activity. In this paper, a recently developed auroral model, the Feature Tracking of Aurora (FTA) model, has been employed to calculate auroral electron precipitation in GITM (GITM w/FTA), and results are compared with the OVATION prime (OP) driven GITM model (GITM w/OP). GITM w/FTA simulated temperature, neutral density, and nitric oxide (NO) density are generally higher compared to the GITM w/OP model. During the geomagnetic storm, the GITM model and GOLD-derived exospheric temperature agree between $\sim$$0^{\circ}$ to $5^{\circ}$N latitude in the equatorial region. GOLD measurements show strong O/N$_2$ peaks and two distinct equatorial zones during the geomagnetic storm period, which is also observed in our model results. During geomagnetic storm conditions, there is an upward shift in the peak altitude profile of NO emission by up to $\approx$10 km. The NO cooling peaks estimated by GITM models are $\sim$20 km lower than SABER observations during geomagnetic storms. The SABER-derived NO emission is better reproduced by the GITM w/FTA model than by the GITM w/OP model during geomagnetic storms at high latitudes.

Modelling the short-term (<50 years) evolution of glaciers is difficult because of issues related to model initialisation and data assimilation. However, this timescale is critical, particularly for water resources, natural hazards, and ecology. Using a unique record of satellite remote-sensing data, combined with a novel optimisation and SMB-calculation method within the framework of the deep-learning-based Instructed Glacier Model, we are able to resolve initialisation issues. We thus model the evolution of all glaciers in the European Alps up to 2050 under present-day climate conditions, assuming no future climate change. We find that the resulting committed ice loss exceeds a third of the present-day ice volume by 2050, with multi-kilometre frontal retreats for even the largest glaciers. Our results show the importance of modelling ice dynamics to accurately retrieve the ice-thickness distribution and to predict future mass changes. Thanks to high-performance GPU processing, we also demonstrate our method’s global potential.

Arctic warming under increased CO2 peaks in winter, but is influenced by summer forcing via seasonal ocean heat storage. Yet changes in atmospheric heat transport into the Arctic have mainly been investigated in the annual mean or winter, with limited focus on other seasons. We investigate the full seasonal cycle of poleward heat transport modelled with increased CO2 or with individually applied Arctic sea-ice loss and global sea-surface warming. We find that a winter reduction in dry heat transport is driven by Arctic sea-ice loss and warming, while a summer increase in moist heat transport is driven by sub-Arctic warming and moistening. Intermodel spread in Arctic warming controls spread in seasonal poleward heat transport. These seasonal changes and their intermodel spread are well-captured by down-gradient diffusive heat transport. While changes in moist and dry heat transport compensate in the annual-mean, their opposite seasonality may support non-compensating effects on Arctic warming.

Winter Euro-Atlantic atmospheric blocking events have significant socioeconomical impacts as they cause various types of weather extremes in a range of regions. According to current climate projections, fewer of these blocking events will occur as temperatures rise. However, the timing of such a reduction is currently highly uncertain. Meanwhile, recent studies indicate that using climate models with high enough ocean resolutions to simulate mesoscale eddies improve simulated winter Euro-Atlantic blocking events significantly. In this paper, we show from a large ensemble of climate simulations based on the highest emission scenario that largely prominent and coarsely resolved non-eddying climate models project a noticeable significant decline in blocking frequencies from the 2030s-2040s, whereas blocking statistics in eddy-permitting simulations are noticeably decreasing only from years 2060s. Our result suggests with a strong level of confidence that winter blocking activity over the next several decades will keep being dominated by internal variability.

Supercooled liquid clouds are ubiquitous over the Southern Ocean (SO), even to temperatures below -20 °C, and comprise a large fraction of the marine boundary layer (MBL) clouds. Earth system models and reanalysis products have struggled to reproduce the observed cloud phase distribution and occurrence of cloud ice in the region. Recent simulations found the microphysical representation of ice nucleation and growth has a large impact on these properties, however, measurements of SO ice nucleating particles (INPs) to validate simulations are sparse. This study presents measurements of INPs from simultaneous aircraft and ship campaigns conducted over the SO in austral summer 2018, which include the first in situ observations in and above cloud in the region. Our results confirm recent observations that INP concentrations are uniformly lower than measurements made in the late 1960s. While INP concentrations below and above cloud are similar, higher ice nucleation efficiency above cloud supports model inferences that the dominant INP composition varies with height. Model parameterizations based solely on aerosol properties capture the mean relationship between INP concentration and temperature but not the observed variability, which is likely related to the only modest correlations observed between INPs and environmental or aerosol metrics. An updated parameterization for marine INPs is proposed, which reduces bias relative to existing methods by including wind speed as an additional variable. Direct and indirect inference of marine INP size suggests MBL INPs, at least those in the sub-2.5 μm range, are dominated by particles with diameters smaller than 500 nm.

We describe and evaluate a system for regional modeling of atmospheric composition with the Met Office Unified Model (UM), suitable for climate, weather forecasting and air quality applications. In this system, named NUMAC (`Nested UM with Aerosols and Chemistry'), a global model provides boundary conditions for regional models nested within it, using the Met Office's Regional Nesting Suite for multi-scale simulations. The regional models, which can run at convection-permitting or cloud-resolving scales, use the same code as the global model. The system includes double-moment prognostic aerosol microphysics with interactive chemistry of sulfur species, ozone, NOx and CO as in the UK Earth System Model (UKESM). Double-moment prognostic cloud microphysics is optional. To test NUMAC, we compare simulations to surface and aircraft measurements from NASA's KORUS-AQ campaign over South Korea. The performance of the regional model, which we run at 5 km resolution, is similar to the well-evaluated global model when the regional and global models use the same emissions. Most species such as ozone, NOx, OH, or PM2.5 are simulated within a factor of 2 of observations most of the time, though they are biased low compared to sensors in polluted areas (observed surface dry PM2.5 averages 28ugm-3 but we simulate 17ugm-3). Meteorology and clouds are represented satisfactorily. With higher-resolution emissions, many of the low model biases are reduced, but a tuning was required to keep NO concentrations realistic, indicating shortcomings in the chemistry scheme. We demonstrate the potential of NUMAC for studies of aerosol-cloud interactions.

Elevated seismic noise for moderate-size earthquakes recorded at teleseismic distances has limited our ability to see their complexity. We develop a machine-learning-based algorithm to separate noise and earthquake signals that overlap in frequency. The multi-task encoder-decoder model is built around a kernel pre-trained on local (e.g., short distances) earthquake data \cite{yin_multitask_2022} and is modified by continued learning with high-quality teleseismic data. We denoise teleseismic P waves of deep Mw5.0+ earthquakes and use the clean P waves to estimate source characteristics with reduced uncertainties of these understudied earthquakes. We find a scaling of moment and duration to be $M_0\simeq \tau^{4.16}$, and a resulting strong scaling of stress drop and radiated energy with magnitude ($\sigma\simeq M_0^{0.2}$ and $E_R \simeq M_0^{1.23}$). The median radiation efficiency is 5\%, a low value compared to shallow earthquakes. Overall, we show that deep earthquakes have weak rupture directivity and few subevents, suggesting a simple model of a circular crack with radial rupture propagation is appropriate. When accounting for their respective scaling with earthquake size, we find no systematic depth variations of duration, stress drop, or radiated energy within the 100-700 km depth range. Our study supports the findings of \citeA{poli_global_2016} with a doubled amount of earthquakes investigated and with earthquakes of lower magnitudes.

Particle-resolved direct numerical simulations (PR-DNS) play an increasing role in investigating aerosol-cloud-turbulence interactions at the most fundamental level of processes. However, the high computational cost associated with high resolution simulations poses considerable challenges for large domain or long duration simulation using PR-DNS. To address these issues, here we present a digital twin model of the complex physics-based PR-DNS developed by use of the data-driven Fourier Neural Operator (FNO) method. The results demonstrate high accuracy at various resolutions and the digital twin model is two orders of magnitude cheaper in terms of computational demand compared to the physics-based PR-DNS model. Furthermore, the FNO digital-twin model exhibits strong generalization capabilities for different initial conditions and ultra-high-resolution without the need to retrain models. These findings highlight the potential of the FNO method as a promising tool to simulate complex fluid dynamics problems with high accuracy, computational efficiency, and generalization capabilities, enhancing our understanding of the aerosol-cloud-precipitation system.

The transit time (TT) of streamflow encapsulates information about how catchments store and release water and solutes of different ages. The young water fraction (Fyw), the fraction of streamflow that is younger than a certain age (normally 2–3 months), has been increasingly used as an alternative metric to the commonly used mean TT (mTT). In the commonly used (‘traditional’) procedure presented by Kirchner (2016), the age threshold (τyw) of Fyw separating young from old water is not pre-defined and differs from catchment to catchment depending on the shape of the (gamma) transit time distribution. However, it can be argued that it is important to use the same pre-defined τyw for inter-catchment comparison of Fyw. In this study, we propose an alternative (‘proposed’) procedure for the estimation of Fyw with any pre-defined τyw. This allows us to also compare the effects of data sampling frequencies on the results of Fyw estimation using the same τyw. We applied the traditional and proposed procedures using daily oxygen isotope (δ18O) data in the Alp and Erlenbach catchments, Switzerland. We found that our proposed and the traditional procedure can give very different Fyw values. With the proposed procedure, the estimated Fyw significantly increases when the sampling frequency changes from sub-monthly to monthly time steps. Overall, our study highlights the importance of the selection of τyw and the sampling frequency in Fyw estimation, which should be given more attention.

The Zagros orogen in the Iranian Plateau is a natural laboratory in which to investigate the tectonic evolution of the transition from oceanic subduction to continental collision. However, where slab detachment occurred and how slab detachment affects shallower continental subduction remain poorly understood. The formation mechanism of the post-collision magmatism is also unclear. Here, we construct a high-resolution Pn-wave attenuation model for the uppermost mantle beneath the Iranian Plateau and surrounding areas using a newly compiled dataset. Weak Pn attenuation delineates the Arabian Plate front near the Moho discontinuity, extending further toward the subduction direction in the northwestern and southeastern parts, possibly due to the up-bending and underplating of the Arabian lithosphere after the loss of slab pull. The correlations among the surface Miocene-Quaternary volcanism and strong Pn attenuation in the uppermost mantle suggest that asthenospheric materials escaped from slab windows and further feed the post-collision volcanoes.

Scientific programming has become increasingly essential for manipulating, visualizing, and interpreting the large volumes of data acquired in earth science research. Yet few discipline-specific instructional approaches have been documented and assessed for their effectiveness in equipping geoscience undergraduate students with coding skills. Here we report on an evidence-based redesign of an introductory Python programming course, taught fully remotely in 2020 in the School of Oceanography at the University of Washington. Key components included a flipped structure, activities infused with active learning, an individualized final research project, and a focus on creating an accessible learning environment. Cloud-based notebooks were used to teach fundamental Python syntax as well as functions from packages widely used in climate-related disciplines. By analyzing quantitative and qualitative data from surveys, online learning platforms, student work, assessments, and a focus group, we conclude that the instructional design facilitated learning and supported self-guided scientific inquiry. Students with less or no prior exposure to coding achieved similar success as peers with more experience, an outcome likely mediated by higher engagement with course resources. We believe that the constructivist approach to teaching introductory programming and data literacy that we present could be broadly applicable across the earth sciences and in other scientific domains.

A holistic review is given of the Southern Ocean dynamic system, in the context of the crucial role it plays in the global climate and the profound changes it is experiencing. The review focuses on connections between different components of the Southern Ocean dynamic system, drawing together contemporary perspectives from different research communities, with the objective of "closing loops" in our understanding of the complex network of feedbacks in the overall system. The review is targeted at researchers in Southern Ocean physical science with the ambition of broadening their knowledge beyond their specific field and facilitating better-informed interdisciplinary collaborations. For the purposes of this review, the Southern Ocean dynamic system is divided into four main components: large-scale circulation; cryosphere; turbulence; and gravity waves. Overviews are given of the key dynamical phenomena for each component, before describing the linkages between the components. The reviews are complemented by an overview of observed Southern Ocean trends and future climate projections. Priority research areas are identified to close remaining loops in our understanding of the Southern Ocean system.

During the NASA Perseverance rover’s exploration of the Jezero crater floor, purple-hued coatings were commonly observed on rocks. These features likely record past water-rock-atmosphere interactions on the crater floor, and understanding their origin is important for constraining timing of water activity and habitability at Jezero. Here we characterize the morphologic, chemical, and spectral properties of the crater floor rock coatings using color images, visible/near-infrared reflectance spectra, and chemical data from the Mastcam-Z and SuperCam instruments. We show that coatings are common and compositionally similar across the crater floor, and consistent with a mixture of dust, fine regolith, sulfates, and ferric oxides indurated as a result of one or more episodes of widespread surface alteration. All coatings exhibit a similar smooth homogenous surface with variable thickness, color, and spatial extent on rocks, likely reflecting variable oxidation and erosional expressions related to formation and/or exposure age. Coatings unconformably overlie eroded natural rock surfaces, suggesting relatively late deposition that may represent one of the last aqueous episodes on the Jezero crater floor. While more common at Jezero, these coatings may be consistent with rock coatings previously observed in-situ at other landing sites and may be related to duricrust formation, suggesting a global alteration process on Mars that is not unique to Jezero. The Perseverance rover likely sampled these rock coatings on the crater floor and results from this study could provide important context for future investigations by the Mars Sample Return mission aimed at constraining the geologic and aqueous history of Jezero crater.

A document by Chun Tao. Click on the document to view its contents.