Most conceptual models for how fluids and sediment influence slip behavior and uplift along subduction margins are poorly constrained by geophysical observations. Given the complexity of subduction systems, overcoming this gap in knowledge will require a systems-level approach which uses high quality geophysical constraints. We present wide-angle, onshore-offshore seismic data collected along the northern Hikurangi margin, New Zealand, from which P-wave velocities were calculated using active- and passive-sources. A gravity model and reflection profiles were also assembled to create a complete, ~400 km long transect which images the incoming plate, down going slab, overthrusting forearc, and backarc rift. Velocities and gravity modelling help to constrain the lithology of the forearc basement to ~20 km depth. Upper plate lower crustal velocities and reflectivity point to the presence of underplated sediments immediately above the lithospheric mantle nose, suggesting that underplated sediments are driving uplift of the forearc. Comparing these results to geophysical images from the southern Hikurangi margin, we suggest that the backarc rift influences along-strike changes in the compressional stresses experienced by the forearc, driving changes in bending stresses within the subducting slab.

The mass transport of volatiles on Mars represents a seasonally changing load onto the lithosphere of the planet. Much like on Earth, as mass is redistributed across the planet, the surface responds in a complex manner becoming displaced downwards or upwards. The magnitude and extent of displacement depend on the properties of the load and mechanical properties of the planetary interior. Based on new estimates of the height variation of the seasonal polar cap (SPC) we predict local surface displacements of up to tens of millimeters with a strong degree 1 signal throughout the Martian year. The long-wavelength portion of the displacement is potentially observable, with a magnitude of a few millimeters, located away from the seasonal polar cap where we could realistically measure it with a landed or orbital mission. We also model the direct contribution of this process to observable time variable gravity where we find the odd zonal coefficients to be in line with previous measurements, although with a smaller magnitude. Future measurements of this displacement could be used to help elucidate the composition of the mantle and crust of Mars, using this process as a probe into the Martian interior. Furthermore, more refined measurements of time-variable gravity would be a powerful tool in constraining the pole-to-pole volatile cycle present on Mars.

Dynamical models used in climate prediction often suffer from systematic errors that can deteriorate their predictions. We propose a hybrid model that combines both dynamical model and artificial neural network (ANN) correcting model errors to improve climate predictions. We conducted a series of experiments using the Modular Arbitrary-Order Ocean-Atmosphere Model (MAOOAM) and trained the ANN with input from both atmospheric and oceanic variables and output from analysis increments. Our results demonstrate that the hybrid model outperforms the dynamical model in terms of prediction skill for both atmospheric and oceanic variables across different lead times. Furthermore, we conducted additional experiments to identify the key factors influencing the prediction skill of the hybrid model. We found that correcting both atmospheric and oceanic errors yields the highest prediction skill while correcting only atmospheric or oceanic errors has limited improvement.

Numerical weather prediction (NWP) and climate models still struggle to correctly predict and represent atmospheric blocking over the European region (EuBL). In recent years, there has been growing evidence that latent heat release in midlatitude weather systems such as warm conveyor belts (WCBs) contribute significantly to the onset and maintenance of blocking anticyclones. In this study, we show that for the European Centre for Medium-Range Weather Forecast’s IFS reforecasts in extended winter (1997–2017) WCB activity around EuBL onsets becomes challenging to predict in pentad 3 (10–14 days) and beyond. This is in line with the short overall WCB forecast skill horizon of around 10 days and partly explains low EuBL skill in NWP models. However, we also show cases in which accurate WCB and EuBL forecasts are possible even in pentad 4 (15–19 days). These cases are associated with accurate WCB forecasts over the North Atlantic and North Pacific pointing towards a teleconnection between the two. Lastly, we find that WCB activity over the North Atlantic emerges way before the block is established and different pathways into EuBL exist in the reforecasts which are characterised by a westward shift of the main WCB inflow and outflow region compared to reanalysis. We conclude that despite intrinsic limits of predictability there is room to improve forecasts of EuBL onset by improving the representation of WCB activity in NWP models.

AbstractHere, we introduce the concept of “outdoor days” defined as those relatively pleasant days when most people may enjoy outdoor activities such as walking, jogging, and cycling. Although most climate studies primarily focus on changes in climate mean and/or extremes, projecting response of outdoor days to climate change is particularly important given their relevance to quality of life for communities. Here, we project how climate change reshapes seasonality of US outdoor days: relatively large drops in summer, late spring, and early fall; and a significant increase in winter. However, despite of global warming, annual outdoor days are projected to change only slightly, with notable exceptions. Consistent with recent observations, we project relatively large drops in southeast (-23%), south (-19%), and Ohio Valley (-18%), and a significant increase in northwest (14%) towards the end of the century. Our findings have implications for quality of life in different regions, and for nationwide travel and tourism.

A document by Ivona Cetinić. Click on the document to view its contents.

Quantitative precipitation forecasting in numerical weather prediction (NWP) models rely on physical parameterization schemes. However, these schemes involve considerable uncertainties due to limited knowledge of the mechanisms involved in the precipitating process, ultimately leading to degraded precipitation forecasting skills. To address this issue, our study proposes using a Swin-Transformer based deep learning (DL) model to quantitatively map fundamental variables solved by NWP models to precipitation maps. Our results show that the DL model effectively extracts features over meteorological variables, leading to improved precipitation skill scores of 21.7%, 60.5%, and 45.5% for light rain, moderate rain, and heavy rain, respectively, on an hourly basis. We also evaluate two case studies under different driven synoptic conditions and show promising results in estimating heavy precipitation during strong convective precipitation events. Overall, the proposed DL model can provide a vital reference for capturing precipitation-triggering mechanisms and enhancing precipitation forecasting skills. Additionally, we discuss the sensitivities of the fundamental meteorological variables used in this study, training strategies, and performance limitations.

Astronomical cycles recorded in stratigraphic sequences offer a powerful data source to estimate Earth’s axial precession frequency k, as well as the frequency of rotation of the planetary perihelia (gi) and of the ascending nodes of their orbital planes (si). Together, these frequencies control the insolation cycles (eccentricity, obliquity and climatic precession) that affect climate and sedimentation, providing a geologic record of ancient Solar system behavior spanning billions of years. Here we introduce two Bayesian methods that harness stratigraphic data to quantitatively estimate ancient astronomical frequencies and their uncertainties. The first method (TimeOptB) calculates the posterior probability density function (PDF) of the axial precession frequency k and of the sedimentation rate u for a given cyclostratigraphic data set, while setting the Solar system frequencies gi and si to fixed values. The second method (TimeOptBMCMC) applies an adaptive Markov chain Monte Carlo algorithm to efficiently sample the posterior PDF of all the parameters that affect astronomical cycles recorded in stratigraphy: five gi, five si, k, and u. We also include an approach to assess the significance of detecting astronomical cycles in cyclostratigraphic records. The methods provide an extension of current approaches that is computationally efficient and well suited to recover the history of astronomical cycles, Earth-Moon history, and the evolution of the Solar system from geological records. As case studies, data from the Xiamaling Formation (N. China, 1.4 Ga) and ODP Site 1262 (S. Atlantic, 55 Ma) are evaluated, providing updated estimates of astronomical frequencies, Earth-Moon history, and secular resonance terms.

At Jupiter, part of the auroral radio emissions are induced by the Galilean moons Io, Europa and Ganymede. Until now, except for Ganymede, they have been only remotely detected, using ground-based radio-telescopes or electric antennas aboard spacecraft. The polar trajectory of the Juno orbiter allows the spacecraft to cross the range of magnetic flux tubes which sustain the various Jupiter-satellite interactions, and in turn to sample in situ the associated radio emission regions. In this study, we focus on the detection and the characterization of radio sources associated with Io, Europa and Ganymede. Using electric wave measurements or radio observations (Juno/Waves), in situ electron measurements (Juno/JADE-E), and magnetic field measurements (Juno/MAG) we demonstrate that the Cyclotron Maser Instability (CMI) driven by a loss-cone electron distribution function is responsible for the encountered radio sources. We confirmed that radio emissions are associated with Main (MAW) or Reflected Alfvén Wing (RAW), but also show that for Europa and Ganymede, induced radio emissions are associated with Transhemispheric Electron Beam (TEB). For each traversed radio source, we determine the latitudinal extension, the CMI-resonant electron energy, and the bandwidth of the emission. We show that the presence of Alfvén perturbations and downward field aligned currents are necessary for the radio emissions to be amplified.

Multispectral mapping data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provide a unique opportunity to characterize south polar ice deposits at higher spectral sampling, spatial resolution, or spatiotemporal coverage than previous work. This new perspective can help to constrain the nature and distribution of different mixtures of CO2 ice, H2O ice, and dust that influence the formation, evolution, and preservation of Mars climate records. We processed 1103 CRISM observations spanning southern summer of six Mars Years (MY) through a combination of k-means clustering and random forest classification. Using a set of 12 spectral endmembers directly tied to previous work with high-resolution CRISM targeted data, we made a series of temporally restricted mosaics showing surface spectral variation over time. The mosaics show the effects of the MY 28 dust storm on the removal of the seasonal CO2 ice cap that year and reveal how this process differed from the years that followed. A mosaic showing residual ice surfaces displays broad agreement with previous compositional maps while resolving new details in the distribution of H2O ice-rich material around the periphery of the bright CO2 ice cap. By showing how surface composition varies across a broad swath of the south polar region though time, the endmember set and classified mosaics produced in this work can provide critical context for future studies of the dynamic processes that shape south polar ice deposits.

Cirrus dominate the longwave radiative budget of the tropics. For the first time, we quantify the variability in cirrus properties and longwave cloud radiative effects (CREs) that arises from differences in microphysics within nudged global storm-resolving simulations from a single model. Nudging allows us to compute radiative biases precisely using coincident satellite measurements and to fix the large-scale dynamics across our set of simulations and isolate the influence of microphysics. We run five-day simulations with four commonly-used microphysics schemes of varying complexity (SAM1MOM, Thompson, M2005 and P3) and find that the tropical average longwave CRE varies over 20 W m$^{-2}$ between schemes. P3 best reproduces observed longwave CRE. M2005 and P3 simulate cirrus with realistic frozen water path but unrealistically high ice crystal number concentrations which commonly hit limiters and lack the variability and dependence on frozen water content seen in aircraft observations. Thompson and SAM1MOM have too little cirrus.

Existing models for estimating hyporheic oxygen mass transfer often require numerous parameters related to flow, bed, and channel characteristics, which are frequently unavailable. We performed a meta-analysis on existing dataset, enhanced with high Reynolds number cases from a validated Computational Fluid Dynamics model, to identify key parameters influencing effective diffusivity at the sediment water interface. We applied multiple linear regression to generate empirical models for predicting eddy diffusivity. To simplify this, we developed two single-parameter models using either a roughness or permeability-based Reynolds number. These models were validated against existing models and literature data. The model using roughness Reynolds number is easy to use and can provide an estimate of the oxygen transfer coefficient, particularly in scenarios where detailed bed characteristics such as permeability might not be readily available.

Rivers are important contributors to global greenhouse gas (GHG) exchange with the atmosphere. However, much less is known about biogeochemical dynamics in rivers when they dry, particularly in isolated pools created by drying. Our objective was to examine the effects of water temperature and allochthonous organic matter (OM) quantity on carbon dioxide (CO2) and methane (CH4) fluxes in isolated pools. We used an automated analyzer to measure CO2 and CH4 from 36 mesocosms filled with sediments and water from a non-perennial river, with temperature (20, 25, 30 °C) and Alnus glutinosa leaf litter (2g, 5g, 10 g) manipulations in triplicate. We found positive individual effects of water temperature and OM quantity on CO2 fluxes, and a synergistic effect of water temperature and OM on CH4 fluxes during the late stages of the incubation. Given the increase in water temperature and OM inputs in rivers associated with climate change, our results indicate an associated increase in CO2, and a disproportionate increase in CH4 fluxes to the atmosphere, potentially contributing towards a positive climate feedback loop.

RESUMO Este trabalho tem por objetivo pesquisar as principais contribuições da entrevista inicial psicológica no contexto da prática clínica na identificação de sintomas depressivos. Portanto, propôs-se também a identificar os principais aspectos e sintomas do transtorno depressivo, bem como a análise dos sintomas a partir do relato do paciente. Foi realizado uma pesquisa bibliográfica nas bases de dados BVS, MedLine e PsycoInfo de artigos indexados e literaturas impressas que discorriam sobre a temática. Utilizou-se das palavras-chave: entrevista inicial, avaliação psicológica, sintomas depressivos. Com isso, concluiu que as principais contribuições encontradas na literatura condizem com a apresentação de comportamentos e emoções disfuncionais que podem indicar a presença do transtorno depressivo ou evoluir para o mesmo, bem como com as contribuições frente aos cuidados e análise criteriosa desses sintomas identificados. Ainda, diante dos resultados, conclui-se que a entrevista inicial enquanto prática, exerce importantes contribuições nas mais variadas aplicabilidades clínicas. Todavia, a literatura chama a atenção para os aspectos da aplicação adequada por parte do profissional. Palavras-chave: Entrevista inicial. Avaliação psicológica. Depressão. Sintomas. Psicologia. ABSTRACT This work aims to research the main contributions of the initial psychological interview in the context of clinical practice in the identification of depressive symptoms. Therefore, it was also proposed to identify the main aspects and symptoms of depressive disorder, as well as the analysis of symptoms based on the patient's report. A bibliographic search was carried out in the VHL, MedLine and PsycoInfo databases of indexed articles and printed literature that discussed the theme. The following keywords were used: initial interview, psychological assessment, depressive symptoms. Thus, he concluded that the main contributions found in the literature are consistent with the presentation of dysfunctional behaviors and emotions that may indicate the presence of the depressive disorder or progress to it, as well as with the contributions towards the care and careful analysis of these identified symptoms. Still, in view of the results, it is concluded that the initial interview as a practice, makes important contributions in the most varied clinical applications. However, the literature draws attention to aspects of proper application by the professional.

As the planet approaches local and global exceedance of the 1.5o C stabilization target, damages from climate change, mostly due to extremes, are growing, far faster than projected. At the same time, assessment models have projected high costs of mitigation, but the cost of energy is dropping faster than projected. Climate policy has assumed that damage costs are manageable while decarbonization is expensive. Both these assumptions are wrong. Damage costs are rising rapidly and green energy costs are dropping quickly. potentially leading to a tipping point in human behavior: scientists need to explore options better aligned with this emerging reality.

A document by Peter Galbraith. Click on the document to view its contents.

Surface hotspot motions are approximately a factor of two faster in the Pacific than the Indo-Atlantic, and the Pacific large low shear velocity province (LLSVP) appears to be significantly shorter than the Indo-Atlantic LLSVP. Hypothesizing that surface hotspot motions are correlated with the motion of plume sources on the upper surface of chemically distinct, intrinsically dense LLSVPs, we use 3D spherical mantle convection models to compute the velocity of plume sources and compare with observed surface hotspot motions. No contrast in the mean speed of Pacific and Indo-Atlantic hotspots is predicted if the LLSVPs are treated as purely thermal anomalies and plume sources move laterally across the core-mantle boundary. However, when LLSVP topography is included in the model, the predicted hotspot speeds are, on average, faster in the Pacific than the Indo-Atlantic, even when modest topography is assigned to both LLSVPs (e.g., 100-300 km). The difference in mean hotspot speed increases to a factor of two for larger and laterally variable LLSVP topography estimated from seismic tomographic model S40RTS (up to 1100-1500 km for the Indo-Atlantic region versus 700-1400 km for the Pacific region) and our results also broadly reproduce the convergence of Pacific hotspots toward the center of the Pacific LLSVP. These largescale features of global hotspot motions are only reproduced when ambient mantle material flows over large, relatively stable topographical features, suggesting that LLSVPs are chemically distinct and intrinsically dense relative to ambient mantle material.

A document by Zhichao Shen. Click on the document to view its contents.