Vertical Velocity Variance Research Articles

Surface Quasi Geostrophic Reconstruction of Vertical Velocities and Vertical Heat Fluxes in the Southern Ocean: Perspectives for SWOT

AbstractMesoscale currents account for 80% of the ocean's kinetic energy, whereas submesoscale currents capture 50% of the vertical velocity variance. SWOT's first sea surface height (SSH) observations have a spatial resolution an order of magnitude greater than traditional nadir‐looking altimeters and capture mesoscale and submesoscale features. This enables the derivation of submesoscale vertical velocities, crucial for the vertical transport of heat, carbon and nutrients between the ocean interior and the surface. This work focuses on a mesoscale energetic region south of Tasmania using a coupled ocean‐atmosphere simulation at km‐scale resolution and preliminary SWOT SSH observations. Vertical velocities (w), temperature anomalies and vertical heat fluxes (VHF) from the surface down to 1,000 m are reconstructed using effective surface Quasi‐Geostrophic (sQG) theory. An independent method for reconstructing temperature anomalies, mimicking an operational gridded product, is also developed. Results show that sQG reconstructs 90% of the modeled w and VHF rms at scales down to 30 km just below the mixed layer and 50%–70% of the rms for scales larger than 70 km at greater depth, with a spatial correlation of 0.6. The reconstruction is spectrally coherent for scales larger than 30–40 km at the surface, slightly degrading ( 0.55) at depth. Two temperature anomaly data sets yield similar results, indicating the dominance of w on VHF. The RMS of sQG and VHF derived from SWOT are twice as large as those derived from conventional altimetry, highlighting the potential of SWOT for reconstructing energetic meso and submesoscale dynamics in the ocean interior.

A probabilistic full waveform inversion of surface waves

AbstractOver the past decades, surface wave methods have been routinely employed to retrieve the physical characteristics of the first tens of meters of the subsurface, particularly the shear wave velocity profiles. Traditional methods rely on the application of the multichannel analysis of surface waves to invert the fundamental and higher modes of Rayleigh waves. However, the limitations affecting this approach, such as the 1D model assumption and the high degree of subjectivity when extracting the dispersion curve, motivate us to apply the elastic full‐waveform inversion, which, despite its higher computational cost, enables leveraging the complete information embedded in the recorded seismograms. Standard approaches solve the full‐waveform inversion using gradient‐based algorithms minimizing an error function, commonly measuring the misfit between observed and predicted waveforms. However, these deterministic approaches lack proper uncertainty quantification and are susceptible to get trapped in some local minima of the error function. An alternative lies in a probabilistic framework, but, in this case, we need to deal with the huge computational effort characterizing the Bayesian approach when applied to non‐linear problems associated with expensive forward modelling and large model spaces. In this work, we present a gradient‐based Markov chain Monte Carlo full‐waveform inversion where we accelerate the sampling of the posterior distribution by compressing data and model spaces through the discrete cosine transform. Additionally, a proposal is defined as a local, Gaussian approximation of the target density, constructed using the local Hessian and gradient information of the log posterior. We first validate our method through a synthetic test where the velocity model features lateral and vertical velocity variations. Then we invert a real dataset from the InterPACIFIC project. The obtained results prove the efficiency of our proposed algorithm, which demonstrates to be robust against cycle‐skipping issues and able to provide reasonable uncertainty evaluations with an affordable computational cost.

Aerosol-induced closure of marine cloud cells: enhanced effects in the presence of precipitation

Abstract. The Weather Research Forecasting (WRF) version 4.3 model is configured within a Lagrangian framework to quantify the impact of aerosols on evolving cloud fields. Kilometer-scale simulations utilizing meteorological boundary conditions are based on 10 case study days offering diverse meteorology during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA). Measurements from aircraft, the ground-based Atmosphere Radiation Measurement (ARM) site at Graciosa Island in the Azores, and A-Train and geostationary satellites are utilized for validation, demonstrating good agreement with the WRF-simulated cloud and aerosol properties. Higher aerosol concentration leads to suppressed drizzle and increased cloud water content in all case study days. These changes lead to larger radiative cooling rates at cloud top, enhanced vertical velocity variance, and increased vertical and horizontal wind speed near the base of the lower-tropospheric inversion. As a result, marine cloud cell area expands, narrowing the gap between shallow clouds and increasing cloud optical thickness, liquid water content, and the top-of-atmosphere outgoing shortwave flux. While similar aerosol effects are observed in lightly to non-raining clouds, they tend to be smaller by comparison. These simulations show a relationship between cloud cell area expansion and the radiative adjustments caused by liquid water path and cloud fraction changes. The adjustments are positive and scale as 74 % and 51 %, respectively, relative to the Twomey effect. While higher-resolution large-eddy simulations may provide improved representation of cloud-top mixing processes, these results emphasize the importance of addressing mesoscale cloud-state transitions in the quantification of aerosol radiative forcing that cannot be attained from traditional climate models.

Diagnostics for Imbalance on the Convective Scale

Abstract The analyses produced by a data assimilation system may be unbalanced, that is dynamically inconsistent with the forecasting model, leading to noisy forecasts and reduced skill. While there are effective procedures to reduce synoptic-scale imbalance, the situation on the convective scale is less clear because the flowon this scale is strongly divergent and non-hydrostatic. In this studywe compare three measures of imbalance relevant to convective-scale data assimilation: (i) surface pressure tendencies, (ii) vertical velocity variance in the vicinity of convective clouds, and (iii) departures from the vertical velocity prescribed by the weak temperature gradient (WTG) approximation. These are applied in a numerical weather prediction system, with three different data assimilation algorithms: 1. Latent Heat Nudging (LHN), 2. Local Ensemble Transform Kalman Filter (LETKF), and 3. LETKF in combination with incremental analysis updates (IAU). Results indicate that surface pressure tendency diagnoses a different type of imbalance than the vertical velocity variance and theWTG departure. The LETKF induces a spike in surface pressure tendencies, with a large-scale spatial pattern that is not clearly related to the precipitation pattern. This anomaly is notably reduced by the IAU. LHN does not generate a pronounced signal in the surface pressure, but produces the most imbalance in the other two measures. The imbalances measured by the partitioned vertical velocity variance andWTG departures are similar, and closely coupled to the convective precipitation. Between these two measures, the WTG departure has the advantage of being simpler and more economical to compute.

Tomographic imaging of South Rewa basin, Central India: Implications of Gondwana rifting and Late Cretaceous volcanism

We have imaged thick (3.0–5.0 km) sub-trappean Gondwana sediments deposited in a typical rift-environment of the south Rewa basin in Central India masked by the Deccan basalts. The basalts intrude through the basin forming several dykes, sills, and other intrusions along with large-scale undulations of the basement showing complex geology and tectonic settings due to Late Cretaceous volcanism (∼65 Ma). To delineate complex subsurface geological structures and understand the tectonic settings, we use long-offset seismic reflection data along the N-S trending 127 km Kuvari-Shahdol profile of the basin. The conventional stack and pre-stack time migration techniques fail to image the complex subsurface structures dominated by steeply dipping faults. The steeply dipping faults with small-scale structures are influenced by strong lateral and vertical velocity variations that cause problems in imaging the basin. Hence, a robust tomographic inversion with pre-stack depth migration technique is adopted to image fine-scale subtle subsurface geological structures with smooth velocity variations. The tomographic velocity model and pre-stack depth migration seismic image could decipher basaltic trap thickness, numerous dyke intrusions, alternate horsts and grabens with deposition of thick hydrocarbon-bearing sub-trappean Gondwana rocks along with the basement configuration. The deep basinal faults with highly distorted basement structures represent the intense tectonic activity of this Gondwana rift-basin. The deep-seated hydrocarbon reservoir is discovered with an excellent trapping mechanism forming both pre-rift and syn-rift settings of the rift-basin. The seismic image is further constrained and corroborated by the inversion of residual Bouguer gravity anomaly data to obtain corresponding density model derived from tomographic velocity model. The large basement faults, horsts and grabens, several intrusives like dyke, sill, laccolith, and thick sub-trappean Gondwana formations with Deccan trap cover indicate complex geology and tectonic settings of south Rewa basin forming the Late Cretaceous Volcanic Province of India.

A case study analysis of the impact of a new free tropospheric turbulence scheme on the dispersion of an atmospheric tracer

AbstractMost Lagrangian dispersion models represent free tropospheric turbulence as a homogeneous steady‐state process. However, intermittent turbulent mixing in the free troposphere may be a significant source of mixing. We test a new parametrization scheme that represents spatial‐ and temporal‐varying turbulence in the free troposphere in the Met Office's Numerical Atmospheric‐dispersion Modelling Environment. We use semi‐idealized emissions of radon‐222 (Rn) from rocks and soil in the United Kingdom to evaluate the impact of using a variable free tropospheric turbulence parameterization on the dispersion of Rn. We performed two experiments, the first using the existing steady‐state scheme and the second using the newly implemented spatio‐temporal‐varying scheme, for two case periods July 2018 and April 2021. We find that the turbulence in the varying scheme (represented by the vertical velocity variance) can range by two to three orders of magnitude (10 to 10 m s) when compared with the steady‐state scheme (10 m s). In particular, low‐altitude turbulence is enhanced when synoptic conditions are conducive to forming low‐level jets. This leads to a greater dispersion in the free troposphere, reducing the mean monthly Rn concentration above the boundary layer by 20–40% relative to the steady‐state scheme. We conclude that without a space–time‐varying free tropospheric turbulence scheme atmospheric dispersion may be significantly underestimated under synoptic conditions that are favourable for low‐level jet formation. This underestimation of dispersion may potentially result in inaccurate estimations of local emissions in top‐down greenhouse gas inventory studies.

Field observations of the wake from a full-scale tidal turbine array

Wake measurements are critical for quantifying the hydrodynamic effects of tidal energy extraction and for designing arrays of tidal turbines. In this investigation field measurements from the wake of PLAT-I, a commercial-scale floating array of four tidal turbines, are presented. Instrumented surface-following drifters are used to measure velocity and turbulence in the wake of PLAT-I while deployed in Grand Passage, an energetic tidal channel in the Bay of Fundy, NS, Canada. Field measurements were obtained when the turbines where fully operational under optimal conditions during spring tides. The collected data are used to construct tridimensional maps of acoustic backscatter, mean velocity, vertical velocity variance and turbulent kinetic energy dissipation rate downstream of the platform at different stages of the tide. The operational turbine array wake was captured for ebb and flood tides. For both ebb and flood, reduced velocities are observed in the upper water column at the depths spanned by the turbine rotors. Vertical profiles of velocity mix quickly during flood tide but velocities remain slower than the undisturbed flow outside of the wake up to 20 effective diameters downstream of the platform. In contrast, during ebb, the velocity deficit persists farther downstream, and the reduced velocity increases slightly. Elevated turbulence levels peak at 2 effective diameters downstream of the turbines and recover to undisturbed flow levels at approximately 10 effective diameters downstream of the platform for both ebb and flood tides. Total energy dissipated through turbulence within the wake is estimated to be less than 10% of the energy extracted for electricity production.

Airborne Measurements of Scale‐Dependent Latent Heat Flux Impacted by Water Vapor and Vertical Velocity Over Heterogeneous Land Surfaces During the CHEESEHEAD19 Campaign

AbstractThe water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio (rv) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity (w) variance (), and rv variance () over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, , and at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in , and 200 m–8 km in . The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by and . The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from and . The monthly temporal variations mainly come from the first two major contributing classified scales in LE, , and . These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information.

Numerical Calculations for Curved Open Channel Flows with Advanced Depth-Integrated Models

This paper examines the effect of coupling several equations for vertical velocity profiles in a depth-integrated model to clarify the roles of three-dimensional flow structures minimizing the errors from the two-dimensional calculation model. In addition, this paper develops a numerical discretization method for the dispersion terms in the horizontal momentum equations. It is revealed that the use of the 2DC model underestimates the water surface elevation through the comparisons with the experimental datasets, advanced 2DC and 3DC results. The prediction of water surface elevation is considerably improved by taking into account of secondary flow effect with vorticity equations. It is clarified that the accuracy in predicting the water surface elevation is increased with increasing the degree of the function for vertical velocity profiles in advanced 2DC models or the number of vertical grids in 3DC model, while non-hydrostatic pressure and variation in vertical velocity have a second importance.

A FEM Flow Impact Acoustic Model Applied to Rapid Computation of Ocean-Acoustic Remote Sensing in Mesoscale Eddy Seas

Mesoscale eddies have an impact on the marine environment mainly in two areas, namely, currents and changes in the sound velocity gradient due to temperature and salt stirring. The traditional underwater-related remote sensing acoustic remote sensing model is capable of analyzing the acoustic field under the change in sound velocity gradient, but it is not capable of analyzing the acoustic field under the influence of ocean currents. In order to more effectively analyze the changes in the acoustic field caused by mesoscale eddies, this paper proposes a FEM flow impact model applied to the rapid computation of acoustic remote sensing of mesoscale eddies in the sea area. The algorithm first performs a grid optimization of the sea area model based on vertical sound velocity variations and completes the classification of sound velocity layer junctions. At the same time, we construct the sound velocity gradient environment affected by the mesoscale eddy and then simplify the fluid flow in the mesoscale eddy into a non-viscous and non-rotating velocity potential, and then participate in the solution of the three-dimensional spatial fluctuation equations in the form of time-harmonic in the frequency domain, from which we can obtain the truncated sound pressure as well as the propagation loss, and quickly and completely characterize the acoustic remote sensing of the sea area of the mesoscale eddy. The paper verifies the effectiveness of the algorithm through SW06-contained flow experiments and further proposes an optimization formula for sound velocity inversion. We analyze this using measured data of mesoscale eddy fields in the Bering Sea waters during 2022 and find that eddies have a greater effect on the propagation of the acoustic field along their flow direction.

Stochastic modelling of the instantaneous velocity profile in rough-wall turbulent boundary layers

The statistical properties of uniform momentum zones (UMZs) are extracted from laboratory and field measurements in rough wall turbulent boundary layers to formulate a set of stochastic models for the simulation of instantaneous velocity profiles. A spatiotemporally resolved velocity dataset, covering a field of view of $8 \times 9\,{\rm m}^2$ , was obtained in the atmospheric surface layer using super-large-scale particle image velocimetry (SLPIV), as part of the Grand-scale Atmospheric Imaging Apparatus (GAIA). Wind tunnel data from a previous study are included for comparison (Heisel et al., J. Fluid Mech., vol. 887, 2020, R1). The probability density function of UMZ attributes such as their thickness, modal velocity and averaged vertical velocity are built at varying elevations and modelled using log-normal and Gaussian distributions. Inverse transform sampling of the distributions is used to generate synthetic step-like velocity profiles that are spatially and temporally uncorrelated. Results show that in the wide range of wall-normal distances and $Re_\tau$ up to $\sim O(10^6)$ investigated here, shear velocity scaling is manifested in the velocity jump across shear interfaces between adjacent UMZs, and attached eddy behaviour is observed in the linear proportionality between UMZ thickness and their wall normal location. These very same characteristics are recovered in the generated instantaneous profiles, using both fully stochastic and data-driven hybrid stochastic (DHS) models, which address, in different ways, the coupling between modal velocities and UMZ thickness. Our method provides a stochastic approach for generating an ensemble of instantaneous velocity profiles, consistent with the structural organisation of UMZs, where the ensemble reproduces the logarithmic mean velocity profile and recovers significant portions of the Reynolds stresses and, thus, of the streamwise and vertical velocity variability.

Investigation of Hydrostatic Imbalance with Field Observations

Abstract The hydrostatic equilibrium addresses the approximate balance between the positive force of the vertical pressure gradient and the negative gravity force and has been widely assumed for atmospheric applications. The hydrostatic imbalance of the mean atmospheric state for the acceleration of vertical motions in the vertical momentum balance is investigated using tower, the global positioning system radiosonde, and Doppler lidar and radar observations throughout the diurnally varying atmospheric boundary layer (ABL) under clear-sky conditions. Because of the negligibly small mean vertical velocity, the acceleration of vertical motions is dominated by vertical variations of vertical turbulent velocity variances. The imbalance is found to be mainly due to the vertical turbulent transport of changing air density as a result of thermal expansion/contraction in response to air temperature changes following surface temperature changes. In contrast, any pressure change associated with air temperature changes is small, and the positive vertical pressure-gradient force is strongly influenced by its background value. The vertical variation of the turbulent velocity variance from its vertical increase in the lower convective boundary layer (CBL) to its vertical decrease in the upper CBL is observed to be associated with the sign change of the imbalance from positive to negative due to the vertical decrease of the positive vertical pressure-gradient force and the relative increase of the negative gravity force as a result of the decreasing upward transport of the low-density air. The imbalance is reduced significantly at night but does not steadily approach zero. Understanding the development of hydrostatic imbalance has important implications for understanding large-scale atmosphere, especially for cloud development. Significance Statement It is well known that the hydrostatic imbalance between the positive pressure-gradient force due to the vertical decrease of atmospheric pressure and the negative gravity forces in the vertical momentum balance equation has important impacts on the vertical acceleration of atmospheric vertical motions. Vertical motions for mass, momentum, and energy transfers contribute significantly to changing atmospheric dynamics and thermodynamics. This study investigates the often-assumed hydrostatic equilibrium and investigate how the hydrostatic imbalance is developed using field observations in the atmospheric boundary layer under clear-sky conditions. The results reveal that hydrostatic imbalance can develop from the large-eddy turbulent transfer of changing air density in response to the surface diabatic heating/cooling. The overwhelming turbulence in response to large-scale thermal forcing and mechanical work of the vast Earth surface contributes to the hydrostatic imbalance on large spatial and temporal scales in numerical weather forecast and climate models.

Role of thermodynamic and turbulence processes on the fog life cycle during SOFOG3D experiment

Abstract. In this study, we use a synergy of in situ and remote sensing measurements collected during the SOuthwest FOGs 3D experiment for processes study (SOFOG3D) field campaign in autumn and winter 2019–2020 to analyse the thermodynamic and turbulent processes related to fog formation, evolution, and dissipation across southwestern France. Based on a unique measurement dataset (synergy of cloud radar, microwave radiometer, wind lidar, and weather station data) combined with a fog conceptual model, an analysis of the four deepest fog episodes (two radiation fogs and two advection–radiation fogs) is conducted. The results show that radiation and advection–radiation fogs form under deep and thin temperature inversions, respectively. For both fog categories, the transition period from stable to adiabatic fog and the fog adiabatic phase are driven by vertical mixing associated with an increase in turbulence in the fog layer due to mechanical production (turbulence kinetic energy (TKE) up to 0.4 m2 s−2 and vertical velocity variance (σw2) up to 0.04 m2 s−2) generated by increasing wind and wind shear. Our study reveals that fog liquid water path, fog top height, temperature, radar reflectivity profiles, and fog adiabaticity derived from the conceptual model evolve in a consistent manner to clearly characterise this transition. The dissipation time is observed at night for the advection–radiation fog case studies and after sunrise for the radiation fog case studies. Night-time dissipation is driven by horizontal advection generating mechanical turbulence (TKE at least 0.3 m2 s−2 and σw2 larger than 0.04 m2 s−2). Daytime dissipation is linked to the combination of thermal and mechanical turbulence related to solar heating (near-surface sensible heat flux larger than 10 W m−2) and wind shear, respectively. This study demonstrates the added value of monitoring fog liquid water content and depth (combined with wind, turbulence, and temperature profiles) and diagnostics such as fog liquid water reservoir and adiabaticity to better explain the drivers of the fog life cycle.

Effect of isothermal rough boundaries on the statistics of velocity and temperature fluctuations in turbulent Rayleigh–Bénard convection

Using direct numerical simulations, we investigate the effect of surface roughness on the statistics of fluctuations in a 2D rectangular cell of aspect ratio Γ = 2 with air as the working fluid. We consider roughly two decades of Rayleigh number, 108≤Ra≤4.64×109, with three roughness configurations of R1, R2, and R3 characterized by their maximum heights of 5%, 10%, and 20% of the cell height, respectively. We show that roughened cells trigger stronger fluctuations, which further gets augmented with increasing Ra. Vertical variations of velocity and temperature fluctuations show different trends. While the temperature fluctuation becomes homogeneous in the bulk, it exhibits strong inhomogeneous vertical velocity fluctuations. The comparison of global heat flux with smooth case shows a significant increment beyond Ra=2.15×108. Surface roughness impacts local heat flux through augmented plumes, which is qualitatively ascertained by instantaneous temperature field. Furthermore, probability distribution functions reveal no particular trend for the taller roughness configurations, though the magnitude is amplified. Through identification of plumes and background regions, we show their behavior as a function of Ra for different rough cases. Finally, we decompose the shear production into its three components (based on the nature of mechanical forces) to understand the energy interaction between the mean flow and fluctuating flow field.

Wind-tunnel measurements of sensible turbulent heat fluxes over melting ice

Accelerated glacier melt and the loss of perennial snowfields have been associated with increased warming in polar regions, at rates up to four times faster than the rest of the world, thereby reinforcing the critical need for improved models (and predictions) of glacier melt. An essential requirement for such models is an improved understanding of the sensible heat fluxes over glaciers. Since their complexity makes them difficult to model, and direct measurements of sensible turbulent heat fluxes over real glaciers are both rare and impractical, the present work involves simultaneous hot-wire anemometry and cold-wire thermometry measurements of two components of velocity and temperature above a melting glacier model in a series of wind-tunnel experiments. Both single- and multi-variable statistics were used to compare the turbulent velocity field measured over melting ice with that of a similar flow in the absence of ice. The results demonstrate that the ice's presence reduces the magnitude of the Reynolds stresses and vertical velocity variance, but also increases the streamwise velocity variance. The transient evolution of temperature statistics throughout the melt process was also investigated and found to be similar when suitably non-dimensionalized. The velocity and temperature fields were furthermore evaluated at an equivalent non-dimensional time during the melt process, in which statistics of the temperature field, and joint statistics of the vertical velocity and temperature, were studied. The present work lays the foundation for future laboratory-scale replications of the flow above melting glaciers, and provides additional insight into turbulent heat transfer over melting ice.

Benchmarking a new 2.5D shallow water model for lava flows

Lava flows associated with effusive volcanic eruptions require accurate modelling in order to forecast potential paths of destruction.This study presents a new depth-averaged model that overcomes the classical shallow water hypothesis by incorporating several enhancements, allowing for a more precise representation of the flow dynamics and behaviour: (i) a parabolic profile which captures the vertical variations in velocity within the flow; (ii) a non-constant vertical profile for temperature, enabling a more realistic representation of thermal gradients within the flowing lava; (iii) a viscoplastic temperature-dependent viscosity model to account for the non-Newtonian behaviour of lava; (iv) a transport equation for temperature accounting for the thermal heat exchanges with the environment and the soil. The first two modifications allow us to describe, under reasonable assumptions, the vertical structure of the flow, and for this reason, we put our model in the class of 2.5D models.To assess the performance of our modified model, comprehensive benchmark tests are conducted using both laboratory experiments and real-world lava flow data related to the 2014–2015 Pico do Fogo, Cape Verde, effusive eruption. The benchmarking analysis demonstrates that this model accurately reproduces, with short execution times, essential flow features such as flow front advancement and cooling processes.

Unravelling the gait and balance: A novel approach for detecting depression in young healthy individuals

Depression is a prevalent mental health disorder that affects people of all ages and origins; therefore, early detection is essential for timely intervention and support. This investigation proposes a novel method for detecting melancholy in young, healthy individuals by analysing their gait and balance patterns. In order to accomplish this, a comprehensive system is designed that incorporates cutting-edge technologies such as a Barometric Pressure Sensor, Beck Depression Inventory (BDI), and t-Distributed Stochastic Neighbour Embedding (t-SNE) algorithm. The system intends to capitalize on the subtle motor and physiological changes associated with melancholy, which may manifest in a person’s gait and balance. The Barometric Pressure Sensor is used to estimate variations in altitude and vertical velocity, thereby adding context to the evaluation. The mood states of participants are evaluated using the BDI, a well-established psychological assessment instrument that provides insight into their emotional health. Integrated and pre-processed data from the Barometric Pressure Sensor, BDI responses, and gait and balance measurements. The t-SNE algorithm is then used to map the high-dimensional data into a lower-dimensional space while maintaining the local structure and identifying underlying patterns within the dataset. The t-SNE algorithm improves visualization and pattern recognition by reducing the dimensionality of the data, allowing for a more nuanced analysis of depression-related markers. As the proposed system combines objective physiological measurements

Divergent response of eastern China precipitation to the Pacific decadal oscillation during the last Interglacial

Understanding the role of the Pacific Decadal Oscillation (PDO) during the Last Interglacial (LIG, ∼127 ka) may advance our knowledge on decadal climate variability in a warmer world. In this study, we investigate the PDO–precipitation relationship over eastern China during the LIG based on the NorESM2-LM, which shows the best performance in capturing the observed PDO pattern and the PDO–precipitation relationship among 12 models from the Paleoclimate Modelling Intercomparison Project Phase 4. Composite analysis shows that summer precipitation during the LIG is generally increased over eastern China in the positive PDO phases relative to the negative phases, which is different from the “drier-wetter-drier” triple pattern in the present day. The discrepant precipitation patterns between the LIG and preindustrial are caused by different responses of composite atmospheric circulations. Moreover, moisture budget analysis indicates that variations of vertical velocity over eastern China largely explain the PDO-linked precipitation patterns during both LIG and preindustrial, although the main causes for vertical motion changes are different across regions and periods based on the quasi-geostrophic ω equation. Additionally, these discrepancies in composite atmospheric circulations are largely linked to differences in PDO patterns and mean climate states between the LIG and preindustrial. Our results suggest a varying relationship between the PDO and precipitation over eastern China in a warmer-than-present world induced by Earth's orbit, which have important implications for PDO reconstructions during the LIG via the PDO-precipitation relationship reported here and shed light on decadal variability of precipitation as well as the associated decadal predictions in a future warmer world.

Comparing Loon Superpressure Balloon Observations of Gravity Waves in the Tropics With Global Storm‐Resolving Models

AbstractSuperpressure balloons, which drift approximately on isopycnal surfaces, get displaced by gravity waves and are thus capable of detecting gravity wave signatures. The project Loon provides superpressure balloon data in the upper troposphere and lower stratosphere from 2011 to 2021. We compare Loon data from the 6 years of best data coverage with output of global storm‐resolving models from the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains winter initiative in the tropics. We study the variance of the vertical velocity and, for the models, the gravity wave momentum flux as function of distance to closest convection. The models show large differences in the variance of the vertical wind velocity, which is crucial for calculating vertical gravity wave momentum fluxes. We find large differences between the models with respect to simulated convection, lateral propagation, and the wave background away from sources. We then sample balloons as models by optimizing the match of vertical wind distributions using a temporal low pass filter. The average distance the balloons travel during the optimum low pass filtering time turns out to correspond approximately to four times the model grid spacing. The functional dependence of the vertical velocity variance on distance to closest convection is similar between the models and the observations sampled as models. The robustness of this result across all models suggests that storm‐resolving models provide a useful resource for machine learning some characteristics of convectively generated gravity waves.

Accelerated particle beams in a 3D simulation of the quiet Sun

Context. Nanoflare heating through small-scale magnetic reconnection events is one of the prime candidates to explain heating of the solar corona. However, direct signatures of nanoflares are difficult to determine, and unambiguous observational evidence is still lacking. Numerical models that include accelerated electrons and can reproduce flaring conditions are essential in understanding how low-energetic events act as a heating mechanism of the corona, and how such events are able to produce signatures in the spectral lines that can be detected through observations. Aims. We investigate the effects of accelerated electrons in synthetic spectra from a 3D radiative magnetohydrodynamics simulation to better understand small-scale heating events and their impact on the solar atmosphere. Methods. We synthesised the chromospheric Ca II and Mg II lines and the transition region Si IV resonance lines from a quiet Sun numerical simulation that includes accelerated electrons. We calculated the contribution function to the intensity to better understand how the lines are formed, and what factors are contributing to the detailed shape of the spectral profiles. Results. The synthetic spectra are highly affected by variations in temperature and vertical velocity. Beam heating exceeds conductive heating at the heights where the spectral lines form, indicating that the electrons should contribute to the heating of the lower atmosphere and hence affect the line profiles. However, we find that it is difficult to determine specific signatures from the non-thermal electrons due to the complexity of the atmospheric response to the heating in combination with the relatively low energy output (∼1021 erg s−1). Even so, our results contribute to understanding small-scale heating events in the solar atmosphere, and give further guidance to future observations.