A document by Nina Nesterova. Click on the document to view its contents.

This paper introduces a modernized application of the falling spheres technique for measurement of neutral winds and densities in the mesosphere and lower thermosphere (MLT) region regardless of time of day or tropospheric conditions, using an Observing System Simulation Experiment (OSSE) of falling spheres equipped with commercial-off-the-shelf (COTS) Global Navigation Satellite Systems (GNSS) receivers. The modernization of this technique is crucial since current techniques to measure the neutral winds in the MLT are often tied to the location of a certain instrument or heavily dependent on clear nighttime skies. We show how state-of-the-art COTS inertial measurement units (IMUs) and GNSS receivers enable precise retrieval of neutral wind and density profiles under various atmospheric conditions represented both by wind profiles measured during the Super Soaker and Auroral Jets sounding rocket missions and by wind profiles simulated via the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X). Even under highly conservative conditions (e.g., relatively extreme position uncertainty of $\sigma =\sim$100 m, a low sampling rate of 100~Hz, and strong vertical winds of 25 m/s) the estimated neutral densities exhibit errors of less than 1\%, while estimated neutral wind errors typically do not exceed 2 m/s. The latter errors are largest where the shears maximize in the lower thermosphere. The significance of this work lies in its potential to enhance our understanding of the dynamics within the MLT region, including in situ processes and the interaction with the lower atmosphere.

A document by Galen Egan. Click on the document to view its contents.

A document by Kedar Dabhadkar. Click on the document to view its contents.

Previous tornado climatology studies often rely on tornado reports, which can suffer from underreporting bias due to heavy reliance on human reporting. This study aims to develop a new tornado climatology based on storm object data built from the Multi-Radar/Multi-Sensor reanalysis and Rapid Refresh modelsimulated near storm environment (NSE) variables. The dataset includes millions of storm clusters from 2005 to 2011, each characterized by over 1,000 radar and NSE variables and derivatives, making it ideal for developing machine learning models to classify tornadic storms. By using storm cluster data collocated with tornado reports, ML models are built using two methods: Random Forest (RF) and TabNet, a deep learning method. Three sub-models for each method, with different tornado damage-rating predictions are developed to understand the effects of sample size and model setup on performance. Both methods produce similar results, with overall Critical Success Index scores ranging from 0.720 to 0.826. TabNet predictions emphasize radar-related predictors, whereas RF predictions rely more on environmental variables with physical relationships to rotating thunderstorms. The RF model slightly outperforms TabNet and is therefore used to assign tornado probabilities to all remaining clusters. The new tornado climatology based on this RF model aligns well with observed data in terms of the magnitude of weak and strong tornadoes occurring each year. The spatial distribution of tornado days also resembles observations, providing confidence in the model's use for future applications.

Understanding the mechanics and rheological properties of the solid Earth requires integrating observations of earthquake cycle deformation with advanced numerical models of the underlying processes. In this article, we introduce a new numerical modeling tool designed for two-dimensional subduction zone geometries that solves the equations for mechanical equilibrium in the lithosphere-asthenosphere system to predict displacements, strains, and stresses throughout the medium. Using a Boundary Element Method (BEM) framework, we reduce the governing partial differential equations to a set of coupled ordinary differential equations, simulating periodic earthquake cycles in a viscoelastic medium with spatially variable power-law viscous rheologies and rate-dependent fault friction. Our approach overcomes key limitations of existing BEM models by ensuring (1) mechanical consistency across timescales, from individual earthquake cycles to geological periods, and (2) precise stress transfer calculations in a viscoelastic medium. We also demonstrate that for spatially heterogeneous linear viscoelastic materials, the coupled ordinary differential equations can be simplified to an eigenvalue problem, significantly enhancing computational efficiency. These advancements offer a powerful tool for predicting spatiotemporal patterns of surface displacement given complex mantle structures and lay the foundation for high-dimensional inverse problems to infer constitutive properties of the lithosphere-asthenosphere system.

This study applies a benchmarking framework to assess a 39-member ensemble of regional climate models which have dynamically downscaled CMIP6 models over the CORDEX Australasian region. Four modelling centres contributed regional climate models to this ensemble using three regional climate models (CCAM, WRF, and BARPA-R), and a total of five model configurations. Assessment is conducted over the Australian continent using a separation into four major climate zones over a 30 year historical climatological period (1985-2014). Rainfall and near-surface temperatures are compared against six benchmarks measuring mean state patterns, spatial and temporal variance, seasonal cycles, long-term trends and selected extreme indices. Benchmark thresholds are derived either from previous studies or comparison with the driving model ensemble. Major model biases vary between ensemble members and include dry biases in northern and southern Australia, winter wet biases and a persistent low bias in the winter diurnal temperature range across all the modelling centres. Daily variability at large length-scales is comparable in the driving global climate model and downscaled regional climate model length-scales, and long-term trends are largely determined by the driving global climate model. Overall, the ensemble was deemed to be fit for purpose for impact studies. Strengths and weaknesses of the systematic benchmarking framework used here are discussed.

Using a substorm onset list from the Imager for Magnetopause to Aurora Global Exploration (IMAGE) and Polar satellite images, we have constructed a new dataset of 63 substorm onsets observed in both hemispheres and their locations. We find that incorporating the history of the interplanetary magnetic field (IMF) improves the predictive power of IMF By in explaining conjugate displacement in Magnetic Local Time (MLT). Our dataset, approximately five times larger than in previous studies, enhances statistical power and focuses on the substorm onset feature. This allows for better correlation of IMF By with MLT conjugate displacement (ΔMLT), since it has been shown that IMF-induced By tends to diminish as substorms progress. In line with previous work, we find a linear relationship between IMF By and ΔMLT, though with a shallower gradient. Additionally, we analyse predictors of conjugate displacement in Magnetic Latitude (ΔMLat), showing that dipole tilt (ψ) is the strongest predictor. However, we find that this relationship is not strictly linear, and that a larger dataset and a better understanding of the physical mechanisms are needed to more accurately capture the exact functional relationship between ψ and ΔMLat.

A document by Rosa Isabella Cuppari. Click on the document to view its contents.

A series of processes involving sediment delivery from channels, its dispersal onto the floodplain, and storage at their channel margins, often generates natural levees. When levees breach, they release water and sediment onto the floodplain, leading to crevasse splays or avulsions. Despite their importance in constructing floodplains and influencing channel mobility, levee growth is poorly understood. Presently, no model fully explains dynamic channel-levee evolution. A common assumption is that levee and channel bed aggradation rates are coupled. If they coevolve, levees should progressively accumulate along any aggrading channel belt, yet observations indicate otherwise. Using a one-dimensional numerical model, we investigate levee growth decoupled from channel bed aggradation across two flood scenarios wherein the flooded level: 1) exceeds the levee crest height (i.e., front loading); 2) is lower than the levee crest causing partial inundation of distal levee deposits (i.e., back loading). Initially, rapid levee aggradation confines the channel and increases bankfull depth, which mitigates flooding. As confinement slows levee growth, channel bed aggrades until bankfull depth is sufficiently reduced to trigger overflows. This releasing process increases flood likelihood and enhances overbank accumulation, promoting front loading and re-confining the channel. Our findings suggest aggradational channels may experience confined-release phases, characterized by episodic levee growth and fluctuations in bankfull depth. Rapid in-channel aggradation increases flood frequency and variability with more confined-release cycles. These results imply that river avulsions and associated floods might preferentially occur when the channel bed aggrades faster than adjacent levees, whereby the channel becomes shallower and destabilized.

A document by Amber Holdsworth. Click on the document to view its contents.

Soil moisture is an important factor that affects terrestrial vegetation ecosystems and biological growth and development, and water deficit is one of the major environmental factors threatening vegetation restoration in the Loess Plateau. To determine the change in the soil water deficit characteristics from farmland to forestland on the Loess Plateau, in this study, we measured the soil water storage and deficit in abandoned grassland, shrubland, pioneer forestland and climax forestland along with vegetation succession. The results showed that the soil water content and the soil water storage with natural vegetation recovery from the abandoned grassland to shrubland and forestland showed a gradual declining trend, while on the contrary, the soil water deficit was increasing during succession, it was more severe in the deep soil than in the shallow soil layers, and the soil water deficit in July and September of the rainy season as well as that the vigorous growing period of plants was more serious than that in May and November, which are in the non-rainy season of the Chinese Loess Plateau. The vegetation types, soil texture and soil depth were the key factors affecting the soil water deficiency status in the process of vegetation succession. The results could have great potential in the sustainable development of forestry and provide a theoretical basis for effective water management and reasonable vegetation restoration in arid and semiarid loess regions.

The increasing incidence and severity of biomass burning (BB) events pose a multidimensional threat impacting economic resilience, national security, and public health. Consequently, growing attention has been devoted to the radiative and chemical effects of BB gas and aerosol emission into the atmosphere, as well as the accompanying effects on human health. The emphasis of the work reported here concerns the efficacy of airborne spectral imaging in the longwave-infrared (LWIR) regime for visualizing and tracking trace gas content of the outflow from BB events, explicitly addressing the need for spatially resolved measurements.

We present a new parametric autocovariance kernel function for characterizing properties of the mesoscale eddy field and the non-phase-locked internal tide from ocean time series records. We demonstrate that the model captures the important spectral properties, namely the spectral roll-off of the mesoscale continuum and the broad spectral “cusps” centered around the tidal forcing frequencies. The spectral cusp model has three main parameters that characterize the non-phase-locked internal tide: the amplitude, a decorrelation timescale and a shape parameter that captures the rate at which the cusp rolls away. Estimation of the third shape parameter is novel. We argue that an integral timescale is the most suitable characteristic timescale and show how it relates to the parametric decorrelation timescale. A key innovation of this work is that we estimate the parameters in the frequency domain using the debiased Whittle likelihood, thus avoiding the computational demands of estimating the autocovariance in the time domain. We apply our spectral parameter estimation technique to output from idealized and realistic numerical experiments of internal tides propagating through a mesoscale eddy field. We robustly demonstrate that both the non-phase-locked amplitude and integral timescale are influenced by the amplitude of the mesoscale flow field. Furthermore, we reveal that the integral timescale is set by global properties of the eddy field, whereas the shape of the spectral cusp is set by its local properties. The semi-diurnal integral timescale, calculated from a 12-month long, realistically forced ocean basin experiment, was 5–7 d and relatively constant in space.

Here, the use of an hybrid methodology, VarDyn, combining minimal physically-based constraints with a variational scheme, is demonstrated to improve mapping capabilities of sea surface height (SSH) and temperature (SST). Synthesizing multi-modal satellite observations, VarDyn improves the accuracy of SSH and SST maps compared to operational products, both in terms of RMSE and effective spatial resolution. Expected, most improvements occur in high energetic ocean regions. Still, the accuracy of SSH maps also slightly improves in low energetic regions, which is a clear improvement compared to other methods. VarDyn SSH fields and associated geostrophic velocities further reveal strong agreements with newly available high-resolution instantaneous SWOT estimates. Remarkably, the assimilation of SST especially benefits SSH reconstruction when only 2 altimeters are available. The VarDyn method thus opens robust means to refine climate SSH records, jointly assimilating SSH from 2 altimeters and SST from microwave sensors.

Swells can travel thousands of kilometers. The source of distant-source swells propagated from the North Pacific Ocean into the China Sea area has not yet been clarified. In this study, WAVEWATCH III was used to calculate the wave fields in two domains of the Northwest Pacific Ocean (WNP) and the North Pacific Ocean (NP), respectively. The swell tracking algorithm was improved to determine the source of distant-source swells. Comparative analysis of bulk wave parameters across two computational domains clearly reveals the propagation of distant-source swells into the China Sea during the autumn and winter seasons. Wave spectra at selected points contain information about these far-field swells, and the algorithm identifies that the far-field swells mainly originate from two source locations in the middle and low latitudes of NP. Frequent changes in the wind direction of the storm system at the swell source location are consistent with the shorter duration of the far-field swells. This work provides a basis for future research on coastal swell forecasting and swell warning.

Precise knowledge of geocenter motion, i.e., the relative motion between the Earth's center of mass (CM) and the center of figure of the Earth's surface (CF), is crucial to high-stakes geodetic applications such as sea level rise monitoring with satellite altimetry or the establishment of regional and global mass budgets with satellite gravimetry. The computation of the latest release of the International Terrestrial Reference Frame, ITRF2020, involved the estimation of a field of seasonal motions for a global network of geodetic stations, expressed with respect to CM, as sensed by Satellite Laser Ranging, from which the translational part represents seasonal geocenter motion. This paper presents two different methods to isolate seasonal geocenter motion from the field of ITRF2020 seasonal station motions, among which a new method based on a direct weighted average of seasonal station motions, with station-specific weights chosen so as to provide a better approximation of CF than the standard network shift approach. The ITRF2020 annual geocenter motion model thus obtained is then compared with other recent geodetic and geophysical estimates. Although different subgroups of estimates with relatively good internal consistency may be identified, the overall scatter of recent geodetic estimates remains at the level of several mm, i.e., close to the amplitude of annual geocenter motion itself. Efforts toward reconciling seasonal geocenter motion estimates therefore still appear necessary. Meanwhile, it would seem safe to assume that seasonal geocenter motion models, in particular those currently used in satellite altimetry and satellite gravimetry, are still uncertain.

Oxygen Deficient Zones (ODZs) are the largest pelagic sink of N containing nutrients in the ocean. The offshore Eastern Tropical North Pacific ODZ has been shown to be organic matter limited. We propose zooplankton/forage fish as a key source of organic matter for N2 production that has previously been ignored. We examined datasets from four cruises (April 2012, Jan 2017, April 2018, Oct 2019) at a station in the central ETNP. Backscattering data was used to determine zooplankton vertical migration depths (250-450 m, maximum at 270-280 m). Metazoan DNA concentrations, as measured by quantitative PCR, had a reproducible maximum at 270-280 m, confirming that these signals indicate the presence of zooplankton/forage fish. Additionally, a large maximum in sinking pteropod shells was found at 270 m, indicating that pteropods were part of the migrating community. While crustacean zooplankton have been shown to reduce respiration and excretion of ammonium under anoxia, we found intermittently measurable ammonium concentrations at 270 m. Here we show signatures consistent with organic matter of zooplankton/forage fish origin in the C:N and \(\delta\)13C of suspended and sinking organic matter at the vertical migration depth that suggest transportation to these depths by migrating zooplankton/forage fish. Also coincident with the migration maximum was a reproducible-between-years maximum in the biological N2 gas, and a tertiary nitrite maximum, which suggest that the migrating zooplankton are linked to N loss. Thus zooplankton/forage fish appear to be one source of organic matter which can fuel biological N2 production in ODZs.