Author(s): Yihua Huang, Zhenhao Liang, Jiaolong Zeng, and Jianmin Yuan
For low-density plasmas, the ionization balance can be properly described by the normal Saha equation in the chemical picture. For dense plasmas, however, nonideal effects due to the interactions between the electrons and ions and among the electrons themselves affect the ionization potential depres…
[Phys. Rev. E 109, 045210] Published Wed Apr 24, 2024
Nature-based climate solutions can help mitigate climate change, especially in forested regions capable of storing and sequestering vast amounts of carbon. New research published in Global Change Biology indicates that a single hurricane in New England, one of the most heavily forested regions in the United States, can down 4.6–9.4% of the total above-ground forest carbon, an amount much greater than the carbon sequestered annually by New England's forests.
Abstract
Exposure to ionizing radiation from galactic cosmic rays (GCR) and solar energetic particles (SEP) at aircraft flight altitudes can have an adverse effect on human health. Although airline crews are classified as radiation workers by the International Commission on Radiological Protection (ICRP), in most countries, their level of exposure is unquantified and undocumented throughout the duration of their career. As such, there is a need to assess pilot ionizing radiation exposure. The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS), a real-time, global, physics-based model is used to assess such exposure. The Automated Radiation Measurements for Aerospace Safety (ARMAS) measurement data set consists of high latitude, high altitude, and long-duration aircraft flights between 2013 and 2023. Here, we characterize radiation exposure at aviation flight altitudes using the NAIRAS model and compare with 45 flight trajectories from the recent ARMAS flight measurement inventory.
Abstract
Smartphone global navigation satellite system measurements in suburban environments suffer from severe multipath and noise, posing a challenge in dealing with the potential outliers. Using the range errors derived from smartphones, the characteristics of range errors can be further utilized to optimize the stochastic model and improve outlier diagnosis in user environments. Compared to existing algorithms, a new adaptive phase/code precision ratio scheme is proposed. Furthermore, a scale factor is utilized to deal with the over-optimization issue in the fitted weighting scheme functions, and adaptive a posteriori residual rejection method which considers the number of rejected measurements is introduced. The positioning improvements brought by the proposed algorithm are validated step by step. The proposed adaptive phase/code precision ratio can reduce the 68th and 95th horizontal positioning errors by 4 cm and 3 cm, respectively, compared to a ratio of 100. The percentage of horizontal positioning errors within 1 m can be improved by 7% (from 50 to 58%). Compared to the conventional carrier-to-noise (C/N0)-based weighting scheme, the proposed weighting scheme can reduce the 68th and 95th percentile horizontal positioning errors by 14 cm and 15 cm, representing improvements of 11% and 8%, respectively. Applying the new residual rejection method, the percentage of positioning errors within 1 m improves from 42 to 54% compared to C/N0-based weighting scheme. The results demonstrate great potential for achieving overall sub-meter level horizontal positioning performance with smartphones in suburban environments.
SummaryEstimating coastal tsunami impact for early-warning or long-term hazard analysis requires the calculation of inundation metrics such as flow-depth or momentum flux. Both applications require the simulation of large numbers of scenarios to capture both the aleatory variability and the epistemic tsunami uncertainty. A computationally demanding step in simulating inundation is solving the nonlinear shallow water (NLSW) equations on meshes with sufficiently high resolution to represent the local elevation accurately enough to capture the physics governing the flow. This computational expense is particularly challenging in the context of Tsunami Early Warning where strict time constraints apply. A Machine Learning (ML) model that predicts inundation maps from offshore simulation results with acceptable accuracy, trained on an acceptably small training set of full simulations, could replace the computationally expensive NLSW part of the simulations for vast numbers of scenarios and predict inundation rapidly and with reduced computational demands. We consider the application of an encoder-decoder based neural network to predict high-resolution inundation maps based only on more cheaply calculated simulated time-series at a limited number of offshore locations. The network needs to be trained using input offshore time-series and the corresponding inundation maps from previously calculated full simulations. We develop and evaluate the ML model on a comprehensive set of inundation simulations for the coast of eastern Sicily for tens of thousands of subduction earthquake sources in the Mediterranean Sea. We find good performance for this case study even using relatively small training sets (order of hundreds) provided that appropriate choices are made in the specification of model parameters, the specification of the loss function, and the selection of training events. The uncertainty in the prediction for any given location decreases with the number of training events that inundate that location, with a good range of flow depths needed for accurate predictions. This means that care is needed to ensure that rarer high-inundation scenarios are well-represented in the training sets. The importance of applying regularization techniques increases as the size of the training sets decreases. The computational gain of the proposed methodology depends on the number of complete simulations needed to train the neural network, ranging between 164 and 4196 scenarios in this study. The cost of training the network is small in comparison with the cost of the numerical simulations and, for an ensemble of around 28000 scenarios, this represents a 6 to 170-fold reduction in computing costs.
Abstract
As an emerging seismic acquisition technology, distributed acoustic sensing (DAS) has drawn significant attention in earth science for long-term and cost-effective monitoring of underground activities. Field seismic experiments with optical fibers in a vertical seismic profile (VSP) configuration were conducted at the Newell County Facility of Carbon Management Canada in Alberta, Canada, for
\({\text{CO}}_2\)
injection and storage monitoring. Seismic full-waveform inversion (FWI) represents one promising approach for high-resolution imaging of subsurface model properties. In this study, anisotropic FWI with variable density is applied to the DAS-recorded walk-away VSP data for characterizing the subsurface velocity, anisotropy, and density structures, serving as baseline models for future time-lapse studies at the pilot site. Synthetic inversion experiments suggest that, without accounting for anisotropy, the inverted density structures by isotropic FWI are damaged by strong trade-off artifacts. Anisotropic FWI can provide more accurate P-wave velocity, density, and valuable anisotropy models. Field data applications are then performed to validate the effectiveness and superiority of the proposed methods. Compared to the inversion outputs of isotropic FWI, the inverted P-wave velocity by anisotropic FWI matches trend variation of the well log more closely. In the inverted density model, the
\({\text{CO}}_2\)
injection formation can be clearly resolved. The inverted anisotropy parameters provide informative references to interpret the structures and lithology around the target
\({\text{CO}}_2\)
injection zone.
Abstract
GPS satellites of Block IIR-M and the subsequent Blocks have the capability to redistribute the transmit power of the individual signal components, which is called flex power. This technology is used to prevent enemy jamming by increasing the power of the designed signal. It is of great importance to detect flex power since it has great impacts on differential code biases, phase shifts, and multiple access interference. Based on geodetic stations, stepwise enhancement in their carrier-to-noise density ratios (C/N0) can reflect the power changes caused by flex power. Thus, we propose a real-time detection method for GPS flex power based on C/N0 patterns. The patterns for 100 International GNSS Service stations uniformly distributed around the world are built according to their azimuths and elevations. In order to evaluate the performance of the proposed method, daily data with 30-s sampling in 2020 and real-time data with 1-s sampling in 2023 are adopted to detect flex power with the new method. Results of experiment show that the average false positive rate for real-time detection is around 10–6, and the true positive rate is 0.999479. The results confirm the effectiveness of our method for real-time flex power detection. Meanwhile, a new flex power mode is discovered in real-time detection experiments, which has the largest coverage area between longitudes 125°W and 180°E.
Abstract
Time-relative positioning (TRP), a global navigation satellite system (GNSS) dead reckoning method with low-cost and highly autonomous characteristics, accumulates the position increments calculated by time-differenced carrier phase (TDCP) between adjacent epochs to extrapolate position. It suffers from error accumulation over time, so it is necessary to judge the availability of positioning services based on predicted accuracy. We propose a new model to predict the accuracy (the root-mean-square error, RMSE) of TRP in real time by determining systematical errors and random errors. The proposed model consists of the following two steps: first, extracting the systematic errors and correlation of position increment errors before position extrapolation; second, predicting RMSE of the positioning results based on the error propagation law during position extrapolation. The experimental results show that after considering the correlation, the predicted RMSE sequences can envelop the actual positioning error more closely. In the case of having static observation before position extrapolation, the predicted RMSEs of extrapolation position in both horizontal and vertical directions decrease by approximately 53.8% compared to the results without considering correlation; in the case where real-time kinematic (RTK) dynamic results are obtained before extrapolation, the predicted RMSE of extrapolation position can decrease by 36.7% in horizontal direction and decrease by 27.9% in vertical direction. The proposed model will be able to provide an important accuracy reference to judge the availability of positioning services when the TRP method is used to extrapolate position under the condition of the augmentation information of RTK interruption.
Abstract
Future space missions dedicated to measuring CO2 on a global scale can make advantageous use of the O2 band at 1.27 μm to retrieve the air column. The 1.27 μm band is close to the CO2 absorption bands at 1.6 and 2.0 μm, which allows a better transfer of the aerosol properties than with the usual O2 band at 0.76 μm. However, the 1.27 μm band is polluted by the spontaneous dayglow of the excited state O2 (1∆), which must be removed from the observed signal. We investigate here our quantitative understanding of the O2(1∆) dayglow with a chemistry-transport model. We show that the previously reported −13% deficit in O2(1∆) dayglow calculated with the same model is essentially due a −20% to −30% ozone deficit between 45 and 60 km. We find that this ozone deficit is due to excessively high temperatures (+15 K) of the meteorological analyses used to drive the model in the mesosphere. The use of lower analyzed temperatures (ERA5), in better agreement with the observations, slows down the hydrogen-catalyzed and Chapman ozone loss cycles. This effect leads to an almost total elimination of the ozone and O2(1∆) deficits in the lower mesosphere. Once integrated vertically to simulate a nadir measurement, the deficit in modeled O2(1∆) brightness is reduced to −4.2 ± 2.8%. This illustrates the need for accurate mesospheric temperatures for a priori estimations of the O2(1∆) brightness in algorithms using the 1.27 μm band.
Abstract
The Southern Annular Mode (SAM) is the most dominant natural mode of variability in the mid-latitudes of the Southern Hemisphere (SH). However, both the sign and magnitude of the feedbacks from the diabatic processes, especially those associated with clouds, onto the SAM remain elusive. By applying the cloud locking technique to the Energy Exascale Earth System Model (E3SM) atmosphere model, this study isolates the positive feedback from the cloud radiative effect (CRE) to the SAM. Feedback analysis based on a wave activity-zonal momentum interaction framework corroborates this weak but positive feedback. While the magnitude of the CRE feedback appears to be secondary compared to the feedbacks from the dry and other diabatic processes, the indirect CRE effects through the interaction with other dynamical and thermodynamical processes appear to play as important a role as the direct CRE in the life cycle of the SAM. The cross-EOF analysis further reveals the obstructive effect of the interactive CRE on the propagation mode of the SH zonal wind directly through the CRE wave source and/or indirectly through modulating other diabatic processes. As a result, the propagation mode becomes more persistent and the SAM it represents becomes more predictable when the interactive CRE is disabled by cloud locking. Future efforts on inter-model comparisons of CRE-denial experiments are important to build consensus on the dynamical feedback of CRE.
Warming temperatures are causing a steady rise in copper, zinc, and sulfate in the waters of Colorado mountain streams affected by acid rock drainage. Concentrations of these metals have roughly doubled in these alpine streams over the past 30 years, a new study finds, presenting a concern for ecosystems, downstream water quality, and mining remediation.
In a recent publication in Science Bulletin, a multidisciplinary team of authors from Tongji University, the Second Institute of Oceanography (Ministry of Natural Resources), the Institute of Earth Environment (Chinese Academy of Sciences), and Utrecht University reports for the first time that massive carbon inputs from volcanism and seafloor spreading have impacted the orbital phase relationships between carbon cycle and climate change.
A research team led by Prof. Xu Yongsheng from the Institute of Oceanology of the Chinese Academy of Sciences has obtained the two-dimensional sea surface height anomaly (SSHA) of about 100 km along the track and the first broadband SSHA wavenumber spectrum using Airborne Interferometric Radar Altimeter (AIRA) observations.
WSL Institute for Snow and Avalanche Research (SLF) researchers expect an elevated wildfire danger in the Alpine Foreland from 2040 onwards due to changing meteorological conditions. The danger currently remains very low in that region, but there is likely to be a shift in this regard as a result of climate change.
CloudSat, a NASA mission that peered into hurricanes, tallied global snowfall rates, and achieved other weather and climate firsts, has ended its operations. Originally proposed as a 22-month mission, the spacecraft was recently decommissioned after almost 18 years observing the vertical structure and ice/water content of clouds.
Abstract
The proton radiation belt contains high fluxes of adiabatically trapped protons varying in energy from ∼one to hundreds of megaelectron volts (MeV). At large radial distances, magnetospheric field lines become stretched on the nightside of Earth and exhibit a small radius of curvature R
C
near the equator. This leads protons to undergo field line curvature (FLC) scattering, whereby changes to the first adiabatic invariant accumulate as field strength becomes nonuniform across a gyroorbit. The outer boundary of the proton belt at a given energy corresponds to the range of magnetic L shell over which this transition to nonadiabatic motion takes place, and is sensitive to the occurrence of geomagnetic storms. In this work, we first find expressions for nightside equatorial R
C
and field strength B
e
as functions of Dst and L* to fit the TS04 field model. We then apply the Tu et al. (2014, https://doi.org/10.1002/2014ja019864) condition for nonadiabatic onset to solve the outer boundary L*, and refine our expression for R
C
to achieve agreement with Van Allen Probes observations of 1–50 MeV proton flux over the 2014–2018 era. Finally, we implement this nonadiabatic onset condition into the British Antarctic Survey proton belt model (BAS-PRO) to solve the temporal evolution of proton fluxes at L ≤ 4. Compared with observations, BAS-PRO reproduces storm losses due to FLC scattering, but there is a discrepancy in mid-2017 that suggests a ∼5 MeV proton source not accounted for. Our work sheds light on outer zone proton belt variability at 1–10 MeV and demonstrates a useful tool for real-time forecasting.
Modeling of indoor 222Rn in data-scarce regions: an interactive dashboard approach for Bogotá, Colombia
Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet
Nat. Hazards Earth Syst. Sci., 24, 1319–1339, https://doi.org/10.5194/nhess-24-1319-2024, 2024
In this study we created a cost-effective alternative to bridge the baseline information gap on indoor radon (a highly carcinogenic gas) in regions where measurements are scarce. We model indoor radon concentrations to understand its spatial distribution and the potential influential factors. We evaluated the performance of this alternative using a small number of measurements taken in Bogotá, Colombia. Our results show that this alternative could help in the making of future studies and policy.
Assessment of wind–damage relations for Norway using 36 years of daily insurance data
Ashbin Jaison, Asgeir Sorteberg, Clio Michel, and Øyvind Breivik
Nat. Hazards Earth Syst. Sci., 24, 1341–1355, https://doi.org/10.5194/nhess-24-1341-2024, 2024
The present study uses daily insurance losses and wind speeds to fit storm damage functions at the municipality level of Norway. The results show that the damage functions accurately estimate losses associated with extreme damaging events and can reconstruct their spatial patterns. However, there is no single damage function that performs better than another. A newly devised damage–no-damage classifier shows some skill in predicting extreme damaging events.
Transformation of internal solitary waves at the edge of ice cover
Kateryna Terletska, Vladimir Maderich, and Elena Tobisch
Nonlin. Processes Geophys., 31, 207–217, https://doi.org/10.5194/npg-31-207-2024, 2024
The transformation of internal waves at the edge of ice cover can enhance the turbulent mixing and melting of ice in the Arctic Ocean and Antarctica. We studied numerically the transformation of internal solitary waves of depression under smooth ice surfaces compared with the processes beneath the ridged underside of the ice. For large keels, more than 40% of wave energy is lost on the first keel, while for relatively small keels energy losses on the first keel are less than 6%.
Evolution of small-scale turbulence at large Richardson numbers
Lev Ostrovsky, Irina Soustova, Yuliya Troitskaya, and Daria Gladskikh
Nonlin. Processes Geophys., 31, 219–227, https://doi.org/10.5194/npg-31-219-2024, 2024
The nonstationary kinetic model of turbulence is used to describe the evolution and structure of the upper turbulent layer with the parameters taken from in situ observations. As an example, we use a set of data for three cruises made in different areas of the world ocean. With the given profiles of current shear and buoyancy frequency, the theory yields results that satisfactorily agree with the measurements of the turbulent dissipation rate.
