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Characterisation of particle single-scattering albedo with a modified airborne dual-wavelength CAPS monitor
Chenjie Yu, Edouard Pangui, Kevin Tu, Mathieu Cazaunau, Maxime Feingesicht, Landsheere Xavier, Thierry Bourrianne, Vincent Michoud, Christopher Cantrell, Timothy B. Onasch, Andrew Freedman, and Paola Formenti
Atmos. Meas. Tech., 17, 3419–3437, https://doi.org/10.5194/amt-17-3419-2024, 2024
To meet the requirements for measuring aerosol optical properties on airborne platforms and conducting dual-wavelength measurements, we introduced A2S2, an airborne dual-wavelength cavity-attenuated phase-shift single monitor. This study reports the results in the laboratory and an aircraft campaign over Paris and its surrounding regions. The results demonstrate A2S2's reliability in measuring aerosol optical properties at both wavelengths and its suitability for future aircraft campaigns.

Enhanced Land Subsidence Interpolation through a Hybrid Deep Convolutional Neural Network and InSAR Time Series
Zahra Azarm, Hamid Mehrabi, and Saeed Nadi
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-15,2024
Preprint under review for GMD (discussion: open, 0 comments)
The article introduces a new method using deep CNN and PSInSAR to estimate land subsidence, addressing the limitations of traditional methods. It focuses on Isfahan province, demonstrating substantial improvement over traditional techniques. The deep CNN method showed a 70 % enhancement in subsidence prediction, with the study area experiencing over 38 cm of subsidence between 2014 and 2020.

AI-NAOS: An AI-Based Nonspherical Aerosol Optical Scheme for Chemical Weather Model GRAPES_Meso5.1/CUACE
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-51,2024
Preprint under review for GMD (discussion: open, 0 comments)
An AI-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of aerosol direct radiation effect (DRE). The AI-NAOS scheme considers BC as fractal aggregates and SD as super-spheroids, encapsulated with hygroscopic aerosols. The AI-NAOS scheme was coupled online with a chemical weather model. Real-case simulations emphasize the necessity of accurately representing nonpsherical and inhomogeneous aerosols in chemical weather models.

Abstract

From the global simulation, we reproduce the solar wind-magnetosphere-ionosphere (S-M-I) interaction under the northward interplanetary magnetic field (IMF) with negative B y. Reconnection structures, the plasma sheet, and lobes are formed in magnetospheric convection, while lobe/round-merging/reciprocal/nightside cells appear in the ionosphere. Associated with the S-M interaction, northern open field is generated at the evening open-closed (O/C) boundary, due to successive cusp and interchange reconnections (in round-merging cell) or by Dungey-type reconnection (in nightside cell). Corresponding interchange and Dungey-type reconnections occur at the southern null. Dungey-type reconnection at the same time generates southern open field on the outer-most magnetopause. Open field injected into the northern polar cap/void/lobe constructs the open field part of the round-merging and nightside cells. After open-field convection in the lobe, reclosures occur by again successive cusp and interchange reconnections on the dayside separator, or separator reconnection on the nightside separator. Former closed field line proceeds toward the evening O/C boundary through the dayside closed-field convection in the round-merging cell, while latter closed field line through the nightside closed-field convection in the nightside cell. Shear that causes the large-scale sun-aligned arc is generated by the process of injecting open magnetic field into the void and the conjugate of process of connecting return flux from the plasma sheet to the nightside cell in counter hemisphere.

Abstract

Unmixing of remanent magnetization curves, either isothermal remanent magnetization (IRM) or backfield IRM, is widely used in rock magnetic and environmental magnetic studies to discriminate between magnetic coercivity components of different origins. However, the wide range of physical properties of natural magnetic particles gives rise to an ambiguous interpretation of these components. To reduce this ambiguity and provide a straightforward interpretation of coercivity components in terms of domain state, interactions, and constituent magnetic phases, we combined backfield IRM unmixing with unmixing of nonlinear Preisach maps for two typical mid-latitude northern hemisphere loess-paleosol sequences. Both backfield IRM and nonlinear Preisach maps unmixing are based on the same non-parametric algorithm, and provide similar endmembers (EMs) in the two sections studied. The first EM (EM1) has a low median coercivity (∼21 mT) and is a non-interacting single domain (SD) magnetite/maghemite of pedogenic origin. The second EM (EM2) has a moderate median coercivity (∼60 mT) and is a mixture of pseudo-single domain/multidomain, SD magnetite/maghemite and non-interacting SD hematite, all of eolian origin. The same EM1 found in both sections suggests that this component's grain size and coercivity are independent of pedogenesis intensity. The same EM2 indicates that a similar magnetic population is being transported and deposited, irrespective of the dust source area and loess granulometry. The approach outlined here provides strong evidence that non-parametric backfield IRM unmixing isolates physically realistic EMs. Unmixing nonlinear Preisach maps elucidates these EMs in terms of domain states and their constituent magnetic phases.

Abstract

Tsunamis propagate over long distances and can cause widespread damage even after crossing ocean basins. Prediction of tsunamis in distant areas based on observations near their sources is critical to mitigating damage. In recent years, the accuracy of numerical models of trans-oceanic tsunami propagation has improved significantly due to the incorporation of effects such as the solid earth response to tsunami loading and wave dispersion. However, these models are computationally expensive and have not been fully utilized for real-time prediction. Here, we derive the adjoint operator for the linear set of equations describing deep-ocean tsunami propagation and show how a pre-computed database of adjoint states can achieve rapid synthesis of tsunami waveforms at target sites from nonpoint arbitrary tsunami sources. The adjoint synthesis method allows for an exhaustive parameter search for tsunami source estimation. A method for simultaneous inversion of fault geometry and slip distribution using adjoint synthesis with Sequential Monte Carlo method was proposed and applied to the 2012 Haida Gwaii earthquake tsunami. The influence of model accuracy and the amount of observed data on the estimation of tsunami sources and waveforms was examined. It was found that with a highly accurate propagation model, using only a limited amount of observed data produced source and waveform estimates very similar to the final models obtained with much larger data sets. The final inferred fault model involved megathrust slip distributed between the Haida Gwaii trench and the Queen Charlotte fault. The proposed method can also quantify the uncertainty of the waveform forecasts.

Influence of meteoric smoke particles on the incoherent scatter measured with EISCAT VHF
Tinna L. Gunnarsdottir, Ingrid Mann, Wuhu Feng, Devin R. Huyghebaert, Ingemar Haeggstroem, Yasunobu Ogawa, Norihito Saito, Satonori Nozawa, and Takuya D. Kawahara
Ann. Geophys., 42, 213–228, https://doi.org/10.5194/angeo-42-213-2024, 2024
Several tons of meteoric particles burn up in our atmosphere each day. This deposits a great deal of material that binds with other atmospheric particles and forms so-called meteoric smoke particles. These particles are assumed to influence radar measurements. Here, we have compared radar measurements with simulations of a radar spectrum with and without dust particles and found that dust influences the radar spectrum in the altitude range of 75–85 km.

Does high-latitude ionospheric electrodynamics exhibit hemispheric mirror symmetry?
Spencer Mark Hatch, Heikki Vanhamäki, Karl Magnus Laundal, Jone Peter Reistad, Johnathan K. Burchill, Levan Lomidze, David J. Knudsen, Michael Madelaire, and Habtamu Tesfaw
Ann. Geophys., 42, 229–253, https://doi.org/10.5194/angeo-42-229-2024, 2024
In studies of the Earth's ionosphere, a hot topic is how to estimate ionospheric conductivity. This is hard to do for a variety of reasons that mostly amount to a lack of measurements. In this study we use satellite measurements to estimate electromagnetic work and ionospheric conductances in both hemispheres. We identify where our model estimates are inconsistent with laws of physics, which partially solves a previous problem with unrealistic predictions of ionospheric conductances.

Abstract

The eruption of Hunga in January 2022 injected a large amount of water into the stratosphere. Satellite measurements from Aura Microwave Limb Sounder (MLS) show that this water vapor (H2O) has now spread throughout the stratosphere and into the lower mesosphere, resulting in an increase of >1 ppmv throughout most of this region. Measurements from three ground-based Water Vapor Millimeter Wave Spectrometer (WVMS) instruments and MLS are in good agreement, and show that in 2023 there was more H2O in the lower mesosphere than at any time since the WVMS measurements began in the 1990's. At Table Mountain, California all WVMS H2O measurements at 54 km since June 2023, and all of the measurements from Mauna Loa, Hawaii, since the resumption of measurements in September 2023, show larger mixing ratios than any previous measurements. At 70 km several recent WVMS retrievals since September 2023 show the largest anomalies ever measured. The MLS measurements show that maximum H2O anomalies over the 2004–2023 record have occurred throughout almost all of the stratosphere and lower mesosphere since the eruption. As of November 2023, almost all of the ∼140 Tg of water originally injected into the stratosphere by the Hunga eruption remains in the middle atmosphere at pressures below 83 hPa (altitudes above ∼17 km). The eruption occurred during a period when stratospheric H2O was already slightly elevated above the 2004–2021 MLS average, and the November 2023 anomaly of ∼160 Tg represents ∼15% of the total mass of H2O in this region.

Abstract

This study explores the impact of coupling cumulus and planetary boundary layer (PBL) parameterizations on diurnal precipitation forecasting during the plum rainy season in Jiangsu Province, China, using a double grid-nesting approach. Results show that coherent coupling of cumulus (only in the 15 km grid outer domain [O]) and PBL parameterizations leads to improved forecasting of diurnal variations in the morning, afternoon, and the evening. Increasing the frequency of the Kain-Fritsch (KF) cumulus scheme in [O] enhances subgrid precipitation while reducing grid-scale precipitation, resulting in a more accurate representation of daytime convective activities and a reduction in over-forecasting of evening valley and early-morning precipitation. Additionally, coupling a suitable PBL scheme mitigates the overpredicted afternoon peak by facilitating turbulent mixing to penetrate higher altitudes with a thicker layer, thereby reducing instability energy accumulation. A higher KF frequency in [O] retains less low tropospheric moisture, reducing moisture convergence into the 1 km grid inner domain [I] and decreasing overpredicted daytime precipitation in [I]. Various PBL schemes produce distinct vertical distributions of turbulent moisture and heat transport, impacting convection and precipitation in [I] resolved by cloud microphysics processes. The coherent coupling of these parameterizations maintains a balanced supply of convective energy and water vapor, significantly improving diurnal precipitation forecasts in [I]. Isolating these parameterizations between nested grids may undermine this improvement.

Abstract

Machine learning-based approaches demonstrate a significant potential in radar quantitative precipitation estimation (QPE) applications. In contrast to conventional methods that depend on local raindrop size distributions, deep learning (DL) can establish an effective mapping from three-dimensional radar observations to ground rain rates. However, the lack of transparency in DL models poses challenges toward understanding the underlying physical mechanisms that drive their outcomes. This study aims to develop a DL-based QPE system and provide a physical explanation of radar precipitation estimation process. This research is designed by employing a deep neural network consisting of two modules. The first module is a quantitative precipitation estimation network that has the capability to learn precipitation patterns and spatial distribution from multidimensional polarimetric radar observations. The second module introduces a quantitative precipitation estimation shapley additive explanations method to quantify the influence of each radar observable on the model estimate across various precipitation intensities.

Abstract

Eruptive dynamics is influenced by gas escape from the ascending magma. Gas pathways form in the magma via bubble coalescence, leading to gas channeling. Magmatic crystals play a key role in gas channel formation. This work constrains experimentally decompression-induced coalescence in high-crystallinity silicic magmas without external deformation, focusing on low gas content and bimodal crystal size (microlites and phenocrysts). All percolating samples have permeabilities of 10−14 m2 at bulk porosities of 7–10 vol% and bulk crystallinities up to 75 vol%. Our results demonstrate the possibility of coalescence-related outgassing at high pressure (120–350 MPa) and without external strain, which corresponds to magma stagnating deep in a volcanic conduit. Channeling at such low gas content implies that bimodal crystallinity favors effusive over explosive volcanic behavior. It may also be the missing physical mechanism explaining gas transfer across magmatic systems despite high melt viscosity and low or absent magma extrusion.

Abstract

Composite analyses of NOAA satellite-based outgoing longwave radiation data and ERA5 reanalysis data for nearly six solar maximum periods support the existence of a response of tropical convection and precipitation to short-term (∼27-day) solar ultraviolet variations. Following solar UV peaks, the response consists of an increase in average convection and precipitation in the equatorial Indian Ocean and a decrease in the western and central tropical Pacific, with maximum amplitude at a lag of 4 to 8 days. The opposite occurs following short-term solar UV minima. The observed responses are most detectable when the Madden-Julian oscillation (MJO) is active and appear to be related to a reduced ability of the MJO to propagate across the Maritime Continent barrier following solar UV peaks relative to UV minima. A similar behavior has previously been found when the stratospheric quasi-biennial oscillation is in its westerly phase relative to its easterly phase.

Abstract

The hydrological and biogeochemical properties of the hyporheic zone in stream and riverine ecosystems have been extensively studied over the past two decades. Although it is widely acknowledged that sediment heterogeneity can influence biogeochemical reactions, little effort has been made to understand the role of heterogeneity on the spatiotemporal variability of riverbed redox conditions under changing flow dynamics at different timescales. Here we integrate a mechanistic model and field data to demonstrate that heterogeneity in permeability plays a vital role in modulating sediment redox conditions at both seasonal (annual) and event (daily-to-weekly) timescales, whereas heterogeneity in particulate organic carbon (POC) content only has a comparable influence on redox conditions at the seasonal timescale. These findings underscore the importance of accurately characterizing sediment heterogeneity, in terms of permeability and POC content, in quantifying biogeochemical dynamics in the riverbed and hyporheic zones of riverine ecosystems.

Abstract

Since volcanic activity was first discovered on Io from Voyager images in 1979, changes on Io's surface have been monitored from both spacecraft and ground-based telescopes. Here, we present the highest spatial resolution images of Io ever obtained from a ground-based telescope. These images, acquired by the SHARK-VIS instrument on the Large Binocular Telescope, show evidence of a major resurfacing event on Io's trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images show that a plume deposit from a powerful eruption at Pillan Patera has covered part of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io's surface using adaptive optics at visible wavelengths.

Abstract

La Palma, Canary Islands, had its largest historical eruption in 2021. From January 2022 to May 2023 there were >2,100 seismic events, primarily at depths ≤20 km, prompting us to update the deformation and modeling study, using interferometric synthetic aperture radar observations and a last generation interpretation tool. We detect the evolution of the remaining magmatic body in the SW portion of the island, with arrival of new magma moving into the oceanic crust out to sea, and a pressurized zone in the central-eastern area, at regions of structural weakness. The current source characteristics have some similarities to the early stage dynamics prior to the 2021 eruption. Operational and multidisciplinary studies must continue to monitor either their stabilization or growth and destabilization. The ability to identify magma ascent using only deformation data over short time periods allows us to characterize unrest patterns and provide new insights into volcanic processes.

Abstract

The evolution of coastal wetlands is a complex process which is difficult to forecast, made more complicated by the addition of changing climatic conditions. Here, long term ecological and geomorphological data are coupled to geotechnical measurements at a coastal wetland in North Inlet estuary, South Carolina. The coupled methodology is presented and discussed in context of understanding coastal wetland system evolution in a changing climate. Specifically, the root shear strength of Spartina alterniflora across a range of elevations was investigated using a cone penetrometer test. Elevation, shear strength, and biomass are shown to be critically interconnected. Root strength was shown to decrease with increased inundation time and decreased elevation (i.e., mudflats). Conversely, the data set illustrates the importance of maintaining key elevation ranges in relation to sea-level to optimize wetland resilience.

Abstract

The climate benefit of blue carbon sequestered by mangrove forests can be partially offset by CH4 emission, but this offset is rarely assessed using multi-year high-frequency measurements. Here, four-year eddy covariance measurements were used to examine temporal patterns of CH4 flux and its blue carbon offset (i.e., reduced climate benefit) in a subtropical estuarine mangrove in China. We found both diel and seasonal CH4 fluxes were mainly driven by soil temperature and tidal activities, showing greater nighttime emission. On average, one-tenth of CO2 uptake was offset by CH4 emission using the sustained-flux global warming potential metric at a 20-year time horizon, while this offset could vary over an order of magnitude due to asynchronous fluxes of CH4 and CO2 across diel and seasonal cycles. These results highlight the significant contribution of nighttime emission to mangrove CH4 budget and the importance of asynchronous flux variations in assessing mangrove's climate benefit.

Abstract

Tornadoes, as highly destructive weather events, require accurate detection for effective decision-making. Traditional radar-based tornado detection algorithms (TDA) face challenges with limited tornado feature extraction capabilities, leading to high false alarm rates and low detection probabilities. This study introduces the Multi-Task Identification Network (MTI-Net), leveraging Doppler radar data to enhance tornado recognition. MTI-Net integrates tornado detection and estimation tasks to acquire comprehensive spatial and locational information. As part of MTI-Net, we introduce a novel backbone network of Multi-Head Convolutional Block (MHCB), which incorporates Spatial and Channel Attention Units (SAU and CAU). SAU optimizes local tornado feature extraction, while CAU reduces false alarms by enhancing dependencies among input variables. Experiments demonstrate the superiority of MTI-Net over TDA, with a decrease in false alarm rates from 0.94 to 0.46 and an increase in hit rates from 0.23 to 0.81, highlighting the effectiveness of MTI-Net in handling small-scale tornado events.

Abstract

The role of internal variability in generating an apparent link between autumn Barents-Kara sea (BKS) ice and the winter North Atlantic Oscillation (NAO) has been intensely debated. In particular, the robustness and causality of the link has been questioned by showing that BKS-NAO correlations exhibit nonstationarity in both reanalysis and climate model simulations. We show that the lack of ice observations means nonstationarity cannot be confidently assessed using reanalysis prior to 1961. Model simulations are used to corroborate an argument that forced nonstationarity could result from ice edge changes due to global warming. Consequently, the observed change in BKS-NAO correlations since 1960 might not be purely a result of internal variability and may also reflect that the ice edge has moved. The change could also reflect the availability of more accurate ice observations. We discuss potential implications for analysis based on coupled climate models, which exhibit large ice edge biases.