bluuebunny/crossref_metadata_2025_split huggingface dataset:
The association between rainforest disturbance and recovery, tree community composition, and community traits in the Yangambi area in the Democratic Republic of the Congo
Authors: Depecker Jonas , Asimonyio Justin A. , Miteho Ronald , Hatangi Yves , Kambale Jean-Léon , Verleysen Lauren , Stoffelen Piet , Janssens Steven B. , Dhed’a Benoit , Vandelook Filip , Honnay Olivier 
Published: August 2022

AbstractDespite their key role in biodiversity conservation, forests in the Congo Basin are increasingly threatened by human activities, but it remains challenging to assess the impact of forest degradation under a more or less intact canopy. Likewise, forest recovery following agricultural abandonment remains poorly understood in the Congo Basin. Here, we surveyed 125 vegetation quadrats across 25 forest inventory plots in the Yangambi area. We aimed to find associations between both selective logging and forest recovery, and a range of forest community and tree community trait characteristics, as compared to reference undisturbed old-growth forest. We found that plots in undisturbed old-growth forest harboured both more tree individuals and tree species with a higher wood density as compared to plots in disturbed old-growth forest. In addition, their tree community composition was significantly different, whereas species diversity recovered since relatively recent agricultural abandonment (< 60 years), community composition and forest structure remained significantly different from the plots in undisturbed old-growth forest. Our study provides some insights into the rate of forest recovery in the Congo basin after agricultural abandonment and highlights the need of proper conservation of the remaining relatively undisturbed old-growth forests. Finally, we stress the need for more extensive vegetation surveys in the Congo Basin to further unravel the effects of anthropogenic disturbance.
Introducing New Metrics for the Atmospheric Pressure Adjustment to Thermal Structures at the Ocean Surface
Authors: Meroni Agostino N. , Desbiolles Fabien , Pasquero Claudia 
Published: August 2022

AbstractThermal structures at the sea surface are known to affect the overlying atmospheric dynamics over various spatio‐temporal scales, from hourly and sub‐kilometric to annual and O(1,000 km). The relevant mechanisms at play are generally identified by means of correlation coefficients (in space or time) or by linear regression analysis using appropriate couples of variables. For fine spatial scales, where sea surface temperature (SST) gradients get stronger, the advection might disrupt these correlations and, thus, mask the action of such mechanisms, just because of the chosen metrics. For example, at the oceanic sub‐mesoscale, around 1–10 km and hourly time scales, the standard metrics used to identify the pressure adjustment mechanism (that involves the Laplacian of sea surface temperature, SST, and the wind divergence) may suffer from this issue, even for weak wind conditions. By exploiting high‐resolution realistic numerical simulations with ad hoc SST forcing fields, we introduce some new metrics to evaluate the action of the pressure adjustment atmospheric response to the surface oceanic thermal structures. It is found that the most skillful metrics is based on the wind divergence and the SST second spatial derivative evaluated in the across direction of a locally defined background wind field.
On the Application of an Observations‐Based Machine Learning Parameterization of Surface Layer Fluxes Within an Atmospheric Large‐Eddy Simulation Model
Authors: Muñoz‐Esparza Domingo , Becker Charlie , Sauer Jeremy A. , Gagne David John , Schreck John , Kosović Branko 
Published: August 2022

AbstractRecently, machine learning techniques have been employed to develop improved models for predicting surface‐layer fluxes of momentum, heat and moisture based on field observations. Herein we explore refinement to these models, in particular artificial neural networks (NN), and investigate their applicability within an atmospheric large‐eddy simulation model as an alternative to the widely adopted standard of Monin − Obukhov (MO) similarity theory. Atmospheric boundary layer (ABL) simulations under different stability conditions are carried out for a variety of scenarios of increasing complexity, from dry steady neutral boundary layers to moist diurnal cycle. Simulations using the NN models result in predicted flux differences with respect to the corresponding MO simulations that are consistent with NN model skill in predicting the tower observations. These differences lead to notable modifications of mean and turbulence quantities throughout the ABL. While these NN models provide an alternative to improve upon MO, it is demonstrated that thorough scrutiny in design and evaluation is necessary to prevent unphysical predictions and establish a robust and generalizable parameterization. Design aspects considered include input feature engineering, applicability under inputs obtained from different heights, biased predictions due to climatological fingerprints, and sensitivity to the choice of activation function. In this context, it is shown how an atmospheric model can contribute toward efficiently investigating these relevant aspects, including expanding the training data set to generalize the NN model to a range of surface roughness values. Finally, we outline remaining challenges to be addressed toward developing a universal parameterization for surface‐layer fluxes using machine learning techniques.
Assimilation of Polarimetric Radar Observation With GSI Cloud Analysis for the Prediction of a Squall Line
Authors: Ding Zhicheng , Zhao Kun , Zhu Kefeng , Feng Yerong , Huang Hao , Yang Zhengwei 
Published: August 2022

AbstractDual‐polarization radars can provide rich three‐dimensional (3D) information on cloud precipitation structure. To utilize the existing polarimetric radar network in operational data assimilation systems, a new polarimetric radar‐based cloud analysis method is introduced. New features include the employment of fuzzy‐logic hydrometeor classification, improved estimation of liquid and ice regions, and newly‐added number concentration estimation. The new scheme is evaluated with a typical squall line case. Results show that the 3D cloud precipitation structure and short‐term precipitation forecast is consistently improved. With extra information from the polarimetric observations, the new scheme is able to produce reasonable polarimetric signatures for analysis. More supercooled water results in more latent heat release which enhances the updraft, leading to stronger convection in the subsequent forecast. This study emphasizes the importance of correct initial liquid and ice particle condition for the prediction of deep convection.
The Interconnected Magmatic Plumbing System of the Natron Rift
Authors: Reiss M. C. , De Siena L. , Muirhead J. D. 
Published: August 2022

AbstractUnderstanding the magmatic plumbing system of rift volcanoes is essential when examining the interplay between magmatic and tectonic forces. Recent seismicity, volcanic activity, magma emplacement, and volatile release make the Natron basin the ideal location to study these processes in the East African Rift System. Here, we present the first high‐resolution tomographic imaging of Oldoinyo Lengai volcano and surrounding volcanic systems using attenuation mapping. High scattering and absorption features reveal fluid‐filled fracture networks below regions of magmatic volatile release at the surface and a close spatial association between carbonatite volcanism and deeply penetrating, fluid‐filled faults. High‐absorption features appear sensitive to fluids and thermal gradients, revealing a central sill complex and connected plumbing system down to the mid‐crust, which links volcanoes and rift segments across the developing magmatic rift.
Self‐Supervised Classification of Weather Systems Based on Spatiotemporal Contrastive Learning
Authors: Wang Liwen , Li Qian , Lv Qi 
Published: August 2022

AbstractThe classification of weather systems provides a simple description of atmospheric circulations and bridges the gap between large‐scale atmospheric conditions and local‐scale environmental variables. However, the existing classification methods are challenged due to a lack of labels and inaccurate similarity measures between data samples. In this letter, we propose a self‐supervised Spatiotemporal Contrastive Learning (SCL) framework for the classification of weather systems without manual labels. In particular, we operate both spatial and temporal augmentation on multivariate meteorological data to fully explore temporal context information and spatial stability in accordance with synoptic nature. For the assessment and comparison of the classification results, we apply a statistical method based on analog forecasting using the classification results as input. The experimental results demonstrate that the proposed SCL model outperforms traditional classification methods.
Decadal Prediction of Marine Heatwaves in MPI‐ESM
Authors: Hövel Laura , Brune Sebastian , Baehr Johanna 
Published: August 2022

AbstractMarine Heatwaves (MHW) are SST extremes that can have devastating impacts on marine ecosystems and can influence circulation patterns in the ocean and the atmosphere. Here, we present a first attempt to study the decadal predictability of MHW in an ensemble of decadal hindcasts based on the Max Planck Institute Earth System Model. For the global mean we find significant skill for the multiyear MHW trends but we cannot predict the interannual to decadal variability of MHW. In the Subpolar North Atlantic, we can predict the interannual to decadal variability of MHW days and frequency up to lead year 8. We demonstrate that in the Subpolar North Atlantic, any increase in SST is accompanied by more MHW and vice versa. Thereby we gain additional information about the decadal evolution of SST that go beyond predicting the yearly mean SST.
Imaging a Decratonized Lithosphere: A Case of the Eastern North China Craton
Authors: Li Hongqiang , Huang Xingfu , Gao Rui , Carbonell Ramon , Gao Lei 
Published: August 2022

AbstractDuring decratonization, the cratonic lithosphere mantle experienced composition transformation and thinning, which have been extensively studied in the North China Craton. Yet, modification from refractory lithospheric mantle to fertile one remains enigmatic due to a shortage of seismically resolvable data on the lithospheric internal structures. New high‐resolution normal incidence seismic reflection transect documents: coexistence of two lithospheric mantles with different reflection characteristics, lithosphere‐scale domes, boudinage upper‐crust, and Cenozoic faulted basins. Reflective and transparent mantles are interpreted to represent the cratonic and the newly formed lithospheric mantles, respectively. The irregular contact boundaries between the ancient and newly formed lithospheric mantles are revealed as channel‐like structures within the mantle, which possibly provide pathways for the rise of melts and/or fluids from the deep mantle. The deep melts/fluids rising through the channel‐like structures are key elements that enable generation of the newly formed lithospheric mantle, and provide means for the modification of cratonic lithospheric mantle.
Quantifying the Size and Duration of a Microburst‐Producing Chorus Region on 5 December 2017
Authors: Elliott S. S. , Breneman A. W. , Colpitts C. , Pettit J. M. , Cattell C. A. , Halford A. J. , Shumko M. , Sample J. , Johnson A. T. , Miyoshi Y. , Kasahara Y. , Cully C. M. , Nakamura S. , Mitani T. , Hori T. , Shinohara I. , Shiokawa K. , Matsuda S. , Connors M. , Ozaki M. , Manninen J. 
Published: August 2022

AbstractMicrobursts are impulsive (<1 s) injections of electrons into the atmosphere, thought to be caused by nonlinear scattering by chorus waves. Although attempts have been made to quantify their contribution to outer belt electron loss, the uncertainty in the overall size and duration of the microburst region is typically large, so that their contribution to outer belt loss is uncertain. We combine datasets that measure chorus waves (Van Allen Probes [RBSP], Arase, ground‐based VLF stations) and microburst (>30 keV) precipitation (FIREBIRD II and AC6 CubeSats, POES) to determine the size of the microburst‐producing chorus source region beginning on 5 December 2017. We estimate that the long‐lasting (∼30 hr) microburst‐producing chorus region extends from 4 to 8 MLT and 2–5 L. We conclude that microbursts likely represent a major loss source of outer radiation belt electrons for this event.
Impact of Warmer Sea Surface Temperature on the Global Pattern of Intense Convection: Insights From a Global Storm Resolving Model
Authors: Cheng Kai‐Yuan , Harris Lucas , Bretherton Christopher , Merlis Timothy M. , Bolot Maximilien , Zhou Linjiong , Kaltenbaugh Alex , Clark Spencer , Fueglistaler Stephan 
Published: August 2022

AbstractIntense convection (updrafts exceeding 10 m s−1) plays an essential role in severe weather and Earth's energy balance. Despite its importance, how the global pattern of intense convection changes in response to warmed climates remains unclear, as simulations from traditional climate models are too coarse to simulate intense convection. Here we use a kilometer‐scale global storm resolving model (GSRM) and conduct year‐long simulations of a control run, forced by analyzed sea surface temperature (SST), and one with a 4 K increase in SST. Comparisons show that the increased SST enhances the frequency of intense convection globally with large spatial and seasonal variations. Changes in the spatial pattern of intense convection are associated with changes in planetary circulation. Increases in the intense convection frequency do not necessarily reflect increases in convective available potential energy. The GSRM results are also compared with previously published traditional climate model projections.
Combined Analysis of Hydrogen and Oxygen 102.6 nm Emission at Mars
Authors: Chaffin Michael S. , Deighan Justin , Jain Sonal , Holsclaw Greg , AlMazmi Hoor , Chirakkil Krishnaprasad , Correira John , England Scott , Evans J. Scott , Fillingim Matt , Lillis Rob , Lootah Fatma , Raghuram Susarla , Eparvier Frank , Thiemann Ed , Curry Shannon , AlMatroushi Hessa 
Published: August 2022

AbstractWater is lost from the Mars upper atmosphere to space as hydrogen and oxygen, both of which can be observed in scattered ultraviolet sunlight at 102.6 nm. We present Emirates Mars Mission Emirates Mars Ultraviolet Spectrometer (EMM/EMUS) insertion orbit observations of this airglow, resolving the independent altitude contributions of H and O for the first time. We present the first airglow modeling of the complete H and O 102.6 nm system and the first 3D azimuthally symmetric modeling of the O emission, retrieving temperatures and densities typical of northern spring. Our model reproduces the emission well above 200 km, but does not incorporate partial frequency redistribution needed to reproduce the observed O brightness at lower altitudes and on the disk. These results support future EMM/EMUS science orbit retrievals of H loss and the use of 102.6 nm observations to constrain planetary atmospheres across the solar system.
Characteristics of the Intraseasonal Oscillation in the Equatorial Mesosphere and Lower Thermosphere Region Revealed by Satellite Observation and Global Analysis by the JAGUAR Data Assimilation System
Authors: Koshin D. , Kohma M. , Sato K. 
Published: August 2022

AbstractClimatological features of the intraseasonal oscillation (ISO) in the equatorial mesosphere and lower thermosphere were analyzed using temperature data from the Aura Microwave Limb Sounder (MLS) and global analysis data from a data assimilation using satellite observations, including the MLS, over 15 years. Based on spectral analyses, fluctuations with a period of 15–90 days were extracted as the ISO component. First, an empirical orthogonal function (EOF) analysis was performed for the ISO components of the zonal mean temperature from the MLS in the region of 10°S–10°N, 68–85 km, where the ISO amplitudes are found to be maximized. The global structure of the ISO anomalies of temperature and zonal winds estimated assuming a gradient wind balance was examined by a regression analysis using the first and second principal EOFs. It is shown that the ISO phases propagate downward with a vertical wavelength of 25–30 km above a height of 60 km and that the ISO signal synchronized with the equatorial ISO is observed even in the middle and high latitude regions of both hemispheres. Second, the global analysis data were used to examine the driving mechanism of the ISO. It was confirmed that the time series of the equatorial ISO zonal mean zonal wind in the analysis agreed well with radar observations, which were not used for assimilation. Results suggest small‐scale phenomena, such as gravity waves not necessarily represented in the parameterization and the meridional advection of angular momentum, mainly contribute to drive the ISO.
Variations in Observations of Geosynchronous Magnetopause and Last Closed Drift Shell Crossings With Magnetic Local Time
Authors: Daggitt Thomas A. , Horne Richard B. , Glauert Sarah A. , Del Zanna Giulio , Freeman Mervyn P. 
Published: August 2022

AbstractWe analyze a set of events in which both electron flux dropouts caused by magnetopause shadowing and geosynchronous magnetopause crossings (GMCs) are observed. These observations are compared to event‐specific last closed drift shell (LCDS) models derived from the TS05 and TS07 external field models and magnetopause standoff distance. The LCDS models show good association with losses due to magnetopause shadowing but fail to reproduce observations of GMCs on the timescale of minutes. We show that different satellites in geostationary orbit observe different trends in electron flux during storm events on timescales of less than a day due to their separation in longitude. These differences demonstrate that both satellite L* and magnetic local time must be taken into account when modeling rapid variations in the outer radiation belt, and at least three satellites in geostationary orbit, ideally more, may be required for accurate forecasting and reconstruction of these events on timescales shorter than days.
Improving Electron Density Predictions in the Topside of the Ionosphere Using Machine Learning on In Situ Satellite Data
Authors: Dutta S. , Cohen M. B. 
Published: August 2022

AbstractModeling the Earth's ionosphere is a critical component of forecasting space weather, which in turn impacts radio wave propagation, navigation and communication. This research focuses on predicting the electron density in the topside of the ionosphere using satellite data, in particular from the Defense Meteorological Satellite Program, a collection of 19 satellites that have been polar orbiting the Earth for various lengths of times, fully covering 1982 to the present. An artificial neural network was developed and trained on two solar cycles worth of data (113 satellite‐years), along with global drivers and indices such as F10.7, interplanetary magnetic field, and Kp to generate an electron density prediction. We tested the model on six years of subsequent data (26 satellite‐years), and found a correlation coefficient of 0.87. Once trained, the model can predict topside electron density at any location specified by latitude and longitude given current/recent geomagnetic conditions. We validated the model via comparison with data from the DEMETER satellite which orbited at a similar altitude, and taking that as an independent source of true electron density values. Comparing our results to the International Reference Ionosphere, we find that our model works better at low to mid‐latitudes, and for quiet and moderately disturbed geomagnetic conditions, but not for highly disturbed conditions.
Beyond Basic Drag in Interplanetary CME Modeling: Effects of Solar Wind Pileup and High‐Speed Streams
Authors: Kay C. , Nieves‐Chinchilla T. , Hofmeister S. J. , Palmerio E. 
Published: August 2022

AbstractCoronal mass ejections (CMEs) cause severe space weather effects throughout our solar system. As a fast CME propagates through interplanetary space, it accumulates solar wind materials at its front. This pileup of materials, or CME‐driven sheath, can be important in determining the geoeffectiveness of a CME. We take an existing arrival time model that includes expansion and deformation of the CME flux rope (ANTEATR; Kay & Gopalswamy, 2018, https://doi.org/10.1029/2018JA025780; Kay & Nieves‐Chinchilla, 2021a, https://doi.org/10.1029/2020JA028911) and add a pileup procedure (PUP) as a physics‐based approach to modeling the CME‐driven sheath. ANTEATR‐PUP solves the Rankine‐Hugoniot equations for an oblique shock to determine the shock speed and sheath density, magnetic field, and temperature. The extra sheath mass affects the background drag calculation. Additionally, ANTEATR can now use any 1D profile for the background solar wind as opposed to the simple empirical models it previously relied upon. We present initial results from ANTEATR‐PUP and compare with previous ANTEATR findings. Using results from an MHD simulation, we explore the effects of interactions with a static high‐speed stream (HSS) on the CME's and sheath's interplanetary evolution. The drag forces essentially disappear while a CME remains within the HSS, but reappear stronger once the CME exits. The HSS‐CME interaction produces the largest changes in the CME and sheath properties at 1 au when it occurs either close to the Sun near the inner simulation boundary at 0.1 au or right before the CME reaches 1 au. We estimate that these changes could significantly affect the geoeffectiveness.