Earth and Space Science最新文献

{"title":"What Sets the Tropical Cold Point in GSRMs During Boreal Winter? Overshooting Convection Versus Cirrus Lofting","authors":"Jacqueline M. Nugent,&nbsp;Christopher S. Bretherton,&nbsp;Peter N. Blossey","doi":"10.1029/2024EA003887","DOIUrl":"https://doi.org/10.1029/2024EA003887","url":null,"abstract":"<p>The cold point tropopause, the minimum temperature within the tropical upper troposphere-lower stratosphere region (UTLS), significantly impacts Earth's climate by influencing the amount of water vapor entering the lower stratosphere. Understanding which mechanisms are most important in setting the cold point temperature and height may help us better predict how it will change in a future warmed climate. In this analysis we evaluate two mechanisms that may influence the cold point—cold point-overshooting convection and the radiative lofting of thin cirrus near the cold point—during boreal winter by comparing 30-day global storm-resolving model (GSRM) simulations from the winter phase of the DYAMOND initiative to satellite observations. GSRMs have explicit deep convection and sufficiently fine grid spacings to simulate convective overshoots and UTLS cirrus, making them promising tools for this purpose. We find that the GSRMs reproduce the observed distribution of cold point-overshooting convection but do not simulate enough cirrus capable of radiative lofting near the cold point. Both the models and observations show a strong relationship between areas of frequent cold point overshoots and colder cold points, suggesting that cold point-overshooting convection has a notable influence on the mean cold point. However, we find little evidence that the radiative lofting of cold point cirrus substantially influences the cold point. Cold point-overshooting convection alone cannot explain all variations in the cold point across different GSRMs or regions; future studies using longer GSRM simulations that consider longer-term UTLS processes are needed to fully understand what sets the cold point.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003887","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SunRISE Ground Radio Lab: Monitoring Solar Radio Bursts With an Expansive Array of Antennae at High Schools Nationwide","authors":"M. Akhavan-Tafti,&nbsp;S. L. Soni,&nbsp;C. Higgins,&nbsp;S. Fung,&nbsp;S. Lepri,&nbsp;J. Lux,&nbsp;J. Lazio,&nbsp;A. Romero-Wolf","doi":"10.1029/2024EA004114","DOIUrl":"https://doi.org/10.1029/2024EA004114","url":null,"abstract":"<p>The Sun Radio Interferometer Space Experiment (SunRISE) Ground Radio Lab (GRL) is a Science, Technology, Engineering, Arts, and Mathematics (STEAM) project, sponsored by NASA's SunRISE mission and organized by the University of Michigan College of Engineering. The project aims to engage and train the next generations of scholars. To achieve this, the project deployed antennas to 18 high schools nationwide to observe solar radio bursts (SRB). SRBs are defined as low-frequency radio emissions emanated by accelerated electrons associated with extreme solar activity, including solar flares and coronal mass ejections (CMEs). Type II SRBs were found to predominantly correspond to coronal shocks caused by CMEs, highlighting particle acceleration events in the solar atmosphere and interplanetary space. These bursts can act as early warning signs of upcoming solar disturbances which can lead to geomagnetic storms. The type II bursts were then investigated to estimate the corresponding shock and Alfvén speeds: 277 &lt; <i>v</i>_shock &lt; 1,480 km/s and 194 &lt; <i>v</i>_A &lt; 947 km/s at heliocentric distances of around 1–2 solar radii, respectively. The Alfvén Mach number was further found to be 1.2 &lt; <i>M</i>_A &lt; 2, while the measured magnetic field strength followed a single power law of <i>B</i>(<i>r</i>) = 0.3 r⁻², where <i>r</i> represents the heliocentric distance. Our results were found to agree with previous studies. Through SunRISE GRL, an ever-expanding catalog of SRBs is being collected by high school students nationwide, curated by a team of solar physics experts, and made publicly available to the scientific community to make progress toward the SunRISE mission's objectives.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2-Day Ionospheric Oscillations at Low Latitudes Due To an Ultra-Fast Kelvin Wave","authors":"Ashish P. Jadhav,&nbsp;Yosuke Yamazaki,&nbsp;S. Gurubaran,&nbsp;Kaoru Sato,&nbsp;Dai Koshin","doi":"10.1029/2025EA004322","DOIUrl":"https://doi.org/10.1029/2025EA004322","url":null,"abstract":"<p>This study establishes an observational connection between an ultra-fast Kelvin wave (UFKW) and the occurrence of counter electrojet (CEJ) in the equatorial E region and planetary wave-like oscillations in low-latitude total electron content (TEC), based on a case study of CEJ events that occurred in December 2017. During this period, noontime CEJ was observed by ground-based magnetometers with a periodicity of ∼2 days. The analysis of hourly wind data from the JAGUAR-DAS Whole neutral Atmosphere Reanalysis reveals the presence of an eastward-propagating UFKW with a zonal wavenumber of 1 (E1) and a period of ∼2 days along with an enhancement of eastward wind in the equatorial dynamo region which coincided with occurrence of CEJ. Observations from the Swarm satellite mission confirm the presence of equatorial electrojet (EEJ) oscillations associated with the UFKW. This is the first time that an UFKW has been identified as a source of day-to-day variability in CEJ. As CEJ is linked to a reduced daytime upward plasma drift over the magnetic equator, TEC at low latitudes also varies at a period of ∼2 days. The analysis of global TEC maps reveals that the 2-day TEC variations consist not only of the eastward propagating wavenumber 1 component but also of the westward propagating wavenumber 2 (W2) component. The latter arises from the interaction of the E1 UFKW with the diurnally varying ionosphere. The 2-day TEC variations exhibit significant longitudinal dependence due to the interplay of constructive and destructive interferences between the E1 and W2 2-day oscillations.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004322","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Method to Obtain Remotely Sensed Grain Size Distributions From Granular Deposits With Complex Surfaces","authors":"H. L. Jacobson,&nbsp;G. Walton,&nbsp;K. R. Barnhart,&nbsp;F. K. Rengers","doi":"10.1029/2025EA004376","DOIUrl":"https://doi.org/10.1029/2025EA004376","url":null,"abstract":"<p>Constraining the grain size distribution of granular deposits with complex surfaces is difficult with existing approaches. Field and laboratory techniques are time consuming and limited by the maximum grain size that laboratories can accommodate. In this study, we present a new method to identify the coarse fraction of the grain size distribution at a debris-flow fan deposit surveyed with terrestrial laser scanning (TLS) in Glenwood Canyon, Colorado, USA. This method is a novel grain segmentation algorithm developed for application to point cloud data of deposits with complex surfaces and angular grains ranging in size from centimeters to a meter. This approach combines an existing random forest machine learning method with a novel iterative clustering algorithm. We compared the grain size distribution from our algorithm with a Wolman pebble count conducted in the field, and found a root mean squared error of less than 2 cm from the 5th to 95th percentile of the grain size distribution of grains ranging from cobble to boulder sized (6.3–78 cm in our application). Finally, we compared our new algorithm with an existing open-source grain segregation algorithm, and our method outperformed the selected alternative when applied to the debris-flow deposit point cloud.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DeFault: DEep-Learning-Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site","authors":"Hanchen Wang,&nbsp;Yinpeng Chen,&nbsp;Tariq Alkhalifah,&nbsp;Ting Chen,&nbsp;Youzuo Lin,&nbsp;David Alumbaugh","doi":"10.1029/2023EA003422","DOIUrl":"https://doi.org/10.1029/2023EA003422","url":null,"abstract":"&lt;p&gt;The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high-quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;DeFault&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $mathit{DeFault}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain-adaptation, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;DeFault&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $mathit{DeFault}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;DeFault&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $mathit{DeFault}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;DeFault&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $mathit{DeFault}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; on a field case study involving &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;DeFault&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $mathit{DeFault}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. T","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EA003422","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pre-Sunrise Equatorial Plasma Bubble Over Indonesia During the 11 May 2024 Super Geomagnetic Storm","authors":"Suraina,&nbsp;A. Rakhman,&nbsp;P. Abadi,&nbsp;L. O. M. M. Kilowasid,&nbsp;A. Y. Putra,&nbsp;S. Perwitasari,&nbsp;T. M. Irnaka","doi":"10.1029/2024EA004152","DOIUrl":"https://doi.org/10.1029/2024EA004152","url":null,"abstract":"<p>Equatorial Plasma Bubbles (EPBs) generally form around sunset in equatorial to low-latitude regions. However, based on observations of the rate total electron content (TEC) change index (ROTI) map over Indonesia and the ionosonde data from the Southeast Asian equatorial station during the super geomagnetic storm on 11 May 2024, we report that EPBs did not form during the post-sunset period. Instead, EPBs were observed to form pre-sunrise in the Indonesian region, an event that occurs rarely. These EPB structures developed and strengthened as they evolved and extended poleward. We suspect that the EPBs formed during the pre-sunrise period were caused by the eastward disturbance dynamo electric field (DDEF), which begins around midnight and continues until sunrise. As a result, plasma bubbles started forming near sunrise and survived until the morning. Observations from three ground-based GPS stations in Southeast Asia on May 11th, showed a significant decrease in TEC caused by EPBs pre-sunrise. However, no GNSS scintillation was detected during this period. In contrast, strong scintillation was observed at mid-latitudes. Before the formation of the EPB pre-sunrise, the peak height of the ionospheric F layer experienced a significant increase, likely caused by the DDEF during the recovery phase. The rise in the F layer height could support the growth rate of Rayleigh-Taylor instability. Therefore, DDEF becomes a major contributor to the formation of EPBs pre-sunrise.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Microphysics Model of Multicomponent Venus' Clouds With a High-Accuracy Condensation Scheme","authors":"H. Karyu,&nbsp;T. Kuroda,&nbsp;A. Mahieux,&nbsp;S. Viscardy,&nbsp;A. Määttänen,&nbsp;N. Terada,&nbsp;S. Robert,&nbsp;A. C. Vandaele,&nbsp;M. Crucifix","doi":"10.1029/2025EA004203","DOIUrl":"https://doi.org/10.1029/2025EA004203","url":null,"abstract":"<p>Accurate modeling of the Venusian cloud structure remains challenging due to its complex microphysical properties. Condensation primarily determines the cloud particle size distribution within the various cloud layers. However, existing Venus microphysics models mainly use a full-stationary bin scheme, which may be prone to numerical diffusion during condensation. To address this, we developed a new microphysics model, the Simulator of Particle Evolution, Composition, and Kinetics (SPECK), which incorporates a moving-center bin scheme designed to minimize numerical diffusion. Furthermore, SPECK can accommodate any number of size distributions with multiple components, enabling versatile applications for more complex cloud systems. The 0-D simulations demonstrated that this microphysics framework is a reliable tool for modeling cloud microphysics under Venusian atmospheric conditions, particularly in capturing condensation and evaporation processes. We further validated SPECK against recent Venus microphysics models in 1-D simulations. The moving-center scheme is shown to exhibit less numerical diffusion compared to an existing model based on a full-stationary bin scheme, allowing for more accurate calculations of microphysical processes. Furthermore, SPECK reproduces the cloud structure observed by the Pioneer Venus Large Probe, using the same computational settings adopted in the latest microphysical model study. Thanks to the suppressed numerical diffusion, SPECK achieves high accuracy at half the typical resolution while reducing computational time sixfold, making it a promising tool for future 3-D modeling. This microphysics framework will be useful for the upcoming EnVision mission and is applicable to other planetary atmospheres, including those of Mars, Titan, gas giants, and exoplanets.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bathymetry and Agricultural Crop Studies From ICESat-2: The Density-Dimension Algorithm","authors":"Xiaomei Lu,&nbsp;Yongxiang Hu,&nbsp;Ali Omar,&nbsp;Charles R. Trepte","doi":"10.1029/2024EA004037","DOIUrl":"https://doi.org/10.1029/2024EA004037","url":null,"abstract":"<p>The Density-Dimension Algorithm (DDA) was originally developed to retrieve land surface, vegetation canopy, and sea ice freeboard heights from the photon clouds measured by the multi-beamed micropulse lidar flying aboard NASA's Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. The DDA employs weight functions to calculate a density field, thereby introducing an additional dimension to the photon clouds. Then, the density field is analyzed using local peak and threshold methods to facilitate the separation of feature signal photons from nearby noise photons. In this work we extend the DDA to water bathymetry (DDA-bathymetry) and agricultural crop (DDA-crop) studies. Our results demonstrate that the technique effectively identifies bathymetric and crop photons across various background conditions, including clear water, turbid water with increased suspended particles, nighttime observations with reduced background noise, and daytime observations with solar background noise.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Satellite Tracking of Surface Water Storage Change in the Era of Surface Water and Ocean Topography (SWOT) Satellite Mission","authors":"Pritam Das,&nbsp;Faisal Hossain","doi":"10.1029/2024EA004178","DOIUrl":"https://doi.org/10.1029/2024EA004178","url":null,"abstract":"<p>The Surface Water and Ocean Topography (SWOT) satellite, launched in December 2022, represents a significant advancement in the remote sensing of global water bodies, providing simultaneous measurements of Water Surface Elevation (WSE) and extent in all-weather conditions. This study evaluates SWOT's capability to estimate reservoir storage dynamics in comparison to pre-SWOT methods. SWOT demonstrates high accuracy in measuring WSE, achieving a median <i>R</i>² close to 1 and root mean square errors nearly an order of magnitude lower compared to earlier non-SWOT approaches. SWOT offers substantial improvement over single-sensor and multi-sensor methods, due to spatial averaging of distributed elevation measurements, which was further validated by similar measurements of the ICESat-2 satellite. The key limiting factor in estimating storage from elevation measuring sensors was found to be the accuracy of Area-Elevation-Volume curve. Furthermore, preliminary applications of machine learning to integrate SWOT with non-SWOT data sets show promise, although constrained by limited data availability of SWOT as of late 2024.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004178","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictions of Equatorial Vertical Plasma Drift Using TEC Data and a Neural Network Model","authors":"S. A. Reddy,&nbsp;X. Pi,&nbsp;C. Forsyth,&nbsp;A. Aruliah,&nbsp;A. Smith","doi":"10.1029/2024EA004167","DOIUrl":"https://doi.org/10.1029/2024EA004167","url":null,"abstract":"<p>Vertical plasma drift, <i>v</i>_<i>z</i>, plays a key role in the dynamics, morphology, and space weather effects of the equatorial and low latitude ionosphere. Modeling the drift has been an on-going effort for climatology-based prediction. To address daily prediction, the <i>Vertical drIfts</i>: <i>Predicting Equatorial ionospheRic dynamics</i> (VIPER) model has been developed. VIPER is a machine learning model that is trained on total electron content (TEC) data to predict low-latitude vertical plasma drift observed by the C/NOFS mission across the period 2009–2015. The uniqueness of VIPER is that it uses TEC data for the prediction, and the data is globally and readily available. A Gaussian fitting routine is developed to strengthen the link between TEC and <i>v</i>_<i>z</i>. VIPER is a multi-layer perceptron framework with Monte Carlo (MC) uncertainty estimation capabilities. It has a mean absolute error of 8.3 m/s, an R of 0.89/1, and a skill of 0.78/1, all of which are strong scores. The model is capped at quiet and unsettled activity levels (Kp &lt; 3). MC analysis reveals that predictions should be interpreted as distributions and the uncertainty can vary with distributions of TEC data and regions of prediction even if the predicted value is the same. VIPER offers longitudinally global coverage and uncertainty estimation capabilities. It could also be expanded to handle storm-time conditions with additional work.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"12 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA004167","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}