Space Weather最新文献

{"title":"Calculating the High-Latitude Ionospheric Electrodynamics Using a Machine Learning-Based Field-Aligned Current Model","authors":"V. Sai Gowtam, Hyunju Connor, Bharat S. R. Kunduri, Joachim Raeder, Karl M. Laundal, S. Tulasi Ram, Dogacan S. Ozturk, Donald Hampton, Shibaji Chakraborty, Charles Owolabi, Amy Keesee","doi":"10.1029/2023sw003683","DOIUrl":"https://doi.org/10.1029/2023sw003683","url":null,"abstract":"We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML-AIM). ML-AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020, https://doi.org/10.1029/2020JA027908), the FAC-derived auroral conductance model of Robinson et al. (2020, https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993, https://doi.org/10.1029/92gl02109). The ML-AIM inputs are 60-min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML-AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML-AIM produces physically accurate ionospheric potential patterns such as the two-cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (Φ_<i>PC</i>) from ML-AIM, the Weimer (2005, https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data-assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML-AIM than others. ML-AIM is unique and innovative because it predicts ionospheric responses to the time-varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005, https://doi.org/10.1029/2004ja010884) designed to provide a quasi-static ionospheric condition under quasi-steady solar wind/IMF conditions. Plans are underway to improve ML-AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"52 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140591964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Localized Geomagnetic Disturbances in Global MHD: Physics and Numerics","authors":"Erik M. Vandegriff, Daniel T. Welling, Agnit Mukhopadhyay, Andrew P. Dimmock, Steven K. Morley, Ramon E. Lopez","doi":"10.1029/2023sw003799","DOIUrl":"https://doi.org/10.1029/2023sw003799","url":null,"abstract":"One of the prominent effects of space weather is the formation of rapid geomagnetic field variations on Earth's surface driven by the magnetosphere-ionosphere system. These geomagnetic disturbances (GMDs) cause geomagnetically induced currents to run through ground conducting systems. In particular, localized GMDs (LGMDs) can be high amplitude and can have an effect on scale sizes less than 100 km, making them hazardous to power grids and difficult to predict. In this study, we examine the ability of the Space Weather Modeling Framework (SWMF) to reproduce LGMDs in the 7 September 2017 event using both existing and new metrics to quantify the success of the model against observation. We show that the high-resolution SWMF can reproduce LGMDs driven by ionospheric sources, but struggles to reproduce LGMDs driven by substorm effects. We calculate the global maxima of the magnetic fluctuations to show instances when the SWMF captures LGMDs at the correct times but not the correct locations. To remedy these shortcomings we suggest model developments that will directly impact the ability of the SWMF to reproduce LGMDs, most importantly updating the ionospheric conductance calculation from empirical to physics-based.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"100 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140591950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Loss of Starlink Satellites in February 2022: How Moderate Geomagnetic Storms Can Adversely Affect Assets in Low-Earth Orbit","authors":"Yoshita Baruah, Souvik Roy, Suvadip Sinha, Erika Palmerio, Sanchita Pal, Denny M. Oliveira, Dibyendu Nandy","doi":"10.1029/2023sw003716","DOIUrl":"https://doi.org/10.1029/2023sw003716","url":null,"abstract":"On 3 February 2022, SpaceX launched 49 Starlink satellites, 38 of which unexpectedly de-orbited. Although this event was attributed to space weather, definitive causality remained elusive because space weather conditions were not extreme. In this study, we identify solar sources of the interplanetary coronal mass ejections that were responsible for the geomagnetic storms around the time of launch of the Starlink satellites and for the first time, investigate their impact on Earth's magnetosphere using magnetohydrodynamic modeling. The model results demonstrate that the satellites were launched into an already disturbed space environment that persisted over several days. However, on performing comparative satellite orbital decay analyses, we find that space weather alone was not responsible but conspired together with a low-altitude insertion and low satellite mass-to-area ratio to precipitate this unusual loss. Our work bridges space weather causality across the Sun–Earth system—with relevance for space-based human technologies.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"26 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PyIRI: Whole-Globe Approach to the International Reference Ionosphere Modeling Implemented in Python","authors":"Victoriya V. Forsythe, Dieter Bilitza, Angeline G. Burrell, Kenneth F. Dymond, Bruce A. Fritz, Sarah E. McDonald","doi":"10.1029/2023sw003739","DOIUrl":"https://doi.org/10.1029/2023sw003739","url":null,"abstract":"The International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models. The development of this model was initiated in the late 1960s using the FORTRAN language; for its programming approach, the model outputs were calculated separately for each given geographic location and time stamp. The Consultative Committee on International Radio (CCIR) and International Union of Radio Science (URSI) coefficients provide the skeleton of the IRI model, as they define the global distribution of the maximum useable ionospheric frequency <i>fo</i>F2 and the propagation factor <i>M</i>(3,000)F2. At the U.S. Naval Research Laboratory, a novel Python tool was developed that enables global runs of the IRI model with significantly lower computational overhead. This was made possible through the Python rebuild of the core IRI component (which calculates ionospheric critical frequency using the CCIR or URSI coefficients), taking advantage of NumPy matrix multiplication instead of using cyclic addition. This paper explains in detail this new approach and introduces all components of the PyIRI package.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"61 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling Geomagnetically Induced Currents in the Alberta Power Network: Comparison and Validation Using Hall Probe Measurements During a Magnetic Storm","authors":"Darcy Cordell, Ian R. Mann, Hannah Parry, Martyn J. Unsworth, Ryan Cui, Colin Clark, Eva Kelemen, Ryan MacMullin","doi":"10.1029/2023sw003813","DOIUrl":"https://doi.org/10.1029/2023sw003813","url":null,"abstract":"During space weather events, geomagnetic disturbances (GMDs) induce geoelectric fields which drive geomagnetically induced currents (GICs) through electrically-grounded power transmission lines. Alberta, Canada—located near the auroral zone and thus prone to large GMDs—has a dense network of magnetometer stations and surface impedance measurements to better characterize the GMD and ground conductivity, respectively. GIC monitoring devices were recently installed at five substation transformer neutrals, providing a unique opportunity to compare data to modeled GICs. GICs are modeled across the &gt;240 kV provincial power transmission network during a moderate GMD event on 24 April 2023. GIC monitoring devices measured larger neutral-to-ground currents than expected up to 117 Amps during peak storm time, providing unequivocal evidence linking network GICs with GMDs. The model performs reasonably well (correlation coefficients &gt;0.5; performance parameter &gt;0.15) at four of five substations, but generally underestimates peak GIC values (sometimes by a factor &gt;2), suggesting that the present model underrepresents overall network risk. The model performs poorly at one of the five substations (correlation = 0.46; performance parameter = 0.10), the reasons for which may be due to simplifications and/or unknowns in network parameters. Despite these underestimates, during this GMD, the model predicts the largest GIC at substations located in the northeastern part of the province (240 kV) or around Edmonton (500 kV)—regions which have significant electrical and industrial infrastructure. Further refinement of the network model with transformer resistances, more line and earthing resistances, and/or including lower voltage levels is necessary to improve data fit.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"14 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparison of Auroral Oval Proxies With the Boundaries of the Auroral Electrojets","authors":"Simon James Walker, Karl Magnus Laundal, Jone Peter Reistad, Anders Ohma, Spencer Mark Hatch, Gareth Chisham, Margot Decotte","doi":"10.1029/2023sw003689","DOIUrl":"https://doi.org/10.1029/2023sw003689","url":null,"abstract":"The boundaries of the auroral oval and auroral electrojets are an important source of information for understanding the coupling between the solar wind and the near-earth plasma environment. Of these two types of boundaries the auroral electrojet boundaries have received comparatively little attention, and even less attention has been given to the connection between the two. Here we introduce a technique for estimating the electrojet boundaries, and other properties such as total current and peak current, from 1-D latitudinal profiles of the eastward component of equivalent current sheet density. We apply this technique to a preexisting database of such currents along the 105° magnetic meridian, estimated using ground-based magnetometers, producing a total of 11 years of 1-min resolution electrojet boundaries during the period 2000–2020. Using statistics and conjunction events we compare our electrojet boundary data set with an existing electrojet boundary data set, based on <i>Swarm</i> satellite measurements, and auroral oval proxies based on particle precipitation and field-aligned currents. This allows us to validate our data set and investigate the feasibility of an auroral oval proxy based on electrojet boundaries. Through this investigation we find the proton precipitation auroral oval is a closer match with the electrojet boundaries. However, the bimodal nature of the electrojet boundaries as we approach the noon and midnight discontinuities makes an average electrojet oval poorly defined. With this and the direct comparisons differing from the statistics, defining the proton auroral oval from electrojet boundaries across all local and universal times is challenging.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"54 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical Models of foF2 and hmF2 Reconstituted by Global Ionosonde and Reanalysis Data and COSMIC Observations","authors":"Fuqing Huang, H. Ruan, J. Lei, J. Zhong, X. Yue, Guozhu Li, Yiding Chen, Jianhui He, Na Li, X. Luan, C. Xiong, Xiankang Dou","doi":"10.1029/2023sw003848","DOIUrl":"https://doi.org/10.1029/2023sw003848","url":null,"abstract":"The F2‐peak plasma frequency (foF2) and the height of the F2 peak (hmF2) are two of the most important parameters for any ionospheric model, as well as radio propagation studies and applications. In this study, we have developed empirical models to capture the most significant variations of foF2 and hmF2. The derived empirical models (referred to as the USTC models within this study) are specified through global ionosonde and reanalysis data based on the International Reference Ionosphere (IRI) Consultative Committee on International Radio (CCIR) method and Constellation Observindg System for Meteorology, Ionosphere, and Climate (COSMIC) observations based on the empirical orthogonal function analysis, respectively. The USTC models are validated against the IRI CCIR model prediction. The comparison results revealed that the empirical foF2 model performs better in capturing the foF2 variations than the IRI CCIR model, which can overcome the underestimation of the IRI CCIR model at low latitudes. Although the IRI CCIR model overestimation at middle latitudes is addressed by the empirical hmF2 model, the visible differences between the model predictions and ionosonde observations still exist at low latitudes, which could be attributed to the significant difference between COSMIC and ionosonde hmF2 measures.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"436 ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140776165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Method and Validation of Real‐Time Global Ionosphere Modeling Constraint by Multi‐Source GNSS/LEO Data","authors":"Jun Chen, X. Ren, Guozhen Xu, Peng-Cheng Yang, Hang Liu, Xiaohong Zhang","doi":"10.1029/2023sw003800","DOIUrl":"https://doi.org/10.1029/2023sw003800","url":null,"abstract":"This study applies the zero‐differenced integer ambiguity method, named PPP‐Fixed, to extract real‐time ionospheric data and eliminate the latencies of rapid/final Global Ionosphere Maps (GIMs). The PPP‐Fixed method is also used to derive ionospheric data for post‐processed GIM generation, named SGG Post‐GIM, combined with low earth orbit satellite data. The obtained hardware delays are applied to revise real‐time ionospheric data. Meanwhile, the estimated multi‐source ionospheric model is regarded as historical data to estimate an ionospheric prediction model for constraint using the semi‐parameter model. Then, the Kalman filter is employed to estimate the parameters to generate real‐time GIM. Finally, the accuracy of estimated real‐time GIM, named SGG RT‐GIM, and SGG Post‐GIM is assessed. During the experimental period, the mean differences of SGG Post‐GIM and SGG RT‐GIM relative to GIMs provided by the international Global Navigation Satellite System service, named IGSG, are −0.46 and −0.57 Total Electron Content Unit (TECU), respectively. The corresponding Root Mean Square (RMS) values are 1.64 and 3.08 TECU. Over the test period, the mean positioning errors of the single‐frequency precise point positioning corrected by IGSG, SGG Post‐GIM, SGG RT‐GIM, and Klobuchar model are 0.14, 0.19, 0.21, and 0.25 m in the horizontal direction, respectively, while the corresponding errors are 0.36, 0.33, 0.38, and 0.64 m in the up direction. Further, the mean biases of experimental days for the self‐consistency assessment are 0.06, −0.01, and −0.07 TECU for IGSG, SGG Post‐GIM, and SGG RT‐GIM, respectively. The corresponding RMS values are 1.19, 1.15, and 1.57 TECU.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"144 3","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140766636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of Radiation Exposure at Aviation Flight Altitudes Using the Nowcast of Aerospace Ionizing Radiation System (NAIRAS)","authors":"Daniel B. Phoenix, Christopher J. Mertens, Guillaume Gronoff, Kent Tobiska","doi":"10.1029/2024sw003869","DOIUrl":"https://doi.org/10.1029/2024sw003869","url":null,"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.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"130 3","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140778002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical Features of Polar Cap North and South Indices in Response to Interplanetary and Terrestrial Conditions: A Revisit","authors":"Jong‐Sun Park, Quan Qi Shi, O. Troshichev, Khan‐Hyuk Kim, J. Shue, T. Pitkänen, Hui Zhang","doi":"10.1029/2024sw003856","DOIUrl":"https://doi.org/10.1029/2024sw003856","url":null,"abstract":"In this study, we investigate statistical features of polar cap north (PCN) and south (PCS) indices in response to various interplanetary conditions (interplanetary magnetic field [IMF] orientation in three‐dimensions) and terrestrial conditions (seasonal and magnetic local time [MLT] locations of the index stations). The concurrent PCN‐PCS pairs for 1998–2002 and 2004–2018 are divided based on their sign type (positive‐positive, negative‐negative, negative‐positive, and positive‐negative PCN‐PCS pairs) and time coverage (the times when both index stations are in the dawn/dusk MLT sector during northern summer/winter). Analyzing the IMF orientation dependence on the occurrence probabilities of concurrent indices and on the differences between the indices in various sign types for each time coverage reveals that the statistical features in PCN‐PCS pairs obtained in the dawn MLT sector can be largely explained by the effects of the three‐component IMF (related to the polar cap convection patterns) combined with season (related to the hemispheric asymmetry in solar illumination‐induced ionospheric conductance). However, those obtained in the dusk MLT sector are controlled dominantly by seasonal effects rather than IMF orientation effects. Our findings indicate that PCN‐PCS pair data provide local views about the solar wind‐magnetosphere‐ionosphere (SW‐M‐I) coupling system with different control efficiencies of IMF orientation and season depending on the MLT location of the stations. Therefore, introducing polar cap indices recorded simultaneously at various locations in both hemispheres and analyzing them are strongly required to infer global views of the coupled SW‐M‐I system in the open field regions with higher confidence.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"38 ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140786201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}