Opal Issan, Pete Riley, Enrico Camporeale, Boris Kramer
Abstract The ambient solar wind plays a significant role in propagating interplanetary coronal mass ejections and is an important driver of space weather geomagnetic storms. A computationally efficient and widely used method to predict the ambient solar wind radial velocity near Earth involves coupling three models: Potential Field Source Surface, Wang‐Sheeley‐Arge (WSA), and Heliospheric Upwind eXtrapolation. However, the model chain has 11 uncertain parameters that are mainly non‐physical due to empirical relations and simplified physics assumptions. We, therefore, propose a comprehensive uncertainty quantification (UQ) framework that is able to successfully quantify and reduce parametric uncertainties in the model chain. The UQ framework utilizes variance‐based global sensitivity analysis followed by Bayesian inference via Markov chain Monte Carlo to learn the posterior densities of the most influential parameters. The sensitivity analysis results indicate that the five most influential parameters are all WSA parameters. Additionally, we show that the posterior densities of such influential parameters vary greatly from one Carrington rotation to the next. The influential parameters are trying to overcompensate for the missing physics in the model chain, highlighting the need to enhance the robustness of the model chain to the choice of WSA parameters. The ensemble predictions generated from the learned posterior densities significantly reduce the uncertainty in solar wind velocity predictions near Earth.
{"title":"Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction","authors":"Opal Issan, Pete Riley, Enrico Camporeale, Boris Kramer","doi":"10.1029/2023sw003555","DOIUrl":"https://doi.org/10.1029/2023sw003555","url":null,"abstract":"Abstract The ambient solar wind plays a significant role in propagating interplanetary coronal mass ejections and is an important driver of space weather geomagnetic storms. A computationally efficient and widely used method to predict the ambient solar wind radial velocity near Earth involves coupling three models: Potential Field Source Surface, Wang‐Sheeley‐Arge (WSA), and Heliospheric Upwind eXtrapolation. However, the model chain has 11 uncertain parameters that are mainly non‐physical due to empirical relations and simplified physics assumptions. We, therefore, propose a comprehensive uncertainty quantification (UQ) framework that is able to successfully quantify and reduce parametric uncertainties in the model chain. The UQ framework utilizes variance‐based global sensitivity analysis followed by Bayesian inference via Markov chain Monte Carlo to learn the posterior densities of the most influential parameters. The sensitivity analysis results indicate that the five most influential parameters are all WSA parameters. Additionally, we show that the posterior densities of such influential parameters vary greatly from one Carrington rotation to the next. The influential parameters are trying to overcompensate for the missing physics in the model chain, highlighting the need to enhance the robustness of the model chain to the choice of WSA parameters. The ensemble predictions generated from the learned posterior densities significantly reduce the uncertainty in solar wind velocity predictions near Earth.","PeriodicalId":49487,"journal":{"name":"Space Weather-The International Journal of Research and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135248443","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}
S. Y. Li, E. A. Kronberg, C. G. Mouikis, H. Luo, Y. S. Ge, A. M. Du
Abstract The information on plasma pressure in the outer part of the inner magnetosphere is important for simulations of the inner magnetosphere and a better understanding of its dynamics. Based on 17‐year observations from both Cluster Ion Spectrometry and Research with Adaptive Particle Imaging Detector instruments onboard the Cluster mission, we used machine‐learning‐based models to predict proton plasma pressure at energies from ∼40 eV to 4 MeV in the outer part of the inner magnetosphere ( = 5–9). Proton pressure distributions are assumed to be isotropic. The location in the magnetosphere, the property of stably trapped particles, and parameters of solar, solar wind, and geomagnetic activity from the OMNI database are used as predictors. We trained several different machine‐learning‐based models and compared their performances with observations. The results demonstrate that the Extra‐Trees Regressor has the best predicting performance. The Spearman correlation between the observations and predictions by the model is about 70%. The most important parameter for predicting proton pressure in our model is the value, which relates to the property of stably trapped particles. The most important predictor of solar and geomagnetic activity is F 10.7 index. Based on the observations and predictions by our model, we find that no matter under quiet or disturbed geomagnetic conditions, both the dusk‐dawn asymmetry at the dayside with higher pressure at the duskside and the day‐night asymmetry with higher pressure at the nightside occur. Our results have direct practical applications, for instance, inputs for simulations of the inner magnetosphere or the reconstruction of the 3‐D magnetospheric electric current system based on the magnetostatic equilibrium.
{"title":"Prediction of Proton Pressure in the Outer Part of the Inner Magnetosphere Using Machine Learning","authors":"S. Y. Li, E. A. Kronberg, C. G. Mouikis, H. Luo, Y. S. Ge, A. M. Du","doi":"10.1029/2022sw003387","DOIUrl":"https://doi.org/10.1029/2022sw003387","url":null,"abstract":"Abstract The information on plasma pressure in the outer part of the inner magnetosphere is important for simulations of the inner magnetosphere and a better understanding of its dynamics. Based on 17‐year observations from both Cluster Ion Spectrometry and Research with Adaptive Particle Imaging Detector instruments onboard the Cluster mission, we used machine‐learning‐based models to predict proton plasma pressure at energies from ∼40 eV to 4 MeV in the outer part of the inner magnetosphere ( = 5–9). Proton pressure distributions are assumed to be isotropic. The location in the magnetosphere, the property of stably trapped particles, and parameters of solar, solar wind, and geomagnetic activity from the OMNI database are used as predictors. We trained several different machine‐learning‐based models and compared their performances with observations. The results demonstrate that the Extra‐Trees Regressor has the best predicting performance. The Spearman correlation between the observations and predictions by the model is about 70%. The most important parameter for predicting proton pressure in our model is the value, which relates to the property of stably trapped particles. The most important predictor of solar and geomagnetic activity is F 10.7 index. Based on the observations and predictions by our model, we find that no matter under quiet or disturbed geomagnetic conditions, both the dusk‐dawn asymmetry at the dayside with higher pressure at the duskside and the day‐night asymmetry with higher pressure at the nightside occur. Our results have direct practical applications, for instance, inputs for simulations of the inner magnetosphere or the reconstruction of the 3‐D magnetospheric electric current system based on the magnetostatic equilibrium.","PeriodicalId":49487,"journal":{"name":"Space Weather-The International Journal of Research and Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135349548","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}
Abstract Characterization of the global ionospheric irregularities as a function of local time, longitude, altitude, and magnetic activities is still a challenge for radio frequency operations, especially at the low‐latitude region. One of the main reasons is lack of observations due to the unevenly distributed instruments. To overcome this constraint, we developed a new spatial density gradient index (DGRI) at two different scale sizes: small scale and medium/large scale. The DGRI is derived from in situ density measurements onboard recently launched constellation of low‐Earth‐orbiting satellites (COSMIC‐2 and ICON) at the rate of 1 Hz. Hence, the DGRI appeared to be suitable parameter that can be used as a proxy to describe the essential features of ionospheric disturbances that may critically affect our radio wave application as well as to identify the “ all clear ” zone as a function of longitude, latitude, and local time—at a refreshment rate of 30 min or less.
{"title":"New Index to Characterize Ionospheric Irregularity Distribution","authors":"Endawoke Yizengaw","doi":"10.1029/2023sw003469","DOIUrl":"https://doi.org/10.1029/2023sw003469","url":null,"abstract":"Abstract Characterization of the global ionospheric irregularities as a function of local time, longitude, altitude, and magnetic activities is still a challenge for radio frequency operations, especially at the low‐latitude region. One of the main reasons is lack of observations due to the unevenly distributed instruments. To overcome this constraint, we developed a new spatial density gradient index (DGRI) at two different scale sizes: small scale and medium/large scale. The DGRI is derived from in situ density measurements onboard recently launched constellation of low‐Earth‐orbiting satellites (COSMIC‐2 and ICON) at the rate of 1 Hz. Hence, the DGRI appeared to be suitable parameter that can be used as a proxy to describe the essential features of ionospheric disturbances that may critically affect our radio wave application as well as to identify the “ all clear ” zone as a function of longitude, latitude, and local time—at a refreshment rate of 30 min or less.","PeriodicalId":49487,"journal":{"name":"Space Weather-The International Journal of Research and Applications","volume":"31 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134993669","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}
Martin G Mlynczak, Delores J Knipp, Linda A Hunt, John Gaebler, Tomoko Matsuo, Liam M Kilcommons, Cindy L Young
Infrared radiative cooling by nitric oxide (NO) and carbon dioxide (CO2) modulates the thermosphere's density and thermal response to geomagnetic storms. Satellite tracking and collision avoidance planning require accurate density forecasts during these events. Over the past several years, failed density forecasts have been tied to the onset of rapid and significant cooling due to production of NO and its associated radiative cooling via emission of infrared radiation at 5.3 μm. These results have been diagnosed, after the fact, through analyses of measurements of infrared cooling made by the Sounding of the Atmosphere using Broadband Emission Radiometry instrument now in orbit over 16 years on the National Aeronautics and Space Administration Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics satellite. Radiative cooling rates for NO and CO2 have been further shown to be directly correlated with composition and exospheric temperature changes during geomagnetic storms. These results strongly suggest that a network of smallsats observing the infrared radiative cooling of the thermosphere could serve as space weather sentinels. These sentinels would observe and provide radiative cooling rate data in real time to generate nowcasts of density and aerodynamic drag on space vehicles. Currently, radiative cooling is not directly considered in operational space weather forecast models. In addition, recent research has shown that different geomagnetic storm types generate substantially different infrared radiative response, and hence, substantially different thermospheric density response. The ability to identify these storms, and to measure and predict the Earth's response to them, should enable substantial improvement in thermospheric density forecasts.
{"title":"Space-Based Sentinels for Measurement of Infrared Cooling in the Thermosphere for Space Weather Nowcasting and Forecasting.","authors":"Martin G Mlynczak, Delores J Knipp, Linda A Hunt, John Gaebler, Tomoko Matsuo, Liam M Kilcommons, Cindy L Young","doi":"10.1002/2017SW001757","DOIUrl":"https://doi.org/10.1002/2017SW001757","url":null,"abstract":"<p><p>Infrared radiative cooling by nitric oxide (NO) and carbon dioxide (CO<sub>2</sub>) modulates the thermosphere's density and thermal response to geomagnetic storms. Satellite tracking and collision avoidance planning require accurate density forecasts during these events. Over the past several years, failed density forecasts have been tied to the onset of rapid and significant cooling due to production of NO and its associated radiative cooling via emission of infrared radiation at 5.3 μm. These results have been diagnosed, after the fact, through analyses of measurements of infrared cooling made by the Sounding of the Atmosphere using Broadband Emission Radiometry instrument now in orbit over 16 years on the National Aeronautics and Space Administration Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics satellite. Radiative cooling rates for NO and CO<sub>2</sub> have been further shown to be directly correlated with composition and exospheric temperature changes during geomagnetic storms. These results strongly suggest that a network of smallsats observing the infrared radiative cooling of the thermosphere could serve as space weather sentinels. These sentinels would observe and provide radiative cooling rate data in real time to generate nowcasts of density and aerodynamic drag on space vehicles. Currently, radiative cooling is not directly considered in operational space weather forecast models. In addition, recent research has shown that different geomagnetic storm types generate substantially different infrared radiative response, and hence, substantially different thermospheric density response. The ability to identify these storms, and to measure and predict the Earth's response to them, should enable substantial improvement in thermospheric density forecasts.</p>","PeriodicalId":49487,"journal":{"name":"Space Weather-The International Journal of Research and Applications","volume":"16 4","pages":"363-375"},"PeriodicalIF":3.7,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/2017SW001757","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41217786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the largest and most hazardous of solar energetic particle (SEP) events, acceleration takes place at shock waves driven out from the Sun by fast CMEs. Multi-spacecraft studies show that the particles from the largest events span more than 180 degrees in solar longitude; the events can last for several days. Protons streaming away from the shock generate waves that trap particles in the acceleration region, limiting outflowing intensities but increasing the efficiency of acceleration to higher energies. Thus, early intensities are bounded, but at the time of shock passage, they can suddenly rise to a peak. These shock peaks extend to >500 MeV in the largest events, creating a serious 'delayed' radiation hazard. At high energies, spectra steepen to form a 'knee.' This spectral knee can vary from ∼10 MeV to ∼1 GeV depending on shock conditions, greatly affecting the radiation hazard. Elements with different charge-to-mass ratios differentially probe the wave spectra near shocks, producing abundance ratios that vary in space and time. These abundance ratios are a tool that can foretell conditions at an oncoming shock.
{"title":"Seps: Space Weather Hazard in Interplanetary Space","authors":"D. Reames","doi":"10.1029/GM125P0101","DOIUrl":"https://doi.org/10.1029/GM125P0101","url":null,"abstract":"In the largest and most hazardous of solar energetic particle (SEP) events, acceleration takes place at shock waves driven out from the Sun by fast CMEs. Multi-spacecraft studies show that the particles from the largest events span more than 180 degrees in solar longitude; the events can last for several days. Protons streaming away from the shock generate waves that trap particles in the acceleration region, limiting outflowing intensities but increasing the efficiency of acceleration to higher energies. Thus, early intensities are bounded, but at the time of shock passage, they can suddenly rise to a peak. These shock peaks extend to >500 MeV in the largest events, creating a serious 'delayed' radiation hazard. At high energies, spectra steepen to form a 'knee.' This spectral knee can vary from ∼10 MeV to ∼1 GeV depending on shock conditions, greatly affecting the radiation hazard. Elements with different charge-to-mass ratios differentially probe the wave spectra near shocks, producing abundance ratios that vary in space and time. These abundance ratios are a tool that can foretell conditions at an oncoming shock.","PeriodicalId":49487,"journal":{"name":"Space Weather-The International Journal of Research and Applications","volume":"2 1","pages":"101-107"},"PeriodicalIF":3.7,"publicationDate":"2013-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86939186","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}
The free energy that drives space weather is created in the convective zone of the Sun with the generation and convective distortion of magnetic fields. The fields rise to the surface where they provide the vigorous suprathermal activity that is the direct parent of space weather. Some aspects of the hydrodynamics and magnetic field generation are understood, while there remains much that is mysterious. An important part of the mystery centers around the complex hydrodynamics of the convective zone and the dominating micro-scale magnetic fibril structure, motion, and interactions at the surface. The next generation Advanced Solar Telescope-the solar microscope- is intended to open up this basic small-scale world to direct observational study. The other major mystery lies in the long- term variations in the general level of solar activity, with the associated variations in space weather and terrestrial climate. Unfortunately long-term variation can be studied only in the long term, although monitoring other solar-type stars has been helpful so far in suggesting the extreme possibilities.
{"title":"Space Weather and the Changing Sun","authors":"E. Parker","doi":"10.1029/GM125P0091","DOIUrl":"https://doi.org/10.1029/GM125P0091","url":null,"abstract":"The free energy that drives space weather is created in the convective zone of the Sun with the generation and convective distortion of magnetic fields. The fields rise to the surface where they provide the vigorous suprathermal activity that is the direct parent of space weather. Some aspects of the hydrodynamics and magnetic field generation are understood, while there remains much that is mysterious. An important part of the mystery centers around the complex hydrodynamics of the convective zone and the dominating micro-scale magnetic fibril structure, motion, and interactions at the surface. The next generation Advanced Solar Telescope-the solar microscope- is intended to open up this basic small-scale world to direct observational study. The other major mystery lies in the long- term variations in the general level of solar activity, with the associated variations in space weather and terrestrial climate. Unfortunately long-term variation can be studied only in the long term, although monitoring other solar-type stars has been helpful so far in suggesting the extreme possibilities.","PeriodicalId":49487,"journal":{"name":"Space Weather-The International Journal of Research and Applications","volume":"40 1","pages":"91-99"},"PeriodicalIF":3.7,"publicationDate":"2013-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86276351","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}
A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g,, regression and curve-fitting, work well as solar activity approaches maximum and provide a month- by-month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but provide an estimate only of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This precursor method gave a smoothed sunspot number maximum of 154+21 for cycle 23. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between recent activity levels and this function. This Combined Solar Cycle Activity Forecast now gives a smoothed sunspot maximum of 140+20 for cycle 23. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity, which occurs many years later in the lower latitudes.
{"title":"Status of Cycle 23 Forecasts","authors":"D. Hathaway, R. Wilson, E. Reichmann","doi":"10.1029/GM125P0195","DOIUrl":"https://doi.org/10.1029/GM125P0195","url":null,"abstract":"A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g,, regression and curve-fitting, work well as solar activity approaches maximum and provide a month- by-month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but provide an estimate only of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This precursor method gave a smoothed sunspot number maximum of 154+21 for cycle 23. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between recent activity levels and this function. This Combined Solar Cycle Activity Forecast now gives a smoothed sunspot maximum of 140+20 for cycle 23. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity, which occurs many years later in the lower latitudes.","PeriodicalId":49487,"journal":{"name":"Space Weather-The International Journal of Research and Applications","volume":"123 3 1","pages":"195-200"},"PeriodicalIF":3.7,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80603025","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}
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