A Summary of National Oceanic and Atmospheric Administration Space Weather Prediction Center Proton Event Forecast Performance and Skill

Bain, H. M.; Steenburgh, R. A.; Onsager, T. G.; Stitely, E. M.

doi:10.1029/2020sw002670

Cited by 28 publications

(46 citation statements)

References 42 publications

(67 reference statements)

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“…Regarding SEP predictions, SEPMOD requires the existence of a shock-observer magnetic field connection and the predicted SEP properties depend on the shock parameters at the connection point. Here we consider the three main areas that were identified by Bain et al (2021) to be of high importance (see also the Introduction), i.e. SEP onset time, event duration, and peak fluxes.…”

Section: Discussionmentioning

confidence: 99%

CMEs and SEPs During November-December 2020: A Challenge for Real-Time Space Weather Forecasting

Palmerio,

Lee,

Mays

et al. 2022

Preprint

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Predictions of coronal mass ejections (CMEs) and solar energetic particles (SEPs) are a central issue in space weather forecasting. In recent years, interest in space weather predictions has expanded to include impacts at other planets beyond Earth as well as spacecraft scattered throughout the heliosphere. In this sense, the scope of space weather science now encompasses the whole heliospheric system, and multi-point measurements of solar transients can provide useful insights and validations for prediction models. In this work, we aim to analyse the whole inner heliospheric context between two eruptive flares that took place in late 2020, i.e. the M4.4 flare of November 29 and the C7.4 flare of December 7. This period is especially interesting because the STEREO-A spacecraft was located ∼60 • east of the Sun-Earth line, giving us the opportunity to test the capabilities of "predictions at 360 • " using remote-sensing observations from the Lagrange L1 and L5 points as input. We simulate the CMEs that were ejected during our period of interest and the SEPs accelerated by their shocks using the WSA-Enlil-SEPMOD modelling chain and four sets of input parameters, forming a "mini-ensemble". We validate our results using in-situ observations at six locations, including Earth and Mars. We find that, despite some limitations arising from the models' architecture and assumptions, CMEs and shock-accelerated SEPs can be reasonably studied and forecast in real time at least out to several tens of degrees away from the eruption site using the prediction tools employed here. Plain Language SummaryCoronal mass ejections (CMEs) and solar energetic particles (SEPs) are phenomena from the Sun that are able to cause significant disturbances at Earth and other planets. Reliable predictions of these events and their effects are amongst the major goals of space weather forecasts, which aim to tackle all processes related to solar activity that can endanger human technology and society. In recent years, the breadth of space weather science has started to encompass other locations than Earth, ranging from all solar system planets to spacecraft scattered throughout space. In this work, we test our current capabilities in predicting space weather events in the inner solar system (i.e., within the orbit of Mars) for a period in late 2020. We use a chain of models that are able to simulate the background solar wind as well as transient phenomena such as CMEs and SEPs, and compare our results with spacecraft measurements from six well-separated locations, including Earth and Mars. We find that our current forecasting tools, despite their limitations, can successfully provide reasonable predictions of both CMEs and SEPs, especially out to several tens of degrees around the corresponding eruption source region on the Sun.

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Section: Discussionmentioning

confidence: 99%

CMEs and SEPs During November-December 2020: A Challenge for Real-Time Space Weather Forecasting

Palmerio,

Lee,

Mays

et al. 2022

Preprint

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“…The probabilities for the days when the reports were not issued were obtained by interpolation from the neighboring days. An extensive study of the SWPC NOAA SPE probabilities was recently performed by Bain et al (2021); we direct the readers to this study for more details about the operational forecasts.…”

Section: Daily Swpc Noaa Proton Event Probabilitiesmentioning

confidence: 99%

“…The current operational daily forecasting of > 10 MeV > 10 pfu SPEs relies on a statistics-based approach, plus a human forecaster to correct the predictions (Balch 1999(Balch , 2008Bain et al 2021). This approach has been validated over several solar cycles.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Solar Proton Events with Machine Learning: Comparison with Operational Forecasts and "All-Clear" Perspectives

Sadykov,

Kosovichev,

Kitiashvili

et al. 2021

Preprint

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Solar Energetic Particle events (SEPs) are among the most dangerous transient phenomena of solar activity. As hazardous radiation, SEPs may affect the health of astronauts in outer space and adversely impact current and future space exploration. In this paper, we consider the problem of daily prediction of Solar Proton Events (SPEs) based on the characteristics of the magnetic fields in solar Active Regions (ARs), preceding soft X-ray and proton fluxes, and statistics of solar radio bursts. The machine learning (ML) algorithm uses an artificial neural network of custom architecture designed for whole-Sun input. The predictions of the ML model are compared with the SWPC NOAA operational forecasts of SPEs. Our preliminary results indicate that 1) for the AR-based predictions, it is necessary to take into account ARs at the western limb and on the far side of the Sun; 2) characteristics of the preceding proton flux represent the most valuable input for prediction; 3) daily median characteristics of ARs and the counts of type II, III, and IV radio bursts may be excluded from the forecast without performance loss; and 4) ML-based forecasts outperform SWPC NOAA forecasts in situations in which missing SPE events is very undesirable. The introduced approach indicates the possibility of developing robust "all-clear" SPE forecasts by employing machine learning methods.

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“…International efforts (see e.g., the SEP Validation Team: https://ccmc.gsfc.nasa.gov/assessment/topics/helio-sep.php) are underway to assess the current status of SEP forecasting and to establish community-wide metrics. Recently, Bain et al (2021) assessed the performance of the National Oceanic and Atmospheric Administration's Space Weather Prediction Center (NOAA/SWPC) proton event forecasts, finding for ≥10 MeV (≥100 MeV) proton warnings a probability of detection of 91% (53%) and a false alarm ratio of 24% (38%), with a median lead time of 88 min (10 min). The authors suggested that these results may serve as a benchmark for SEP models that can operate in a nowcast setting, and noted that a particular challenge is to accurately predict the onset, peak, and end times and fluxes of SEP events in different energy ranges.…”

Section: Introductionmentioning

confidence: 99%

CMEs and SEPs During November–December 2020: A Challenge for Real‐Time Space Weather Forecasting

et al. 2022

View full text Add to dashboard Cite

Predictions of coronal mass ejections (CMEs) and solar energetic particles (SEPs) are a central issue in space weather forecasting. In recent years, interest in space weather predictions has expanded to include impacts at other planets beyond Earth as well as spacecraft scattered throughout the heliosphere. In this sense, the scope of space weather science now encompasses the whole heliospheric system, and multipoint measurements of solar transients can provide useful insights and validations for prediction models. In this work, we aim to analyze the whole inner heliospheric context between two eruptive flares that took place in late 2020, that is, the M4.4 flare of 29 November and the C7.4 flare of 7 December. This period is especially interesting because the STEREO-A spacecraft was located ∼60° east of the Sun-Earth line, giving us the opportunity to test the capabilities of "predictions at 360°" using remote-sensing observations from the Lagrange L1 and L5 points as input. We simulate the CMEs that were ejected during our period of interest and the SEPs accelerated by their shocks using the WSA-Enlil-SEPMOD modeling chain and four sets of input parameters, forming a "mini-ensemble." We validate our results using in situ observations at six locations, including Earth and Mars. We find that, despite some limitations arising from the models' architecture and assumptions, CMEs and shockaccelerated SEPs can be reasonably studied and forecast in real time at least out to several tens of degrees away from the eruption site using the prediction tools employed here.Plain Language Summary Coronal mass ejections (CMEs) and solar energetic particles (SEPs) are phenomena from the Sun that are able to cause significant disturbances at Earth and other planets. Reliable predictions of these events and their effects are among the major goals of space weather forecasts, which aim to tackle all processes related to solar activity that can endanger human technology and society. In recent years, the breadth of space weather science has started to encompass other locations than Earth, ranging from all solar system planets to spacecraft scattered throughout space. In this work, we test our current capabilities in predicting space weather events in the inner solar system (i.e., within the orbit of Mars) for a period in late 2020. We use a chain of models that are able to simulate the background solar wind as well as transient phenomena such as CMEs and SEPs, and compare our results with spacecraft measurements from six well-separated locations, including Earth and Mars. We find that our current forecasting tools, despite their limitations, can successfully provide reasonable predictions of both CMEs and SEPs, especially out to several tens of degrees around the corresponding eruption source region on the Sun.

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A Summary of National Oceanic and Atmospheric Administration Space Weather Prediction Center Proton Event Forecast Performance and Skill

Abstract: The ≥ 10 MeV proton Warnings have a Probability of Detection of 91% and a False Alarm Ratio 24% with a median lead time of 88 minutes.• The ≥ 100 MeV proton Warnings have a Probability of Detection of 53% and a False Alarm Ratio 38% with a median lead time of 10 minutes.

Cited by 28 publications

References 42 publications

CMEs and SEPs During November-December 2020: A Challenge for Real-Time Space Weather Forecasting

CMEs and SEPs During November-December 2020: A Challenge for Real-Time Space Weather Forecasting

Prediction of Solar Proton Events with Machine Learning: Comparison with Operational Forecasts and "All-Clear" Perspectives

CMEs and SEPs During November–December 2020: A Challenge for Real‐Time Space Weather Forecasting

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