The National Space Weather Program

Tascione, Thomas F.; Cliffswallow, W.

doi:10.2514/6.1995-550

Cited by 9 publications

(2 citation statements)

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“…Given the availability of terrestrial radiation epidemiological data, radiation risks are relatively well defined for low-linear energy transfer (LET) radiation exposures at high dose-rates. However, the space radiation environment is composed of accelerated fully charged, high-energy particles (87% protons, 12% helium ions, 1% heavier ions by particle fluence), which differs substantially from radiation exposures humans experience terrestrially that is primarily light particles from radioactivity and photon-type radiation ( 1 ). In addition to differences in the type of radiation in space and on Earth, the magnitude of naturally occurring radiation exposure is considerably higher in space ( 2 ).…”

Section: Introductionmentioning

confidence: 99%

Of Men and Mice: Using Terrestrial Radiation Epidemiology Methods to Inform Analysis of Animal Models for Space Radiation Risk Assessment

2023

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Prediction of cancer risk from space radiation exposure is critical to ensure spaceflight crewmembers are adequately informed of the risks they face when accepting assignments to ambitious long-duration exploratory missions. Although epidemiological studies have assessed the effects of exposure to terrestrial radiation, no robust epidemiological studies of humans exposed to space radiation exist to support estimates of the risk from space radiation exposure. Mouse data derived from recent irradiation experiments provides valuable information to successfully develop mouse-based excess risks models for assessing relative biological effectiveness for heavy ions that can provide information to scale unique space radiation exposures so that excess risks estimated for terrestrial radiation can be adjusted for space radiation risk assessment. Bayesian analyses were used to simulate linear slopes for excess risk models with several different effect modifiers for attained age and sex. Relative biological effectiveness values for all-solid cancer mortality were calculated from the ratio of the heavy-ion linear slope to the gamma linear slope using the full posterior distribution and resulted in values that were substantially lower than what is currently applied in risk assessment. These analyses provide an opportunity to improve characterization of parameters used in the current NASA Space Cancer Risk (NSCR) model and generate new hypotheses for future animal experiments using out-bred mouse populations.

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Section: Introductionmentioning

confidence: 99%

Of Men and Mice: Using Terrestrial Radiation Epidemiology Methods to Inform Analysis of Animal Models for Space Radiation Risk Assessment

2023

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“…Indeed, this more applied usage of space weather has been the focus of this journal since its inception (Lanzerotti, ; R. Robinson, ). Space weather is being increasingly recognized as a natural hazard of significant importance to space‐ and ground‐based infrastructure (DHS Office of Risk Management and Analysis, ; Jonas & McCarron, ; National Research Council, ; Royal Academy of Engineering, ; Schrijver et al, ; T. Tascione & Cliffswallow, ), and many challenges await the space weather research and operations communities.…”

Section: Introductionmentioning

confidence: 99%

Challenges and Opportunities in Magnetospheric Space Weather Prediction

Morley

2020

Space Weather

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Space Weather is the study of the dynamics of the coupled Solar‐Terrestrial environment, as these dynamics impact technological systems and human activity. This paper reviews a selection of the advances, challenges, and new opportunities for magnetospheric space weather, and while the focus is on specific phenomena, many other aspects of space weather will have similar challenges and needs. As a scientific field with direct applications, the field of space weather is partly driven by imperatives from both policy and operations. We provide an introduction to some of the context in which the field exists and discuss how this might shape future developments and norms within the space weather enterprise. We briefly examine benchmarking, as a policy and operationally driven activity, as it provides immediate societal relevance and an opportunity to stretch scientific understanding. As numerical space weather prediction now becomes routine, and exascale computing is in the near future, we identify challenges relating to computational expense and big data, capturing and accounting for uncertainties, and specification of boundary conditions. Here, as with the observations supporting numerical space weather prediction, the key challenge lies in extending the lead time of predictions. We also discuss the role of data, particularly in regard to model validation and empirical modeling. Due to the growing societal impact of space weather, we also examine the relationships between space weather and its terrestrial counterpart and look at the importance of continuous evaluation, monitoring progress in predictive capability, and communication with researchers, forecasters, and end users.

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Automatic recognition of complex magnetic regions on the Sun in SDO magnetogram images and prediction of flares: Techniques and results for the revised flare prediction program Flarecast

et al. 2017

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In the present paper, solar magnetograms provided by the Helioseismic and Magnetic Imager onboard Solar Dynamics Observatory spacecraft are used to identify active regions automatically by thresholding the line‐of‐sight component of the solar magnetic field. The flare potential of the regions is predicted by locating potential active regions with strong‐gradient polarity inversion lines (SPILs) and estimating 18 physically relevant parameters of these regions. In particular, parameters of interest include the sum of north‐south gradients, sum of east‐west gradients, length of SPIL, and total integrated magnetic flux. For deterministic prediction of flares, analyses for thresholding of single parameters and different combinations, which include up to four parameters, are presented and compared. If the false alarm rate does not exceed 10% (20%), the probabilities for correct prediction of X‐ray flares of class M and greater, M5 and greater, and X in the 24 h window are 71% (86%), 84% (96%), and 94% (100%), respectively. These probabilities are for the best four‐parameter technique found. A technique for probabilistic forecasting was also developed. These deterministic and probabilistic techniques will be implemented in a revised version of the flare warning program, Flarecast, which will be operational in the Australian Space Forecast Centre.

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The National Space Weather Program

Cited by 9 publications

References 0 publications

Of Men and Mice: Using Terrestrial Radiation Epidemiology Methods to Inform Analysis of Animal Models for Space Radiation Risk Assessment

Of Men and Mice: Using Terrestrial Radiation Epidemiology Methods to Inform Analysis of Animal Models for Space Radiation Risk Assessment

Challenges and Opportunities in Magnetospheric Space Weather Prediction

Automatic recognition of complex magnetic regions on the Sun in SDO magnetogram images and prediction of flares: Techniques and results for the revised flare prediction program Flarecast

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