Global Solar Activity Data Portal for Long-Term Forecasting
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We have reviewed the solar wind data obtained over a period of more than three decades. The data coverage on the Omnitape begins on 27 November 1963 and ends on 31 December 1993, for the version used by us. The coverage is very uneven, ranging from less than 40% to greater than 80%. We find that a correlation continues to exist between the measured values of the solar wind speed (V) and the geomagnetic index Ap. For the period when the coverage is greater than or equal to 85%, the data fit the equation: V (km/s) = 11.7 A(sub p) + 260. The correlation coefficient is 0.8, at a confidence level of 99.95%. However, we find that the predicted value of V may differ from the observed value by as much as 15% for a year in which the coverage is poorer. A comparison of IMP 8 with Pioneer Venus Orbiter (PVO) data indicates that the average values at the former are systematically higher by as much as 35 km/s (approximately 8%) for an overlapping time period. Also, we draw attention to the observed three solar cycle periodicity in A(sub p) data for the 1932 to 1994 period and its implications for forecasting the parameters for solar cycle 23 as well as on the computations of the modulation parameters for cosmic rays.
During 1990-1992, pyrheliometric measurements from the Earth Radiation Budget Satellite (ERBS) indicate that the total solar irradiance is decreasing at an annual rate of -0.2 Wm exp -2 with declining solar magnetic activity. Regression analyses of spacecraft irradiance measurements and of solar magnetic activity indices (10.7-cm solar radio flux and photometric sunspot index) verified the ERBS decreasing trend. The decreasing rate suggests that the irradiance should decrease 0.1 percent by 1997 when minimum solar magnetic activity is forecasted. If the forecasted 1990-1997 irradiance decrease is equal in magnitude to the magnitude of the 1986-1989 irradiance rise, one could conclude that solar irradiance variability has a strong 11-year component and no significant 22-year component. The ERBS measurements yielded 1365.4 +/- 0.7 Wm exp -2 as the mean irradiance value. In this paper, 1981-1992 spacecraft irradiance measurements are presented and compared with solar indices.
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 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.
Solar activity is a manifestation of magnetic self-organization processes that involve complex dynamical coupling of various layers of the Sun acting over a broad range of spatial and temporal scales. Synergy of observational, theoretical, and modeling efforts is key to understanding solar activity variation, dynamics, and evolution and to developing reliable physics-based forecasts of long-term solar cycles and short-term activity manifestations, “seasons of solar activity”, such as periods of enhanced flaring and CME activity. The session welcomes observers, modelers, and theoreticians to share their results and ideas and to discuss current challenges, development of emerging fields (such as data assimilation), and the analysis of historical and modern observational data using theoretical modeling, interpretations, and predictions.
The real-time solar monitoring information supplied to support SPARCS-equipped rocket launches, the routine collection and analysis of 3.3-mm solar radio maps, short-term flare forecasts based on these maps, longer-term forecasts based on the recurrence of active regions, and results of the synoptic study of solar active regions at 3.3-mm wavelength are presented. Forecasted flares in the 24-hour forecasts were 81% accurate, and those in the 28-day forecasts were 97% accurate. Synoptic radio maps at 3.3-mm wavelength are presented for twenty-three solar rotations in 1967 and 1968, as well as synoptic flare charts for the same period.
Tiros operational satellite system including weather forecasting, cloud photography, and solar activities
High-speed commercial flight transportation is being studied for intercontinental operations in the 21st century, the projected operational characteristics for these aircraft are examined, the radiation environment as it is now known is presented, and the relevant health issues are discussed. Based on a critical examination of the data, a number of specific issues need to be addressed to ensure an adequate knowledge of the ionizing radiation health risks of these aircraft operations. Large uncertainties in our knowledge of the physical fields for high-energy neutrons and multiply-charged ion components need to be reduced. Improved methods for estimating risks in prenatal exposure need to be developed. A firm basis for solar flare monitoring and forecasting needs to be developed with means of exposure abatement.
The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.
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Long duration of low solar activity in the last solar minimum has an undesirable consequence of extending the lifetime of orbital debris. The AFRL TacSat-2 satellite decommissioned in 2008 has finally re-entered into the atmosphere on February 5th after more than one year overdue. Concerning its demise we have monitored its orbital decay and monthly forecasted Tacsat-2 re-entry since September 2010 by using the Orbital Element Prediction (OEP) model developed by the AFRL Orbital Drag Environment program. The model combines estimates of future solar activity with neutral density models, drag coefficient models, and an orbit propagator to predict satellite lifetime. We run the OEP model with solar indices forecast by the NASA Marshall Solar Activity Future Estimation model, and neutral density forecast by the MSIS-00 neutral density model. Based on the two line elements in 2010 up to mid September, we estimated at a 50% confidence level TacSat-2's re-entry time to be in early February 2011, which turned out to be in good agreement with Tacsat-2's actual re-entry date. The potential space weather effects of the coming low activity solar cycle on satellite lifetime and orbital debris population are examined. The NASA long-term orbital debris evolutionary model, LEGEND, is used to quantify the effects of solar flux on the orbital debris population in the 200-600 km altitude environment. The results are discussed for developing satellite orbital drag application product.
Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, maps of the measured field in the photosphere, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). For each type of event, the expected rate is readily converted to the chance that the active region will produce such an event in any given forward time window of a day or so. If the chance is small enough (e.g. <5%), the forecast is All Clear for that type of event. We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram.
Predictions of solar activity are an essential part of our Space Weather forecast capability. Users are requiring usable predictions of an upcoming solar cycle to be delivered several years before solar minimum. A set of predictions of the amplitude of Solar Cycle 24 accumulated in 2008 ranged from zero to unprecedented levels of solar activity. The predictions formed an almost normal distribution, centered on the average amplitude of all preceding solar cycles. The average of the current compilation of 105 predictions of the annual-average sunspot number is 106 +/- 31, slightly lower than earlier compilations but still with a wide distribution. Solar Cycle 24 is on track to have a below-average amplitude, peaking at an annual sunspot number of about 80. Our need for solar activity predictions and our desire for those predictions to be made ever earlier in the preceding solar cycle will be discussed. Solar Cycle 24 has been a below-average sunspot cycle. There were peaks in the daily and monthly averaged sunspot number in the Northern Hemisphere in 2011 and in the Southern Hemisphere in 2014. With the rapid increase in solar data and capability of numerical models of the solar convection zone we are developing the ability to forecast the level of the next sunspot cycle. But predictions based only on the statistics of the sunspot number are not adequate for predicting the next solar maximum. I will describe how we did in predicting the amplitude of Solar Cycle 24 and describe how solar polar field predictions could be made more accurate in the future.
Over the past decade the concept of space weather has been introduced and matured in both the scientific community and popular press. Likewise the concept of space climatology recently also is being advanced. Closely linked to these concepts are their impacts on ground- and space-based technological systems; one such system commonly mentioned is manned space flight exemplified by the Space Shuttle and International Space Station (ISS). From a manned space flight perspective, space weather and space climatology have significant effects on the amount of radiation exposure received by humans in space from the ambient high-energy charged particles present in interplanetary space and trapped in the geomagnetosphere. Whereas the impact of space weather for most technological systems is usually discrete and well correlated in time, the principle impact of space weather and space climatology is to increase the probability of latent cancer formation in thetraveler cohort. In this regard, while space weather may be the dominating factor for a given mission, over the life of a long-term program such as the Space Shuttle or ISS space climatology is the controlling factor of latent cancer risk. Human radiation exposure enhancements associated with space weather disturbances has been a concern among scientist and mission controllers since the inception of manned spaceflight nearly forty years ago. This led NASA to develop, in conjunction with the Environmental Science Services Administration s Space Disturbance Forecast Center and the USAF/AWS, the Solar Particle Alert Network (SPAN)-the foundation of an initial U.S. space weather monitoring and forecasting service. Since Apollo, routine space flight operations have evolved to include the use of space weather and climatology data provided through a world-wide network of operational space weather data services to predict and recommend actions to minimize astronaut radiation exposures. NASA Space Radiation Analysis Group (SRAG) flight controllers use real-time space weather data to detect and assess the impact of solar particle events, outer electron belt enhancements, the formation of pseudo-stable additional trapped radiation belts, and the solar cycle modulation of trapped radiation belts and galactic cosmic rays. Energetic particle data from GOES spacecraft are automatically ingested from NOAA Space Environment Center data servers and used to drive a model for the estimating the exposure to astronauts from solar particle events. While adequate for current manned space flight support, the existing operational space weather support system requires improvements to address the anticipated evolution in both the character of manned missions as well as space flight operations management. Necessary space weather data improvements include: reliably available (near) real-time space weather data on a fixed schedule via redundant access methods that support autonomous data acquisition by computer systems behind enterprise firewalls; and rapid transition of promising research sensors into operational systems.
Understanding the solar dynamics is critical for improving our capabilities to forecast the evolution of space weather conditions. We take advantage of currently available computational capabilities to model solar dynamics from the deep interior to the corona and investigate mechanisms that may drive space weather conditions. The simulations are performed using the 3D radiative MHD code StellarBox. Comparison of synthetic spectroscopic observables obtained from numerical simulations and actual observations allows us to uncover physical processes associated with observed phenomena. To facilitate a transition from modeling short-term physical phenomena to developing a reliable forecast-oriented model, we suggest using the data assimilation approach. It allows us to cross-analyze dynamo model solutions and observations and to consider possible uncertainties and errors. In this presentation, we briefly summarize current multi-scale modeling capabilities and results and discuss ongoing developments to build a reliable physics-based forecast-oriented model of solar activity.
Understanding the solar dynamics is critical for improving our capabilities to forecast the evolution of space weather conditions. We take advantage of currently available computational capabilities to model solar dynamics from the deep interior to the corona and investigate mechanisms that may drive space weather conditions. The simulations are performed using the 3D radiative MHD code StellarBox. Comparison of synthetic spectroscopic observables obtained from numerical simulations and actual observations allows us to uncover physical processes associated with observed phenomena. To facilitate a transition from modeling short-term physical phenomena to developing a reliable forecast-oriented model, we suggest using the data assimilation approach. It allows us to cross-analyze dynamo model solutions and observations and to consider possible uncertainties and errors. In this presentation, we briefly summarize current multi-scale modeling capabilities and results and discuss ongoing developments to build a reliable physics-based forecast-oriented model of solar activity
Understanding the solar dynamics is critical for improving our capabilities to forecast the evolution of space weather conditions. We take advantage of currently available computational capabilities to model solar dynamics from the deep interior to the corona and investigate mechanisms that may drive space weather conditions. The simulations are performed using the 3D radiative MHD code StellarBox. Comparison of synthetic spectroscopic observables obtained from numerical simulations and actual observations allows us to uncover physical processes associated with observed phenomena. To facilitate a transition from modeling short-term physical phenomena to developing a reliable forecast-oriented model, we suggest using the data assimilation approach. It allows us to cross-analyze dynamo model solutions and observations and to consider possible uncertainties and errors. In this presentation, we briefly summarize current multi-scale modeling capabilities and results and discuss ongoing developments to build a reliable physics-based forecast-oriented model of solar activity