Prediction of Extreme Ultraviolet Variability Experiment (EVE)/Extreme Ultraviolet Spectro-Photometer (ESP) Irradiance from Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) Images Using Fuzzy Image Processing and Machine Learning

YesThe cadence and resolution of solar images have been increasing dramatically with the launch of new spacecraft such as STEREO and SDO. This increase in data volume provides new opportunities for solar researchers, but the efficient processing and analysis of these data create new challenges. We introduce a fuzzy-based solar feature-detection system in this article. The proposed system processes SDO/AIA images using fuzzy rules to detect coronal holes and active regions. This system is fast and it can handle different size images. It is tested on six months of solar data (1 October 2010 to 31 March 2011) to generate filling factors (ratio of area of solar feature to area of rest of the solar disc) for active regions and coronal holes. These filling factors are then compared to SDO/EVE/ESP irradiance measurements. The correlation between active-region filling factors and irradiance measurements is found to be very high, which has encouraged us to design a time-series prediction system using Radial Basis Function Networks to predict ESP irradiance measurements from our generated filling factors

Neutral H density at the termination shock: a consolidation of recent results

We discuss a consolidation of determinations of the density of neutral interstellar H at the nose of the termination shock carried out with the use of various data sets, techniques, and modeling approaches. In particular, we focus on the determination of this density based on observations of H pickup ions on Ulysses during its aphelion passage through the ecliptic plane. We discuss in greater detail a novel method of determination of the density from these measurements and review the results from its application to actual data. The H density at TS derived from this analysis is equal to 0.087 \pm 0.022 cm-3, and when all relevant determinations are taken into account, the consolidated density is obtained at 0.09 \pm 0.022 cm-3. The density of H in CHISM based on literature values of filtration factor is then calculated at 0.16 \pm 0.04 cm-3.Comment: Submitted to Space Science Review

Extreme Ultra-Violet Spectroscopy of the Lower Solar Atmosphere During Solar Flares

The extreme ultraviolet portion of the solar spectrum contains a wealth of diagnostic tools for probing the lower solar atmosphere in response to an injection of energy, particularly during the impulsive phase of solar flares. These include temperature and density sensitive line ratios, Doppler shifted emission lines and nonthermal broadening, abundance measurements, differential emission measure profiles, and continuum temperatures and energetics, among others. In this paper I shall review some of the advances made in recent years using these techniques, focusing primarily on studies that have utilized data from Hinode/EIS and SDO/EVE, while also providing some historical background and a summary of future spectroscopic instrumentation.Comment: 34 pages, 8 figures. Submitted to Solar Physics as part of the Topical Issue on Solar and Stellar Flare

Solar parameters for modeling interplanetary background

The goal of the Fully Online Datacenter of Ultraviolet Emissions (FONDUE) Working Team of the International Space Science Institute in Bern, Switzerland, was to establish a common calibration of various UV and EUV heliospheric observations, both spectroscopic and photometric. Realization of this goal required an up-to-date model of spatial distribution of neutral interstellar hydrogen in the heliosphere, and to that end, a credible model of the radiation pressure and ionization processes was needed. This chapter describes the solar factors shaping the distribution of neutral interstellar H in the heliosphere. Presented are the solar Lyman-alpha flux and the solar Lyman-alpha resonant radiation pressure force acting on neutral H atoms in the heliosphere, solar EUV radiation and the photoionization of heliospheric hydrogen, and their evolution in time and the still hypothetical variation with heliolatitude. Further, solar wind and its evolution with solar activity is presented in the context of the charge exchange ionization of heliospheric hydrogen, and in the context of dynamic pressure variations. Also the electron ionization and its variation with time, heliolatitude, and solar distance is presented. After a review of all of those topics, we present an interim model of solar wind and the other solar factors based on up-to-date in situ and remote sensing observations of solar wind. Results of this effort will further be utilised to improve on the model of solar wind evolution, which will be an invaluable asset in all heliospheric measurements, including, among others, the observations of Energetic Neutral Atoms by the Interstellar Boundary Explorer (IBEX).Comment: Chapter 2 in the planned "Cross-Calibration of Past and Present Far UV Spectra of Solar System Objects and the Heliosphere", ISSI Scientific Report No 12, ed. R.M. Bonnet, E. Quemerais, M. Snow, Springe

Overview, Progress and Next Steps for Our Understanding of the Near-Earth Space Radiation and Plasma Environment: Science and Applications

The Near-Earth Space Radiation and Plasma Environment falls within the realm of G3 Cluster (G3 refers to ‘Near-Earth Radiation and Plasma Environment’ of the ‘Coupled Geospace System’) under the COSPAR (Committee On Space Research) /International Space Weather Action Teams (ISWAT) Initiative. The diverse and dynamic particle populations from this region pose challenges from both science and space weather-impact perspectives. The G3 cluster has intimate connections with solar, heliosphere clusters, and the other Geospace ones (G1, G2) through a chain of physical processes. This paper reviews recent scientific advances in understanding this complex space environment, identifies gaps in research and space weather applications, and maps out our recommendations on priorities for the next 5-10 years

Model evaluation guidelines for geomagnetic index predictions

Geomagnetic indices are convenient quantities that distill the complicated physics of some region or aspect of near‐Earth space into a single parameter. Most of the best‐known indices are calculated from ground‐based magnetometer data sets, such as Dst, SYM‐H, Kp, AE, AL, and PC. Many models have been created that predict the values of these indices, often using solar wind measurements upstream from Earth as the input variables to the calculation. This document reviews the current state of models that predict geomagnetic indices and the methods used to assess their ability to reproduce the target index time series. These existing methods are synthesized into a baseline collection of metrics for benchmarking a new or updated geomagnetic index prediction model. These methods fall into two categories: (1) fit performance metrics such as root‐mean‐square error and mean absolute error that are applied to a time series comparison of model output and observations and (2) event detection performance metrics such as Heidke Skill Score and probability of detection that are derived from a contingency table that compares model and observation values exceeding (or not) a threshold value. A few examples of codes being used with this set of metrics are presented, and other aspects of metrics assessment best practices, limitations, and uncertainties are discussed, including several caveats to consider when using geomagnetic indices