Using SDO-EVE Satellite Data to Model for the First Time How Large Solar Flares Influence the Earths Ionosphere

The ionosphere is important in our everyday communicaBons. Many satellites, like GPS satellites, have to send signals through the ionosphere, and many emergency radio communicators depend on the ionosphere to extend the range of their communicaBons. We also have many satellites and even the InternaBonal space staBon located in this region of the atmosphere. It becomes important for the astronauts in the ISS and for the health of the satellites to know what is going on in the ionosphere and how it can affect their systems. The lower regions are important because the E-­‐region will extend the distance that a High Frequency (HF) radio operator can communicate, and when the E-­‐region is expanded it will absorb the communicaBons and cause a radio blackout, so any emergency personnel that depend on those HF radio communicaBons won\u27t be able to communicate. And both the F and E regions will affect GPS satellites communicaBon and can cause errors in posiBon on the earth of up to 20 meters

Modeling the ionospheric E and F1 regions: Using SDO-EVE observations as the solar irradiance driver

Over the altitude range of 90–150 km, in dayside nonauroral regions, ionization is controlled almost entirely by solar ultraviolet irradiance; the response time for ionization during solar exposure is almost instantaneous, and likewise, the time scale for recombination into neutral species is very fast when the photoionizing source is removed. Therefore, if high-resolution solar spectral data are available, along with accurate ionization cross sections as a function of wavelength, it should be possible to model this ionospheric region with greater accuracy. The Extreme Ultraviolet Variability Experiment (EVE) instrument on the National Aeronautics and Space Administration Solar Dynamics Observatory (SDO) satellite, launched in February 2010, is intended to provide just such solar data, at high resolution in both wavelength and time cadence. We use the Utah State University time-dependent ionospheric model to assess the sensitivity in modeling that this solar irradiance data provide, under quiet solar conditions as well as during X-class flares. The sensitivity studies show that the E and F1 regions, as well as the valley region, are strongly dependent upon wavelength in both electron density and ion composition

Resolving Ionospheric E-region Modeling Challenges: The Solar Photon Flux Dependence

The EVE instrument of the NASA Solar Dynamics Observatory (SDO) provides for the first time EUV and XUV measurements of the solar irradiance that adequately define the major source of ionization of the atmosphere. In our study we modeled the E-region of the ionosphere and analyzed how it is affected by the solar irradiance data obtained by EVE and contrast this with the S2000 Solar Irradiance model, used previously. The ionosphere has two major layers, the E-layer at 100 km, and the F-layer at 300 km. The difference in solar irradiances are small except at some wavelength bands, it is these differences that lead to a better understanding of the physical/chemical processes of the E-region. Observations of the ionospheric layers is best achieved using incoherent scatter radars (ISR). We have compared our model with ISR data available from Arecibo Puerto Rico in an effort to understand how specific solar irradiance wavelength bands affect the E-region. This study focuses on two specific wavelength bands 0.1-15 nm and 91-103 nm. Both are responsible for E-region production, but in quite different manners

On the Importance of the Flare's Late Phase for the Solar Extreme Ultraviolet Irradiance

The new solar extreme ultraviolet (EUV) irradiance observations from NASA Solar Dynamics Observatory (SDO) have revealed a new class of solar flares that are referred to as late phase flares. These flares are characterized by the hot 2-5 MK coronal emissions (e.g., Fe XVI 33.5 nm) showing large secondary peaks that appear many minutes to hours after an eruptive flare event. In contrast, the cool 0.7-1.5 MK coronal emissions (e.g., Fe IX 17.1 nm) usually dim immediately after the flare onset and do not recover until after the delayed second peak of the hot coronal emissions. We refer to this period of 1-5 hours after the fl amrea sin phase as the late phase, and this late phase is uniquely different than long duration flares associated with 2-ribbon flares or large filament eruptions. Our analysis of the late phase flare events indicates that the late phase involves hot coronal loops near the flaring region, not directly related to the original flaring loop system but rather with the higher post-eruption fields. Another finding is that space weather applications concerning Earth s ionosphere and thermosphere need to consider these late phase flares because they can enhance the total EUV irradiance flare variation by a factor of 2 when the late phase contribution is included

Observations and Modeling of the Mars Low‐Altitude Ionospheric Response to the 10 September 2017 X‐Class Solar Flare

Solar extreme ultraviolet and X‐ray photons are the main sources of ionization in the Martian ionosphere and can be enhanced significantly during a solar flare. On 10 September 2017, the Mars Atmosphere and Volatile EvolutioN orbiter observed an X8.2 solar flare, the largest it has encountered to date. Here we investigate the ionospheric response before, during, and after this event with the SuperThermal Electron Transport model. We find good agreement between modeled and measured photoelectron spectra. In addition, the high photoelectron fluxes during the flare provide adequate statistics to allow us to clearly and repeatedly identify the carbon Auger peak in the ionospheric photoelectron energy spectra at Mars for the first time. By applying photochemical equilibrium, O2+ and CO2+ densities are obtained and compared with Mars Atmosphere and Volatile EvolutioN observations. The variations in ion densities during this event due to the solar irradiance enhancement and the neutral atmosphere expansion are discussed.Plain Language SummarySolar extreme ultraviolet and X‐ray photons are the main source of ionization in the Martian ionosphere, photoionizing the neutral particles and producing photoelectrons and ions. These short‐wavelength photon fluxes can be enhanced by a factor of a few to orders of magnitudes during a solar flare (the result of the rapid conversion of magnetic energy to kinetic energy in the solar corona). On 10 September 2017, the Mars Atmosphere and Volatile EvolutioN mission encountered the largest solar flare (X8.2) to date. The comprehensive measurements from Mars Atmosphere and Volatile EvolutioN provide us with an opportunity to evaluate the ionospheric response to this flare event in detail with models. In particular, we investigate the photoelectron flux and ion density response to the flare with an electron transport model. The modeled and measured photoelectron fluxes are in a good agreement. Ion density enhancement at a fixed altitude is from tens of percent to 1500% due to a combination of intensified solar photon fluxes and the heated and then expanded neutral atmosphere during this flare event.Key PointsThe modeled and measured photoelectron spectra are in good agreement during an X8.2 solar flare eventThe carbon Auger peak is clearly and repeatedly identified in electron energy spectra of the Martian ionosphere for the first timeThe ion density enhancement due to the flare at a fixed altitude is from tens to 1,500%Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145576/1/grl57692.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145576/2/grl57692_am.pd

Chapter 13 : Marshalling Resources and Dynamic Capabilities to Overcome Innovative Barriers and Foster Creativity in the Service Sector: Part. 2 Economics of creativity, fi rms and organizations

International audienceUnderstanding the economic implication of creative individuals and firms is at the heart of the new economy and of related fields such as the economics of knowledge, the economics of science and innovation management. This book brings together a panel of theoretical and empirical contributions which address the generation of creative ideas and their transformation into products and services by firms or universities, as well as the interplay of those organizations in networks and markets. The word 'creativity' has been used a great deal recently in relation to efforts to recover from the global financial crisis and re-launch economic activity. Little has been added to explain how and why an economic approach of creativity is useful and necessary. It is useful to understand how the most creative people work and think, and how to foster their creative productivity. It is useful to understand how organizations integrate and exploit creative ideas. It is useful to understand how market mechanisms can handle creativity and how policies must be adapted. It is necessary in the light of the recent economic crises that made innovation, invention and creativity the basis of a new industrialization and fuel for a new economic development. This new book assesses the economic impact of creativity, defining the term and then going on to explore theoretically and practically the economic consequences of creativity through a range of themes including: creativity and evolutionary theories of technological change; creativity and organizational learning; creativity and technological policy; and creativity and economics of networks. This volume offers a rich source of inspiration and ideas for the pursuit of research which merges economic tradition and management perspectives

Chapter 13 : Marshalling Resources and Dynamic Capabilities to Overcome Innovative Barriers and Foster Creativity in the Service Sector: Part. 2 Economics of creativity, fi rms and organizations

International audienceUnderstanding the economic implication of creative individuals and firms is at the heart of the new economy and of related fields such as the economics of knowledge, the economics of science and innovation management. This book brings together a panel of theoretical and empirical contributions which address the generation of creative ideas and their transformation into products and services by firms or universities, as well as the interplay of those organizations in networks and markets. The word 'creativity' has been used a great deal recently in relation to efforts to recover from the global financial crisis and re-launch economic activity. Little has been added to explain how and why an economic approach of creativity is useful and necessary. It is useful to understand how the most creative people work and think, and how to foster their creative productivity. It is useful to understand how organizations integrate and exploit creative ideas. It is useful to understand how market mechanisms can handle creativity and how policies must be adapted. It is necessary in the light of the recent economic crises that made innovation, invention and creativity the basis of a new industrialization and fuel for a new economic development. This new book assesses the economic impact of creativity, defining the term and then going on to explore theoretically and practically the economic consequences of creativity through a range of themes including: creativity and evolutionary theories of technological change; creativity and organizational learning; creativity and technological policy; and creativity and economics of networks. This volume offers a rich source of inspiration and ideas for the pursuit of research which merges economic tradition and management perspectives

Marshalling Resources and Dynamic Capabilities to Overcome Innovative Barriers and Foster Creativity in the Service Sector

Understanding the economic implication of creative individuals and firms is at the heart of the new economy and of related fields such as the economics of knowledge, the economics of science and innovation management. This book brings together a panel of theoretical and empirical contributions which address the generation of creative ideas and their transformation into products and services by firms or universities, as well as the interplay of those organizations in networks and markets. The word 'creativity' has been used a great deal recently in relation to efforts to recover from the global financial crisis and re-launch economic activity. Little has been added to explain how and why an economic approach of creativity is useful and necessary. It is useful to understand how the most creative people work and think, and how to foster their creative productivity. It is useful to understand how organizations integrate and exploit creative ideas. It is useful to understand how market mechanisms can handle creativity and how policies must be adapted. It is necessary in the light of the recent economic crises that made innovation, invention and creativity the basis of a new industrialization and fuel for a new economic development. This new book assesses the economic impact of creativity, defining the term and then going on to explore theoretically and practically the economic consequences of creativity through a range of themes including: creativity and evolutionary theories of technological change; creativity and organizational learning; creativity and technological policy; and creativity and economics of networks. This volume offers a rich source of inspiration and ideas for the pursuit of research which merges economic tradition and management perspectives

MAVEN H- Data (2014-2023)

These data were primarily obtained from the Neutral Gas and Ion Mass Spectrometer (NGIMS), Solar Wind Ion Analyzer (SWIA), and Solar Wind Electron Analyzer (SWEA) onboard the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft. These data sets were derived from these three instruments' data products and utilized in the article Characterizing Precipitation Behaviors of H- in the Martian Atmosphere, which is being submitted to JGR: Space Physics. Additional data sets include the list of orbits examined, relevant cross sections mentioned throughout the manuscript, and solar wind conditions derived from MAVEN data & an artificial neural network