GOES-R Series Solar Dynamics

C H A P T E R

18 GOES-R Series Solar Dynamics Daniel B. Seaton*,†, Jonathan M. Darnel*,†, Vicki Hsu*,†, J. Marcus Hughes‡ Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado-Boulder, Boulder, CO, United States, †NOAA National Centers for Environmental Information (NCEI), Boulder, CO, United States, ‡Computer Science Department, University of Colorado-Boulder, Boulder, CO, United States

*

18.1 INTRODUCTION Space weather generally refers to the conditions in the heliosphere and near-Earth space that can affect and potentially disrupt technological systems both in orbit and on the ground. Almost all space weather in the near-Earth environment is driven by phenomena that originate in the Sun’s atmosphere (Schwenn, 2006; Gopalswamy, 2018). Magnetic fields (Chapter 21), solar plasma, energetic electromagnetic radiation (Chapter 19) and energetic particles (Chapter 20) travel from the Sun to the near-Earth environment to drive a wide range of effects that occur on timescales that themselves range between minutes and days. Space weather is primarily a threat to technological systems—although it can also pose health risks to astronauts in orbit and aircrews traveling over high latitudes. Changes in Earth’s magnetic field can cause widespread damage to power grids; solar X-ray radiation can cause radio blackouts; and energetic particles can damage sensitive electronic components on hardware in space. Space weather can also interfere with GPS navigation, cause increased drag on satellites in low Earth orbit, and has even been linked to technological impacts during military operations (Kelly et al., 2014; Knipp et al., 2018). Space weather also sometimes triggers spectacular displays of the aurora in polar regions. During severe space weather events, occasionally aurorae are visible at latitudes far from the poles. Because most space weather drivers originate in the Sun’s atmosphere, space weather forecasting generally begins with monitoring this region, which itself is composed of four layers: the photosphere (the visible surface of the Sun), the chromosphere, the transition region, and the corona. The upper three layers are where most solar activity originates and are thus most important for space weather. However, because these three layers are obscured by the extremely bright photosphere—which is one million times brighter than the corona—these regions were generally only observed during total solar eclipses until the second half of the 20th century, when the advent of spaceborne ultraviolet and X-ray observatories made it possible to directly image these regions (see Aschwanden, 2005, Chapter 1.1). The Geostationary Operational Environmental Satellites (GOES)-R Series Solar Ultraviolet Imager (SUVI) observes these regions in six different passbands between 94 and 304 Å, covering a range of temperatures from about 50,000 K to >10 million K. Fig. 18.1 shows the approximate temperature and density of the solar atmosphere as a function of height, showing how the density falls and the temperature rises as altitude increases. The first layer above the photosphere, the chromosphere (Zirin, 1996) is a thin layer, roughly 5000 km (or just 0.7% of one solar radius) in depth, that lies just above the visible surface of the Sun, the photosphere. The chromosphere is composed of relatively cool, dense plasma that ranges in temperature from about 4500 K at the base of the chromosphere to a few tens of thousands of K at its top. The transition region (Mariska, 1992) is an even narrower region where the temperature of the solar atmosphere jumps rapidly from tens of thousands of K to about one million degrees. Below the transition region, the dynamics of the Sun are dominated by the gravitational force of the Sun, while above the transition region dynamic forces, largely driven by the interaction between the Sun’s strong magnetic field and solar plasma, dominate.

The GOES-R Series. https://doi.org/10.1016/B978-0-12-814327-8.00018-4

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FIG. 18.1  Electron temperature (solid line, left axis) and density (dash-dotted line, right axis) as a function of altitude in the solar atmosphere. The approximate locations of the boundaries between photosphere (which begins at an altitude of 0 km), chromosphere, transition region, and corona are indicated by the dotted vertical lines. Data for Te < 104.5 K are from Vernazza et al. (1981) and data for Te > 104.5 K are from Mariska (1992). This plot is an adaptation of work that originally appeared in McIntosh, 1998.

The corona (Golub and Pasachoff, 2009) is the outer layer of the Sun’s atmosphere, and extends from heights of a few thousand km to millions of km, eventually giving rise to the solar wind, which fills the solar system. The density of the corona is extremely low, much less dense than the chromosphere (see Fig. 18.1). The corona is fully ionized plasma, an electrically neutral, highly conductive mixture of electrons and atomic nuclei. Although it is a fluid, not unlike Earth’s atmosphere, its enormous electrical conductivity means that its dynamics are highly influenced by magnetic fields. The motions of such magnetized fluids are described by magnetohydrodynamic (MHD; Priest, 2014) equations, which combine the Navier–Stokes equations of fluid dynamics with Maxwell’s equations of electromagnetism. Under most circumstances, the corona is well described by the so-called ideal MHD equations, which treat the plasma as a perfect conductor. In the ideal MHD regime, the plasma itself is strongly coupled to the magnetic field. Coronal plasma will flow along magnetic field lines with no resistance but cannot move across magnetic field lines, which is a key reason that the corona is so highly structured by its magnetic field. This phenomenon is often referred to as the frozen-flux condition; the field lines are said to be frozen-in to the coronal plasma. The corona can be observed in white light, as in a total solar eclipse, because light from the photosphere is scattered by free electrons in the corona through a process known as Thomson scattering (Pasachoff, 2009, 2017). The amount of scattered light is proportional to the electron density of the corona, so observations in white light reveal regions of different density. However, the corona also emits light in a variety of X-ray and extreme ultraviolet (EUV) wavelengths generated by ions of various elements. In this case, the emission is largely a function of temperature, so these observations reveal the temperature structure of the corona (see, e.g., O’Dwyer et al., 2010). It is this emission that SUVI observes.

18.1.1  Solar Drivers of Space Weather In general, three key factors that originate in the solar atmosphere are responsible for all space weather. Electromagnetic radiation, primarily X-rays and EUV, drives changes in Earth’s upper atmosphere that can interfere with radio communications (e.g. Redmon et al., 2018b) and spacecraft orbital dynamics. Bursts of energetic particles, some of which travel from the Sun to Earth at nearly the speed of light, can pose a variety of hazards to both hardware and humans in space. Finally, outflows of magnetized plasma in both the steady solar wind and transient events can interact with Earth’s magnetosphere, affecting a variety of applications from spacecraft operations to power transmission to the aurora (Redmon et al., 2018a and references therein).



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The Sun’s most common influence on space weather is via the solar wind (see Marsch, 2006 and references therein), which is a steady outflow of charged particles, mostly composed of electrons, protons, and helium nuclei. The solar wind fills nearly all interplanetary space in the solar system, which is often referred to as the heliosphere. Although solar physicists have speculated about the connection between some sort of solar outflow and effects near Earth since the 1850s (Carrington, 1859), the solar wind was only first described in detail by Eugene Parker in 1958. Parker showed that the corona’s extremely high temperature imparts so much energy into the particles within that they are accelerated to supersonic speeds sufficient to escape the Sun’s gravity (Parker, 1958). In fact, the solar wind that originates from regions of the Sun near the equator flows at 250–500 km/s and is referred to as the slow solar wind (McComas et al., 1998). The slow solar wind appears to originate from regions on the Sun that are dominated by complex, closed magnetic fields—that is, fields that have both ends anchored in the photosphere. Because plasma in the corona is largely confined to magnetic field lines, the plasma in this region cannot stream freely away from the Sun. The source of this outflow, therefore, remains poorly understood.1 In some regions of the corona, however, the Sun’s magnetic field is not confined to loops but rather opens into the heliosphere. In these regions, coronal plasma is free to stream rapidly away from the Sun along the magnetic field, and these regions, therefore, have much lower density than most of the corona and appear dark in EUV and X-ray images of the corona. These regions are referred to as coronal holes, and the outflow from these regions, with speeds of 500–750 km/s, is referred to as the fast solar wind (Cranmer, 2009). Interactions between regions of fast and slow solar wind can produce complex structures and magnetic fields. Because the Sun rotates, these interface regions also rotate along with the Sun and are referred to as co-rotating interaction regions (CIRs; Cranmer, 2009). These regions sweep over Earth as they rotate and can generate unsettled space weather when they do. Thus, a key observation that drives space weather forecasting is the location of coronal holes. Such observations allow forecasters to predict the arrival of fast solar wind streams and CIRs using models like the WSA-Enlil solar wind model (Pizzo et al., 2011). More severe space weather is generally driven by transient events, many of which have their origins in active regions (van Driel-Gesztelyi and Green, 2015). These regions are formed when bundles of strong magnetic fields emerge from inside the Sun and protrude into the corona. These fields are rooted in the photosphere, where they inhibit the convection that heats this region, producing cooler, darker regions on the Sun's surface referred to as sunspots (Solanki, 2003). In the corona, these field lines usually appear as bright, complex networks of loops. Unlike the photosphere, in the corona the presence of strong magnetic fields leads to localized heating, and active regions often reach temperatures of 2–4 million K, considerably hotter than the surrounding quiet corona. What process or processes cause this heating remains an open question and is an area of active study in the solar physics community. The evolution of active regions is largely driven by complex motion in the photosphere, where the magnetic fields that comprise these regions are rooted, due to intense convection from the interior of the Sun. Because the field lines are frozen in to the active region plasma, it is not possible for the topology of the fields to change easily, and considerable magnetic stress can build up as field lines become entwined, tangled, and sheared. When sufficient stress builds up, structures in equilibrium in the corona can be destabilized, causing solar flares, impulsive brightening of the corona’s emission, particularly in X-rays, and coronal eruptions, rapid accelerations of coronal material away from the Sun and into the heliosphere (Benz, 2017; Švestka and Cliver, 1992). Flares and eruptions, which are often—but not always—related, can release vast quantities of energy in just minutes; the most powerful flares and eruptions can release as much as 1025 joules, which is likely more than all energy consumed on Earth in all of human history. Although a variety of mechanisms can trigger flares and eruptions, and a variety of phenomena can erupt on the Sun, most models of eruptive flares begin with a filament. Filaments are protrusions of relatively cool, dense chromospheric plasma, suspended high in the solar atmosphere by twisted tubes of magnetic field sometimes referred to as magnetic flux ropes. Filaments generally appear as dark, threadlike structures when viewed from above against the solar disk, but they appear bright against the background of space when viewed above the solar limb. In this latter case, filaments are often referred to as prominences (Parenti, 2014). The Parker Solar Probe, named for Eugene Parker and launched in August 2018, will pass within 9 solar-radii of the Sun where it will sample the local plasma conditions and might definitively answer the question of the source of the slow solar wind. 1

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EXIS/XRS

Alert!

R scale

X-rays

Sunlit Ionospheric disturbance

Radio Alert! Radio interference due to radio waves

due to ionospheric storm

SEISS

Alert!

Warn!

S scale

Energetic particles

Non-GOES measurement due to energetic particles

Radiation PCA Event

Solar plasma

Watch

SUVI & coronagraph imagery contribute to CME arrival forecast

Warn!

Alert!

DSCOVR & MAG for warning Kp for alert

Magnetic storm 1 min

(t = 0 is 8 minutes after eruption onset)

10 min

1h

10 h

1 day

G scale

Watch for solar events

Observations support SWPC scales and situational awareness

Filaments can often remain stable and quiescent in the solar atmosphere for days or weeks. Occasionally, however, filaments can become unstable and erupt. As the filament erupts, the magnetic fields surrounding the filament become rapidly stretched. As stress builds up, the frozen-flux condition breaks down, and the field topology can change through a process known as magnetic reconnection (Priest and Forbes, 2000). Reconnection impulsively releases energy stored in the magnetic field, which drives both the solar flare and further accelerates the erupting structure. Eruptions of this kind are often referred to as coronal mass ejections (CMEs; Chen, 2011; Webb and Howard, 2012). The acceleration phase of a CME can often be observed off the solar disk in EUV images. When a CME occurs on disk, we often observe it as a rapid darkening of a region of the corona called a coronal dimming. Dimmings are believed to occur because the erupting coronal structures carry away much of the plasma that is emitting EUV radiation, resulting in a decrease in brightness of the region where the CME originated. There is no single agreed-upon definition for exactly what constitutes a flare, but flares are typically classified by their brightness in X-rays. The reconnection process releases enough energy to heat the surrounding corona plasma to tens of millions of degrees K, which in turn causes it to radiate brilliantly in X-rays, increasing the background X-ray emission of the corona by many orders of magnitude. This bright X-ray illumination can trigger changes in the ionosphere, leading to radio blackouts on Earth. Because X-rays travel at the speed of light, the flare’s effects can already be underway as soon as the flare is detected at Earth. Flare irradiance is described in more detail in Chapter 19 on the Extreme Ultraviolet and X-ray Irradiance Sensors (EXIS). The reconnection process and the impulsive acceleration of a CME can also lead to the rapid acceleration of particles in the corona. The most energetic particles can reach velocities close to the speed of light, typically traveling to Earth within a few tens of minutes. These particles are referred to as solar energetic particles (SEPs). Additional discussion of energetic particles appears in Chapter 20. CMEs, meanwhile, reach speeds between a few hundred km/s and a few thousand km/s (Gopalswamy, 2018). The fastest events can reach Earth within half a day, while slower CMEs might take up to five days to make the trip. CMEs are complex structures and can contain both density enhancements and depletions embedded in complicated magnetic fields. They are often preceded by a magnetohydrodynamic shock. Their impact on Earth and its magnetosphere is difficult to predict and depends on particle density, shock strength, and orientation of the magnetic field inside the CME. Because CMEs evolve considerably as they transit interplanetary space, these properties generally can only be determined by in situ measurements made by spacecraft such as the Deep Space Climate Observatory (DSCOVR), which is situated about 1.5-million-km sunward from Earth. Fig. 18.2 shows the actions forecasters, such as those at the Space Weather Prediction Center (SWPC), might take when a major solar event is detected by SUVI and EXIS, in order, based on the times at which each effect begins to influence Earth. From Redmon et al. (2018b):

10 days

Time (log scale)

FIG. 18.2  GOES observations drive some of SWPC’s space weather scales, and provide critical forecast input for others. The chart below shows a subset of the forecast alerts, warnings, and watches that must be issued over the course of the several days following a solar event, the relative timing of each action and effect, and GOES and other observations used in the process. Adapted from Redmon et al. (2018b).



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Forecasters issue an alert to ‘indicate that the observed conditions, highlighted by the warnings, have crossed a preset threshold or that a space weather event has already started,’ a watch ‘when the risk of a potentially hazardous space weather event has increased significantly, but its occurrence or timing is still uncertain,’ and a warning ‘when a significant space weather event is occurring, imminent or likely. A warning is a short‐term, high confidence prediction of imminent activity.’

Among the tools SWPC employs to alert users of important space weather events are three space weather scales (https://www.swpc.noaa.gov/noaa-scales-explanation): The R scale classifies the severity of radio blackouts resulting from X-rays, the S scale classifies radiation storms arising from SEPs, and the G scale classifies geomagnetic effects. The R and S scales are directly driven by GOES measurements from EXIS and the Space Environment In Situ Suite (SEISS). The G scale depends on the planetary K-index, Kp, which is measured by ground-based magnetometers. However, solar imagery from SUVI and coronagraph imagers (see Section 18.2.1) as well as in situ measurements from DSCOVR spacecraft and GOES Magnetometers all provide data that forecasters sometimes use to shape long-range and short-term forecasts as the CME travels from the Sun to Earth. (Although no coronagraph is present on GOES-16 or GOES-17, one is planned for GOES-U, to be launched in 2024.)

18.1.2  The GOES-R Solar Ultraviolet Imager (SUVI) SUVI is a generalized Cassegrain telescope (Fig. 18.3), a very widely used design in which the observed light is focused using a concave hyperbolic primary mirror and a convex hyperbolic secondary mirror. This design offers several advantages for space-based platforms, most notably that its folded optics allow the telescope to fit in a relatively compact space, even though the focal length of the telescope is relatively long. Additionally, SUVI’s design ensures a high-quality, well-focused image over its entire focal plane without artifacts that are present in observations from telescopes of other designs (Martínez-Galarce et al., 2010, 2013; Seaton & Darnel, 2018). EUV photons are not reflected by traditional mirrors like visible light is, thus SUVI uses mirrors specially coated with a multilayered material that boosts the reflectivity of the mirror using constructive interference. Each layer individually only reflects a small amount of light, but by using many, precisely spaced layers, the multiple reflected light waves actually amplify one another and yield a mirror that can reflect EUV light (Windt et al., 2004). These multilayer coatings offer an additional benefit, in that they are only reflective over relatively narrow wavelength ranges.

FIG. 18.3  A schematic view of the SUVI telescope and instrument electronics box. Figure reprinted from GOES-R Series Data Book, 2019.

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Thus the mirrors themselves allow SUVI to achieve its spectral selection for each of the six passbands—94, 131, 171, 195, 284, and 304 Å—in which it observes the Sun. The instrument response in each band is also affected by the use of thin films of aluminum and zirconium that are used to reject visible light from the telescope, but these filters have very broad spectral throughput and it is mainly the mirror reflectivity that determines what SUVI observes in each passband. In order to observe in six different passbands using a single telescope, SUVI’s two mirrors are actually segmented into six wedges each with its own unique coating. Rotating a window at the telescope’s entrance aperture causes different mirror segments to be illuminated, and internal baffling in the telescope prevents cross-contamination between the different mirror segments. Thus allowing us to use a single, compact telescope body to capture all of the six ­passbands SUVI observes (Martínez-Galarce et al., 2013; see Section 18.2.1 for a detailed discussion of SUVI’s passbands). SUVI uses a back-illuminated charge-coupled device (CCD) for its camera. Back-illuminated CCDs have been widely used in astronomical applications due to their favorable signal-to-noise performance even in low-light conditions. However, SUVI’s CCD does not have sufficient dynamic range to capture both faint features like coronal holes and bright sources like flares in a single exposure. Therefore, SUVI makes observations with a variety of long and short exposure times to cover bright and faint features, which can then be combined in software on the ground to make high dynamic range (HDR) composite images. We discuss these images in Section 18.3.1. SUVI’s CCD is a 1280 × 1280 pixel imager, and each pixel is a 2.5 arcsec square, so the total field of view of the instrument is about 53.3 arcmin. An important feature of SUVI’s CCD is its antiblooming protection, which prevents extremely bright signals in one pixel from spilling over into the pixel’s neighbors. This is a common behavior in many scientific CCDs, and it can cause large regions of the image to become obscured during important events that produce very bright phenomena, such as solar flares. Antiblooming protection ensures that even when a pixel registers a signal that exceeds the limit of its recording range, or saturates the pixel, the signal in neighboring pixels is protected and the image quality is preserved. The apparent angular size of the solar disk varies over the course of Earth’s orbit, ranging from about 31.4 arcmin at perihelion to 32.5 arcmin at aphelion. As a result, the field of view of the instrument also varies with respect to the size of the Sun, revealing the corona out to heights between 1.64 and 1.7 RSun in the horizontal direction, depending on Earth’s location in its orbit. The field of view is somewhat larger along the diagonal direction—up to as much as 2.4 RSun—but due to vignetting, at least one corner of the image in every passband is obscured from view. Nonetheless, SUVI’s field of view allows it to image the EUV corona to heights that have not been previously observed in a number of the instrument’s passbands. SUVI operates on a 4-min observing cycle that allows it to image the full dynamic range in each of its six passbands at least once per cycle, and to observe key passbands for tracking dynamic phenomena more frequently. SUVI can autonomously determine when key calibration observations are needed and diverge temporarily from its operational sequence to obtain them. For most of the year, SUVI observes the Sun continuously. However, at the equinoxes, when Earth’s equatorial plane and the ecliptic are aligned, SUVI’s orbit carries it into Earth’s shadow around the time of local midnight, causing a brief interruption of SUVI observations. However, because there are multiple GOES platforms with identical instrumentation available at different locations around Earth, another SUVI instrument provides continuity of observations at this time.

18.2  SUVI IMAGERY AND LEVEL 1B DATA PRODUCTS 18.2.1  SUVI’s View of the Sun SUVI observes the solar atmosphere to track features that carry a significant risk of space weather impacts. Because these features have a variety of characteristics—most importantly, temperature—that influence their visibility at any single EUV wavelength, SUVI observes in six passbands to allow it to capture the complete range of solar phenomena that can influence space weather. Table 18.1 shows an overview of SUVI’s six passbands, the primary ions they image at various temperatures, and the variety of phenomena that are primarily observed in each passband. We can characterize properties of coronal plasma on the basis of its appearance in each passband thanks to characteristic emission lines that form at different temperatures (O’Dwyer et al., 2010). Very hot plasma, with temperatures approaching 10 million K, will generally be visible only in the passbands most sensitive to highly ionized iron lines that form at these very high temperatures, 94 and 131 Å (and, occasionally, in a secondary line in the



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TABLE 18.1  SUVI Passbands, Temperature Response, and Primary Phenomena Wavelength

94 Å

Primary ions observed Fe xvii

Log T (K)

6.8

131 Å

171 Å

195 Å

284 Å

Fe vii Fe xxia Fe xxiiia

Fe ix Fe x

Fe xi Fe xii Fe xxiva

Fe xv

5.6, 7.05, 7.15

5.85, 6.05

6.15, 6.2, 7.25

6.3

✔

✔

Coronal holes Quiet Sun

✔

✔

He ii 4.7

✔

Filaments and prominences

✔

Active regions

✔

✔

✔

Eruptions

✔

✔

✔

Flares

304 Å

✔

✔

✔

aRThese lines are generally only observed during solar flares.

FIG. 18.4  Temperature response for each of the six SUVI passbands. The response, in radiance cm5 per pixel, tells you the expected radiance recorded in a SUVI channel given the density of emitting plasma, or emission measure, along the line of sight as a function of temperature. (Because EUV emission generally results from collisional excitation, it scales as the density squared, cm−6. Integration along the line of sight transforms this to cm−5, which is the reason the line of sight emission measure has these units.)

195 Å passband). On the other hand, cool chromospheric plasma, with temperatures of a few 10,000 K will only be observed in the 304 Å passband. One widely used technique in solar physics allows us to characterize the amount of material at different temperatures in the corona by combining images from multiple passbands. For each passband, we can compute how much radiance we expect the specific instrument to detect from plasma of given volume and density over a range of temperatures. We refer to this as the instrument’s temperature response function for each passband; Fig. 18.4 shows the response of the six SUVI bands. Comparing the radiance recorded across multiple channels allows us to estimate the amount of material emitting at different temperatures in each pixel of the image. Fig. 18.5 shows an overview of SUVI’s view of the Sun on January 29, 2017, during a relatively quiet period in the solar activity cycle. SUVI data are typically presented in false color to aid data users in recognizing the various spectral components being shown. However, it is worth pointing out that EUV observations have no intrinsic color, rather, the observations record radiance per pixel. SUVI’s 94 and 131 Å channels, which, in general, have the hottest response functions, are most useful for detecting and characterizing the very hot plasma that forms during solar eruptions and flares. (SUVI's 195 Å channel is also sensitive to emission from very high temperature Fe xxiv, which forms around 20 MK, but is very rarely observed outside of the largest solar flares.) Fig. 18.6 (Animation 18.1 in the online version at https://doi.org/10.1016/B9780-12-814327-8.00018-4) shows the evolution of high-temperature plasma from an X8.2 class flare on September 10,

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94 Å

131 Å

171 Å

195 Å

284 Å

304 Å

FIG. 18.5  SUVI images of the Sun in each of the imager’s six passbands showing the variety of phenomena detected in each band from January 29, 2017.

FIG. 18.6  SUVI 131 Å observations of the development of a very powerful X8.2 flare and solar eruption that occurred on September 10, 2017. The spine of hot material, indicated by the arrow in the panel at 16:21:54 UTC, shows where magnetic reconnection is releasing the energy to power the flare and eruption. Animation 18.1 of this figure is available in the online version at https://doi.org/10.1016/B978-0-12-814327-8.00018-4.



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2017, one of the most energetic events of the past solar cycle (Redmon et al., 2018a; Seaton & Darnel, 2018), observed in SUVI’s 131 Å passband. The earliest time shows the preflare conditions, with very little bright 131 Å emissions. At this point, most of the emission we see is from relatively cool Fe xviii emission in the solar transition region. The panels at 15:49:54 and 15:53:54 UTC reveal the onset of the eruption on the Sun’s west (right) limb, with bright emission and complex looplike structures forming as a result of the magnetic reconfiguration associated with this event. The lower three panels show the development of postflare conditions, with a core of very bright, very hot flare plasma in the region where the event occurred, and a bright spine of hot material, likely associated with the process of magnetic reconnection that releases stored magnetic energy that drives the event. (The cross-shaped feature is an artifact caused by diffraction on the mesh that supports the foil filters that block visible light from entering the SUVI telescope.) Fig. 18.7 (Animation 18.2 in the online version at https://doi.org/10.1016/B978-0-12-814327-8.00018-4) shows the same eruption as Fig. 18.6 but in the 195 Å passband, which largely captures plasma at about 1.5 million K. Here we see better the structure of the eruption itself as it rises out of the corona at speeds up to 2000 km/s, and we see how the shockwave it set off disrupted the magnetic structure of the solar corona on global scales over the course of just a few minutes. The 195 Å is also sensitive to a very high-temperature line from Fe xxiv, which forms at about 20 million K. It is likely that some of the emission we detect in the vicinity of the flare itself is actually from this high-­temperature line. These images also reveal a large coronal hole near the Sun’s north pole. In fact, in addition to their influence on space weather, coronal holes can become involved in eruptions as well. In the September 10, 2017 eruption, the coronal hole significantly disrupted the propagation of the strong shockwave from the eruption, even reflecting it back on itself in places. In some cases, a coronal hole can influence the propagation direction of an eruption, pushing the erupting structures away from the hole and the fast solar wind stream emerging from it as it travels into the heliosphere. Thus, images like these that provide the global context for an eruption are of great use in space weather forecasting. Fig. 18.8 shows three co-temporal views of the Sun from March 27, 2017, in the 171, 195, and 284 Å passbands, highlighting the appearance of a coronal hole and an active region in these three bands. These phenomena have different appearances at different temperatures and different heights in the corona. Active regions, which are generally hotter than the bulk corona, have a very clear signature in 284 Å images, which capture plasma around 2 million K. Coronal holes, on the other hand, are most prominent as dark regions in 195 Å images. These images, with a peak temperature around 1.5 million degrees (see Fig. 18.4), capture the most ubiquitous plasma in the corona, so low-­ density regions in coronal holes are very prominent here.

FIG. 18.7  SUVI 195 Å observations of the September 10, 2017 eruption, showing first the onset of the eruption in the million-degree corona, and then the strong shockwave that disrupted the corona as a result of the eruption. The arrow in the panel on image 15:18:24 UTC indicates the direction of solar north. Animation 18.2 of this figure is available in the online version at https://doi.org/10.1016/B978-0-12-814327-8.00018-4.

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171 Å

195 Å

284 Å

FIG. 18.8  Co-temporal SUVI 171, 195, and 284 Å images from March 27, 2017, revealing a large coronal hole extending from the Sun’s south pole to well above the equator (arrow, center panel) and an active region (arrow, right panel).

In 171 Å, which has a temperature response closer to 800,000 K, we see both of these types of features but less prominently. These images are more useful in characterizing the complex, underlying magnetic structure of the corona, particularly coronal loops associated with active regions and the widespread regions of the quiet sun. During active periods, 171 Å images often reveal huge magnetic fans extending out to the edge of the SUVI field of view, hinting at a large-scale connection between the dynamics and structure of the low corona and the extended corona and heliosphere often observed by coronagraphs like the Large Angle Spectroscopic Coronagraph (LASCO; Brueckner et al., 1995) onboard the National Aeronautics and Space Administration’s (NASA’s) Solar and Heliospheric Observatory (SOHO) spacecraft. Coronagraphs use a small disk, or occulter, to create an artificial eclipse and block the bright light from the photosphere, allowing them to observe the extended corona and heliosphere. However, because of the occulter, they do not provide a view of the solar disk or inner corona. The coolest temperature plasma SUVI observes, at about 50,000 K in the 304 Å passband, is largely chromospheric, and is considerably denser than the coronal plasma observed in other SUVI passbands. A consequence of this is that, unlike the optically thin corona, the plasma we observe in the 304 Å passband is not transparent. Sometimes the plasma we observe in this passband obscures other EUV emissions behind it and appears as a dark silhouette in other passbands. This means that 304 Å observations are especially important for interpreting observations of large, dense structures suspended in the corona such as filaments. When filaments and prominences erupt, the 304 Å passband often provides the clearest view of the nascent eruptions and can aid space weather forecasters in making early assessments of the acceleration and density of an eruption. Fig. 18.9 (Animation 18.3 in the online version at https://doi.org/10.1016/B978-0-12-814327-8.00018-4) shows one such eruption, a dramatic one SUVI observed on July 28, 2017. From the images, it is evident that the impressive eruption originated from the backside of the Sun, and was thus directed harmlessly away from Earth. Whether an eruption is Earth-directed or not is not always obvious from coronagraph observations, so observations like these from SUVI are key examples of how SUVI works to complement other observations used by forecasters. The use of multiple instruments and views can help forecasters deduce more about any event than could be learned from any single set of observations.

18.2.2  SUVI Level 1 Data Products SUVI Level 1b files are available in two formats, as netCDF and Flexible Image Transport System (FITS) files. FITS, which dates to the early 1980s, remains the standard file format in astronomy and solar physics and offers a few advantages over netCDF, the most important being its compatibility with large libraries of software in several languages used for astronomical data analysis. FITS image navigation metadata, which provides information about the coordinate system, instrument pointing and rotation, and observation viewpoint, uses a format called the World Coordinate System (WCS). For consistency, SUVI netCDF files also use analogous metadata entries that follow this same system. SUVI L1b image data is reported in units of radiance, or W m−2 sr−1. Radiance tells the observer the amount of flux originating from a solid angle element on the sky in the SUVI passband of interest. One can convert radiance to irradiance, W m−2, or the total flux from the corona measured by SUVI, by integrating the image over its entire angular area. In general, radiance is well correlated with the energy released into the corona by a feature or event, and as a result, is a useful unit to assess the energetic significance of events and features for space weather forecasts. SUVI L1b data provides the first data point for use in forecasting space weather events, so SUVI observations are geared specifically toward operational needs. The field of view, passbands and temperature response, observing



18.3 Level 2 Products

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FIG. 18.9  SUVI 304 Å observations of the development of a prominence eruption that occurred on July 28, 2017. The panel in the lower right shows the relationship between the eruption, seen by SUVI, and simultaneous coronagraph observations from LASCO. SUVI can help resolve possible ambiguity in propagation direction in observations of coronal mass ejections like these. Animation 18.3 of this figure is available in the online version at https://doi.org/10.1016/B978-0-12-814327-8.00018-4.

cadence (and the cadence of each passband), and instrument sensitivity are designed to meet specific operational requirements, particularly during fast dynamic events. However, SUVI data is of great value in basic solar physics research, and the files are widely used by the solar physics research community. Correspondingly, SUVI data conform to all standards required for solar physics research and are expected to be available via interfaces widely used in the solar community, including Helioviewer (https://helioviewer.org/) and the Virtual Solar Observatory (https:// www.virtualsolar.org/).

18.3  LEVEL 2 PRODUCTS SUVI Level 2 products generally serve one of two purposes. Some products synthesize multiple exposures into images with wider dynamic range or better signal-to-noise characteristics than can be obtained in a single SUVI exposure. Others provide context, distilling the types of features in SUVI observations, their locations, and characteristics.

18.3.1  High Dynamic Range Composite Images In several of SUVI’s passbands, the radiance of features in the solar corona spans some six orders of magnitude, from very dark coronal holes to extremely bright solar flares. However, SUVI’s camera, like most CCDs, has a useful dynamic range of only a few orders of magnitude. SUVI gets around this limitation by combining multiple images of different exposures and filter configurations into HDR composite images. These images share many characteristics with SUVI L1b files, but they can span the entire range of radiances observed in the corona. Like SUVI L1b data, HDR composites are delivered in FITS format with most of the same metadata information present in L1b files. Since a SUVI observing cycle lasts 4 min—that is, SUVI captures at least one set of images in each of the six passbands it observes every 4 min— SUVI composite images are generated on a 4-min cycle. Each composite synthesizes all observations for a given passband into a single HDR image. To do this, the composite image algorithm takes a weighted average of each pixel in the SUVI images it is processing. When a pixel in a short exposure records a very bright signal, the corresponding pixels in the long exposure receive zero weight. When a pixel in a long exposure records a faint signal, its short exposure counterparts are discarded. The result is a high-quality,

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FIG. 18.10  SUVI long (left) and short (center) exposure inputs for the composite on the right. The red contour (left) indicates the location where saturated pixels in the long image are replaced by unsaturated pixels in the short image (center).

high signal-to-noise image that can capture the entire dynamic range of the corona regardless of the conditions on the Sun. Fig. 18.10 shows an example of how composites are constructed, using multiple exposures from the same set of observations of the September 10, 2017, X8.2 flare as Fig. 18.6. SUVI HDR composite images are the root product for all of the SUVI L2 products that describe the conditions in the corona.

18.3.2  SUVI Thematic Maps The thematic map product is a FITS file that encodes the prevailing solar conditions in each SUVI pixel in a single image frame. To do this, the thematic map algorithm ingests each of the six SUVI HDR composite images from a given 4-min cycle and applies one of several possible classifier algorithms to determine which solar feature is present in each pixel. One available method uses a maximum likelihood classifier similar to that described in (Rigler et al., 2012; Hughes et al., 2019), where each of the possible classifications is described as a Gaussian Mixture that serves as input to the classifier. To ensure that noise does not contaminate the analysis, a preprocessing step applies a 5 × 5 pixel median filter to the image before analysis. Another available method uses a random forest classifier, which works using a collection of decision trees. Each decision tree has a branching pattern of yes-no decisions based on brightness thresholds for various channels. A multichannel pixel moves from the top of the tree downward, until reaching the bottom of the tree where a theme label is assigned. For example, a pixel in the 171 Å channel with a radiance of 2.0 W m−2 sr−1 might, at some point in the tree, encounter a rule stating that the 171 Å value must be >5. Since, in this case, that statement is false, the pixel continues down the tree to the left, whereas if the statement were true the pixel would branch to the right. These branching rules and theme assignments are learned beforehand by an algorithm using expert-created thematic maps and their associated SUVI images. The random forest, being an ensemble of many trees, more robustly classifies values than either a single tree or, generally speaking, Gaussian classifiers (Hughes et al., 2019). During this process, an optional synthetic channel can be used to help identify the location of the solar limb, where the long line of sight of the observation can pass through multiple features and create confusion for the classifier. After processing, each solar feature is denoted with a specific integer value in the thematic map, which can then be used to generate maps of the changing conditions in the corona, such as those in Fig. 18.11. There are seven solar classifications tracked by the thematic maps algorithm, all of which are described in Section 18.1.1: quiet sun, coronal hole, solar limb, filaments, prominences, bright regions, and flares. An additional category called outer space records regions at large heights in the corona where no coronal signal is detected. The thematic maps algorithm also supports an unlabeled category, which is generally reserved for files used for expert training inputs for the algorithm.

18.3.3  Bright Region, Flare Location, and Coronal Hole Reports The SUVI bright region, flare location, and coronal hole reports are netCDF files that distill thematic maps into reports that track the location and characteristics of features in the corona with important space weather impacts. These reports cluster the feature identified in thematic maps to isolate the location of the feature of interest in SUVI composite image files, and then reports on the characteristics, such as radiance, of these regions and their locations in heliographic coordinates.



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18.3 Level 2 Products

Bright region

Flare

Coronal hole

Limb

Quiet sun Outer space

Filament

Prominence

Unlabeled

FIG. 18.11  SUVI 195 and 304 Å images (left and center, respectively) and the corresponding thematic map (right) identifying key regions on the Sun.

The bright region report characterizes the location and radiance of bright regions. The locations of bright regions are important because these regions are often the sources of powerful solar eruptions, and their location can determine the geoeffectiveness of the events they spawn. Their radiance is important because changing EUV solar irradiance due to bright regions is a primary driver of the expansion of the upper atmosphere, which can cause drag on spacecraft in low Earth orbit. These products include an entry for each unique bright region in the SUVI thematic maps product and, when possible, associate these regions with National Oceanic and Atmospheric Administration (NOAA) Active Region numbers that are tracked for all sunspot groups observed by SWPC forecasters. The flare location report is similar to the bright region report, but it also uses data from the X-ray Sensor (XRS) on the EXIS instrument (Chapter 19), which helps classify solar flares. This report provides the location, area, and flux of flares detected in the SUVI thematic maps, and, when possible, associates SUVI-detected events with their EXISderived flare counterparts. The coronal hole location product provides the locations of coronal hole boundaries detected in SUVI thematic maps. Unlike the two products above, instead of just the centroid of the feature of interest, the product provides a path describing the boundaries of coronal holes in heliographic coordinates. Knowledge of coronal hole boundaries is particularly important for space weather forecasting because coronal hole location is closely correlated with the presence of high-speed solar wind streams that can induce space weather effects at Earth.

18.3.4  Other Image-Based SUVI L2 Products In addition to HDR composite images, there are several additional image-based SUVI L2 products that can help provide valuable inputs for forecasters. All are provided in FITS format similar to the SUVI HDR composite images. Running difference images reveal how the corona has changed between two composite images. To generate these images, the algorithm computes the difference between the most recent SUVI composite in each passband and the second most recent composite. If a region of the corona has brightened, it will have a positive signal in the ­running-difference image, while regions that have darkened (due to a coronal dimming, for example) will show a negative signal. Regions that are stable will have a signal near zero, thus this product can help forecasters hone in on dynamic features in the corona. Fixed difference images are similar to running difference images but rather than a real-time running measure of dynamics, they compare the state of the corona throughout an event to the state of the corona at the onset of the event. This algorithm is triggered by the EXIS XRS flare detection algorithm, and runs throughout the duration of a solar flare, using the flare start time as the epoch image. Because the Sun can potentially rotate a considerable amount in the duration of an event, this algorithm uses an image transformation routine that keeps each pixel aligned to the corresponding pixel in the epoch image throughout the event. Coronal hole images provide high signal-to-noise composites that can be used to track details of very dark coronal features such as coronal holes. The algorithm that produces these composites uses the same approach as the HDR composite algorithm but works on a full hour of data at a time rather than 4 min. This algorithm also corrects for the rotation of the Sun using the same image transformation scheme as described above. In principle, all of these image products can drive the generation of movies, which allow visual tracking of changing features that is not possible in static images. A movie generation tool and movie files derived from these images will be available to SUVI data users. SUVI data and additional information are available via https://doi.org/10.7289/V5FT8J93. Product user guides and additional information can be found at the NOAA NCEI website https://www.ngdc.noaa.gov/stp/satellite/goes-r. html. Additional documents and user resources can be found at the GOES-R Series website https://www.goes-r.gov/.

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Acknowledgments We extend a special thanks to Elke D’Huys of the Royal Observatory of Belgium for her thorough review of this article. Thanks to Scott McIntosh of the High Altitude Observatory for his assistance in assembling Fig. 18.1. The SUVI instruments were built at the Lockheed Martin Advanced Technology Center in Palo Alto, California. The authors thank Chris Edwards, Dnyanesh Mathur, David Sabolish, Ralph Seguin, Margaret Shaw, Lawrence Shing, Greg Slater, and Gopal Vasudevan for support throughout SUVI’s commissioning and calibration process, and for sharing their considerable knowledge of the instrument’s operation and performance. Thanks also to Steven Hill of NOAA’s Space Weather Prediction Center for support and assistance in SUVI’s integration into operations. Thanks to the GOES-R Program for support and assistance with a variety of aspects of the SUVI mission. The work at CIRES was supported by the GOES-R Program and the NCEI through NOAA Cooperative Agreements NA15OAR4320137 and NA17OAR4320101.

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