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Since radio propagation measurements using either natural or spacecraft radio signals are essentially our only means for probing the solar wind in the vicinity of the Sun, they represent a key tool for studying the interplanetary consequences of solar structure and dynamic phenomena.
The paper will develop the background and information necessary to explain what a sun-synchronous orbit is how it works. Handy back of the envelope equations will be provided to enable the mission analyst and system engineer to do quick and simple calculations for the orbit parameters selection and to compute mission parameters important to satellite design without having to resort to sophisticated computer programs.
Highly sensitive radio occultation and white light measurements of path-integrated density have shown that the solar corona comprises three distinct morphological regions, streamer, quiet Sun, and polar coronal hole, which except for the streamer region, extend radially into interplanetary space from 1.15 R***s*** to at least 30 R***s***. The authors build on these results by comparing solar wind flow speeds observed at the same time as path-integrated density.
Project SUN was initiated via a small grant from NASA's Mission to Planet Earth. It was designed to be an educational program that was driven by scientific requirements.
The Solar Polar Sail Mission uses solar-sail propulsion to place a spacecraft in a circular orbit 0.48 AU from the Sun with an inclination of 90 °.
NASA’s Deep Space Network (DSN) recently underwent a paradigm shift in its operations approach called Follow the Sun Operations (FtSO) in an effort to increase efficiency for forthcoming expansion of the network. This change requires each Deep Space Communications Complex (DSCC) to remotely control the other two complexes’ antennas during their local day shift, in contrast to locally controlling only their own antennas 24x7. Remote operations increases the workload of each complex during their day shift, specifically that of the Link Control Operators (LCOs), and presents a new challenge for planning and managing the distribution of responsibility for each link. A new DSN software assembly, the Link Complexity and Maintenance (LCM) software, was developed to support workload management for LCOs, as well as for planning site-local maintenance activities. The LCM deployment was a vital part of the transition to FtSO in November 2017. This paper discusses the architecture of LCM, its feature set, and lessons learned during its development and rollout.
We present the direct imaging discovery of a substellar companion to the nearby Sun-like star, HD 33632 Aa, at a projected separation of ∼20 au, obtained with SCExAO/CHARIS integral field spectroscopy complemented by Keck/NIRC2 thermal infrared imaging. The companion, HD 33632 Ab, induces a 10.5σ astrometric acceleration on the star as detected with the Gaia and Hipparcos satellites. SCExAO/CHARIS JHK (1.1–2.4 μm) spectra and Keck/NIRC2 L(sub p) (3.78 μm) photometry are best matched by a field L/T transition object: an older, higher-gravity, and less dusty counterpart to HR 8799 cde. Combining our astrometry with Gaia/Hipparcos data and archival Lick Observatory radial velocities, we measure a dynamical mass of 46.4 ± 8 MJ and an eccentricity of e < 0.46 at 95% confidence. HD 33632 Ab’s mass and mass ratio (4.0% ± 0.7%) are comparable to the low-mass brown dwarf GJ 758 B and intermediate between the more massive brown dwarf HD 19467 B and the (near-)planet-mass companions to HR 2562 and GJ 504. Using Gaia to select for direct imaging observations with the newest extreme adaptive optics systems can reveal substellar or even planet-mass companions on solar system–like scales at an increased frequency compared to blind surveys
The Aerosol Robotic Network (AERONET) has provided highly accurate, ground-truth measurements of the aerosol optical depth (AOD) using Cimel Electronique Sun–sky radiometers for more than 25 years. In Version 2 (V2) of the AERONET database, the near-real-time AOD was semiautomatically quality controlled utilizing mainly cloud-screening methodology, while additional AOD data contaminated by clouds or affected by instrument anomalies were removed manually before attaining quality-assured status (Level 2.0). The large growth in the number of AERONET sites over the past 25 years resulted in significant burden to the manual quality control of millions of measurements in a consistent manner. The AERONET Version 3 (V3) algorithm provides fully automatic cloud screening and instrument anomaly quality controls. All of these new algorithm updates apply to near-real-time data as well as post-field-deployment processed data, and AERONET reprocessed the database in 2018. A full algorithm redevelopment provided the opportunity to improve data inputs and corrections such as unique filter-specific temperature characterizations for all visible and near-infrared wavelengths, updated gaseous and water vapor absorption coefficients, and ancillary data sets. The Level 2.0 AOD quality-assured data set is now available within a month after post-field calibration, reducing the lag time from up to several months. Near-real-time estimated uncertainty is determined using data qualified as V3 Level 2.0 AOD and considering the difference between the AOD computed with the pre-field calibration and AOD computed with pre-field and post-field calibration. This assessment provides a near-real-time uncertainty estimate for which average differences of AOD suggest a +0.02 bias and one sigma uncertainty of 0.02, spectrally, but the bias and uncertainty can be significantly larger for specific instrument deployments. Long-term monthly averages analyzed for the entire V3 and V2 databases produced average differences (V3–V2) of +0.002 with a ±0.02 SD (standard deviation), yet monthly averages calculated using time-matched observations in both databases were analyzed to compute an average difference of −0.002 with a ±0.004 SD. The high statistical agreement in multiyear monthly averaged AOD validates the advanced automatic data quality control algorithms and suggests that migrating research to the V3 database will corroborate most V2 research conclusions and likely lead to more accurate results in some cases.
The Earth’s magnetosphere is region that is carved out by the solar wind as it flows past and interacts with the terrestrial magnetic field. The inner magnetosphere is the region that contains the plasmasphere, ring current, and the radiation belts all co-located within about 6.6 Re, nominally taken to be bounding this region. This region is highly dynamic and is home to a variety of plasma waves and particle populations ranging in energy from a few eV to relativistic and ultra-relativistic electrons and ions. The interplanetary magnetic field (IMF) embedded in the solar wind via the process of magnetic reconnection at the sub-solar point sets up plasma convection and creates the magnetotail. Magnetic reconnection also occurs in the tail and is responsible for explosive phenomena known as substorms. Substorms inject low-energy particles into the inner magnetosphere and help generate and sustain plasma waves. Transients in the solar wind such as coronal mass ejections (CMEs), co-rotating interaction regions (CIRs), and interplanetary shocks compress the magnetosphere resulting in geomagnetic storms, energization, and loss of energetic electrons in the outer radiation belt and enhance the ring current, thereby driving the geomagnetic dynamics. The Specification and Prediction of the Coupled Inner-Magnetospheric Environment (SPeCIMEN) is one of the four elements of VarSITI (Variability of the Sun and Its Terrestrial Impact) program which seeks to quantitatively predict and specify the inner magnetospheric environment based on Sun/solar wind driving inputs. During the past 4 years, the SPeCIMEN project has brought together scientists and researchers from across the world and facilitated their efforts to achieve the project goal. This review provides an overview of some of the significant scientific advances in understanding the dynamical processes and their interconnectedness during the VarSITI era. Major space missions, with instrument suites providing in situ measurements, ground-based programs, progress in theory, and modeling are briefly discussed. Open outstanding questions and future directions of inner magnetospheric research are explored.
Computational heliophysics has shed light on the fundamental physical processes inside the Sun, such as the differential rotation, meridional circulation, and dynamo-generation of magnetic fields. However, despite the substantial advances, the current results of 3D MHD simulations are still far from reproducing helioseismic inferences and surface observations. The reason is the multi-scale nature of the solar dynamics, covering a vast range of scales, which can-not be solved with the current computational resources. In such a situation, significant progress has been achieved by the mean-field approach, based on the separation of small-scale turbulence and large-scale dynamics. The mean-field simulations can reproduce solar observations, qualitatively and quantitatively, and uncover new phenomena. However, they do not reveal the complex physics of large-scale convection, solar magnetic cycles, and the magnetic self-organization that causes sunspots and solar eruptions. Thus, developing a synergy of these approaches seems to be a necessary but very challenging task.
Despite drastically different plasma conditions in the two systems, eruptive energy release events in solar active regions and in Earth’s magnetosphere have a lot in common. Both solar active region eruptions and the substorm activity in the nightside magnetosphere are known to be associated with an abrupt large-scale reorganization of the supporting magnetic systems enabling the conversion and dissipation of the stored free magnetic energy. The rate of energy accumulation in either system tends to be by orders of magnitude slower than the energy release rate, leading to the formation of an impulsive loading-unloading cycle involving a relatively long pre-reconnection phase (substorm growth phase, pre-flare stressing of an active region magnetic field), a short and explosive reconnection phase (substorm breakup and expansion, eruptive flares and CMEs), and a prolonged post-reconnection phase (substorm recovery phase and the post-flare active region reconfiguration). In Earth’s magnetosphere, this loading-unloading cycle is diagnosed by monitoring characteristic changes in the particle precipitation pattern in the northern and southern auroral ovals marking the boundary between the open and close magnetic flux. The position, shape, structure, and dynamics of the auroral borealis were shown to communicate critically important information about an upcoming substorm, the location and timing of the initial reconnection onset, and the subsequent return of the magnetosphere to a lower-energy state. On the Sun, a similar role is played by the chromospheric flare ribbons which enable a detailed diagnostics of the overlying reconnecting magnetic field. In this talk, we’ll discuss similarities and differences in using auroral and flare ribbon observations for monitoring eruptive energy release in respectively Earth’s magnetosphere and solar corona. Special emphasis will be placed on the quantitative interpretation of the two types of optical signatures for empirical diagnostics of the underlying reconnection activity and for constraining its theoretical models. We’ll also compare forecasting capabilities of the two types of optical signatures in the context of space weather prediction objectives.
Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments (e.g., coarse mode sea salt and dust versus fine mode terrestrial anthropogenic emissions, biomass burning, and maritime secondary production). For the years 2016 through 2019, we performed an analysis of 550 nm total AOD550, fine mode AOD (FAOD550; also known as FM AOD in the literature), coarse mode AOD (CAOD550), and fine mode fraction (η550) between Moderate Resolution Spectral Imaging Radiometer (MODIS) V6.1 MOD/MYD04 dark target aerosol retrievals and the International Cooperative for Aerosol Prediction (ICAP) core four multi-model consensus (C4C) of analyses/short term forecasts that assimilate total MODIS AOD550. Differences were adjudicated by the global shipboard Maritime Aerosol Network (MAN) and selected island AERONET sun photometer observations with the application of the spectral deconvolution algorithm (SDA). Through a series of conditional and regional analyses, we found divergence included regions of terrestrial influence and latitudinal dependencies in the remote oceans. Notably, MODIS and the C4C and its members, while having good correlations overall, have a persistent +0.04 to +0.02 biases relative to MAN and AERONET for typical AOD550 values (84th% < 0.28), with the C4C underestimating significant events thereafter. Second, high biases in AOD550 are largely associated with the attribution of the fine mode in satellites and models alike. Thus, both MODIS and C4C members are systematically overestimating AOD550 and FAOD550 but perform better in characterizing the CAOD550. Third, for MODIS, findings are consistent with previous reports of a high bias in the retrieved Ångström Exponent, and we diagnosed both the optical model and cloud masking as likely causal factors for the AOD550 and FAOD550 high bias, whereas for the C4C, it is likely from secondary overproduction and perhaps numerical diffusion. Fourth, while there is no wind-speed-dependent bias for surface winds <12 m s−1, the C4C and MODIS AOD550s also overestimate CAOD550 and FAOD550, respectively, for wind speeds above 12 m/s. Finally, sampling bias inherent in MAN, as well as other circumstantial evidence, suggests biases in MODIS are likely MODIS and the C4C products have their own strengths and challenges for a given climate application and discuss needed research. even larger than what was diagnosed here. We conclude with a discussion on how
Jupiter’s core is generally assumed to have formed beyond the snow line. Here we consider an alternative scenario, that Jupiter’s core may have accumulated in the innermost parts of the protoplanetary disk. A growing body of research suggests that small particles (“pebbles”) continually drift inward through the disk. If a fraction of drifting pebbles is trapped at the inner edge of the disk a several Earth-mass core can quickly grow. Subsequently, the core may migrate outward beyond the snow line via planet-disk interactions. Of course, to reach the outer Solar System Jupiter’s core must traverse the terrestrial planet-forming region. We use N-body simulations including synthetic forces from an underlying gaseous disk to study how the outward migration of Jupiter’s core sculpts the terrestrial zone. If the outward migration is fast (τ(sub mig) ∼ 10(exp 4) years), the core simply migrates past resident planetesimals and planetary embryos. However, if its migration is slower (τ(sub mig) ∼ 10(exp 5) years) the core removes solids from the inner disk by shepherding objects in mean motion resonances. In many cases the disk interior to 0.5-1 AU is cleared of embryos and most planetesimals. By generating a mass deficit close to the Sun, the outward migration of Jupiter’s core may thus explain the absence of terrestrial planets closer than Mercury. Jupiter’s migrating core often stimulates the growth of another large (∼ Earth-mass) core – that may provide a seed for Saturn’s core – trapped in exterior resonance. The migrating core also may transport a fraction of terrestrial planetesimals, such as the putative parent bodies of iron meteorites, to the asteroid belt.
We present the direct-imaging discovery of a substellar companion in orbit around a Sun-like star member of the Hyades open cluster. So far, no other substellar companions have been unambiguously confirmed via direct imaging around main-sequence stars in Hyades. The star HIP 21152 is an accelerating star as identified by the astrometry from the Gaia and Hipparcos satellites. We detected the companion, HIP 21152 B, in multiple epochs using the high-contrast imaging from SCExAO/CHARIS and Keck/NIRC2. We also obtained the stellar radialvelocity data from the Okayama 188 cm telescope. The CHARIS spectroscopy reveals that HIP 21152 B’s spectrum is consistent with the L/T transition, best fit by an early T dwarf. Our orbit modeling determines the semimajor axis and the dynamical mass of HIP 21152 B to be 17 +7.2 −3.8 and 27.8 +8.4 −5.4 M Jub , respectively. The mass ratio of HIP 21152 B relative to its host is ≈2%, near the planet/brown dwarf boundary suggested by recent surveys. Mass estimates inferred from luminosity-evolution models are slightly higher (33–42 MJup). With a dynamical mass and a well-constrained age due to the system’s Hyades membership, HIP 21152 B will become a critical benchmark in understanding the formation, evolution, and atmosphere of a substellar object as a function of mass and age. Our discovery is yet another key proof of concept for using precision astrometry to select direct-imaging targets.
Gamma-ray emission from solar eruptions can last far beyond the impulsive phase of the associated flares, and hence termed as sustained gamma-ray emission (SGRE). These gamma-rays result from the decay of neutral pions produced when >300 MeV protons collide with hydrogen and heavier elements in the solar photosphere. The source of protons producing SGRE has two possible origins: (i) particles accelerated in the associated flare are somehow trapped in magnetic structures and diffuse slowly to the chromosphere, and (ii) particles accelerated at the shock front that diffuse back to the Sun. In this presentation, we compile currently available observations and inferences that support these two possibilities. We use the gamma-ray data from the Fermi Large Area Telescope (Fermi/LAT) in conjunction with coronal mass ejection (CME) data from the Solar and Heliospheric Observatory (SOHO) and type II radio burst information from the Wind spacecraft. We also use the GOES soft X-ray flare information.
A hyperspectral field sensor (FloX) was installed in Adventdalen (Svalbard, Norway) in 2019 as part of the Svalbard Integrated Arctic Earth Observing System (SIOS) for monitoring vegetation phenology and Sun-Induced Chlorophyll Fluorescence (SIF) of high-Arctic tundra. This northernmost hyperspectral sensor is located within the footprint of a tower for long-term eddy covariance flux measurements and is an integral part of an automatic environmental monitoring system on Svalbard (AsMovEn), which is also a part of SIOS. One of the measurements that this hyperspectral instrument can capture is SIF, which serves as a proxy of gross primary production (GPP) and carbon flux rates. This paper presents an overview of the data collection and processing, and the 4-year (2019–2021) datasets in processed format are available at: https://thredds.met.no/thredds/catalog/arcticdata/infranor/NINA-FLOX/raw/catalog.html associated with https://doi.org/10.21343/ZDM7-JD72 under a CC-BY-4.0 license. Results obtained from the first three years in operation showed interannual variation in SIF and other spectral vegetation indices including MERIS Terrestrial Chlorophyll Index (MTCI), EVI and NDVI. Synergistic uses of the measurements from this northernmost hyperspectral FLoX sensor, in conjunction with other monitoring systems, will advance our understanding of how tundra vegetation responds to changing climate and the resulting implications on carbon and energy balance.
Many questions remain about the compressibility of solar wind turbulence with respect to its origins and properties. Low plasma beta (ratio of thermal to magnetic pressure) environments allow for the easier generation of compressible turbulence, enabling study of the relationship between density fluctuations and turbulent Mach number. Utilizing Parker Solar Probe plasma data, we examine the normalized proton density fluctuations as a function of turbulent Mach number M t conditioned on plasma beta and cross helicity. With consideration of statistical error in the parameters computed from in situ data, we find a general result consistent with both linear-wave theory and nearly incompressible turbulence in an inhomogeneous background field. We compare observational results conditioned on plasma beta and cross helicity with 3D magnetohydrodynamic simulations and observe rather significant similarities with respect to how those parameters affect the proportionality between density fluctuations and turbulent Mach number. This study further investigates the complexity of compressible turbulence as viewed by the density scaling relationship and may help better understand the compressible environment of the near-Sun solar wind.
The main problems with understanding and predicting solar activity are tightly linked to limitations in describing the global evolution of the Sun from the deep interior to the corona. Because of the complexity of interactions in a wide range of dynamical, turbulent, and spatial scales and dramatic changes in thermodynamic and magnetic field conditions, only physics-based models can provide essential background to generate reliable solar activity forecasts. However, performing accurate model calibration and estimating uncertainties is often challenging due to the unavailability of a long time series of observations. To mitigate these limitations, we have developed the Global Solar Activity (GSA) Data Portal, which enables convenient access to a variety of modern and historical data. The portal supports a dynamic visualization for 1D time series (such as the sunspot number and solar irradiance) and quick-look visualization for 2D datasets (e.g., synoptic magnetograms, the solar internal rotation, and flows). The GSA portal includes a search engine that enables data retrieval from user-specified data sources and time intervals. In this presentation, we will discuss the current and upcoming capabilities of the data portal and its potential applications for space weather studies.