Extending the Atmospheric River Concept to Aerosol and Trace Gas Transports
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Wong, Corisa↗
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A Layered Debris Disk around M Star TWA 7 in Scattered Light
We have obtained Hubble Space Telescope (HST) coronagraphic observations of the circumstellar disk around M star TWA 7 using the Space Telescope Imaging Spectrograph (STIS) instrument in visible light. Together with archival observations, including HST/NICMOS using the F160W filter and Very Large Telescope/SPHERE at the H-band in polarized light, we investigate the system in scattered light. By studying this nearly face-on system using geometric disk models and Henyey–Greenstein phase functions, we report a new discovery of a tertiary ring and a clump. We identify a layered architecture: three rings, a spiral, and an ≈150 au 2 elliptical clump. The most extended ring peaks at 28 au, and the other components are on its outskirts. Our point-source detection-limit calculations demonstrate the necessity of disk modeling in imaging fainter planets. Morphologically, we witness a clockwise spiral motion, and the motion pattern is consistent with both solid body motion and local Keplerian motion; we also observe underdensity regions for the secondary ring that might result from mean-motion resonance or moving shadows: both call for re-observations to determine their nature. Comparing multi-instrument observations, we obtain blue STIS-NICMOS color, a STIS-SPHERE radial distribution peak difference for the tertiary ring, and a high SPHERE-NICMOS polarization fraction; these aspects indicate that TWA 7 could retain small dust particles. By viewing the debris disk around M star TWA 7 at a nearly face-on vantage point, our study allows for the understanding of such disks in scattered light in both system architecture and dust property.
Debris disks↗
The Apparent Absence of Forward Scattering in the HD 53143 Debris Disk
HD 53143 is a mature Sun-like star and host to a broad disk of dusty debris, including a cold outer ring of planetesimals near 90 au. Unlike most other inclined debris disks imaged at visible wavelengths, the cold disk around HD 53143 appears as disconnected "arcs" of material, with no forward-scattering side detected to date. We present new, deeper Hubble Space Telescope Imaging Spectrograph coronagraphic observations of the HD 53143 debris disk and show that the forward-scattering side of the disk remains undetected. By fitting our KLIP-reduced observations via forward modeling with an optically thin disk model, we show that fitting the visible wavelength images with an azimuthally symmetric disk with unconstrained orientation results in an unphysical edge-on orientation that is at odds with recent ALMA observations, while constraining the orientation to that observed by ALMA results in nearly isotropically scattering dust. We show that the HD 53143 host star exhibits significant stellar variations due to spot rotation and revisit age estimates for this system.
Christopher C Stark↗
CME Propagation Through the Heliosphere: Status and Future of Observations and Model Development
The ISWAT (International Space Weather Action Teams) heliosphere clusters H1 and H2 have a focus on interplanetary space and its characteristics, especially on the large-scale co-rotating and transient structures impacting Earth. Solar wind stream interaction regions, generated by the interaction between high-speed solar wind originating in large-scale open coronal magnetic fields and slower solar wind from closed magnetic fields, are regions of compressed plasma and magnetic field followed by high-speed streams that recur at the ~27 day solar rotation period. Short-term reconfigurations of the lower coronal magnetic field generate flare emissions and provide the energy to accelerate enormous amounts of magnetised plasma and particles in the form of coronal mass ejections into interplanetary space. The dynamic interplay between these phenomena changes the configuration of interplanetary space on various temporal and spatial scales which in turn influences the propagation of individual structures. While considerable efforts have been made to model the solar wind, we outline the limitations arising from the rather large uncertainties in parameters inferred from observations that make reliable predictions of the structures impacting Earth difficult. Moreover, the increased complexity of interplanetary space as solar activity rises in cycle 25 is likely to pose a challenge to these models. Combining observational and modeling expertise will extend our knowledge of the relationship between these different phenomena and the underlying physical processes, leading to improved models and scientific understanding and more-reliable space-weather forecasting. The current paper summarizes the efforts and progress achieved in recent years, identifies open questions, and gives an outlook for the next 5–10 years. It acts as basis for updating the existing COSPAR roadmap by Schrijver et al. (2015), as well as providing a useful and practical guide for peer-users and the next generation of space weather scientists.
Space weather↗
The Circulation of the Plasmasphere Fluid during the Erosion Event on September 8, 2017
A strong solar wind pressure pulse triggered the magnetic storm on September 7, 2017. Near the end of September 7, the z-component of the interplanetary magnetic field (IMF Bz) dropped from 9 to -10 nT in 30 min. The IMF Bz remained at the level of -10 nT for 2 hours and then had another rapid drop to -31 nT in 30 min. The sudden plunge of IMF Bz and the associated strong convection electric field stirred up the storm main phase with Dst falling from 0 to -122 nT from 2200 UT on September 7 to 0200 UT on the 8th. Severe plasmasphere erosion was observed on September 8 by multiple spacecraft, such as the Van Allen Probes and the Arase satellite. In this study, we examine the fate of the eroded plasmasphere particles during this event by model simulation as well as satellite data analysis. The simulation tool we use is the Space Weather Modeling Framework (SWMF)/Block-Adaptive Tree Solarwind Roe-type Upwind Scheme (BATS-R-US) model coupled with the Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model. One of the distinctive capabilities of the SWMF/BATSRUS-CIMI model is that it treats the cold plasmas in the plasmasphere as a separate fluid in the MHD equations. As a result, the transport and circulation of the plasmasphere fluid in the global magnetosphere can be traced and the impacts of this cold fluid on the global magnetosphere can be evaluated. In this paper, we will show how the drainage plume is formed during the storm and how the plasmasphere fluid is transported to the flank and lobe regions and eventually to the plasma sheet and reenters into the plasmasphere. We will validate our simulation by plasmasphere signatures observed in both the inner and outer magnetosphere.
Mei-Ching Fok↗
The optimization of model ensemble composition and size can enhance the robustness of crop yield projections
Linked climate and crop simulation models are widely used to assess the impact of climate change on agriculture. However, it is unclear how ensemble configurations (model composition and size) influence crop yield projections and uncertainty. Here, we investigate the influences of ensemble configurations on crop yield projections and modeling uncertainty from Global Gridded Crop Models and Global Climate Models under future climate change. We performed a cluster analysis to identify distinct groups of ensemble members based on their projected outcomes, revealing unique patterns in crop yield projections and corresponding uncertainty levels, particularly for wheat and soybean. Furthermore, our findings suggest that approximately six Global Gridded Crop Models and 10 Global Climate Models are sufficient to capture modeling uncertainty, while a cluster-based selection of 3-4 Global Gridded Crop Models effectively represents the full ensemble. The contribution of individual Global Gridded Crop Models to overall uncertainty varies depending on region and crop type, emphasizing the importance of considering the impact of specific models when selecting models for local-scale applications. Our results emphasize the importance of model composition and ensemble size in identifying the primary sources of uncertainty in crop yield projections, offering valuable guidance for optimizing ensemble configurations in climate-crop modeling studies tailored to specific applications.
Agriculture↗
Toward High-Endurance Nonvolatile Reconfigurable Metasurfaces
The applications of adaptive optics extend across multiple sectors, encompassing areas such as LiDAR, biological and chemical sensing, and free-space optical communications. The advent of metasurfaces optics with reconfigurability has offered a versatile platform for the design of compact optical components, offering a compelling alternative to their conventional bulky counterparts. In this study, we introduce the PROWESS (Phase change Reconfigurable Optical WavEfront Synthesis System project at NASA LaRC), electrically reconfigurable metasurfaces using low-loss, high-contrast phase change material (PCM), Ge2Sb2Se4Te integrated with IR-transparent silicon microheater for various practical applications. The talk covers a reliable platform for switching large-scale PCM-based devices utilizing a microheater and an architecture for the metasurface switching within an integrated circuit configuration, which is compatible with standard foundry fabrication processes. The utilization of near- to midinfrared transparent silicon microheater in the proposed architecture opens possibilities for the development of reconfigurable transmissive optics such as filters, zoom lenses, and beam steering modules. We demonstrated switching of 140 µm × 140 µm PCM pixel, on a 200 µm × 200 µm silicon microheater for several thousand cycles. Further, we performed an in-depth investigation into the failure mechanism utilizing techniques such as transmission electron microscopy and thermal modeling. Guidelines for device performance improvement are proposed, and an improved design with larger endurance is shown in progress. With further progress, we aim to unlock the full potential of PCM-based devices and advance the field of adaptive optics with demonstrable examples including a reconfigurable beam steerer for ocean surface flash LiDAR and Navigation Doppler LiDAR for precise lunar landing missions.
metasurface optics↗
Toward Accurate Thermal Modeling of Phase Change Material Based Photonic Devices
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Kiumars Aryana↗
Sources of Formaldehyde in U.S. Oil and Gas Production Regions
We analyzed observational and model data to study the sources of formaldehyde over oil and gas production regions and to investigate how these observations may be used to constrain oil and gas VOC emissions. The analysis of aircraft and satellite data consistently found that formaldehyde over oil and gas production regions during spring and summer is mostly formed by the photooxidation of precursor VOCs. Formaldehyde columns over the Permian basin, one of the largest oil and gas producing regions in the United States, are correlated with production locations. Formaldehyde simulations by the atmospheric chemistry and transport model WRF-Chem, which included oil and gas NOx and VOC emissions from the fuel-based oil and gas inventory, were in very good agreement with TROPOMI satellite measurements. Sensitivity studies illustrated that VOCs released from oil and gas activities are important precursors to formaldehyde, but other sources of VOCs contribute as well, and that the formation of secondary formaldehyde is highly sensitive to NOx. We also investigated the ability of the chemical mechanism used in WRF-Chem to represent formaldehyde formation from oil and gas hydrocarbons by comparing against the Master Chemical Mechanism. Further, our work provides estimates of primary formaldehyde emissions from oil and gas production activities, with per basin averages ranging from 0.07 kg h -1 to 2.2 kg h -1 in 2018. A separate estimate for natural gas flaring found that flaring emissions could contribute 5% to 12% to the total primary formaldehyde emissions for the Permian basin in 2018.
SAF↗
Ionospheric Response to Electron Precipitation Driven by Whistler-Mode Chorus Waves Measured by Arase Satellite and Simulated by STET and SPEAH-RIT
The origin of pulsating auroras has long been an open question. Arase satellite observation reported the direct evidence that precipitated electrons in pulsating aurora are driven by whistler-mode chorus wave activity. Our study presents the theoretical analysis of this observational event based on SuperThermal Electron Transport (STET) code that simulates the highly dynamic environment of measured wave intensities and particle fluxes. Specifically, the STET code simulated results confirm the delicate loss-cone observation results of this mission and reveal the broader energy range of precipitated electron fluxes that were not measurable by Arase satellite. These highly dynamic precipitating electron fluxes were applied to a newly developed code, the Superthermal Proton, Electron and Atomic Hydrogen tRansport in the Ionosphere and Thermosphere (SPEAH-RIT), to simulate ionospheric response of this phenomena, in particular, the enhancement of electron density, plasma temperatures, and ionospheric electric conductance at the footprints of Arase satellite.
George V. Khazanov↗
The Circulation of the Plasmasphere Fluid during the Erosion Event on September 8, 2017
A strong solar wind pressure pulse triggered the magnetic storm on September 7-8, 2017. Near the end of September 7, the z-component of the IMF Bz dropped from 9 to -10 nT in 30 min and then had another rapid drop to -31 nT in 30 min. The sudden plunge of IMF Bz and the associated strong convection electric field stirred up the storm main phase with Dst falling from 0 to -122 nT from 2200 UT on September 7 to 0200 UT on the 8th. Severe plasmasphere erosion was observed on September 8 by multiple spacecraft, such as the Van Allen Probes and the Arase satellite. In this study, we examine the fate of the eroded plasmasphere particles during this event by model simulation as well as satellite data analysis. The simulation tool we use is the SWMF/BATS-R-US model coupled with the CIMI model. The cold plasmas in the plasmasphere is treated as a separate fluid in the MHD equations. As a result, the transport and circulation of the plasmasphere fluid in the global magnetosphere can be traced and the impacts of this cold fluid on the global magnetosphere can be evaluated. In this paper, we will show how the drainage plume is formed during the storm and how the plasmasphere fluid is transported to the flank and lobe regions and eventually to the plasma sheet and reenters into the inner magnetosphere. We will validate our simulation by plasmasphere signatures observed in both the inner and outer magnetosphere.
Mei-Ching Fok↗
A Review on Sensor Spatial Resolution and A Proposal on Grid Pixel Sizing
Sensor spatial resolution (SSR) is a determining factor in developing remote sensing instruments for earth observations. The SSR is defined as the full width at half maximum (FWHM) of sensor point/line spread function (PSF/LSF). This presentation first discusses large variations in image absolute SSR and SSR ratios to ground sampling distance (GSD) or grid pixel size from multiple instruments including AVHRR (Advanced Very-High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), WorldView and Planet. When the physics based SSR is more than twice the nominal grid pixel size, a more appropriate grid pixel size is proposed.
Guoqing (Gary) Lin↗
The Electron Heat Fluxes Associated with Electron Precipitation in the Region of Diffuse Aurora
Electron heat flux that comes from the magnetosphere to the upper ionospheric altitudes controls the value of electron temperature in the core plasma, and, as a result, the total electron density content that is required for different kinds of space weather applications. Knowing the thermal electron heat flux at the upper ionospheric boundaries is the Achilles' heel of all ionospheric models. Such a thermal heat flux setting is especially difficult to justify in the region of the diffuse aurora that is connected to a large energy reservoir of electrons with energies of a few kiloelectron volts, the Earth's plasma sheet, where magnetosphere-ionosphere coupling processes are strongly interconnected. We use the simulated heat flux provided by SuperThermal Electron Transport (STET) code to estimate electron temperatures at the upper ionospheric altitudes and compare these results with corresponding observations from the Defense Meteorological Satellite Program satellite during Saint Patrick's Days 2013 and 2015 Geomagnetic Storms.
George V. Khazanov↗
How Auroral Electron Precipitations Contribute to the Formation of Electron Heat Fluxes to the Ionosphere?
Electron heat fluxes (also called electron thermal fluxes) in the ionosphere are carried by thermal electrons whose energy is below a few eV. Electron heat fluxes greatly impact on electron temperature, which is a fundamental parameter in the ionospheric dynamics. At the high latitude in the auroral regions electron heat flux is originated dominantly from the magnetosphere through high-energy electron energy fluxes. High-energy electron fluxes in the diffuse auroral region can undergo multiple backscatters between the magnetically conjugated regions of both hemispheres, and different kind of wave-particle interactions along the magnetic field line. High-energy electron fluxes in discrete auroral region can be trapped below the auroral acceleration region and can also undergo backscatter and multiple reflection. These processes, in turn, amplify super-thermal electrons (<~500-600 eV) that dominantly form electron heat fluxes through Coulomb collision between thermal electrons. Such electron heat fluxes play an important role to determine electron temperature profile in the ionosphere, which is one of the key parameters that controls the ionospheric dynamics. Thus, it is necessary to include electron heat flux as a topside energy input in all global ionospheric models. We demonstrate all above results based on Superthermal Electron Transport (STET), Superthermal Proton, Electron and Atomic Hydrogen tRansport in the Ionosphere and Thermosphere (SPEAH-RIT), and Comprehensive Inner Magnetosphere and Ionospheres (CIMI) codes developed at NASA Goddard Space Flight Center.
George V. Khazanov↗
What Processes are Defining the Ionospheric Conductivity and its Variability During Geomagnetic Disturbances?
Modeling of electrodynamic coupling between the magnetosphere, ionosphere, and upper atmosphere (MIA) depends on accurate specification of ionospheric conductance produced by auroral precipitation of high-energy electrons and ions. The precipitation of energetic electrons into the ionosphere is the result of a three-step process that relies on the proper selections of the simulation tools for the ionospheric conductivity studies, while observation can only measure the results of the three steps. In the region of diffuse aurora, the first step is the initiation of electron precipitation into both magnetically conjugate foot points from the Earth’s magnetosphere via wave-particle interactions. The second step is the multiple atmospheric backscatters (or reflections) of electrons at the two magnetic conjugate points, which produces secondary superthermal electron fluxes. The third step is namely the self-consistent electric and magnetic fields that influence magnetospheric particle transport and re-distribute precipitating electrons and ions through the ionospheric electrodynamics. These steps are especially important for revealing electron precipitation dynamics that carry most of the energy in the aurora, resulting also from ion precipitation production and the formation of ionospheric conductance during geomagnetic disturbances. We demonstrate all above results based on SuperThermal Electron Transport (STET), Superthermal Proton, Electron and Atomic Hydrogen tRansport in the Ionosphere and Thermosphere (SPEAH-RIT), and Comprehensive Inner Magnetosphere and Ionospere (CIMI) codes developed at NASA Goddard Space Flight Center.
George V. Khazanov↗
Improving IPATS Channel-to-Channel Registration Assessment
The Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) is a primary tool for assessing INR performance of GOES-R series ABI images. IPATS assesses five INR metrics: navigation, channel-to-channel registration (CCR), frame-to-frame registration, within-frame registration, and swath-to-swath registration. It was discovered that CCR assessment results between Visible-Near-Infrared (VNIR) channels and Infrared (IR) channels exhibits an annual oscillation in the north-south (NS) direction and a diurnal oscillation in the east-west (EW) direction, with an amplitude of approximately 5 μrad and 2.5 μrad, respectively. However, differences of navigation assessment results between VNIR and IR channels do not exhibit the annual or diurnal oscillations observed in CCR results. This indicates that the observed oscillations are due to measurement errors. The characteristics of the oscillations imply that cloud shadows are a possible cause of these measurement errors. In this study, several methods are explored to minimize the impact of cloud shadows on VNIR to IR CCR assessments: a) assessment at landmark locations only; b) using navigation assessment results to filter CCR assessments; c) using the ABI clear-sky-ratio product as a cloud mask; and d) smaller CCR assessment windows. In this paper, each method and a combination of several methods are evaluated based on assessment accuracy and the number of successful assessments. The selected approach is then used to reprocess GOES-16 ABI CCR data to show reductions in the annual and diurnal measurement error oscillations.
INR↗
Assessment of High Resolution Commercial Satellite Geolocation Accuracy
Commercial companies such as Maxar, PlanetScope, and BlackSky have launched many satellites with revisit times ranging from two hours to one day and have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. A key step in assessing changes in these images is co-registration of various images to each other. High geolocation accuracy (at most 0.5 pixels of offset) allows for easy co-registration of images across different times and sensors. Here, we assess the latest PlanetScope imagery and evaluate it for geolocation accuracy. For our assessment, we compare the target image to a reference image with known geolocation accuracy (WorldView imagery) and determine the offset between these images by shifting them to maximize their Pearson Cross-Correlation (PCC) value. Offsets required to maximize the PCC give the geolocation accuracy of the target image relative to the reference image. Previously, our global assessment of Planet data revealed large variability in geolocation accuracy from one continent to another. The measured root mean squared errors (RMSEs) range from 5.4 m in North America to 14.9 m in Africa. We have updated this previous assessment to include both their newest SuperDove series as well as a more robust assessment of the temporal stability of PlanetScope's geolocation accuracy.
Alana G. Semple↗
Geometric Assessment of PlanetScope Imagery
Commercial companies such as Maxar, Planet Labs, and BlackSky have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. The high spatial resolution allows scientists to push studies to a fine scale such as monitoring agricultural growth experiments or detecting vehicles for traffic management. Scientists using these data need to know geolocation accuracy, band-to-band registration (BBR), and pixel footprint size to best determine appropriate applications as well as what extra steps they will need to take to use the data. Here, we find those key geometric properties for images from Planet Labs’ SuperDove constellation. Geolocation accuracy is assessed relative to WorldView images at globally distributed cities, band-to-band registration (BBR) is examined for every image we acquired (200+ images), and pixel footprint sizes are calculated from edge responses of the images over Cal/Val sites in China, India, or USA both near launch time and 1+ years after launch. We find that SuperDove geolocation is highly self-consistent with average global offsets among SuperDove images of 3.80 m (1.27 pixels). Despite this self-consistency, relative geolocation accuracy (with WorldView images as reference) varies by location from 3.20 m – 28.09 m mean offset. SuperDove BBR is sub-pixel and varies by band, with a mean radial offset relative to red band varying from 0.39 - 1.13 m. SuperDove image footprint size improves after 1+ years in orbit, with an average footprint size of 3.41 pixels (10.24 m) soon after launch and 3.23 pixels (9.7 m) 1+ years after launch. The BBR and self-consistency offsets are relatively small, given the large footprint sizes. A similarly extensive investigation is in progress for Planet Labs’ Dove-R series.
Alana G. Semple↗