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At least 1,639 records · Page 91

Spring Dust in Western North America and its Interannual Variability – Understanding the Role of Local and Transported Dust

Mineral dust over western North America is an important aerosol type contributing up to one half of surface aerosol concentrations in spring. In the present study, we use data from in-situ and remote-sensing observations and the NASA Unified WRF (NU-WRF) model to investigate the sources and interannual variations of the springtime fine-mode dust over western North America. The horizontal distribution, seasonality, and interannual variability of the springtime dust over the region are characterized with observations of fine dust concentrations at the Interagency Monitoring of Protected Visual Environments (IMPROVE) sites and dust optical depth (DOD) from the Aerosol Robotic Network (AERONET) measurements. We have conducted detailed modeling and analysis for April in selected years of 2005, 2008, and 2009, to understand the causes of interannual variabilities of the springtime dust with model experiments that separate the dust generated from local deserts with that transported across the Pacific Ocean. The results suggest that although several permanent deserts and semi-arid regions in the western North America are the major source of surface fine dust concentrations in the immediate vicinity, long-range transpacific transported dust is a dominant dust source in springtime, especially over the coastal regions and areas remote from the local deserts. Interannual variability of fine dust over western North America is explained with both local dust emission and long-range transported dust.

North America spring dust↗

Space Algae: Understanding the Genomic Impacts on Microalgae After Growth in the International Space Station

Plants and microbes can be used for biological support of crewed space missions. The radiation and microgravity environment of spaceflight is expected to increase genetic mutation of all organisms. It is essential to understand how spaceflight impacts mutation rates in photosynthetic organisms to enable appropriate countermeasures and ensure productivity during long duration and deep space missions. The Space Algae flight experiments to the International Space Station (ISS) are studying the genomic stability of microalgae that could potentially be used in biological life support systems. Space Algae-1 grew ultraviolet light mutagenized Chlamydomonas reinhardtii in the VEGGIE plant growth chamber for approximately 40 mitotic generations over one month on the ISS. Whole genome sequencing from pooled cell samples every 10 generations revealed that spaceflight cultures had an ~50% increase in DNA polymorphisms relative to ground controls. These mutations had a novel base substitution signature and suggested a risk that microalgae may be unstable for long-term production in space. Space Algae-2 is focusing on the edible cyanobacterium Arthrospira platensis, commonly known as Spirulina. This experiment seeks to grow serial cultures to allow the organism to evolve in long-term spaceflight. Biological responses of the cells to spaceflight will be assessed with multi-omics analyses to determine mutation load, gene/protein expression, metabolic/nutritional composition, and cell morphology.

Algae↗

Preservation of Provenance and Context to Ensure Future Understandability of Airborne Earth Observations and Derived Data Products

Open-source science goes beyond making data from scientific projects (e.g., on-orbit/satellite missions, airborne and field investigations, and other data producing activities) openly available after they are generated, but involves and open sharing of information throughout the project lifecycle. Preservation of the data and associated information required for understanding and reusing the data well after the scientific projects is a contributor to open-source science as well. Considering the high investment in the on-orbit/satellite missions, we had developed a document titled “NASA Earth Science Data Preservation Content Specification (PCS)” in 2011. This document has been used as a requirement for recent on-orbit/satellite missions by NASA. Recently it became clear that the specifications should be applied to other scientific projects as well. Therefore, the document was revised to cover other types of projects, and a Preservation Content Implementation Guidance (PCIG) document was also developed. The revised PCS, and the PCIG, were published in 2022. The purpose of this presentation is to highlight the contents of these documents as they apply to suborbital/airborne investigations. The PCS calls for content preservation in eight general categories - Measuring Instrument/Platform Description, Instrument and Science Data Products and Metadata, Science Raw Data, Product and Algorithm Documentation, Instrument Calibration, Science Algorithm Software, Science Data Product Algorithm Inputs, Science Data Product Validation, and Science Data Access and Analysis Tools. While all these categories apply to various types of projects, a few clarifying sentences have been added to the descriptions of contents in each of the categories to show which categories are especially important to airborne and field investigations and where some contents are not applicable (or difficult to obtain). The PCIG document provides some general guidance applicable to all types of projects and specific guidance in a separate section for airborne and field investigations. This section calls out typical artifacts produced during such investigations that can meet the spirit of the various PCS categories.

remote sensing↗

Using Controlled Impact Experiments to Understand the Effects of Cohesive Blocks on the Cratering Process

When considering large-scale impact events that occur in the gravity-regime, smallscale target heterogeneities (on order of the projectile diameter) are anticipated to have a minimal effect on the cratering process and are therefore not considered in scaling relations [1-3]. Such heterogeneities and other details of the target's strength and structure, however, become increasingly influential as the magnitude of the impact decreases [4]. At the scale of craters forming mostly in regolith on the Moon (< a few meters), for example, target properties such as cohesive strength, density, porosity, and friction have more leverage than gravity to influence the resultant crater dimensions [5]. Further complications beyond just target properties can manifest in many forms, such as subsurface layers [6]; the presence of random, competent blocks [7]; buried lenses of impact melt; and/or pockets of regolith compacted or indurated to varying degrees by previous impacts. Summing the total effect of target properties and any additional heterogeneities for integration into scaling relations is not straightforward, as each individual parameter will have unequal, and so far, unquantified, effects on the final crater. Even when craters are produced under a best-case scenario of controlled laboratory conditions, understanding the entire relevant parameter space can be a formidable task, and deconvolution of all the contributing factors can be a complex undertaking. To begin the process of quantifying such effects, we are conducting an extensive series of impact experiments to build a framework for the interpretation of craters observed on the characteristically complex surfaces throughout the solar system. Here we present the first, and simplest, configuration to be examined in this multi-year experimental campaign: one in which solitary, cohesive blocks are placed in the path of the projectile’s trajectory at different burial depths in granular, sand targets. Among the variables to be investigated in this configuration are the influence of block size, compressive strength, and burial depth.

impact crater↗

Space Algae: Understanding the Genomic Impacts on Microalgae After Growth in the International Space Station

Plants and microbes can be used for biological support of crewed space missions. The radiation and microgravity environment of spaceflight is expected to increase genetic mutation of all organisms. It is essential to understand how spaceflight impacts mutation rates in photosynthetic organisms to enable appropriate countermeasures and ensure productivity during long duration and deep space missions. The Space Algae flight experiments to the International Space Station (ISS) are studying the genomic stability of microalgae that could potentially be used in biological life support systems. Space Algae-1 grew ultraviolet light mutagenized Chlamydomonas reinhardtii in the VEGGIE plant growth chamber for approximately 40 mitotic generations over one month on the ISS. Whole genome sequencing from pooled cell samples every 10 generations revealed that spaceflight cultures had an ~50% increase in DNA polymorphisms relative to ground controls. These mutations had a novel base substitution signature and suggested a risk that microalgae may be unstable for long-term production in space. Space Algae-2 is focusing on the edible cyanobacterium Arthrospira platensis, commonly known as Spirulina. This experiment seeks to grow serial cultures to allow the organism to evolve in long-term spaceflight. Biological responses of the cells to spaceflight will be assessed with multi-omics analyses to determine mutation load, gene/protein expression, metabolic/nutritional composition, and cell morphology.

Algae↗

LECTURE 8: Understanding Global Cloud Radiative Impacts

The influence of clouds on the radiation budget is one of the most important facets of the Earth’s climate. Satellite observations in the last 35 years have helped us understand the bulk radiative effects of different classes of clouds. Bill Rossow has spearheaded efforts in that direction, demonstrating the value of the International Satellite Cloud Climatology Project (ISCCP) cloud retrievals as a foundation for the full reconstruction of Earth’s Radiation Budget components. This main aim of this document is to provide an overview of the global radiative impacts of clouds at annual time scales. While geographical and seasonal aspects receive some attention, it is cloud radiative effect decomposition by cloud category (or“class” ) that is the main focal point. Furthermore, this document addresses the large-scale radiative behavior of clouds only for the current climate, with no further discussion of how this behavior may change in the future and what its climatic impact may be [please refer to Del Genio (2018) for an excellent overview of this topic]. Cloud classes can be defined in many ways, and are often referred to with terms such as “cloud type”and “cloud regime”. Some of the definitions are more meaningful at the level of individual instrument footprints (“pixels” for passive or “rays” for active satellite observations) while others for larger areas (e.g., “mesoscale”).This distinction will become apparent below.

Lazaros Oreopoulos↗

Understanding Thermal Stability in Zirconia-Based Aerogels

For lightweight, thermal insulation needs above 1000ºC, the high surface to volume ratios of ceramic-based aerogels are practically unparalleled. Yet realizing the full potential of aerogel-based thermal protection systems requires not only increased thermal stability, but also a broadened menu of stabilizing mechanisms. Here we will review our recent efforts to understand the impact of synthetic parameters and dopant chemistry on the evolution of zirconia-based ceramics. A broad parametric window for thermal stability is established, in which the more sensitive variable of composition has been probed. However, dopant chemistry is actually an aggregate for many closely related material parameters including surface energy, enthalpy of formation, each of which may contribute uniquely to aerogel destabilization. A truly predictive design framework for ceramic-based aerogels requires further decoupling of these underlying properties through systematic and comprehensive evaluation of thermodynamic properties.

aerogel↗

Understanding the Vertical Slope of Mesoscale Snow Band Reflectivity Signatures

Mesoscale snow bands are frequently responsible for dumping large amounts of snow over a relatively small region and pose a considerable forecasting challenge. The ongoing NASA Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign observed several instances of mesoscale snow bands during January and February of 2020 and 2022. These snow bands were sampled by a combination of airborne (NASA ER-2 and P-3) and ground-based remote sensing and in-situ instruments. Along-band cross sections of these snow bands reveal that many of them are vertically sloped. Our preliminary analysis into one of these snow bands suggests that the vertical slope is not maintained by isentropic lift and does not appear to be tied to horizontal deformation. A combined analysis of the reflectivity and wind retrievals from the ER-2 radars raises the possibility that these features could be produced by vertical wind shear layers deforming fall streaks into bands that extend hundreds of kilometers. The present study will focus on extending our preliminary analysis to additional cases and understanding the mechanisms that support these features using a combination of radar data, in-situ aircraft measurements, and numerical modeling.

Charles Helms↗

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗

Evolution of Astrodynamics for Multibody Environments, Numerical Precision and Dynamical Understanding

The innovative nature of dynamical systems theory and its applications in trajectory design enabled many recent missions by opening up new transfer and capture opportunities to meet mission requirements, reduce fuel costs, and address various launch constraints and contingencies. With a combination of proven numerical methods and an advanced understanding of the dynamics, an ‘experienced’ user can rapidly design multibody and cislunar missions such as Lunar IceCube and Artemis/Themis and relatively quickly conceive trajectory concepts for Sun-Earth mission orbits, such as the Space Weather Follow On-L1 Lissajous orbit—one that can be achieved and maintained.

David C Folta↗

Evolution of Astrodynamics for Multibody Environments, Numerical Precision and Dynamical Understanding

The innovative nature of dynamical systems theory and its applications in trajectory design enabled many recent missions by opening up new transfer and capture opportunities to meet mission requirements, reduce fuel costs, and address various launch constraints and contingencies. With a combination of proven numerical methods and an advanced understanding of the dynamics, an ‘experienced’ user can rapidly design multibody and cislunar missions such as Lunar IceCube and Artemis/Themis and relatively quickly conceive trajectory concepts for Sun-Earth mission orbits, such as the Space Weather Follow On-L1 Lissajous orbit—one that can be achieved and maintained.

Dynamical Systems↗

Understanding Volume Estimation Uncertainty of Lakes and Wetlands Using Satellites and Citizen Science

We studied variations in the volume of water stored in small lakes and wetlands using satellite remote sensing and lake water height data contributed by citizen scientists. A total of 94 water bodies across the globe were studied using satellite data in the optical and microwave wavelengths from Landsat 8, Sentinel-1, and Sentinel-2. The uncertainty in volume estimation as a function of geography and geophysical factors, such as cloud cover, precipitation, and water surface temperature, was studied. The key finding that emerged from this global study is that uncertainty is highest in regions with a distinct precipitation season, such as in the monsoon dominated South Asia or the Pacific Northwestern region of the USA. This uncertainty is further compounded when small lakes and wetlands are seasonal with alternating land use as a water body and agricultural land, such as the wetlands of Northeastern Bangladesh. On an average, 45% of studied lakes could be estimated of their volume change with a statistical significant uncertainty that is less than the expected volume in South Asia. In North America, this statistically significant uncertainty in volume estimation was found to be around 50% in lakes eastward of the 108th meridian with lowest uncertainty found in lakes along the East coast of the USA. The article provides a baseline for understanding the current state of the art in estimating volumetric change of lakes and wetlands using citizen science in anticipation of the recently launched Surface Water and Ocean Topography Mission.

Shahzaib Khan↗

Accounting for Herbaceous Communities in Process-Based Models Will Advance Our Understanding of “Grassy” Ecosystems

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

biogeochemistry↗

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Recent Advancements in spoken language processing technologies have enabled the development of reliable automation tools to assist air traffic control (ATC) operations. These advancements present a unique opportunity to strategically implement digital taxi instructions for aircraft movement on the ground. Digital taxi instructions issue taxiing procedures to pilots as textual or graphical instructions. There are several benefits of digital instructions, including a reduction in radio congestion, elimination of communication errors, and improved aircraft monitoring capabilities. Natural language understanding (NLU) models can extract digital taxi instructions from verbal instructions issued by air traffic controllers. This capability enables the implementation of a digital taxi communication framework with minimal changes to the existing air traffic controller operational environment. We explore a novel application for NLU: automatically generating digital taxi instructions from air traffic controller speech. We describe the development of an annotation scheme to represent (aircraft) ground traffic communications in the US National Airspace System (NAS).Our annotation scheme uses intent classification and slot filling to extract taxi instructions, enabling NLU models to leverage syntactic information. Several neural network models were trained to categorize the controller’s intent and label information relevant to his or her intent.Our research demonstrates that it is feasible to use NLU to automatically generate digitaltaxi instructions, suggesting that it is a powerful tool for the implementation of digital taxi communications.

Hillel Steinmetz↗

The Role of Isotopes in Understanding of the Formation and Evolution of the Solar System

Comparative planetology via isotope geochemistry has played a critical role in advancing our understanding of the inventories of both volatiles and organics in the atmospheres of solar system bodies. For example, the 12 C/ 13 C measured from atmospheric methane in Titan provided upper limits on the amount of time that methane has been present in the atmosphere, demonstrating that methane was only present in Titan’s atmosphere during at most the last 1 billion years (Gyr). As another example, measurements of 14 N/ 15 N in atmospheric HCN and N 2 provide direct evidence of how photochemistry influences stable isotopes. These observations were used to determine that Titan’s nitrogen originated as NH 3 in the protosolar nebula, thus constraining the origin and delivery of volatiles to the Saturnian moon Titan. These measurements of 12 C/ 13 C and 14 N/ 15 N in Titan’s atmosphere were obtained with remote and in situ observations from the Cassini spacecraft in Saturn orbit. However, combining spacecraft observations like these throughout the solar system with Earth-based telescope observations, including both ground-based and from orbiting telescopes, produces far more powerful results. For example, the lower limit obtained for 14 N/ 15 N in HCN in Pluto’s atmosphere by ALMA combined with New Horizons observations of the atmospheric composition provides a valuable tool for determining the origin of nitrogen for Pluto if the influences of condensation and aerosol trapping on isotopes can be constrained. Isotopes measured at Jupiter and Saturn and their moons, combined with composition measurements from comets provide information on giant planet formation processes and primordial conditions when the solar system was forming. In all of these studies, measurements of isotope ratios in comets have served as a reference for processes in the protosolar nebula.

Kathleen E. Mandt↗

Understanding Sun-as-a-Star Variability of Solar Balmer Lines

Precise, high-cadence, long-term records of stellar spectral variability at different temporal scales lead to better understanding of a wide variety of phenomena including stellar atmospheres and dynamos, convective motions, and rotational periods.

solar activity, solar cycle↗

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and F1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

LSTM↗