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NASA NTRS2022

Keweenaw Bay Water Resources: Turbidity Data Decision Support for Shoreline Assessment and Management in Lake Superior'S Keweenaw Bay

The Keweenaw Bay Indian Community (KBIC) has shoreline along the south of Lake Superior that is contaminated with copper stamp sands from legacy mining. The stamp sands have been capped with sandy-loam soils and restored native species, but erosion and flooding threaten to re-deposit these stamp sands onto wetlands and into the bay. Erosion and flooding also threaten loss of beaches and shoreline, infrastructure, wetland restoration projects, and coastal highways, which has driven shoreline armoring. However, while shoreline armoring can be effective in protecting the intended areas, it can also exacerbate erosion in nearby unarmored areas, so its net impact on the shoreline is yet to be quantified. The DEVELOP team partnered with KBIC and the Environmental Protection Agency (EPA) to utilize imagery from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) in order to analyze turbidity proxies. The results from these analyses showed that seasonal variation in study area was greatest during the season dominated by rain, but spatial variability across our study period did not show a clear trend. These results will be used to better inform future shoreline management efforts and support resilience in the face of more coastal erosion.

remote sensing↗

NASA NTRS2001

H(alpha) Proxies for EIT Crinkles: Further Evidence for Preflare "Breakout"-Type Activity in an Ejective Solar Eruption

We present H(alpha) observations from Big Bear Solar Observatory of an eruptive flare in NOAA Active Region 8210, occurring near 22:30 UT on 1998 May 1. Previously, using the Extreme Ultraviolet Imaging Telescope (EIT) on the Solar and Heliospheric Observatory (SOHO) spacecraft, we found that a pattern of transient, localized brightenings, which we call 'EIT crinkles,' appears in the neighborhood of the eruption near the time of flare onset. These EIT crinkles occur at a location in the active region well separated from the sheared core magnetic fields, which is where the most intense features of the eruption are concentrated. We also previously found that high-cadence images from the Soft X-ray Telescope (SXT) on Yohkoh indicate that soft X-ray intensity enhancements in the core begin after the start of the EIT crinkles. With the H(alpha) data, we find remote flare brightening counterparts to the EIT crinkles. Light curves as functions of time of various areas of the active region show that several of the remote flare brightenings undergo intensity increases prior to the onset of principal brightenings in the core region, consistent with our earlier findings from EIT and SXT data. These timing relationships are consistent with the eruption onset mechanism known as the breakout model, introduced by Antiochos and colleagues, which proposes that eruptions begin with reconnection at a magnetic null high above the core region. Our observations are also consistent with other proposed mechanisms that do not involve early reconnection in the core region. As a corollary, our observations are not consistent with the so-called tether-cutting models, which say that the eruption begins with reconnection in the core. The H(alpha) data further show that a filament in the core region becomes activated near the time of EIT crinkle onset, but little if any of the filament actually erupts, despite the presence of a halo coronal mass ejection (CME) associated with this event.

Sterling, Alphonse C.↗

NASA NTRS2018

Long-Term Solar Activity Studies Using Microwave Imaging Observations and Prediction for Cycle 25

We use microwave imaging observations from the Nobeyama Radioheliograph at 17 GHz for long-term studies of solar activity. In particular, we use the polar and low-latitude brightness temperatures as proxies to the polar magnetic field and the active-regions, respectively. We also use the location of prominence eruptions as a proxy to the filament locations as a function of time. We show that the polar microwave brightness temperature is highly correlated with the polar magnetic field strength and the fast solar wind speed. We also show that the polar microwave brightness at one cycle is correlated with the low latitude brightness with a lag of about half a solar cycle. We use this correlation to predict the strength of the solar cycle: the smoothed sunspot numbers in the southern and northern hemispheres can be predicted as 89 and 59, respectively. These values indicate that cycle 25 will not be too different from cycle 24 in its strength. We also combined the rush to the pole data from Nobeyama prominences with historical data going back to 1860 to study the north-south asymmetry of sign reversal at solar poles. We find that the reversal asymmetry has a quasi-periodicity of 3-5 cycles.

N. Gopalswamy↗

NASA NTRS1991

Basin-scale estimates of oceanic primary production by remote sensing - The North Atlantic

The monthly averaged CZCS data for 1979 are used to estimate annual primary production at ocean basin scales in the North Atlantic. The principal supplementary data used were 873 vertical profiles of chlorophyll and 248 sets of parameters derived from photosynthesis-light experiments. Four different procedures were tested for calculation of primary production. The spectral model with nonuniform biomass was considered as the benchmark for comparison against the other three models. The less complete models gave results that differed by as much as 50 percent from the benchmark. Vertically uniform models tended to underestimate primary production by about 20 percent compared to the nonuniform models. At horizontal scale, the differences between spectral and nonspectral models were negligible. The linear correlation between biomass and estimated production was poor outside the tropics, suggesting caution against the indiscriminate use of biomass as a proxy variable for primary production.

Platt, Trevor↗

NASA NTRS2023

Great Salt Lake Health and Air Quality: Monitoring Lakebed Exposure and its Impact on Air Quality and Environmental Hazards in the Great Salt Lake Watershed

Water flow into the Great Salt Lake has declined rapidly over the last forty years due to human withdrawals and climate change. As a result of declining lake levels, over 50% of the lakebed is now exposed. Dust storms may grow in frequency and intensity across Northern Utah as lakebed dust becomes airborne under specific meteorological conditions. In our research project, we utilized satellite imagery from Terra and Aqua, Sentinel-5P, CALIPSO, Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI-2, Suomi NPP, ground sensor environmental data, and demographic data to understand the relationship between lake desiccation and dust, and the impact of pollution upon the communities surrounding the Great Salt Lake. By plotting changes in Lake Surface Area against Aerosol Optical Depth (AOD) over our study period (2010-2022), we found an inverse relationship (R2=0.3423) between lake surface area and dust levels within our study area. We conducted a Vertical Feature Mask (VFM) and Extinction Coefficient Plot, from which we identified that during dust events, the aerosol type is mainly polluted dust and the aerosol height is 200 meters from the surface. Lastly, we created bivariate choropleth maps, which demonstrate which census tracts within our study area are most vulnerable to AOD (a proxy for PM2.5 from dust), NO2 and HCHO (precursors to ozone). In summary, our findings revealed that declining lake levels are associated with an increase in intensity of dust events, and these dust events will particularly impact residents of Tooele County and the west side of Salt Lake City. Project resources support partner needs by informing targeted air monitoring efforts, lakebed management practices, and advocacy efforts for GSL stewardship.

Terminal Saline Lake↗

NASA NTRS2019

An Automatic Light Rain Detection Algorithm on NASA MPLNET Lidar Observations in the Frame of WMO GALION Project

The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics. Results from the algorithm, besides filling a gap in precipitation and virga detection by radars, are of particular interest for the scientific community because will help to better understand long-term aerosol-cloud interactions and aerosol atmospheric removal (scavenging effect) by rain as multi-year database being available for several MPLNET permanent observational sites across the globe. Moreover, we developed the automatic algorithm at Universitat Politecnica de Catalunya (UPC) Barcelona, the unique permanent observation station member of MPLNET and the European Aerosol Lidar Network (EARLINET) In the future the algorithm can be then easily applied to any other lidar and/or ceilometer network infrastructure in the frame of World Meteorological Organization (WMO) Global Aerosol Watch (GAW) aerosol lidar observation network (GALION)

Simone Lolli↗

NASA NTRS2021

Features and Characteristics of the New NASA MicroPuLse NETwork (MPLNET) Automatic Rain Detection Algorithm

S. Lolli↗

NASA NTRSDate not supplied

The CheMin X-ray Diffractometer on MSL Curiosity: A Decade of Mineralogical Observations from Gale Crater, Mars

For more than a decade, the CheMin X-ray Diffraction instrument on the Mars Science Laboratory rover Curiosity has been returning quantitative mineralogical data from Gale crater, Mars. CheMin receives and analyzes sieved soil and powdered rock samples from Curiosity’s Sample Acquisition / Sample Processing and Handling (SA/SPaH) system. To date, 38 samples have been analyzed over the course of a 28 km transit. These samples document more than 600 vertical meters of flat-lying lacustrine, fluvial and aeolian sediments that comprise the lower part of the central mound of Gale crater (commonly called Mt. Sharp).The principal mineralogy of the sediments is basaltic, with evidence of early and late-stage diagenetic overprinting. The rocks in many cases preserve most of their primary mineralogy and sedimentary features, suggesting that they were never strongly heated or deformed. Using aeolian soil composition as a proxy for the composition of the deposited and lithified sediment, it appears that in many cases the diagenetic changes observed are principally isochemical. Exceptions to this include secondary nodules, calcium sulfate veining and rare alteration halos. A striking hematite-rich feature in lower Mt. Sharp called Vera Rubin Ridge is interpreted to be lake sediment diagenetically altered by silica-poor fluids. A surprising and as yet poorly understood observation is that nearly all of the 3.7 Gyr old sedimentary rocks analyzed to date are comprised of 25-50% X-ray amorphous material. Overall, this 600 m vertical section of sedimentary rock explored in lower Mt. Sharp documents a perennial shallow lake environment grading upward into alternating lacustrine/fluvial and aeolian environments. The mineralogical changes observed going up-section include a transition from trioctahedral to dioctahedral clay minerals and a transition from magnetite to hematite. More recently, in the last 150 m of section, CheMin has documented an overall decrease in clay minerals and increase in Fe3+ oxides and oxyhydroxides. The mineralogical changes observed in Gale crater may document the gradual drying out and oxidation of the martian hydrosphere.

CHEMIN↗

DOE OSTI2024

Quantifying Seasonal and Diurnal Cycles of Solar‐Induced Fluorescence With a Novel Hyperspectral Imager

Abstract Solar‐induced fluorescence (SIF) is a proxy of ecosystem photosynthesis that often scales linearly with gross primary productivity (GPP) at the canopy scale. However, the mechanistic relationship between GPP and SIF is still uncertain, especially at smaller temporal and spatial scales. We deployed a ultra‐hyperspectral imager over two grassland sites in California throughout a soil moisture dry down. The imager has high spatial resolution that limits mixed pixels, enabling differentiation between plants and leaves within one scene. We find that imager SIF correlates well with diurnal changes in leaf‐level physiology and gross primary productivity under well‐watered conditions. These relationships deteriorate throughout the dry down event. Our results demonstrate an advancement in SIF imaging with new possibilities in remotely sensing plant canopies from the leaf to the ecosystem. These data can be used to resolve outstanding questions regarding SIF's meaning and usefulness in terrestrial ecosystem monitoring.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1988

Deccan volcanism at the Cretaceous-Tertiary boundary

The accuracy with which one can claim that Deccan trap volcanism occurred at the Cretaceous-Tertiary boundary (KTB) over a very short time interval is of key importance in deciding whether a volcanic origin of the KTB events should be taken seriously. In the two years since paleomagnetic, paleontological and geodynamic evidence was published, further data have become available and the case now appears to be well constrained. The Ar-40/Ar-39 results from six labs have yielded some 24 reliable plateau ages that narrow the age range to 65 to 69 Ma. Moreover, it appears that a significant part of this range results from inter-lab spread and possible minor alteration. Paleontology demonstrates that volcanism started in the Maestrichtian, more precisely in the A. mayaroensis zone. Paleomagnetism shows that volcanism spanned only 3 chrons and only one correlation remains possible, that of the main central reversed chron with 29R. Therefore, whereas Ar-40/Ar-39 is able only to restrict the duration of volcanism to some 4 Ma, paleomagnetism restricts it to 0.5 Ma. Using some geochemical indicators such as C-13 as proxy, it is suggested that volcanism actually consists of a few shorter events of unequal magnitude. Extrusion rates may be as high as 100 cu km/yr and fissure lengths as long as several 100 km. Such a scenario appears to be at least as successful as others in accounting for most anomalies observed at the KTB. Particularly important are Iridium and other platinum group elements (PGE) profiles, Sr-87/Sr-86, C-13, 0-18, other exotic geochemical signatures, spherules, soot, shocked minerals, selective and stepwise extinctions. The environmental impact of CO2 possibly released during explosive phases of volcanism, and SO2 released during effusive phases, and the ability of volcanism to ensure worldwide distribution of KTB products are now all addressed. In conclusion, the case for a causal link between internal hotspot activity, birth of the Reunion hotspot itself as the Deccan and KTB events appears to rest on an increasingly stronger basis.

Courtillot, V.↗

NASA NTRS2017

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗

DOE OSTI2024

Probing Postmeasurement Entanglement without Postselection

We study the problem of observing quantum collective phenomena emerging from large numbers of measurements. These phenomena are difficult to observe in conventional experiments because, in order to distinguish the effects of measurement from dephasing, it is necessary to postselect on sets of measurement outcomes with Born probabilities that are exponentially small in the number of measurements performed. An unconventional approach, which avoids this exponential “postselection problem”, is to construct cross-correlations between experimental data and the results of simulations on classical computers. However, these cross-correlations generally have no definite relation to physical quantities. We first show how to incorporate classical shadows into this framework, thereby allowing for the construction of quantum information-theoretic cross-correlations. We then identify cross-correlations that both upper and lower bound the measurement-averaged von Neumann entanglement entropy, as well as cross-correlations that lower bound the measurement-averaged purity and entanglement negativity. These bounds show that experiments can be performed to constrain postmeasurement entanglement without the need for postselection. To illustrate our technique, we consider how it could be used to observe the measurement-induced entanglement transition in Haar-random quantum circuits. We use exact numerical calculations as proxies for quantum simulations and, to highlight the fundamental limitations of classical memory, we construct cross-correlations with tensor-network calculations at finite bond dimension. Our results reveal a signature of measurement-induced criticality that can be observed using a quantum simulator in polynomial time and with polynomial classical memory. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2019

Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET) Automatic Precipitation Detection Algorithm

Precipitation modifies atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially for low-intensity precipitation) within global scale models is crucial. In addition to improving our modeling of the hydrological cycle, this will reduce the associated uncertainty of global climate models in correctly forecasting future scenarios, and will enable the application of mitigation strategies. In this manuscript we present a proof of concept algorithm to automatically detect precipitation from lidar measurements obtained from the National Aeronautics and Space Administration Micropulse lidar network (MPLNET). The algorithm, once tested and validated against other remote sensing instruments, will be operationally implemented into the network to deliver a near real time (latency <1.5 h) rain masking variable that will be publicly available on MPLNET website as part of the new Version 3 data products. The methodology, based on an image processing technique, detects only light precipitation events (defined by intensity and duration) such as light rain, drizzle, and virga. During heavy rain events, the lidar signal is completely extinguished after a few meters in the precipitation or it is unusable because of water accumulated on the receiver optics. Results from the algorithm, in addition to filling a gap in light rain, drizzle, and virga detection by radars, are of particular interest for the scientific community as they help to fully characterize the aerosol cycle, from emission to deposition, as precipitation is a crucial meteorological phenomenon accelerating atmospheric aerosol removal through the scavenging effect. Algorithm results will also help the understanding of long term aerosol–cloud interactions, exploiting the multi-year database from several MPLNET permanent observational sites across the globe. The algorithm is also applicable to other lidar and/or ceilometer network infrastructures in the framework of the Global Aerosol Watch (GAW) aerosol lidar observation network (GALION).

Simone Lolli↗

NASA NTRS2009

Tele-Supervised Adaptive Ocean Sensor Fleet

The Tele-supervised Adaptive Ocean Sensor Fleet (TAOSF) is a multi-robot science exploration architecture and system that uses a group of robotic boats (the Ocean-Atmosphere Sensor Integration System, or OASIS) to enable in-situ study of ocean surface and subsurface characteristics and the dynamics of such ocean phenomena as coastal pollutants, oil spills, hurricanes, or harmful algal blooms (HABs). The OASIS boats are extended- deployment, autonomous ocean surface vehicles. The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. One feature of TAOSF is the adaptive re-planning of the activities of the OASIS vessels based on sensor input ( smart sensing) and sensorial coordination among multiple assets. The architecture also incorporates Web-based communications that permit control of the assets over long distances and the sharing of data with remote experts. Autonomous hazard and assistance detection allows the automatic identification of hazards that require human intervention to ensure the safety and integrity of the robotic vehicles, or of science data that require human interpretation and response. Also, the architecture is designed for science analysis of acquired data in order to perform an initial onboard assessment of the presence of specific science signatures of immediate interest. TAOSF integrates and extends five subsystems developed by the participating institutions: Emergent Space Tech - nol ogies, Wallops Flight Facility, NASA s Goddard Space Flight Center (GSFC), Carnegie Mellon University, and Jet Propulsion Laboratory (JPL). The OASIS Autonomous Surface Vehicle (ASV) system, which includes the vessels as well as the land-based control and communications infrastructure developed for them, controls the hardware of each platform (sensors, actuators, etc.), and also provides a low-level waypoint navigation capability. The Multi-Platform Simulation Environment from GSFC is a surrogate for the OASIS ASV system and allows for independent development and testing of higher-level software components. The Platform Communicator acts as a proxy for both actual and simulated platforms. It translates platform-independent messages from the higher control systems to the device-dependent communication protocols. This enables the higher-level control systems to interact identically with heterogeneous actual or simulated platforms.

Lefes, Alberto↗

NASA NTRS2024

The Chemistry and Mineralogy (CheMin) X-Ray Diffractometer on the MSL Curiosity Rover: A Decade of Mineralogy From Gale Crater, Mars

For more than a decade, the CheMin X-ray diffraction instrument on the Mars Science Laboratory rover Curiosity has been returning definitive and quantitative mineralogical and mineral-chemistry data from ~3.5-billion-year-old (Ga) sediments in Gale crater, Mars. To date, 40 drilled rock samples and 3 scooped soil samples have been analyzed during the rover’s 30+ km transit. These samples document the mineralogy of over 800 meters of flat-lying fluvial, lacustrine and aeolian sedimentary rocks that comprise the lower strata of the central mound of Gale crater (Aeolis Mons; informally known as Mt. Sharp) and the surrounding plains (Aeolis Palus, informally known as the Bradbury Rise). The principal mineralogy of the sedimentary rocks is basaltic, with evidence of early and late-stage diagenetic overprinting. The rocks in many cases preserve much of their primary mineralogy and sedimentary features, suggesting that they were never strongly heated or deformed. Using aeolian soil composition as a proxy for the composition of the deposited and lithified sediment, it appears that in many cases diagenetic changes observed are principally isochemical. Exceptions to this trend include secondary nodules, calcium sulfate veining, and rare Si-rich alteration halos. A surprising and yet poorly understood observation is that nearly all the ~3.5 Ga sedimentary rocks analyzed to date contain 15-70 wt.% of X-ray amorphous material. Over-all, this >800-meter section of sedimentary rock explored in lower Mt. Sharp documents a perennial shallow lake environment grading upward into alternating lacustrine/fluvial and aeolian environments, many of which would have been habitable to microbial life.

Mars↗

DOE OSTI2025

Investigating Electron Conductivity Regimes in the Bacterial Cytochrome Wire OmcS

The anaerobic bacterium Geobacter sulfurreducens produces extracellular, electronically conductive cytochrome polymer wires that are conductive over micron length scales. Structure models from cryo-electron microscopy data show OmcS wires form a linear chain of hemes along the protein wire axis, which is proposed as the structural basis supporting their electronic properties. However, the mechanism by which this heme arrangement supports long-range electronic conduction remains unknown. Structure models from cryo-electron microscopy data show these wires form a linear chain of hemes along the protein wire axis, which is proposed as the structural basis supporting their electronic properties. Existing computational models using static heme redox potentials and coupling energies fail to explain experimental observations, predicting conductances 10,000 to 100,000 times lower than measured values. Here, we investigate how dynamic disorder affects site energies, interheme coupling, and long-range electronic conductivity within these cytochrome wires. We introduce an approach to extract charge carrier site information directly from Kohn–Sham density functional theory, without employing projector schemes, and show that site and coupling energies are highly sensitive to changes in interheme geometry and the surrounding electrostatic environment. Unlike models that incorporate dynamic disorder as a thermally averaged quantity, our quantum charge carrier model incorporates proxies for dynamic disorder through decoherence corrections, yielding predicted diffusion coefficient closer to what is expected from experiment and comparable with other organic-based electronic materials. Based on these simulations, we propose that the instantaneous fluctuations of the local electrostatic environment can transiently lift energy degeneracies and delocalize charge carriers. Furthermore, these studies reveal how incorporating dynamic fluctuations associated with the environment resolves the discrepancy between theory and experiment in microbial cytochrome wires and highlight design principles for bioinspired, heme-based conductive materials.

Bioinorganic chemistry↗

NASA NTRSDate not supplied

Status and Progress of All-Sky Hyperspectral IR Radiance Assimilation in GEOS

The majority of hyperspectral infrared radiance observations that peak in the lower and mid-troposphere have been excluded from the assimilation in the operational GEOS by the cloud detection scheme. The significance and challenges of assimilating these cloud-affected observations have attracted the attention of the research community, encouraged by the progress in utilizing all-sky microwave radiances affected by clouds and precipitation in many data assimilation systems, including GEOS. While the Global Modeling and Assimilation Office (GMAO) has made significant progress on the assimilation of cloud-cleared infrared radiances, this parallel study marks the first effort to directly assimilate cloud-affected hyperspectral infrared radiances in the GEOS. This initial study is focused on CrIS-FSR wa:wqter-vapor channels. The capability of the GEOS model and CRTM in simulating infrared radiances affected by clouds has been evaluated, and the all-sky brightness temperature Jacobians with respect to temperature, specific humidity, and hydrometeors are examined closely in varying cloud conditions. With hydrometeor control variables in the GEOS, several important aspects of all-sky IR radiance assimilation are investigated. The symmetric cloud effects are assessed for their robustness when used as the cloud proxy in observation error modeling that incorporates the inter-channel correlations with error situation dependency on the amount of cloud. The effective radius, bias correction and quality control processes will also be adapted to accommodate modifications necessary for all-sky infrared assimilation before comprehensive four-dimensional ensemble-variational(4dEnVar) experiments are conducted to assess their impacts on the analysis and forecast performance of GEOS.

Wei Gu↗

NASA NTRS2010

Optimizing Air Transportation Service to Metroplex Airports: Analysis of Historical Data - Part 1

The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation (+4% annual growth), resulting in unreliable service and systemic delays. Estimates of the impact of delays and unreliable air transportation service on the economy range from $32B to $41B per year. This report describes the results of an analysis of airline strategic decision-making with regards to: (1) geographic access, (2) economic access, and (3) airline finances. This analysis evaluated markets-served, scheduled flights, aircraft size, airfares, and profit from 2005-2009. During this period, airlines experienced changes in costs of operation (due to fluctuations in hedged fuel prices), changes in travel demand (due to changes in the economy), and changes in infrastructure capacity (due to the capacity limits at EWR, JFK, and LGA). This analysis captures the impact of the implementation of capacity limits at airports, as well as the effect of increased costs of operation (i.e. hedged fuel prices). The increases in costs of operation serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed.

Donohue, George↗