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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

BOREAS (Boreal Ecosystem-Atmosphere Study): Global change and biosphere-atmosphere interactions in the boreal forest

The Boreal Ecosystems Atmosphere Study (BOREAS) is a cooperative field and analysis project involving elements of land surface climatology, tropospheric chemistry, and terrestrial ecology. The goal of the study is to understand the interactions between the boreal forest biome and the atmosphere in order to clarify their roles in global change. The study will be centered on two 20 by 20 km sites within the North American boreal forest region, located near the northern and southern limits of the biome. Studies based at these sites will be used to explore the roles of various environmental factors in controlling the extent and character of the biome. The sites will be the subject of surface, airborne, and satellite based observations which aim to improve understanding of the biological and physical processes and states which govern the exchanges of energy, water, carbon, and trace gases between boreal forest ecosystems and the atmosphere. Particular reference will be made to those processes and states that may be sensitive to global change. The study also aims to develop the use of remote sensing techniques to transfer understanding of the above process from local scales out to regional scales. The BOREAS project is being planned for 1992-1996, with a major field effort in 1994.

Sellers, Piers J.↗
NASA NTRSDate not supplied

GEOS Constituent Data Assimilation Beyond Aura MLS: Assimilating NASA SAGE III/ISS Profiles of Stratospheric Water Vapor

Ozone and water vapor in the lower stratosphere are important trace gases for atmospheric chemistry and radiative budget. The Stratospheric Aerosol and Gas Experiment (SAGE) missions have been crucial in monitoring the stratospheric ozone loss and the subsequent recovery as well as the trends in water vapor linked to surface temperature trends. The SAGE III instrument aboard the International Space Station (ISS) continues the SAGE mission record, with high vertical resolution profiles of ozone and water vapor available since mid 2017. The NASA GEOS Earth system model has the new capability to assimilate multi-constituents from ground and space-based instruments using the GEOS Constituent Data Assimilation System (CoDAS). The recently released MERRA-2 Stratospheric Composition Reanalysis with Aura MLS (M2-SCREAM) assimilates version 4.2 MLS ozone, water vapor and other chemically-reactive species with the NASA GEOS model coupled to a stratospheric-only chemistry mechanism and transport constrained to the MERRA-2 reanalysis. While the number of solar occultation observations a day from SAGE III/ISS is about 1% of the total number of profiles observed globally by MLS, the chemical timescales of ozone and water vapor in the lower stratosphere are long enough that the SAGE III/ISS data may provide a useful constraint on the assimilated product. Using the same GEOS CoDAS configuration as M2-SCREAM, we will present a series of experiments to investigate if water vapor trends are consistent with the assimilation of SAGE observations with and without Aura retrievals, and to determine if the assimilation of SAGE observations produces a steady product for trend analysis, especially as the end of the Aura mission nears. In our experiments, assimilating only SAGE III/ISS water vapor profiles results in water vapor fields more consistent with experiments that assimilate MLS v5; however, in the polar regions SAGE III/ISS observations are not available and the modelled values are unconstrained. We are encouraged by the positive benefit assimilating the less frequent SAGE III/ISS observations has on stratospheric composition. Sensitivity experiments such as these will allow us to assess the added value of SAGE data for continued monitoring of the stratospheric composition for climate and ozone recovery assessments.

K Emma Knowland↗
NASA NTRS2004

Use of Radon for Evaluation of Atmospheric Transport Models: Sensitivity to Emissions

This paper presents comparative analyses of atmospheric radon (Rn) distributions simulated using different emission scenarios and the observations. Results indicate that the model generally reproduces observed distributions of Rn but there are some biases in the model related to differences in large-scale and convective transport. Simulations presented here use an off-line three-dimensional chemical transport model driven by assimilated winds and two scenarios of Rn fluxes (atom/cm s) from ice-free land surfaces: (A) globally uniform flux of 1.0, and (B) uniform flux of 1.0 between 60 deg. S and 30 deg. N followed by a sharp linear decrease to 0.2 at 70 deg. N. We considered an additional scenario (C) where Rn emissions for case A were uniformly reduced by 28%. Results show that case A overpredicts observed Rn distributions in both hemispheres. Simulated northern hemispheric (NH) Rn distributions from cases B and C compare better with the observations, but are not discernible from each other. In the southern hemisphere, surface Rn distributions from case C compare better with the observations. We performed a synoptic scale source-receptor analysis for surface Rn to locate regions with ratios B/A and B/C less than 0.5. Considering an uncertainty in regional Rn emissions of a factor of two, our analysis indicates that additional measurements of surface Rn particularly during April-October and north of 50 deg. N over the Pacific as well as Atlantic regions would make it possible to determine if the proposed latitude gradient in Rn emissions is superior to a uniform flux scenario.

Gupta, Mohan L.↗
DOE OSTI2024

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid-related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug-testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)-decorated single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) are utilized for machine learning-assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave-one-out cross-validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au-SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au-SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL –1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Assessing the representation of the Australian carbon cycle in global vegetation models

Australia plays an important role in the global terrestrial carbon cycle on inter-annual timescales. While the Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations of net biome production (NBP) and the carbon stored in vegetation between 1901 to 2018 from 13 DGVMs (TRENDY v8 ensemble). We focused our analysis on Australia's short-term (inter-annual) and long-term (decadal to centennial) terrestrial carbon dynamics. The TRENDY models simulated differing magnitudes of NBP on inter-annual timescales, and these differences resulted in significant differences in long-term vegetation carbon accumulation (–4.7 to 9.5 Pg C). We compared the TRENDY ensemble to several satellite-derived datasets and showed that the spread in the models' simulated carbon storage resulted from varying changes in carbon residence time rather than differences in net carbon uptake. Differences in simulated long-term accumulated NBP between models were mostly due to model responses to land-use change. The DGVMs also simulated different sensitivities to atmospheric carbon dioxide (CO 2 ) concentration, although notably, the models with nutrient cycles did not simulate the smallest NBP response to CO 2 . Our results suggest that a change in the climate forcing did not have a large impact on the carbon cycle on long timescales. However, the inter-annual variability in precipitation drives the year-to-year variability in NBP. We analysed the impact of key modes of climate variability, including the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), on NBP. While the DGVMs agreed on sign of the response of NBP to El Niño and La Niña and to positive and negative IOD events, the magnitude of inter-annual variability in NBP differed strongly between models. In addition, we find that differences in the timing of simulated phenology and fire dynamics are associated with differences in simulated or prescribed vegetation cover and process representation. We further find model disagreement in simulated vegetation carbon, phenology, and apparent carbon residence time, indicating that the models have different types and coverage of vegetation across Australia (whether prescribed or emergent). Our study highlights the need to evaluate parameter assumptions and the key processes that drive vegetation dynamics, such as phenology, mortality, and fire, in an Australian context to reduce uncertainty across models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

GEOS Constituent Data Assimilation Beyond Aura MLS: Assimilating NASA SAGE III/ISS Profiles of Stratospheric Water Vapor and Ozone

Ozone and water vapor in the lower stratosphere are important trace gases for atmospheric chemistry and radiative budget. The Stratospheric Aerosol and Gas Experiment (SAGE) missions have been crucial in monitoring the stratospheric ozone loss and the subsequent recovery as well as the trends in water vapor linked to surface temperature trends. The SAGE III instrument aboard the International Space Station (ISS) continues the SAGE mission record, with high vertical resolution profiles of ozone and water vapor available since mid 2017. The NASA GEOS Earth system model has the new capability to assimilate multi-constituents from ground and space-based instruments using the GEOS Constituent Data Assimilation System (CoDAS). The recently released MERRA-2 Stratospheric Composition Reanalysis with Aura MLS (M2-SCREAM) assimilates version 4.2 MLS ozone, water vapor and other chemically-reactive species with the NASA GEOS model coupled to a stratospheric-only chemistry mechanism and transport constrained to the MERRA-2 reanalysis. While the number of solar occultation observations a day from SAGE III/ISS is about 1% of the total number of profiles observed globally by MLS, the chemical timescales of ozone and water vapor in the lower stratosphere are long enough that the SAGE III/ISS data may provide a useful constraint on the assimilated product. Using the same GEOS CoDAS configuration as M2-SCREAM, we will present a series of experiments to investigate if ozone and water vapor trends are consistent with the assimilation of SAGE observations with and without Aura retrievals, and to determine if the assimilation of SAGE observations produces a steady product for trend analysis, especially as the end of the Aura mission nears. In our experiments, assimilating only SAGE III/ISS water vapor profiles results in water vapor fields more consistent with experiments that assimilate MLS v5; however, in the polar regions SAGE III/ISS observations are not available and the values are unconstrained. We are encouraged by the positive benefit assimilating the less frequent SAGE III/ISS observations has on stratospheric composition. Sensitivity experiments such as these will allow us to assess the added value of SAGE data for continued monitoring of the stratospheric composition for climate and ozone recovery assessments.

SAGE↗
NASA NTRS2022

Re-Evaluation of Low Cloud Amount Relationships With Lower-Tropospheric Stability and Estimated Inversion Strength

Lower-tropospheric stability (LTS) and estimated inversion strength (EIS) have a widely accepted relationship with low cloud amount and are key observational foundations for understanding and modeling low-level stratiform clouds. Using the updated surface-based and satellite cloud data, we find that low cloud amount is not as strongly correlated with LTS, and not as sensitive to LTS, as established in the past. EIS does not provide a stronger correlation with low cloud amount than LTS over all eight regions (including the midlatitudes). Further analyzing the relationships between LTS and EIS with different types of low clouds, we find that there is a strong correlation of LTS and EIS with stratocumulus only. This explains the weaker correlation of low cloud fraction (including cumulus, stratocumulus, and stratus) to both LTS and EIS. These results also suggest the need to re-evaluate these relationships in Earth system models. Plain Language Summary: Low-level clouds play an important role in the global radiation budget. Low cloud amount has two established linear relationships with lower-tropospheric stability (LTS) and estimated inversion strength (ETS). These two relationships are re-evaluated here using three separate observational cloud and two reanalysis datasets for three distinct but overlapping time periods. The analysis shows that the strength of the LTS and ETS relationships with low cloud amount varies, depending on the cloud data used. They have a strong relationship with stratocumulus cloud amount only.

Lauren Cutler↗
NASA NTRS2020

Optimized Profile Retrievals of Aerosol Microphysical Properties from Simulated Spaceborne Multiwavelength Lidar

This work is an expanded study of one previously published onretrievals of aerosol microphysical properties from space-borne multiwavelengthlidarmeasurements. The earlier studiesand this one weredone in the framework of the NASA Aerosol-Clouds-Ecosystems (now the Aerosol Clouds Convection and Precipitation) NASA mission. The focus here is on the capabilities of a simulated spacebornemultiwavelengthlidar system for retrieving aerosol complex refractive index (m = mr+ imi) and spectral single scattering albedo (SSA(λ)), although other bulk parameters such as effective (reff) radius and particle volume (V) and surface (S) concentrations are also studied. The novelty presented here is the use of recently published, case dependent optimized-constraints on the microphysical retrievals using three backscattering coefficients (β) at 355, 532 and 1064 nm and two extinction coefficients (α) at 355 and 532 nm, typically known as the stand-alone 3β+2α lidar inversion. Case-dependent optimized-constraints (CDOC) limit the ranges of refractive index, both real (mr) and imaginary (mi) parts, and of radii that are permitted in the retrievals. Such constraints are selected directly from the 3β+2α41measurements through an analysis of the relationship between spectral dependence of aerosol extinction-to-backscatter ratios (LR) and the Ångström exponent of extinction. The analyses presented here for different sets ofsize distributions and refractive indices reveal that the direct determination of CDOCareonly feasible for cases where the uncertaintiesin the input optical data areless than 15 %.Forthe same simulated spacebornesystem and yield than in Whiteman et al., (2018), we demonstrated that the use of CDOC as essential for the retrievals of refractive index and also largely improved retrieval of bulk parameters. A discussion of the global representativeness of CDOC is presented using simulated lidar data from a 24-hour satellite track using GEOS model output to initialize the lidar simulator.We found that CDOCare representative of many aerosol mixtures in spite of some outliers (e.g. highly hydrated particles) associatedwith the assumptions of bimodal size distributions and of the same refractive index for fine and coarse modes. Moreover, sensitivity tests performed using synthetic data reveal that retrievals of imaginary refractive index (mi) and SSA are extremely sensitive to β(355).

NASA Aerosol-Clouds-Ecosystems↗
NASA NTRS2000

The Geoscience Laser Altimeter System (GLAS) for the ICESAT Mission

The Laser In space Technology Experiment, Shuttle Laser Altimeter and the Mars Observer Laser Altimeter have demonstrated accurate measurements of atmospheric backscatter and Surface heights from space. The recent MOLA measurements of the Mars surface have 40 cm vertical resolution and have reduced the global uncertainty in Mars topography from a few km to about 5 m. The Geoscience Laser Altimeter System (GLAS) is a next generation lidar for Earth orbit being developed as part of NASA's Icesat Mission. The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, establish a grid of accurate height profiles of the Earth's land topography, and profile the vertical backscatter of clouds and aerosols on a global scale. GLAS is being developed to fly on a small dedicated spacecraft in a polar orbit with a 590 630 km altitude at inclination of 94 degrees. GLAS is scheduled to launch in the summer 2001 and to operate continuously for a minimum of 3 years with a goal of 5 years. The primary mission for GLAS is to measure the seasonal and annual changes in the heights of the Greenland and Antarctic ice sheets. GLAS will continuously measure the vertical distance from orbit to the Earth's surface with 1064 nm pulses from a ND:YAG laser at a 40 Hz rate. Each 5 nsec wide laser pulse is used to produce a single range measurement, and the laser spots have 66 m diameter and about 170 m center-center spacings. When over land GLAS will profile the heights of the topography and vegetation. The GLAS receiver uses a 1 m diameter telescope and a Si APD detector. The detector signal is sampled by an all digital receiver which records each surface echo waveform with I nsec resolution and a stored echo record lengths of either 200, 400, or 600 samples. Analysis of the echo waveforms within the instrument permits discrimination between cloud and surface echoes. Ground based echo analysis permits precise ranging, determining the roughness or slopes of the surface as well as the vertical distributions of vegetation illuminated by the laser. Accurate knowledge of the laser beam's pointing angle is needed to prevent height biases when over sloped surfaces. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam's centroid to about 8 urad is needed to achieve 10 cm height accuracy. GLAS uses a stellar reference system (SRS) to determine the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith and a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser is measured pulse relative to the star camera with a laser reference system (LRS). Optically measuring each laser far field pattern relative to the orientation of the star camera and gyroscope permits the precise pointing angle of each laser pulse to be determined. GLAS will also determine the vertical distributions of clouds and aerosols by measuring the vertical profile of laser energy backscattered by the atmosphere at both 1064 and 532 nm. The 1064 nm measurements use the Si APD detector and profile the height and vertical structure of thicker clouds. The measurements at 532 nm use new highly sensitive photon counting, detectors, and measure the height distributions of very thin Clouds and aerosol layers. With averaging these can be used to determine the height of the planetary boundary layer. The instrument design and expected performance will be discussed.

Abshire, James B.↗
DOE OSTI2023

Surface temperature comparison of the Arctic winter MOSAiC observations, ERA5 reanalysis, and MODIS satellite retrieval

Atmospheric model systems, such as those used for weather forecast and reanalysis production, often have significant and systematic errors in their representation of the Arctic surface energy budget and its components. The newly available observation data of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (2019/2020) enable a range of model analyses and validation in order to advance our understanding of potential model deficiencies. In the present study, we analyze deficiencies in the surface radiative energy budget over Arctic sea ice in the ERA5 global atmospheric reanalysis by comparing against the winter MOSAiC campaign data, as well as, a pan-Arctic level-2 MODIS ice surface temperature remote sensing product. We find that ERA5 can simulate the timing of radiatively clear periods, though it is not able to distinguish the two observed radiative Arctic winter states, radiatively clear and opaquely cloudy, in the distribution of the net surface radiative budget. The ERA5 surface temperature over Arctic sea ice has a conditional error with a positive bias in radiatively clear conditions and a negative bias in opaquely cloudy conditions. The mean surface temperature error is 4°C for radiatively clear situations at MOSAiC and up to 15°C in some parts of the Arctic. The spatial variability of the surface temperature, given by 4 observation sites at MOSAiC, is not captured by ERA5 due to its spatial resolution but represented in the level-2 satellite product. The sensitivity analysis of possible error sources, using satellite products of snow depth and sea ice thickness, shows that the positive surface temperature errors during radiatively clear events are, to a large extent, caused by insufficient sea ice thickness and snow depth representation in the reanalysis system. A positive bias characterizes regions with ice thickness greater than 1.5 m, while the negative bias for thinner ice is partly compensated by the effect of snow.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

The Influence of Summertime Convection Over Southeast Asia on Water Vapor in the Tropical Stratosphere

The relative contributions of Southeast Asian convective source regions during boreal summer to water vapor in the tropical stratosphere are examined using Lagrangian trajectories. Convective sources are identified using global observations of infrared brightness temperature at high space and time resolution, and water vapor transport is simulated using advection-condensation. Trajectory simulations are driven by three different reanalysis data sets, GMAO MERRA, ERA-Interim, and NCEP/NCAR, to establish points of consistency and evaluate the sensitivity of the results to differences in the underlying meteorological fields. All ensembles indicate that Southeast Asia is a prominent boreal summer source of tropospheric air to the tropical stratosphere. Three convective source domains are identified within Southeast Asia: the Bay of Bengal and South Asian subcontinent (MON), the South China and Philippine Seas (SCS), and the Tibetan Plateau and South Slope of the Himalayas (TIB). Water vapor transport into the stratosphere from these three domains exhibits systematic differences that are related to differences in the bulk characteristics of transport. We find air emanating from SCS to be driest, from MON slightly moister, and from TIB moistest. Analysis of pathways shows that air detrained from convection over TIB is most likely to bypass the region of minimum absolute saturation mixing ratio over the equatorial western Pacific; however, the impact of this bypass mechanism on mean water vapor in the tropical stratosphere at 68 hPa is small 0.1 ppmv). This result contrasts with previously published hypotheses, and it highlights the challenge of properly quantifying fluxes of atmospheric humidity.

Wright, J. S.↗
NASA NTRS2016

Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

A global, monthly averaged time series of Sun-induced Fluorescence (SiF), spanning January 2007 to June 2015, was derived from Metop-A Global Ozone Monitoring Experiment 2 (GOME-2) spectral measurements. Far-red SiF was retrieved using the filling-in of deep solar Fraunhofer lines and atmospheric absorption bands based on the general methodology described by Joiner et al, AMT, 2013. A Principal Component (PC) analysis of spectra over non-vegetated areas was performed to describe the effects of atmospheric absorption. Our implementation (SiF KNMI) is an independent algorithm and differs from the latest implementation of Joiner et al, AMT, 2013 (SiF NASA, v26), because we used desert reference areas for determining PCs (as opposed to cloudy ocean and some desert) and a wider fit window that covers water vapour and oxygen absorption bands (as opposed to only Fraunhofer lines). As a consequence, more PCs were needed (35 as opposed to 12). The two time series (SiF KNMI and SiF NASA, v26) correlate well (overall R of 0.78) except for tropical rain forests. Sensitivity experiments suggest the strong impact of the water vapour absorption band on retrieved SiF values. Furthermore, we evaluated the SiF time series with Gross Primary Productivity (GPP) derived from twelve flux towers in Australia. Correlations for individual towers range from 0.37 to 0.84. They are particularly high for managed biome types. In the de-seasonalized Australian SiF time series, the break of the Millennium Drought during local summer of 2010/2011 is clearly observed.

Australia↗
DOE OSTI2024

Globally optimal interferometry with lossy twin Fock probes

Parity or quadratic spin (e.g., J z 2 ) readouts of a Mach–Zehnder (MZ) interferometer probed with a twin Fock (TF) input state allow saturating the optimal sensitivity attainable among all mode-separable states with a fixed total number of particles but only when the interferometer phase θ is near zero. When more general Dicke state probes are used, the parity readout saturates the quantum Fisher information (QFI) at θ = 0, whereas better-than-standard quantum limit performance of the J z 2 readout is restricted to an o ( N ) occupation imbalance. We show that a method of moments readout of two quadratic spin observables J z 2 and J + 2 + J − 2 is globally optimal for Dicke state probes; i.e., the error saturates the QFI for all θ . In the lossy setting, we derive the time-inhomogeneous Markov process describing the effect of particle loss on TF states, showing that the method of moments readout of four at-most-quadratic spin observables is sufficient for globally optimal estimation of θ when two or more particles are lost. The analysis culminates in a numerical calculation of the QFI matrix for distributed MZ interferometry on the four-mode state | N 4 , N 4 , N 4 , N 4 〉 and its lossy counterparts, showing that an advantage for the estimation of any linear function of the local MZ phases θ 1 and θ 2 (compared to independent probing of the MZ phases by two copies of | N 4 , N 4 〉 ) appears when more than one particle is lost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2016

Towards a Radar/Radiometer Mode on the Dual-Frequency, Dual-Polarized, Doppler Radar (D3R) System

The dual-­frequency, dual-­polarized, Doppler radar (D3R) system was developed in support of the ground validation segment of the Global Precipitation Measurement (GPM) mission. Although its main purpose is to provide active, Ku/Ka­‐band, dual­‐polarized measurements of precipitation, the design presents an opportunity to study its operation in an active/passive mode. The opportunity arises from use of solid-­state transmitters employing a multi­‐frequency waveform and receiving system. Typically, a sequence of three pulses separated in frequency is transmitted to achieve its radar sensitivity and minimum range. However, one of the three pulses can be disabled with a tolerable decrease in sensitivity and its receive channel can be repurposed to support passive measurements. This work focuses on progress in the characterization of the Ku-­band H polarized passive channel operating simultaneously with two active as a step towards the provision of brightness temperatures along with the other radar derived products. The methodology developed will be applied to the V polarized channel and Ka­‐band subsystem in the near future. The study consists on the analysis of the antenna performance, receiver architecture, transfer function and achievable number of independent samples, calibration method and preliminary observation analysis. All within the context of the instrument's current configuration and possible future improvements.

radar↗
NASA NTRS2019

New York City Panel on Climate Change 2019 Report Chapter 4: Coastal Flooding

Coastal flooding from storm surge is one of the most dangerous and damaging natural hazards that societies face. It was responsible for half of all hurricane related mortalities in the United States from 1963 to 2012, far more than any other factor. Coastal extreme water levels are increasing globally, mainly driven by rises in mean sea level. Sea level rise is also causing rapid increases in the annual number of shallow “nuisance floods” for low-lying neighborhoods. The objectives of this chapter are to review the latest knowledge on New York City flood risk from storms and tides, and to evaluate how climate change will affect this risk between now and the end of the century. Methods used by NPCC (2015) for assessing storm-driven extreme floods are generally repeated here, including the use of the Federal Emergency Management Agency (FEMA, 2013) baseline flood hazards (e.g., the 100-year flood(sup a)) and the methods for adding sea level rise and mapping the resulting hazard. New advancements include an innovative analysis of monthly tidal flooding based on a dynamic model, a broadened set of sea level rise scenarios supplemented with the Antarctic Rapid Ice Melt (ARIM) scenario (see Chapter 3), and sensitivity analyses that show how differing methods would affect our results. Wind is a primary factor for coastal storm surge, and a brief review is given in Appendix 4.A, with the latest scientific knowledge on what drives extreme wind events in the New York City area and how they may change in the future.

Orton, Philip↗
DOE OSTI2024

Core Design Optimization of the Westinghouse Lead Fast Reactor

Westinghouse is pursuing an advanced Nuclear Power Plant design based on Lead Fast Reactor (LFR) technology for global commercialization. To achieve an optimal combination of key attributes, such as safety, sustainability, and economic competitiveness, Westinghouse and ANL partnered in developing and applying a formalized core design optimization strategy. An LFR analysis workflow was developed to automate a suite of reactor physics, fuels performance, safety, and economics simulations on a selected LFR concept. The workflow streamlines analysis of a wide range of LFR designs with different dimensions and fuel types to assess their viability and economic performance, significantly reducing human processing time and risks of processing errors. The LFR optimization exercise was defined, resulting in selection of the design constraints (geometric, neutronics, thermo-mechanical, safety, thermal-hydraulics, and economics) and performance metrics researched (minimization of both the fuels LCOE and the first core inventory cost). A total of 14 varied design parameters were considered, including assembly dimensions, coolant temperature, and enrichment distribution throughout the core. The LFR analysis workflow was connected to DAKOTA for sensitivity and optimization analyses. Due to the extremely large size of the potential LFR optimization solution space relative to the computing time required to characterize one LFR solution, a multi-stage optimization approach was proposed to breakdown the problem into several stages with more reasonable sizes. This optimization approach enabled finding various viable core solutions with different cost tradeoffs that were considered by Westinghouse and justify selection of a smaller core with multi-batch 2-year cycle length.

Stauff, Nicolas E.↗
NASA NTRS2002

Sensitivity Studies for Assimilated Ozone Profiles

An ozone data assimilation system at the NASA/Goddard Data Assimilation Office (DAO) produces three-dimensional global ozone fields. They are obtained by assimilating ozone retrieved from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) measurements into an off-line parameterized chemistry and transport model. In this talk we focus on the quality of lower stratospheric assimilated ozone profiles. Ozone in the lower stratosphere plays a key role in the forcing of climate. A biased ozone field in this region will adversely impact calculations of the stratosphere-troposphere exchange and, when used as a first guess in retrievals, the values determined from satellite observations. The SBUV/2 ozone data have a coarse vertical resolution with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone profiles in the lower stratosphere are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. We investigate the sensitivity of assimilated ozone profiles to changes in a variety of system inputs: TOMS and SBUV/2 data selection, forecast and observations error covariance models, inclusion or omission of a parameterized chemistry model, and different versions of DAO assimilated wind fields used to drive the transport model. Comparisons of assimilated ozone fields with independent observations, primarily ozone sondes, are used to determine the impact of each of these changes.

Stajner, Ivanka↗
NASA NTRS2009

Overview of Proposal on High Resolution Climate Model Simulations of Recent Hurricane and Typhoon Activity: The Impact of SSTs and the Madden Julian Oscillation

This talk gives an update on the progress and further plans for a coordinated project to carry out and analyze high-resolution simulations of tropical storm activity with a number of state-of-the-art global climate models. Issues addressed include, the mechanisms by which SSTs control tropical storm. activity on inter-annual and longer time scales, the modulation of that activity by the Madden Julian Oscillation on sub-seasonal time scales, as well as the sensitivity of the results to model formulation. The project also encourages companion coarser resolution runs to help assess resolution dependence, and. the ability of the models to capture the large-scale and long-terra changes in the parameters important for hurricane development. Addressing the above science questions is critical to understanding the nature of the variability of the Asian-Australian monsoon and its regional impacts, and thus CLIVAR RAMP fully endorses the proposed tropical storm simulation activity. The project is open to all interested organizations and investigators, and the results from the runs will be shared among the participants, as well as made available to the broader scientific community for analysis.

Schubert, Siegfried↗