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Observing System Simulations for the AOS Mission

The Earth System Observatory (ESO) is NASA’s response to the recommendations of the 2017 Earth Sciences Decadal Survey conducted by the US National Academy of Sciences, Engineering and Medicine. The ESO is being conceived as a set of fully integrated missions addressing 4 main Earth science focus areas including aerosols, clouds, convection and precipitation (jointly re-ferred to as AOS, the Atmosphere Observing System). ESO ground breaking observations will provide critical measurements to address societally relevant problems in climate change, natural hazard mitiga-tion, fighting forest fires, and improving real-time agricultural processes. A critical element of the AOS observing strategy is to make extensive use of new passive and active sen-sors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. In order to achieve maximum benefit, all these observations need to be integrated into comprehensive observing and modeling/data assimilation systems. Such an approach requires compre-hensive model-data synthesis capabilities that needs to be conceived in conjunction with the space-based and suborbital components of AOS. In this presentation we will summarize the major science goals of AOS including cloud feedbacks, at-mospheric convection, emphasizing aerosol processes and aerosol radiative effects, and the synergistic aspects of clouds-precipitation-aerosol interactions. We will describe examples of the observing system simulation capabilities being developed for AOS, including global storm resolving nature runs, detailed instrument and retrieval simulators, as well as fast retrieval emulators for instrumenting climate models. This simulation environment, being developed under NASA’s open-source science initiative, will permit us to explore how AOS data will be used across space and time to better initialize forecasts and train modeling systems, and to infuse models and data assimilation systems with AOS data, well before launch.

Arlindo da Silva↗

NASA NTRS2006

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗

DOE OSTI2024

Improvement and generalization of ABCD method with Bayesian inference

To find New Physics or to refine our knowledge of the Standard Model at the LHC is an enterprise that involves many factors, such as the capabilities and the performance of the accelerator and detectors, the use and exploitation of the available information, the design of search strategies and observables, as well as the proposal of new models. We focus on the use of the information and pour our effort in re-thinking the usual data-driven ABCD method to improve it and to generalize it using Bayesian Machine Learning techniques and tools. We propose that a dataset consisting of a signal and many backgrounds is well described through a mixture model. Signal, backgrounds and their relative fractions in the sample can be well extracted by exploiting the prior knowledge and the dependence between the different observables at the event-by-event level with Bayesian tools. We show how, in contrast to the ABCD method, one can take advantage of understanding some properties of the different backgrounds and of having more than two independent observables to measure in each event. In addition, instead of regions defined through hard cuts, the Bayesian framework uses the information of continuous distribution to obtain soft-assignments of the events which are statistically more robust. To compare both methods we use a toy problem inspired by pp\to hh\to b\bar b b \bar b p p → h h → b b ‾ b b ‾ , selecting a reduced and simplified number of processes and analysing the flavor of the four jets and the invariant mass of the jet-pairs, modeled with simplified distributions. Taking advantage of all this information, and starting from a combination of biased and agnostic priors, leads us to a very good posterior once we use the Bayesian framework to exploit the data and the mutual information of the observables at the event-by-event level. We show how, in this simplified model, the Bayesian framework outperforms the ABCD method sensitivity in obtaining the signal fraction in scenarios with 1% and 0.5% true signal fractions in the dataset. We also show that the method is robust against the absence of signal. We discuss potential prospects for taking this Bayesian data-driven paradigm into more realistic scenarios.

Alvarez, Ezequiel↗

DOE OSTI2023

Structural transition and chemical reactivity of atomic carbon chains

The sp-hybridized carbon chain (carbyne) is a representative 1D atomic material, whose bonding structure and chemical reactivity have remained a mystery for a century. Here, in this work, we report the unexpected alternating bond orders of 1.4 and 2.6 for the most stable carbon chain and the in situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) detection of the temperature-dependent reversible change of the bond order alternation. Moreover, we revealed its reactivities with O 2 , H 2 , and CO 2 at temperatures up to 600 °C and created an end-group-protection strategy to stabilize it. These observations open a new door to the chemistry of atomic materials.

25 ENERGY STORAGE↗

DOE OSTI2023

CDK4/6 inhibition enhances SHP2 inhibitor efficacy and is dependent upon RB function in malignant peripheral nerve sheath tumors

Malignant peripheral nerve sheath tumors (MPNSTs) are highly aggressive soft tissue sarcomas with limited treatment options, and new effective therapeutic strategies are desperately needed. We observe antiproliferative potency of genetic depletion of PTPN11 or pharmacological inhibition using the SHP2 inhibitor (SHP2i) TNO155. Our studies into the signaling response to SHP2i reveal that resistance to TNO155 is partially mediated by reduced RB function, and we therefore test the addition of a CDK4/6 inhibitor (CDK4/6i) to enhance RB activity and improve TNO155 efficacy. In combination, TNO155 attenuates the adaptive response to CDK4/6i, potentiates its antiproliferative effects, and converges on enhancement of RB activity, with greater suppression of cell cycle and inhibitor-of-apoptosis proteins, leading to deeper and more durable antitumor activity in in vitro and in vivo patient-derived models of MPNST, relative to either single agent. Overall, our study provides timely evidence to support the clinical advancement of this combination strategy in patients with MPNST and other tumors driven by loss of NF1.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2022

Surface Biology and Geology (SBG) Visible to Short Wavelength Infrared (VSWIR) Wide Swath Instrument Concept

The 2017 Decadal Survey: Thriving on Our Changing Planet, A Decadal Strategy for Earth Observation from Space has called new observations including global coverage Visible to Short Wavelength Infrared (VSWIR) Wide Swath (WS) imaging spectroscopy measurements as part of the Surface Biology and Geology (SBG) Designated Observable. The SBG VSWIR-WS along with the companion SBG Thermal Infrared (TIR) imager is an important element of NASA’s larger Earth System Observatory (ESO).

Walch, Marc↗

NASA NTRS2022

Surface Biology and Geology (SBG) Visible to Short Wavelength Infrared (VSWIR) Wide Swath Instrument Concept

The 2017 Decadal Survey: Thriving on Our Changing Planet, A Decadal Strategy for Earth Observation from Space has called new observations including global coverage VSWIR Wide Swath (VSWIR-WS) imaging spectroscopy measurements as part of the Surface Biology and Geology (SBG) Designated Observable. The SBG VSWIR-WS along with the companion SBG Thermal Infrared (TIR) imager is an important element of NASA’s larger Earth System Observatory (ESO).

Walch, Marc↗

NASA NTRS2011

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗

NASA NTRS2012

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗

NASA NTRS2010

The Utility of the OMI HCHO/NO2 in Air Quality Decision-Making Activities

I will discuss a novel and practical application of the OMI HCHU and NO2 data products to the "weight of evidence" in the air quality decision-making process (e.g., State Implementation Plan (SIP)) for a city, region, or state to demonstrate that it is making progress toward attainment of the National Ambient Air Quality Standard (NAAQS) for ozone. Any trend, or lack thereof, in the observed OMI HCHO/NO2 may support that an emission control strategy implemented to reduce ozone is or is not occurring for a metropolitan area. In addition, the observed OMI HCHO/NO2 may be used to define new emission control strategies as the photochemical environments of urban areas evolve over time. I will demonstrate the utility of the OMI HCHO/NO2 over the U.S. for air quality applications with support from simulations with both a regional model and a photochemical box model. These results support mission planning of an OMI-like instrument for the proposed GEO-CAPE satellite that has as one of its objectives to study air quality from space. However, I'm attending the meeting as the Aura Deputy Project Scientist, so I don't technically need to present anything to justify the travel.

Duncan, Bryan↗

NASA NTRS1996

Mission to Planet Earth Strategic Enterprise Plan 1996-2002

Mission to Planet Earth's (MTPE's) first Strategic Enterprise Plan, issued in May 1995, defined the Agency's major goals and objectives as well as constraints. This update of the Strategic Enterprise Plan identifies the following major changes: a focused Science Research Plan that integrates space-based and in situ observational critical science to address critical science uncertainties; a technology infusion plan to reduce the cost of future missions; a series of flight opportunities to infuse new science into the overall program; and a tighter coupling between NASA and NOAA to reduce costs and to improve the overall program. Three important new initiatives are also under development and are described briefly in this plan: MTPE Education Strategy, MTPE Commercial Strategy, and an emerging concept for an Integrated Global Observing Strategy. This first update to the MTPE Strategic Enterprise Plan captures these new developments, and takes a significant step forward in planning this complex Earth system science endeavor. The plan and other information on MTPE may be viewed via the Internet at http://www.hq.nasa.gov/office/mtpe/.

Source record↗

DOE OSTI2022

Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements

Abstract. Large changes in the Arctic carbon balance are expected as warming linked to climate change threatens to destabilize ancient permafrost carbon stocks. The eddy covariance (EC) method is an established technique to quantify net losses and gains of carbon between the biosphere and atmosphere at high spatiotemporal resolution. Over the past decades, a growing network of terrestrial EC tower sites has been established across the Arctic, but a comprehensive assessment of the network's representativeness within the heterogeneous Arctic region is still lacking. This creates additional uncertainties when integrating flux data across sites, for example when upscaling fluxes to constrain pan-Arctic carbon budgets and changes therein. This study provides an inventory of Arctic (here > = 60∘ N) EC sites, which has also been made available online (https://cosima.nceas.ucsb.edu/carbon-flux-sites/, last access: 25 January 2022). Our database currently comprises 120 EC sites, but only 83 are listed as active, and just 25 of these active sites remain operational throughout the winter. To map the representativeness of this EC network, we evaluated the similarity between environmental conditions observed at the tower locations and those within the larger Arctic study domain based on 18 bioclimatic and edaphic variables. This allows us to assess a general level of similarity between ecosystem conditions within the domain, while not necessarily reflecting changes in greenhouse gas flux rates directly. We define two metrics based on this representativeness score: one that measures whether a location is represented by an EC tower with similar characteristics (ER1) and a second for which we assess if a minimum level of representation for statistically rigorous extrapolation is met (ER4). We find that while half of the domain is represented by at least one tower, only a third has enough towers in similar locations to allow reliable extrapolation. When we consider methane measurements or year-round (including wintertime) measurements, the values drop to about 1/5 and 1/10 of the domain, respectively. With the majority of sites located in Fennoscandia and Alaska, these regions were assigned the highest level of network representativeness, while large parts of Siberia and patches of Canada were classified as underrepresented. Across the Arctic, mountainous regions were particularly poorly represented by the current EC observation network. We tested three different strategies to identify new site locations or upgrades of existing sites that optimally enhance the representativeness of the current EC network. While 15 new sites can improve the representativeness of the pan-Arctic network by 20 %, upgrading as few as 10 existing sites to capture methane fluxes or remain active during wintertime can improve their respective ER1 network coverage by 28 % to 33 %. This targeted network improvement could be shown to be clearly superior to an unguided selection of new sites, therefore leading to substantial improvements in network coverage based on relatively small investments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2013

1SXPS: A Deep Swift X-Ray Telescope Point Source Catalog with Light Curves and Spectra

We present the 1SXPS (Swift-XRT point source) catalog of 151,524 X-ray point sources detected by the Swift-XRT in 8 yr of operation. The catalog covers 1905 sq deg distributed approximately uniformly on the sky. We analyze the data in two ways. First we consider all observations individually, for which we have a typical sensitivity of approximately 3 × 10(exp −13) erg cm(exp −2) s(exp −1) (0.3-10 keV). Then we co-add all data covering the same location on the sky: these images have a typical sensitivity of approximately 9 × 10(exp −14) erg cm(exp −2) s(exp −1) (0.3-10 keV). Our sky coverage is nearly 2.5 times that of 3XMM-DR4, although the catalog is a factor of approximately 1.5 less sensitive. The median position error is 5.5 (90% confidence), including systematics. Our source detection method improves on that used in previous X-ray Telescope (XRT) catalogs and we report greater than 68,000 new X-ray sources. The goals and observing strategy of the Swift satellite allow us to probe source variability on multiple timescales, and we find approximately 30,000 variable objects in our catalog. For every source we give positions, fluxes, time series (in four energy bands and two hardness ratios), estimates of the spectral properties, spectra and spectral fits for the brightest sources, and variability probabilities in multiple energy bands and timescales.

telescope↗

DOE OSTI2025

New Ideas on the Formation and Astrophysical Detection of Primordial Black Holes

Recently, a number of novel scenarios for primordial black hole (PBH) formation have been discovered. Some of them require very minimal new physics, some others require no new ingredients besides those already present in commonly considered models, such as supersymmetry. At the same time, new strategies have emerged for detection of PBHs. For example, an observation of an orphan kilonova unaccompanied by the gravitational waves signal of merging neutron stars, but associated with a fast radio burst, could be a smoking gun of PBH dark matter. We review some new ideas for PBH formation and detection.

Flores, Marcos M.↗

NASA NTRS1986

Solution of nonlinear finite difference ocean models by optimization methods with sensitivity and observational strategy analysis

The paper studies with finite difference nonlinear circulation models the uncertainties in interesting flow properties, such as western boundary current transport, potential and kinetic energy, owing to the uncertainty in the driving surface boundary condition. The procedure is based upon nonlinear optimization methods. The same calculations permit quantitative study of the importance of new information as a function of type, region of measurement and accuracy, providing a method to study various observing strategies. Uncertainty in a model parameter, the bottom friction coefficient, is studied in conjunction with uncertain measurements. The model is free to adjust the bottom friction coefficient such that an objective function is minimized while fitting a set of data to within prescribed bounds. The relative importance of the accuracy of the knowledge about the friction coefficient with respect to various kinds of observations is then quantified, and the possible range of the friction coefficients is calculated.

Schroeter, Jens↗

NASA NTRS1990

Tropical Pacific moisture variability: Its detection, synoptic structure and consequences in the general circulation

Satellite data analysis tools are developed and implemented for the diagnosis of atmospheric circulation systems over the tropical Pacific Ocean. The tools include statistical multi-variate procedures, a multi-spectral radiative transfer model, and the global spectral forecast model at NMC. Data include in-situ observations; satellite observations from VAS (moisture, infrared and visible) NOAA polar orbiters (including Tiros Operational Satellite System (TOVS) multi-channel sounding data and OLR grids) and scanning multichannel microwave radiometer (SMMR); and European Centre for Medium Weather Forecasts (ECHMWF) analyses. A primary goal is a better understanding of the relation between synoptic structures of the area, particularly tropical plumes, and the general circulation, especially the Hadley circulation. A second goal is the definition of the quantitative structure and behavior of all Pacific tropical synoptic systems. Finally, strategies are examined for extracting new and additional information from existing satellite observations. Although moisture structure is emphasized, thermal patterns are also analyzed. Both horizontal and vertical structures are studied and objective quantitative results are emphasized.

Mcguirk, James P.↗

NASA NTRS1992

The abundances of the elements in sharp-lined early type stars

An International Ultraviolet Explorer (IUE) observing strategy that has yielded co-added spectra with enhanced S/N ratios for several A and B stars was established. New observations by Roby and Adelman using the same technique were added two new Hg-Mn stars into this sample. A long-term study of elemental abundances in this uniform, high-quality set of IUE spectra for 13 stars was begun. The first stages of this project are reported: abundances for N, Cr, Mn, Fe, Co, and Ni. The study of the Fe-peak elements show that our data set can provide accurate abundances and that abundances obtained from UV and optical spectra often are in good agreement. The groundwork for selfconsistent abundance analyses of more exotic elements in our long term project was provided.

Adelman, Saul J.↗

NASA NTRS2008

Using Sensor Web Processes and Protocols to Assimilate Satellite Data into a Forecast Model

The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

Goodman, H. Michael↗