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NASA NTRS2020

Designing an Optimal Ensemble Strategy for GMAO S2S Forecast System

The NASA Global Modeling and Assimilation Office (GMAO) Sub-seasonal to Seasonal (S2S) prediction system is being readied for a major upgrade. An important factor in successful extended range forecasting is the definition of the ensemble. Our overall strategy is to run a relatively large ensemble of about 40 members up to 3 months (focusing on the sub-seasonal forecast problem), after which we sub-sample the ensemble, and continue the forecast with about 10 members (up to 12 months). Here we present the results of our testing of various ways to generate the initial perturbations and the validation of a stratified sampling approach for choosing the members of the smaller ensemble. For the initialization of the ensemble we propose a combination of lagged and burst initial conditions. To generate perturbations for the burst ensemble members we used scaled differences of pairs of analysis states (chosen randomly from the corresponding season) separated by 1-10 days. We consider perturbing separately the atmosphere and the ocean, or both. By varying the separation times between the analysis states, we are able to produce perturbations that resemble well-known modes of variability. Focusing on the ENSO SST indices, we found that all types of perturbations are important for the ensemble spread with, however, considerable differences in the timing of the impacts on spread for the atmospheric and oceanic perturbations.Our initial (larger) ensemble size was determined so as to maximize the skill of predicting some of the leading modes of boreal winter atmospheric modes (namely the NAO, PNA and AO). Since it is not feasible for us to run with the larger ensemble beyond about 3 months, we employ a stratified sampling procedure that identifies the emerging directions of error growth to subset the ensemble. By comparing the results from the stratified ensemble with that of the randomly sampled ensemble of the same size, we find that the former provides substantially better estimates the mean of the original large ensemble.

Borovikov, Anna↗
NASA NTRS2020

Designing an Optimal Ensemble Strategy for GMAO S2S Forecast System

GMAO Sub/Seasonal prediction system (S2S) is being readied for a major upgrade to GEOS-S2S Version 3. An important factor in successful extended range forecast is the definition of an ensemble For initialization of the ensemble we propose a combination of lagged and burst initial conditions. We plan to run a relatively large ensemble of 40 members for sub-seasonal forecast (up to 3 months), at which point we sub-sample the ensemble, and continue the forecast with 10 members (up to 12 months). Here we present the results of the extensive testing of various ways to generate the perturbations to the initial conditions and the validation of the stratified sampling strategy we chose.To generate perturbations for the burst ensemble members we used scaled differences of pairs of analysis states separated by 1-10 days, randomly chosen from a corresponding season. We considered perturbing separately only the atmospheric fields or only the ocean or both of the forecast initial conditions. Considering varying separation times between the analysis states, we were able to produce perturbations sampling various modes of variability. Focusing on the ENSO SST indices, we found that all types of perturbations are important for the ensemble spread.Our ensemble size for sub-seasonal forecasts was determined as to maximize the skill of predicting some of the leading modes of boreal winter atmospheric modes, NAO, PNA and AO. It is not feasible to run equally large ensemble for seasonal forecasts. Using a stratified sampling procedure we can identify the emerging directions of error growth. By comparing the stratified ensemble with randomly sampled ensemble of the same size, we were able to show that the former better estimates the mean of the original large ensemble.

Borovikov, Anna↗
NASA NTRS2018

Optical Performance Prediction of the Thirty Meter Telescope after Initial Alignment Using Optical Modeling

We present an estimate of the optical performance of the Thirty Meter Telescope (TMT) after execution of the full telescope alignment plan. The TMT alignment is performed by the Global Metrology System (GMS) and the Alignment and Phasing System (APS). The GMS first measures the locations of the telescope optics and instruments as a function of elevation angle. These initial measurements will be used to adjust the optics positions and build initial elevation look-up tables. Then the telescope is aligned using starlight as the input for the APS at multiple elevation angles. APS measurements are used to refine the telescope alignment to build elevation and temperature dependent look-up tables. Due to the number of degrees of freedom in the telescope (over 10,000), the ability of the primary mirror to correct aberrations on other optics, the tight optical performance requirements and the multiple instrument locations, it is challenging to develop, test and validate these alignment procedures. In this paper, we consider several GMS and APS operational scenarios. We apply the alignment procedures to the model-generated TMT, which consists of various quasi-static errors such as polishing errors, passive supports errors, thermal and gravity deformations and installation position errors. Using an integrated optical model and Monte-Carlo framework, we evaluate the TMT’s aligned states using optical performance metrics at multiple instrument and field of view locations. The optical performance metrics include the Normalized Point Source Sensitivity (PSSN), RMS wavefront error before and after Adaptive Optics (AO) correction, pupil position change, and plate scale distortion.

Rogers, John↗
NASA NTRS2018

Nature of and Lessons Learned from Lunar Ice Cube and the First Deep Space Cubesat 'Cluster'

Cubesats operating in deep space face challenges Earth-orbiting cubesats do not. 15 deep space cubesat 'prototypes' will be launched over the next two years including the two MarCO cubesats, the 2018 demonstration of dual communication system at Mars, and the 13 diverse cubesats being deployed from the SLS EM1 mission within the next two years. Three of the EM1 cubesat missions, including the first deep space cubesat 'cluster', will be lunar orbiters with remote sensing instruments for lunar surface/regolith measurements. These include: Lunar Ice Cube, with its 1-4 micron broadband IR spectrometer, BIRCHES, to determine volatile distribution as a function of time of day; Lunar Flashlight, to confirm the presence of surface ice at the lunar poles, utilizing an active source (laser), and looking for absorption features in the returning signal; and LunaH-Map to characterize ice at or below the surface at the poles with a compact neutron spectrometer. In addition, the BIRCHES instrument on Lunar Ice Cube will provide the first demonstration of a microcryocooler (AIM/IRIS) in deep space. Although not originally required to do so, all will be delivering science data to the Planetary Data System, the first formal archiving effort for cubesats. 4 of the 20 recently NASA-sponsored (PSDS3) study groups for deep space cubesat/smallsat mission concepts were lunar mission concepts, most involving 12U cubesats. NASA SIMPLEX 2/SALMON 3 AO will create ongoing opportunities for low-cost missions as 'rides' on government space program or private sector vehicles as these become available.

Bujold, Emily↗
NASA NTRS2019

Magnification, dust, and time-delay constraints from the first resolved strongly lensed Type Ia supernova iPTF16geu

We report lensing magnifications, extinction, and time-delay estimates for the first resolved, multiply imaged Type Ia supernova iPTF16geu, at z = 0.409, using Hubble Space Telescope (HST) observations in combination with supporting ground-based data. Multiband photometry of the resolved images provides unique information about the differential dimming due to dust in the lensing galaxy. Using HST and Keck AO reference images taken after the SN faded, we obtain a total lensing magnification for iPTF16geu of μ = 67.8(+2.6−2.9), accounting for extinction in the host and lensing galaxy. As expected from the symmetry of the system, we measure very short time-delays for the three fainter images with respect to the brightest one: −0.23 ± 0.99, −1.43 ± 0.74, and 1.36 ± 1.07 d. Interestingly, we find large differences between the magnifications of the four supernova images, even after accounting for uncertainties in the extinction corrections: ∆m(1) = −3.88(+0.07−0.06), ∆m(2) = −2.99(+0.09−0.08), ∆m(3) = −2.19(+0.14−0.15),and ∆m(4) = −2.40(+0.14−0.12) mag, discrepant with model predictions suggesting similar image brightnesses. A possible explanation for the large differences is gravitational lensing by substructures, micro- or millilensing, in addition to the large-scale lens causing the image separations. We find that the inferred magnification is insensitive to the assumptions about the dust properties in the host and lens galaxy.

S Dhawan↗
NASA NTRSDate not supplied

Science Objectives of the ACCP/AOS Millimeter- and Submillimeter-Wave Radiometers

Passive microwave radiometers provide highly useful information regarding the Earth system by measuring thermal emission (from the surface and atmosphere) that is reflected, absorbed, and scattered by the surface and the atmosphere. As such, radiometers have been instrumental across Earth-observing concepts with heritage tracing back to the Nimbus era, and clouds and precipitation have been key geophysical phenomena these sensors have targeted. As millimeter-wave (particularly ≥85 GHz) and submillimeter-wave technologies have advanced, the applicability of microwave radiometers has expanded to encompass falling snow and ice clouds, respectively. Given the strong heritage of microwave radiometry and the emergence of submillimeter-wave sensors for sensing falling snow and ice clouds, the National Academies’ 2017 Decadal Survey for Earth Science and Applications from Space recommended passive sensors covering these wavelengths be included in observing systems that address the Aerosols, Clouds, Convection, and Precipitation (ACCP) combined designated observable. To showcase the capabilities for addressing the ACCP science objectives, we will provide an overview of the passive microwave capabilities envisioned for the Atmosphere Observing System (AOS, part of the recently unveiled NASA Earth System Observatory), including descriptions of the radiometers for the inclined and polar orbits and the primary geophysical variables of interest related to ice-phase clouds and precipitation. We will also discuss secondary science objectives, such as precipitation mapping, that can be achieved with the ACCP/AOS radiometers. Examples from the analyses performed for the ACCP/AOS architecture study and subsequent sensor definition exercises will be presented, outlining the basis for the radiometer configuration within the context of the overarching ACCP/AOS goals to elucidate the connections between atmospheric dynamics, weather (including extreme events), air quality, and climate.

Ian S Adams↗
NASA NTRSDate not supplied

Improving the Transient Sensitivity of AMEGO-X Using Single-site Events

AMEGO-X is a Compton/pair gamma-ray telescope, submitted to NASA's 2021 MIDEX AO, which will image and survey the medium-energy gamma-ray sky between 100 keV and 1 GeV. It is designed to detect and characterize gamma-ray emission from multi-messenger sources. On short time scales (<100s), including information from single-site events (photoelectric effect interactions) significantly increases AMEGO-X's sensitivity and lowers its energy threshold down to 25 keV. In this presentation, we will present AMEGO-X's sensitivity to transient events such as gamma-ray bursts and magnetar giant flares, and discuss the improvements due to the inclusion of single-site events. We will also discuss AMEGO-X's ability to localize transient sources and alert the community for follow-up observations.

Henrike Fleischhack↗
NASA NTRSDate not supplied

Spacecraft Materials Degradation Under Space-Simulated Low Earth Orbit (LEO) Environment

External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons, atomic oxygen (AO), and vacuum ultraviolet (VUV), of several modern spacecraft materials. The studied materials represent the “flight duplicates” of samples that are launched as a part of the 16th Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022.

Elena A Plis↗
NASA NTRSDate not supplied

Ground Testing of the MISSE-16 Materials

External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons and atomic oxygen (AO), of heritage and novel spacecraft materials selection. The studied materials represent the “flight duplicates” of samples that are launched as a part of the 16th Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022.

Elena A. Plis↗
NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global chemistry-climate models (CCMs) where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) CCM through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗
NASA NTRS2022

Global Total Ozone Recovery Trends Attributed to Ozone-Depleting Substance (ODS) Changes Derived From Five Merged Ozone Datasets

We report on updated trends using different merged zonal mean total ozone datasets from satellite and ground-based observations for the period from 1979 to 2020. This work is an update of the trends reported in Weber et al. (2018) using the same datasets up to 2016. Merged datasets used in this study include NASA MOD v8.7 and NOAA Cohesive Data (COH) v8.6, both based on data from the series of Solar Backscatter Ultraviolet (SBUV), SBUV-2, and Ozone Mapping and Profiler Suite (OMPS) satellite instruments (1978–present), as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone – Essential Climate Variable (GTO-ECV) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (both 1995–present), mainly comprising satellite data from GOME, SCIAMACHY, OMI, GOME-2A, GOME-2B, and TROPOMI. The fifth dataset consists of the annual mean zonal mean data from ground-based measurements collected at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. The addition of 4 more years consolidated the fact that total ozone is indeed slowly recovering in both hemispheres as a result of phasing out ozone-depleting substances (ODSs) as mandated by the Montreal Protocol. The near-global (60° S–60° N) ODS-related ozone trend of the median of all datasets after 1995 was 0.4 ± 0.2 (2σ) %/decade, which is roughly a third of the decreasing rate of 1.5 ± 0.6 %/decade from 1978 until 1995. The ratio of decline and increase is nearly identical to that of the EESC (equivalent effective stratospheric chlorine or stratospheric halogen) change rates before and after 1995, confirming the success of the Montreal Protocol. The observed total ozone time series are also in very good agreement with the median of 17 chemistry climate models from CCMI-1 (Chemistry-Climate Model Initiative Phase 1) with current ODS and GHG (greenhouse gas) scenarios (REF-C2 scenario). The positive ODS-related trends in the Northern Hemisphere (NH) after 1995 are only obtained with a sufficient number of terms in the MLR accounting properly for dynamical ozone changes (Brewer–Dobson circulation, Arctic Oscillation (AO), and Antarctic Oscillation (AAO)). A standard MLR (limited to solar, Quasi-Biennial Oscillation (QBO), volcanic, and El Niño–Southern Oscillation (ENSO)) leads to zero trends, showing that the small positive ODS-related trends have been balanced by negative trend contributions from atmospheric dynamics, resulting in nearly constant total ozone levels since 2000.

Total Column Ozone Trends↗
NASA NTRSDate not supplied

Spacecraft Materials Degradation Under Space-Simulated Low Earth Orbit (LEO) Environment

External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons, atomic oxygen (AO), and vacuum ultraviolet (VUV), of several modern spacecraft materials. The studied materials represent the “flight duplicates” of samples that are launched as a part of the 16th Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022.

Elena Plis↗
NASA NTRSDate not supplied

High Latitude Atmospheric Rivers: Teleconnections and Impacts

Atmospheric rivers (ARs) are long, narrow synoptic scale features that act as moisture transport vehicles by moving water vapor poleward. They are typically found in storm tracks and often have profound implications for regional hydroclimate. For high latitude locales such as Antarctica and the Arctic, ARs are fewer in number but often have an outsized impact by either producing significant snow accumulation events, or, depending on their thermal characteristics, initiating melt events on ice sheets, ice shelves, and sea ice. In this study, we apply both reanalysis and climate model data to evaluate high latitude ARs for both the Arctic and Antarctic in the context of teleconnections and modes of variability. Specifically, we fold in both MERRA-2 and ERA5 reanalysis as well as historical and climate change simulations from the CESM2 (Community Earth System Model, Version 2) and E3SMv2 (Energy Exascale Earth System Model, v2) with multiple ensemble members to better understand natural variability versus climate change signals. An overview of AR climatology and impacts will be presented, including a baseline uncertainty quantification analysis using data from ARTMIP (the Atmospheric River Tracking Method Intercomparison Project). AR impacts during specific modes of variability will be characterized by diagnosing precipitation and boundary layer temperature associated with Ars influencing the cryosphere. Modes of variability investigated include the SAM (Southern Annular Mode), PDO (Pacific Decadal Oscillation), PSA2 (Pacific South American Mode 2), the IOD (Indian Ocean Dipole), and the AO (Arctic Oscillation).

Atmospheric Rivers↗
NASA NTRSDate not supplied

Development of a Transition-Edge Sensor Anti-Coincidence Detector for a Probe Class Mission

The Light Element Mapper (LEM), a probe class mission proposal slated for submission in 2023, combines a large X-ray optic with an extremely large format microcalorimeter array to probe the physics of galaxy formation with a grasp 22x greater than ATHENA and 7x greater than Lynx. The focal plane for LEM requires a larger anti-coincidence detector than the other missions while maintaining or exceeding their high-speed response, presenting a challenge for claiming technical readiness at the time of the announcement of opportunity (AO). We will perform a rapid demonstration in the next year including design, fabrication and integration and test of a high-fidelity transition-edge sensor (TES) based device at a scale suitable for LEM.

James Chervenak↗
NASA NTRSDate not supplied

VEDA: Visualization, Exploration, & Data Analysis

NASA's Visualization, Exploration, and Data Analysis (VEDA) project is an open-source science cyberinfrastructure for data processing, visualization, exploration, and geographic information systems (GIS) capabilities. Developed collaboratively and mostly reusing existing open-source components, VEDA consolidates GIS delivery mechanisms, processing platforms, analysis services, and visualization tools and provides an ecosystem of open tools for addressing Earth science research and application needs through the public-facing VEDA Dashboard. In this presentation, Dr. Freitag will provide an overview of VEDA and how it can potentially serve the AOS community.

Brian Freitag↗
NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗
NASA NTRSDate not supplied

Predictability of the Minimum Sea Ice Extent from Late Winter Fram Strait Ice Export: Model vs Observations

Late winter coastal divergence along the Eurasian coastline (referred to as the ice factory) – or the Fram Strait ice export, a proxy for coastal divergence in the ice factory – is a skillful predictor of the minimum sea ice extent (Williams et al., 2016; Brunette et al., 2018; Sesternikov and, 1979). Coastal divergence leads to the formation of coastal polynya where new ice grows but to a thickness that is not large enough to survive the following summer melt. This signal is then amplified by the ice albedo feedback and leads to more open water at the end of the summer melt season. In this thesis project, we will identify if this source of predictive skill in the seasonal forecast of the minimum sea ice extent is present in General Circulation Models, more precisely in the CESM2-LE, GISS-E2.1-G, GFDL FLOR-LE, CNRM-CM6-1 and the CanESM5. Since even small biases in the large-scale atmospheric circulation simulated by a model can short circuit this coupling between dominant modes of atmospheric variability (NAO and AO), coastal divergence along the Eurasian coastline, Fram Strait ice export and therefore seasonal forecasting skill of the model, failure to reproduce this coupling observed in the real Arctic will be used to identify biases in GCM. Preliminary results show that subtle changes in the large-scale atmospheric circulation leads to opposite statistical relationship between Fram Strait ice area export, coastal divergence along the Eurasian coastline, and seasonal predictability of the minimum sea ice extent both in the CESM2-LE and the GISS-E2.1-G models. Differences are linked with the partitioning between recirculation within the Beaufort Gyre, ice exported through Fram Strait and ridging north of the Canadian Arctic Archipelago.

Sea ice↗