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At least 235 records · Page 13

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NASA NTRS2021

Quantifying the Observational Requirements of a Space-borne LiDAR Snow Mission

This study quantifies the level of observational accuracy required from a spaceborne light detection and ranging (LiDAR) snow depth retrieval mission for enabling beneficial impacts for snow estimation. The study is conducted over a region in Western Colorado using a suite of observing system simulation experiments(OSSEs).The Joint UK Land Environment Simulator, version 5.0 (JULES v5.0) is employed to simulate a suite of idealized LiDAR observations, considering a range of LiDAR snow depth retrieval errors, different hypothetical sensor swath widths, and the impact of cloud cover on observability. These simulated observations are then assimilated into the Noah land surface modelwith multi-parameterization options, version 3.6 (Noah-MP v3.6) model. This data assimilation setup is used to systematically evaluate the potential utility of LiDAR observations for improving modeled snow water equivalent (SWE)estimates and water budget variables such as runoff. Results from the OSSE runsshow that, in general, assimilation of synthetic LiDAR observations provide beneficial impacts when theLiDAR snow depth retrieval error standard deviation (σerror) is below 60 cm.Based on comparisons between the realistic (i.e., swath-limited and cloud-attenuated) case and the idealized (i.e., infinite swath width in the absence of cloud cover) case,this study concludes that observations with a conservative error standard deviation threshold of 40 cm (i.e., upper limit of the snow depth retrieval error that adds value to the SWE estimates viaassimilation) are needed for improving modeled snow estimates. More than a 33% reduction in SWEroot mean square errors and more than a 15% increase in correlation coefficientsare achieved when σ error ≤ 40 cmusing a 170-km sensor swath width in the presence of cloud attenuation effects. Further, the integrated hydrologic response, as represented by total (surface and subsurface) runoff estimates during the snow ablation season, are also enhanced when assimilating synthetic LiDAR snow depth retrievals with errors below this level.

Yonghwan Kwon↗

NASA NTRSDate not supplied

Impacts of Assimilating Geostationary Infrared Sounders within NASA’s Observing System Simulation Experiment Framework

The National Oceanic and Atmospheric Administration (NOAA) has proposed including a hyperspectral infrared sounder onboard the Geostationary eXtended Observations (GeoXO) platform, scheduled to begin launching in the 2030s. A set of observing system simulation experiments (OSSEs) was preformed to investigate the impact of assimilating data from the GeoXO Sounder (GXS) using the National Aeronautics and Space Administration (NASA) Global Modeling and Assimilation Office (GMAO) OSSE system. The aim of this study is to identify the global gains achieved by the assimilation of geostationary infrared sounders from a numerical weather prediction perspective. Progress of current experimentation and future directions will be presented.

Erica Mcgrath-Spangler↗

NASA NTRS2023

Impacts of Marine Surface Pressure Observations From A Spaceborne Differential Absorption Radar Investigated With an Observing System Simulation Experiment

A new instrument has been proposed for measuring surface air pressure over the marine surface with a combined active/passive scanning multi-channel differential absorption radar (DAR) to provide an estimate of the total atmospheric column oxygen content. A demonstrator instrument, the Microwave Barometric Radar and Sounder (MBARS), has been funded by the National Aeronautics and Space Administration (NASA) for airborne test missions. Here, a proof-of-concept study to evaluate the potential impact of spaceborne surface pressure data on numerical weather prediction is performed using the Goddard Modeling and Assimilation Office global observing system simulation experiment (OSSE) framework. This OSSE framework employs the Goddard Earth Observing System model and the hybrid 4D ensemble variational Gridpoint Statistical Interpolation data assimilation system. Multiple flight and scanning configurations of potential spaceborne orbits are examined. Swath width and observation spacing for the surface pressure data are varied to explore a range of sampling strategies. For wider swaths, the addition of surface pressures reduces the root mean square surface pressure analysis error by as much as 20% over some ocean regions. The forecast sensitivity observation impact tool estimates impacts on the Pacific Ocean basin boundary layer 24-hour forecast temperatures for spaceborne surface pressures on par with rawinsondes and aircraft, and greater impacts than the current network of ships and buoys. The largest forecast impacts are found in the southern hemisphere extratropics.

N.C. Privé↗

NASA NTRSDate not supplied

Using the GEOS 5 Nature Run to Simulate 2053 nm Coherent Doppler Wind Lidar Observations

Wind observations are a critical part of the current global observation system used for Numerical Weather Prediction (NWP). Wind lidars have been cited as precise instruments that can provide 3-dimensional wind measurements. Several studies have conducted observing system experiments (OSEs) with existing lidar observations or observing system simulation experiments (OSSEs) with simulated lidar observations highlighting the benefits of wind lidar measurements to NWP. Previous studies using simulated lidar observations have typically tied aerosol optical properties to functions of relative humidity instead of to aerosol properties. A methodology is presented for simulating wind measurements from a novel 2053 nm lidar using aerosol properties derived using the GEOS-5 Nature Run, along with estimating winds derived from cloud information. Some assumptions regarding aerosol scattering and the distribution of clouds are explored, along with the role of observation weighting, and implications for representativeness error. Results from a preliminary OSSE are presented highlighting the importance of assumptions used to derive data from cloud returns and aerosol scattering. While a longer duration study is required, results show a general reduction in analysis error when lidar measurements are ingested.

Bryan M. Karpowicz↗

NASA NTRSDate not supplied

Using the GEOS 5 Nature Run to Simulate 2053 nm Coherent Doppler Wind Lidar Observations

Bryan M. Karpowicz↗

NASA NTRSDate not supplied

Estimates of Future Numerical Weather Prediction Impacts from Hyperspectral Sounders

The United States’ satellite programs are currently in the process of evaluating the future of satellite observations of the Earth’s atmosphere, both as an individual nation and within the context of international partnerships. In an effort to better understand the impacts of various alternatives, the Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework has been utilized to evaluate several configurations of the international hyperspectral infrared sounder constellation from the perspective of global numerical weather prediction (NWP). This was done with an emphasis on the proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) Sounder (GXS), planned to launch in the mid-2030s, and similar planned missions from international partners. GXS, in addition to contributions from EUMETSAT and JMA, will form a global ring of geostationary sounders consistent with the WMO’s 2040 vision. In addition to a novel geostationary IR sounder program, considerations extend to the future of the Low Earth Orbit (LEO) sounder program with the upcoming demise of several existing instruments and plans for future missions ongoing. The GMAO OSSE framework has examined the potential roles of GEO and LEO sounders in weather prediction improvement. Overall, the inclusion of both GEO sounders in a global ring and LEO sounders produces the most beneficial observation impact and the most accurate global weather forecasts as evaluated using several metrics, including hurricanes and the FSOI.

Erica Mcgrath-Spangler↗

NASA NTRSDate not supplied

The Potential of GEO Sounders for Numerical Weather Prediction

The future of Earth observations from space is currently being decided upon in the United States. To better understand the impacts of various configurations, the Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework has been utilized to examine the impact of various hyperspectral infrared sounder constellations from the perspective of global numerical weather prediction (NWP). With an emphasis on the proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) Sounder (GXS), planned to launch in the mid-2030s, the NWP benefit of a global ring of geostationary sounders, consistent with the WMO’s 2040 vision is evaluated. In addition, considerations extend to the future of the Low Earth Orbit (LEO) sounder program with the loss of several existing instruments and plans for future missions ongoing. The GMAO OSSE framework has examined the potential complementarities of GEO and LEO sounders in weather prediction improvement. Overall, the inclusion of both GEO and LEO sounders produces the most beneficial impact on NWP for regional and global scales and the most accurate global weather forecasts as evaluated using several metrics, including hurricanes and the forecast sensitivity observation impact (FSOI).

Erica Mcgrath-Spangler↗

NASA NTRSDate not supplied

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗

NASA NTRS2024

Observing System Simulation Experiments Exploring Potential Spaceborne Deployment Options for a Differential Absorption Radar Measuring Marine Surface Pressures

A new technology for remote measurements of marine surface pressure has been proposed, employing a V-band differential absorption radar and a radiometric temperature sounder to calculate the total column atmospheric mass. Observing System Simulation Experiments (OSSEs) are performed to evaluate the potential impact of Spaceborne Marine Surface Pressure (SMSP) on Numerical Weather Prediction. These experiments build on prior efforts (Privé, McLinden, et al., 2023, https://doi.org/10.16993/tellusa.3254), but with an updated version of the OSSE framework and with more sophisticated simulation of the SMSP observations and a longer experiment period. Several different instrument configurations are compared, including both scanning and non-scanning orbits. SMSP impacts are calculated for analysis quality and forecast skill, and a forecast sensitivity observation impact tool is employed to place SMSP observations in context with the global observing network. The effects of rain contamination on observation quality are explored. Different magnitudes of simulated SMSP observation error are tested in the context of data assimilation to show the range of potential behaviors. Overall, SMSP observations are found to be most beneficial in the southern hemisphere extratropics, with statistically significant forecast improvements for the first 72 hr of the forecast. A constellation of four non-scanning SMSP satellites is found to outperform a single scanning instrument with a 250 km wide swath.

N C Prive↗

NASA NTRS2015

Spectral Analysis of Forecast Error Investigated with an Observing System Simulation Experiment

The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

OSSE↗

NASA NTRS2015

Observing System Simulation Experiments for Fun and Profit

Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed

Observational Networks↗

NASA NTRS2015

Towards an Understanding of Atmospheric Balance

During a 35 year period I published 30+ pear-reviewed papers and technical reports concerning, in part or whole, the topic of atmospheric balance. Most used normal modes, either implicitly or explicitly, as the appropriate diagnostic tool. This included examination of nonlinear balance in several different global and regional models using a variety of novel metrics as well as development of nonlinear normal mode initialization schemes for particular global and regional models. Recent studies also included the use of adjoint models and OSSEs to answer some questions regarding balance. lwill summarize what I learned through those many works, but also present what l see as remaining issues to be considered or investigated.

Balance↗

NASA NTRS2020

Evaluation of adjoint-based observation impacts as a function of forecast length using an Observing System Simulation Experiment

Adjoints of numerical weather prediction models may be employed for Forecast Sensitivity to Observation (FSO) in order to monitor the contribution of ingested observation data on short-term forecast skill. However, the calculation of short-term forecast error is difficult due to the lack of a truly independent dataset for verification. In an Observing System Simulation Experiment framework, the Nature Run is able to provide a true and complete verification dataset and allows accurate evaluation of short term forecast errors. In this work, an OSSE developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office is used to explore the impact of observational data on forecasts in the 6 to 48 hour range. An adjoint of the Global Earth Observing System model is employed to compare the observation impacts estimated using both self-analysis verification and the true Nature Run verification. Self-analysis verification is found to inflate the estimated forecast error growth during the early forecast period, resulting in overestimations of observation impacts, particularly in the 6-12 hour forecast range. By 48 hours, the self-analysis verification estimates of forecast error and observation impacts more closely match the true values. The fraction of beneficial observations is also overinflated at short forecast times when self-analysis verification is used. The progression of impacts of an individual observation or data type depends on the character of the growth of the initial condition error that each observation affects.

numerical weather prediction↗

NASA NTRS2022

Investigation of the Potential Saturation of Information from Global Navigation Satellite System Radio Occultation Observations with an Observing System Simulation Experiment

The potential impact of large numbers of Global Navigation Satellite System radio occultation (GNSS-RO) observations on numerical weather prediction is investigated using a global observing system simulation experiment (OSSE). The hybrid four-dimensional ensemble variational Gridpoint Statistical Interpolation (GSI) data assimilation system and Global Earth Observing System (GEOS) model are used to ingest up to 100,000 GNSS-RO soundings per day in addition to the current suite of conventional and radiance data. Analysis quality, forecast skill, and forecast sensitivity to observation impact are examined with differing quantities of additional GNSS-RO profiles. It is found that saturation of information from additional RO soundings has not been reached with 100,000 soundings per day. There are some indications of suboptimal performance of the GSI in handling GNSS-RO observations particularly in the middle and lower tropospheric extratropics.

GNSS-RO↗

DOE OSTI2023

Exciton Binding Energy in Organic Polymers: Experimental Considerations and Tuning Prospects

Discrepancies in reported values of exciton binding energy (E b ) for organic semiconductors (OSs) necessitate a comprehensive study. Traditionally, E b is defined as the difference between the transport gap (E t ) and the optical gap (E opt ). Here, the E b values of PBnDT‐TAZ polymer variants are determined using two commonly employed methods: a combination of ultraviolet photoemission spectroscopy and low‐energy inverse photoemission spectroscopy (UPS‐LEIPS) and solid‐state cyclic voltammetry (CV). E b values obtained by UPS‐LEIPS show low dispersion and no clear correlation with the polymer structure and thedielectric properties. In contrast, CV reveals a larger dispersion (200 meV‐1 eV) and an apparent qualitative E b ‐molecular structure correlation, as the lowest E b values are observed for oligo‐ethylene glycol side chains. This discrepancy is discussed by examining the implications of the traditional definition of E b . Additionally, the impact of both intrinsic and extrinsic factors contributing to the derived experimental values of E t is discussed. The differences in intrinsic and extrinsic factors highlight the context‐dependent nature of measurement when drawing global conclusions. Notably, the observed E b trend derived from CV is not intrinsic to the pure materials but likely linked to electrolyte swelling and associated changes in dielectric environment, suggesting that high‐efficiency single‐material organic photovoltaics with low E b may be possible via high dielectric materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Architecture and performance of Perlmutter's 35 PB ClusterStor E1000 all-flash file system

NERSC's newest system, Perlmutter, features a 35 PB all-flash Lustre file system built on HPE Cray ClusterStor E1000. Here, we present its architecture, early performance figures, and performance considerations unique to this architecture. We demonstrate the performance of E1000 OSSes through low-level Lustre tests that achieve over 90% of the theoretical bandwidth of the SSDs at the OST and LNet levels. We also show end-to-end performance for both traditional dimensions of I/O performance (peak bulk-synchronous bandwidth) and nonoptimal workloads endemic to production computing (small, incoherent I/Os at random offsets) and compare them to NERSC's previous system, Cori, to illustrate that Perlmutter achieves the performance of a burst buffer and the resilience of a scratch file system. Finally, we discuss performance considerations unique to all-flash Lustre and present ways in which users and HPC facilities can adjust their I/O patterns and operations to make optimal use of such architectures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Tuning the fluid wetting dynamics on gold microstructures using photoactive compounds

This work demonstrates how photoactive compounds can be used to tune the surface chemistry, surface free energy, and the wetting velocity of fluids on Spiropyran functionalized surfaces with different surface microstructures. Evidence of this photowetting effect is based on data showing: (1) the cyclic changes in the static, advancing, and receding contact angles $\theta$ CA for multiple UV$\rightleftarrows$vis photoswitching cycles with both smooth and microstructured surfaces and (2) the changes in the fluid wicking velocity (via UV$\rightleftarrows$vis photoswitching) on different Spiropyran functionalized hemiwicking surfaces. X-ray photoelectron spectroscopy is used to determine the efficiency of photoswitching caused by the quality of the Spiropyran functionalization. Reversible photoisomerization of Spiropyran generates a gradient in surface free energy, resulting in a similar change in contact angle ($\theta$ CA ) in the photoswitchable surfaces. In conclusion, by incorporating these changes into the Owens-Wendt and Van Oss surface energy models, the energy of smooth Au surfaces can also be predicted for both UV and visible light irradiations, where reversible contact angle variations of $\Delta$$\theta$ CA ≈ 5–10° are achieved with both water and water-ethanol mixtures due to the conversion of SP to merocyanine, which corresponds to a total free energy change of ~13% on the photoswitchable surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Overset meshes for incompressible flows: On preserving accuracy of underlying discretizations

This study on overset meshes for incompressible-flow simulations is motivated by accurate prediction of wind farm aerodynamics involving large motions and deformations of components with complex geometry. Specifically, using first-order hyperbolic and elliptic equation proxies for the incompressible Navier-Stokes (NS) equations, we investigate the influence of information exchange between overset meshes on numerical performance where the underlying discretization is second-order accurate. The first aspect of information exchange surrounds interpolation of solution where we examine Lagrange and point-cloud-based interpolation for creating constraint equations between overset meshes. To maintain overall second-order accuracy, higher-order interpolation is required for elliptic problems, but linear interpolation is sufficient for hyperbolic problems in first-order form. Higher-order point-cloud-based interpolation provides a pathway to maintaining accuracy in unstructured meshes, but at higher complexity. The second aspect of information exchange focuses on comparing the approaches of overset single system (OSS) and overset Additive Schwarz (OAS) for coupling the linear systems of the overlapping meshes. While the former involves a single linear system, in the latter the discrete linear systems are solved separately, and solving the global system is accomplished through outer iterations and sequential information exchange in a Jacobi fashion. For the test cases studied, accuracy for hyperbolic problems is maintained by performing two outer iterations, whereas many outer iterations are required for elliptic systems. The order-of-accuracy studies explored here are critical for verifying the overset-mesh coupling algorithms used in engineering simulations. Accuracy of these simulations themselves is, however, quantified using engineering quantities of interest such as drag, power, etc. Consequently, we conclude with numerical experiments using NS equations for incompressible flows where we show that linear interpolation and few outer iterations are sufficient for achieving asymptotic convergence of engineering quantities of interest.

97 MATHEMATICS AND COMPUTING↗