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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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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

The Impact of Surface Boundary Forcing on Simulation of the 1998 Summer Drought Over the US Midwest Using Factor Separation Technique

The factor separation (FS) technique has been utilized to evaluate quantitatively the impact of surface boundary forcings on simulation of the 1988 summer drought over the Midwestern part of the U.S. The four surface boundary forcings used are: (1)Sea Surface Temperature (SST), (2) soil moisture, (3) snow cover, and (4) sea ice. The Goddard Earth Observing System(GEOS) General Circulation Model (GCM) is used to simulate the 1988 U.S. drought. A series of sixteen simulations are performed with climatological and real 1988 surface boundary conditions. The major single and mutual synergistic factors/impacts are analyzed. The results show that SST and soil moisture are the major single pro-drought factors. The couple synergistic effect of SST and soil moisture is the major anti-drought factor. The triple synergistic impact of SST, soil moisture, and snow cover is the strongest pro-drought impact and is, therefore, the main contributor to the generation of the drought. The impact of the snow cover and sea ice anomalies for June 1988 on the drought is significant only when combined with the SST and soil moisture anomalies.

Stein, Uri↗
DOE OSTI2020

Climate change and the future productivity and distribution of crab in the Bering Sea

Crab populations in the eastern Bering Sea support some of the most valuable fisheries in the United States, but their future productivity and distribution are uncertain. Here, we explore observed changes in the productivity and distribution for snow crab, Tanner crab, and Bristol Bay red king crab. We link historical indices of environmental variation and predator biomass with observed time series of centroids of abundance and extent of crab stock distribution; we also fit stock–recruit curves including environmental indices for each stock. We then project these relationships under forcing from global climate models to forecast potential productivity and distribution scenarios. Our results suggest that the productivity of snow crab is negatively related to the Arctic Oscillation (AO) and positively related to ice cover; Tanner crab’s productivity and distribution are negatively associated with cod biomass and sea surface temperature. Aspects of red king crab distribution and productivity appear to be related to bottom temperature, ice cover, the AO, and/or cod biomass. Projecting these relationships forward with available forecasts suggests that Tanner crab may become more productive and shift further offshore, red king crab distribution may contract and move north, and productivity may decrease for snow crab as the population contracts northward.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Constraining Physical Understanding of Aerosol Loading, Biogeochemistry, and Snowmelt Hydrology from Hillslope to Watershed Scale in the East River Scientific Focus Area

The mountain snowpack is a critical component of regional hydrology, ecology, biogeochemistry, and climate in the Western US. This project leveraged the East River Scientific Focus Area (SFA), as an outdoor laboratory to address a significant gap in our understanding of the mountain snowpack; namely, how atmospheric constituent deposition on snowpack influences snow energy balance and nutrient/chemical cycling, and how snowmelt timing and intensity exerts controls on emergent biogeochemical and ecohydrologic behavior. This aligned with East River SFA goals to integrate landscape scale measurements and physical based modeling tools to improve understanding of controls on runoff production, ecohydrology, biogeochemical cycling, and land surface energy partitioning in high mountain watersheds. The project included observations of snowpack at multiple scales, measurements of snow and deposited aerosols properties, in situ time series of surface energy balance, and spatially distributed, process-based snowmelt modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site

Numerical simulations are essential tools for understanding the complex hydrologic response of Arctic regions to a warming climate. However, strong coupling among thermal and hydrological processes on the surface and in the subsurface and the significant role that subtle variations in surface topography have in regulating flow direction and surface storage lead to significant uncertainties. Careful model evaluation against field observations is thus important to build confidence.We evaluate the integrated surface/subsurface permafrost thermal hydrology models in the Advanced Terrestrial Simulator (ATS) against field observations from polygonal tundra at the Barrow Environmental Observatory. ATS couples a multiphase, 3D representation of subsurface thermal hydrology with representations of overland nonisothermal flows, snow processes, and surface energy balance. We simulated thermal hydrology of a 3D ice-wedge polygon with geometry that is abstracted but broadly consistent with the surface microtopography at our study site. The simulations were forced by meteorological data and observed water table elevations in ice-wedge polygon troughs. With limited calibration of parameters appearing in the soil evaporation model, the 3-year simulations agreed reasonably well with snow depth, summer water table elevations in the polygon center, and high-frequency soil temperature measurements at several depths in the trough, rim, and center of the polygon. Upscaled evaporation is in good agreement with flux tower observations. The simulations were found to be sensitive to parameters in the bare soil evaporation model, snowpack, and the lateral saturated hydraulic conductivity.Timing of fall freeze-up was found to be sensitive to initial snow density, illustrating the importance of including snow aging effects. The study provides new support for an emerging class of integrated surface/subsurface permafrost simulators.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Radiobrightness Forward Modelling vs Observations from Local to Satellite Scales during the 2003 NASA Cold Land Processes Experiment

A key issue for passive microwave Earth sensing applications is subpixel heterogeneity and its role in the connection between local-scale conditions vs. what is observed at the satellite footprint scale. The recently-completed NASA Cold Land Processes Field Experiment (CLPX-1) was designed to provide microwave remote sensing observations and ground truth for studies of snow and from ground remote sensing, particularly issues related to scaling. CLPX-1 was conducted in the spring of 2003 in Colorado, USA. Measurements of radiobrightness were made with nested footprint sizes ranging from scales of meters at a single site to 25 x 25 km across the entire CLPX-1 domain. Corresponding measurements of snowpack conditions (snow depth and temperature. density, and grain size profiles) as well as weather analyses were used to provide input data for forward radiative transfer model investigations. This paper will focus on the ability of forward modelling, based primarily on Dense Medium Radiative Transfer (DMRT) theory, combined with snowpack measurements and weather data to reproduce the radiobrightness signatures observed at multiple scales during both the third and fourth Intensive Observing Periods (February and March, 2003). The conditions include both wet and dry periods as well as a variety of forest cover conditions, providing a valuable test of model performance. These analyses will help guide the choice of future snow retrieval algorithm and the design of future Cold Lands observing systems.

Kim, Edward J.↗
DOE OSTI2021

Description and Demonstration of the Coupled Community Earth System Model v2 – Community Ice Sheet Model v2 (CESM2‐CISM2)

Abstract Earth system/ice‐sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea‐level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy‐balance‐based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice‐sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO 2 scenario. The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.

Muntjewerf, Laura↗
DOE OSTI2022

A hydrological simulation dataset of the Upper Colorado River Basin from 1983 to 2019

Abstract This article presents a hydrological reconstruction of the Upper Colorado River Basin with an hourly temporal resolution, and 1-km spatial resolution from October 1982 to September 2019. The validated dataset includes a suite of hydrologic variables including streamflow, water table depth, snow water equivalent (SWE) and evapotranspiration (ET) simulated by an integrated hydrological model, ParFlow-CLM. The dataset was validated over the period with a combination of point observations and remotely sensed products. These datasets provide a long-term, natural-flow, simulation for one of the most over-allocated basins in the world.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Snow and ice surfaces measured by the Nimbus 5 microwave spectrometer

The 22.2- and 31.4-GHz channels of the microwave spectrometer on board the Nimbus 5 earth observatory satellite provide information about the global distribution and character of various types of snow and ice. Observations for the winter and summer of 1973 are presented for both polar regions. Well-defined spectral signatures are found for snow, sea ice, and land ice in Greenland and Antarctica. A simple model with subsurface temperature gradients in a lossy homogeneous dielectric does not account for the observations; internal scattering effects appear to play a dominant role.

Kunzi, K. F.↗
NASA NTRS1978

The albedo of Titan

It is shown that a two-layer model of Titan's atmosphere is required in order to match laboratory data on methane absorption to ground-based IR observations of Titan. An excellent fit to the observations is obtained with a model where the dust in Titan's atmosphere is confined to a region containing 50 m-am of methane and located above an atmosphere with 1.95 km-am of methane, with the amount of dust being the value required for an extinction optical depth of 5 at 0.5 micron. The surface reflectivity required by this model is about 40% to 50%, which is typical for both dirty snow and clouds. The possibility is discussed of distinguishing between two scenarios for the observed surface of Titan (a true surface or just cloud tops) on the basis of limb-darkening curves obtained at many wavelengths with an orbiting telescope or a flyby mission.

Podolak, M.↗
NASA NTRS1981

The influence of initial and surface boundary conditions on a model-generated January climatology

The influence on a model-generated January climate of various surface boundary conditions, as well as initial conditions, was studied by using the GISS coarse-mesh climate model. Four experiments - two with water planets, one with flat continents, and one with mountains - were used to investigate the effects of initial conditions, and the thermal and dynamical effects of the surface on the model generated-climate. However, climatological mean zonal-symmetric sea surface temperature is used in all four runs over the model oceans. Moreover, zero ground wetness and uniform ground albedo except for snow are used in the last experiments.

Wu, K. F.↗
NASA NTRS1982

Applications of remote sensing technology to U.S. Water resource management

Applications of Landsat data to assessing the available water supply in the U.S. for agricultural puposes as a program of the NASA Office of Space Science and Applications are described. Snow melt runoff predictions are performed with multitemporal Landsat imagery to measure the extent of mountain snow packs in the Rockies in order to produce stream flow forecast models. The data is used for decisions of which crops to plant, based on irrigation water which will be accessible in eleven western U.S. states. Imagery has tracked the growth of irrigated lands watered from the Ogallala aquifer in the central U.S., and is providing a data base for calculating the aquifer depletion rates. Studies are preceeding in temporally mapping the kinds of vegetation growing in the Suwannee Sound in Florida to monitor the intrusion of salt water, which would reduce the River's usefulness for irrigation. Finally, capabilities of the Thematic Mapper are reviewed.

Weber, J. D.↗
NASA NTRS1999

Parameterizations of Depositional Growth of Cloud Ice in a Bulk Microphysical Scheme

Two aspects of the cloud ice parameterization in the Goddard Cumulus Ensemble Model cloud physics parameterization are examined: the conversion of cloud ice to snow by depositional growth, designated PSFI, and the saturation adjustment scheme. The original formulation of PSFI is shown to produce excessive conversion of cloud ice to snow because of an implicit assumption that the relative humidity is 100% with respect to water even though the air may actually be quite less humid. Two possible corrections to this problem are proposed, the first involving application of a relative humidity dependent correction factor to the original formulation of PSFI, and the second involving a new formulation of PSFI based on the equation for depositional growth of cloud ice. The sensitivity of these formulations of PSFI to the assumed masses of the ice particles is examined. Possible problems associated with using a saturation adjustment scheme for cloud ice are discussed and simulations of a squall line with and without application of the adjustment scheme for ice are compared.

Braun, Scott A.↗
NASA NTRS2005

Evaluation of Ten Methods for Initializing a Land Surface Model

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth"s water cycle and climate variability. NASA"s Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type).

Rodell, M.↗
NASA NTRS2011

Land and Atmosphere Near-Real-Time Capability for Earth Observing System

The past decade has seen a rapid increase in availability and usage of near-real-time data from satellite sensors. The EOSDIS (Earth Observing System Data and Information System) was not originally designed to provide data with sufficiently low latency to satisfy the requirements for near-real-time users. The EOS (Earth Observing System) instruments aboard the Terra, Aqua and Aura satellites make global measurements daily, which are processed into higher-level 'standard' products within 8-40 hours of observation and then made available to users, primarily earth science researchers. However, applications users, operational agencies, and even researchers desire EOS products in near-real-time to support research and applications, including numerical weather and climate prediction and forecasting, monitoring of natural hazards, ecological/invasive species, agriculture, air quality, disaster relief and homeland security. These users often need data much sooner than routine science processing allows, usually within 3 hours, and are willing to trade science product quality for timely access. While Direct Broadcast provides more timely access to data, it does not provide global coverage. In 2002, a joint initiative between NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration), and the DOD (Department of Defense) was undertaken to provide data from EOS instruments in near-real-time. The NRTPE (Near Real Time Processing Effort) provided products within 3 hours of observation on a best-effort basis. As the popularity of these near-real-time products and applications grew, multiple near-real-time systems began to spring up such as the Rapid Response System. In recognizing the dependence of customers on this data and the need for highly reliable and timely data access, NASA's Earth Science Division sponsored the Earth Science Data and Information System Project (ESDIS)-led development of a new near-real-time system called LANCE (Land, Atmosphere Near-Real-Time Capability for EOS) in 2009. LANCE consists of special processing elements, co-located with selected EOSDIS data centers and processing facilities. A primary goal of LANCE is to bring multiple near-real-time systems under one umbrella, offering commonality in data access, quality control, and latency. LANCE now processes and distributes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments within 3 hours of satellite observation. The Rapid Response System and the Fire Information for Resource Management System (FIRMS) capabilities will be incorporated into LANCE in 2011. LANCE maintains a central website to facilitate easy access to data and user services. LANCE products are extensively tested and compared with science products before being made available to users. Each element also plans to implement redundant network, power and server infrastructure to ensure high availability of data and services. Through the user registration system, users are informed of any data outages and when new products or services will be available for access. Building on a significant investment by NASA in developing science algorithms and products, LANCE creates products that have a demonstrated utility for applications requiring near-real-time data. From lower level data products such as calibrated geolocated radiances to higher-level products such as sea ice extent, snow cover, and cloud cover, users have integrated LANCE data into forecast models and decision support systems. The table above shows the current near-real-time product categories by instrument. The ESDIS Project continues to improve the LANCE system and use the experience gained through practice to seek adjustments to improve the quality and performance of the system. For example, anGC-compliant Web Map Service (WMS) will be added shortly that will allow users to download geo-referenced MODIS images for arbitrary bounding boxes. Further, an OGC-compliant Web Coverage Service (WCS) will be added later this year that will expedite user access to arbitrary data subsets or re-formatted products. AIRS images are now served through WMS and available in multiple formats (PNG, GeoTIFF, KMZ). NASA has established a LANCE User Working Group to steer the development of the system and create a forum for sharing ideas and experiences that are expected to further improve the LANCE capabilities. The LANCE system has proved a success by satisfying the growing needs of the applications and operational communities for land and atmosphere data in near-real-time. NASA's Earth Sciences Division was able to leverage existing science research capabilities to provide the near-real-time community with products and imagery that support monitoring of disasters in a timely manner.

Murphy, Kevin J.↗
NASA NTRS2011

Ares I Scale Model Acoustic Test Instrumentation for Acoustic and Pressure Measurements

Ares I Scale Model Acoustic Test (ASMAT) is a 5% scale model test of the Ares I vehicle, launch pad and support structures conducted at MSFC to verify acoustic and ignition environments and evaluate water suppression systems Test design considerations 5% measurements must be scaled to full scale requiring high frequency measurements Users had different frequencies of interest Acoustics: 200 - 2,000 Hz full scale equals 4,000 - 40,000 Hz model scale Ignition Transient: 0 - 100 Hz full scale equals 0 - 2,000 Hz model scale Environment exposure Weather exposure: heat, humidity, thunderstorms, rain, cold and snow Test environments: Plume impingement heat and pressure, and water deluge impingement Several types of sensors were used to measure the environments Different instrument mounts were used according to the location and exposure to the environment This presentation addresses the observed effects of the selected sensors and mount design on the acoustic and pressure measurements

Vargas, Magda B.↗
NASA NTRS2012

Iterative Atmospheric Correction Scheme and the Polarization Color of Alpine Snow

Characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of a few geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of these measurements is overwhelmed by that of instruments with polarization capabilities: proposed models in this case are based on the Fresnel reflectance of an isotropic distribution of facets. Because of its remarkable lack of spectral contrast, the polarized reflectance of land surfaces in the shortwave infrared spectral region, where atmospheric scattering is minimal, can be used to model the surface also at shorter wavelengths, where aerosol retrievals are attempted based on well-established scattering theories. In radiative transfer simulations, straightforward separation of the surface and atmospheric contributions is not possible without approximations because of the coupling introduced by multiple reflections. Within a general inversion framework, the problem can be eliminated by linearizing the radiative transfer calculation, and making the Jacobian (i.e., the derivative expressing the sensitivity of the reflectance with respect to model parameters) available at output. We present a general methodology based on a Gauss-Newton iterative search, which automates this procedure and eliminates de facto the need of an ad hoc atmospheric correction. In this case study we analyze the color variations in the polarized reflectance measured by the NASA Goddard Institute of Space Studies Research Scanning Polarimeter during a survey of late-season snowfields in the High Sierra. This insofar unique dataset presents challenges linked to the rugged topography associated with the alpine environment and a likely high water content due to melting. The analysis benefits from ancillary information provided by the NASA Langley High Spectral Resolution Lidar deployed on the same aircraft. The results obtained from the iterative scheme are contrasted against the surface polarized reflectance obtained ignoring multiple reflections, via the simplistic subtraction of the atmospheric scattering contribution. Finally, the retrieved reflectance is modeled after the scattering properties of a dense collection of ice crystals at the surface. Confirming that the polarized reflectance of snow is spectrally flat would allow to extend the techniques already in use for polarimetric retrievals of aerosol properties over land to the large portion of snow-covered pixels plaguing orbital and suborbital observations.

Polarized BRDF↗
NASA NTRS2015

Assimilation of GPM GMI Rainfall Product with WRF GSI

The Global Precipitation Measurement (GPM) is an international mission to provide next-generation observations of rain and snow worldwide. The GPM built on Tropical Rainfall Measuring Mission (TRMM) legacy, while the core observatory will extend the observations to higher latitudes. The GPM observations can help advance our understanding of precipitation microphysics and storm structures. Launched on February 27th, 2014, the GPM core observatory is carrying advanced instruments that can be used to quantify when, where, and how much it rains or snows around the world. Therefore, the use of GPM data in numerical modeling work is a new area and will have a broad impact in both research and operational communities. The goal of this research is to examine the methodology of assimilation of the GPM retrieved products. The data assimilation system used in this study is the community Gridpoint Statistical Interpolation (GSI) system for the Weather Research and Forecasting (WRF) model developed by the Development Testbed Center (DTC). The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this research explores regional assimilation of the GPM products with case studies. Our presentation will highlight our recent effort on the assimilation of the GPM product 2AGPROFGMI, the retrieved Microwave Imager (GMI) rainfall rate data for initializing a real convective storm. WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to other GPM products. Further details of the methodology of data assimilation, preliminary result and test on the impact of GPM data and the influence on precipitation forecast will be presented at the conference.

Li, Xuanli↗
NASA NTRS2016

Using Ground Targets to Validate S-NPP VIIRS Day-Night Band Calibration

In this study, the observations from S-NPP VIIRS Day-Night band (DNB) and Moderate resolution bands (M bands) of Libya 4 and Dome C over the first four years of the mission are used to assess the DNB low gain calibration stability. The Sensor Data Records produced by NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired from nearly nadir overpasses for Libya 4 desert and Dome C snow surfaces. A kernel-driven bidirectional reflectance distribution function (BRDF) correction model is used for both Libya 4 and Dome C sites to correct the surface BRDF influence. At both sites, the simulated top-of-atmosphere (TOA) DNB reflectances based on SCIAMACHY spectral data are compared with Land PEATE TOA reflectances based on modulated Relative Spectral Response (RSR). In the Libya 4 site, the results indicate a decrease of 1.03% in Land PEATE TOA reflectance and a decrease of 1.01% in SCIAMACHY derived TOA reflectance over the period from April 2012 to January 2016. In the Dome C site, the decreases are 0.29% and 0.14%, respectively. The consistency between SCIAMACHY and Land PEATE data trends is good. The small difference between SCIAMACHY and Land PEATE derived TOA reflectances could be caused by changes in the surface targets, atmosphere status, and on-orbit calibration. The reflectances and radiances of Land PEATE DNB are also compared with matching M bands and the integral M bands based on M4, M5, and M7. The fitting trends of the DNB to integral M bands ratios indicate a 0.75% decrease at the Libya 4 site and a 1.89% decrease at the Dome C site. Part of the difference is due to an insufficient number of sampled bands available within the DNB wavelength range. The above results indicate that the Land PEATE VIIRS DNB product is accurate and stable. The methods used in this study can be used on other satellite instruments to provide quantitative assessments for calibration stability.

Chen, Xuexia↗