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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Dynamical predictability of monthly means

The concept of predictability which is conditioned by synoptic-scale disturbance instabilities is extended to that of time averages, which are determined by low-frequency planetary wave predictability, in an attempt to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed, nonfluctuating external forcings. Sixty-day integrations of a global general circulation model with nine different initial conditions but identical boundary conditions of sea surface temperatures, snow, sea ice and soil moisture are carried out, where the rms vector wind error between the observed initial conditions is greater than 15 m/sec. It is found that while the variances among the first 30-day means, predicted from mostly different initial conditions, are significantly different from the variances due to random perturbations in the initial conditions, variances for days 31-60 are not so distinguishable. These results suggest that the evolution of long waves remains predictable for between one month and 45 days.

Shukla, J.↗
NASA NTRS2001

Ensemble Cannonical Correlation Prediction of Seasonal Precipitation Over the US

This paper presents preliminary results of an ensemble cannonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into nonoverlapping sectors. The cannonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all regions of the US and for all seasonal compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible for enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduced the spring predictability barrier over all regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and regional regional data. Moreover, the ECC forecasts can be applied to other climate subsystems and, in conjunction with further diagnostic or model studies will enables a better understanding of the dynamic links between climate variations and precipitation, not only for the US, but also for other regions of the world.

Lau, William K. M.↗
NASA NTRS2011

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Peters-Lidard, Christa D.↗
NASA NTRS2004

Investigation of the Seasonal Freeze/Thaw Cycle of Soils in the GAPP Regions

The objective of this project is to understand the current and future impacts and feedbacks of seasonally frozen ground on the regional and global climate system and the ecosystem as a whole. More specifically, we proposed to: investigate the dynamics of the seasonally freezing and thawing processes and their relations to current climatic conditions through in situ data analysis and numerical modeling; develop a comprehensive algorithm to detect surface soil freeze/thaw status for snow-free land surface using passive microwave remote sensing data and for snow-covered land surface using numerical modeling, and validate the algorithm and numerical model using available ground-based measurements; investigate seasonal and inter-annual variations of frozen soils in the GAPP regions using data generated from the new validated algorithm and their relations to the environmental factors such as air temperature, snow cover, surface morphology, soil type and soil moisture; generate a frozen soil data set which describes the timing, duration, thickness, and area extent of seasonally frozen ground for the period from 1978 to present. The proposed research will be accomplished through data analysis, remote sensing, and numerical modeling.

FREEZE-THAW TESTS↗
NASA NTRS2011

Performance Tests of Snow-Related Variables Over the Tibetan Plateau and Himalayas Using a New Version of NASA GEOS-5 Land Surface Model that Includes the Snow Darkening Effect

The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GO CART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3 ; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [Ion.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1) was used.

Yasunari, Tppei J.↗
NASA NTRS1971

The Nimbus image dissector camera system - An evaluation of its meteorological applications.

Brief description of the electronics and operation of the Nimbus image dissector camera system (IDCS). The geometry and distortions of the IDCS are compared to the conventional AVCS camera on board the operational ITOS and ESSA satellites. The unique scanning of the IDCS provides for little distortion of the image, making it feasible to use a strip grid for the IDCS received in real time by local APT stations. The dynamic range of the camera favors the white end (high reflectance) of the gray scale. Thus, the camera is good for detecting cloud structure and ice features through brightness changes. Examples of cloud features, ice, and snow-covered land are presented. Land features, on the other hand, show little contrast. The 2600 x 2600 km coverage by the IDCS is adequate for the early detection of weather systems which may affect the local area. An example of IDCS coverage obtained by an APT station in midlatitudes is presented.

Sabatini, R. R.↗
NASA NTRS1976

Study of mesoscale phenomena, winter monsoon clouds and snow area based on LANDSAT data

The author has identified the following significant results. Most longitudinal clouds which appear as continuous linear clouds are composed of small transversal clouds. There are mountain waves of different wavelength in a comparatively narrow area indicating complicated orographical effects on wind and temperature distribution or on both dynamical and static stability condition. There is a particular shape of cirrus cloud suggestive of turbulence in the vicinity of CAT in the upper troposphere near jet stream level and its cold air side. Thin cirrus of overcast condition can be distinguished by MSS; however, extremely thin cirrus of partly cloudy condition cannot be detected even in LANDSAT data. This presents a serious problem in the interpretation of satellite thermal infrared radiation data since they affect the value.

Tsuchiya, K.↗
NASA NTRS1987

Satellite-derived attributes of cloud vortex systems and their application to climate studies

Defense Meteorological Satellite Program (DMSP) visible and infrared mosaics are analyzed in conjunction with synoptic meteorological observations of sea level pressure (SLP) and upper-air height to derive composite patterns of cyclonic cloud vortices for the Northern Hemisphere. The patterns reveal variations in the structure and implied dynamics of cyclonic systems at different stages of development that include: (1) increasing vertical symmetry of the lower-level and upper-air circulations and (2) decreasing lower-tropospheric thicknesses and temperature advection, associated with increasing age of the vortex. Cloud vortices are more intense in winter than in summer and typically reach maximum intensity in the short-lived prespiral signature stage. There are major structural differences among frontal wave, polar air, and 'instant occlusion' cyclogenesis types. Cyclones in the dissipation stage may reintensify (deepen), as denoted by the appearance in the imagery of an asymmetric cloud band or a tightened spiral vortex. The satellite-derived statistics on cloud vortex intensity, which are seasonal- and latitude- as well as type-dependent, are applied to a preliminary examination of the synoptic manifestations of seasonal climate variability. An apparently close relationship is found, for two winter and spring seasons, between Northern Hemisphere cyclonic activity and variations in cryosphere variables, particularly the extent of Arctic sea ice. The results may indicate that increased snow and ice extent accompany a southward displacement of cyclonic activity and/or a predominance of deeper systems. However, there is also a strong regional dependence to the ice-synoptics feedback. This study demonstrates the utility of high resolution meteorological satellite imagery for studies of climate variations (climate dynamics).

Carleton, Andrew M.↗
NASA NTRS2005

Chapter 12A - Rotorcraft Flight Envelope Unique Considerations

As noted in Section 12, the term flight envelope is used to refer to the boundaries of aircraft loading and flight conditions within which operation of the aircraft is satisfactory, and beyond which some aspect becomes unacceptable. Each aircraft has its own peculiar set of operating conditions and limitations, and this is particularly true of rotorcraft. In addition to the concerns of the fixed wing aircraft test engineer, the helicopter test engineer has to be concerned with dynamic components such as main and tail rotors and their associated control components, transmissions, noise, vibrations, and environmental factors such as swirling particulates which can cause visual obscuration and/or aircraft erosion when operating in unprepared areas like desert, snow, or over salt water. Operation in the hover/low speed regime is a unique capability and is therefore the forte of the helicopter. This "new" regime has its own envelope concerns. This Section provides a brief overview of some of the considerations when establishing/expanding the flight envelope of a rotorcraft. Types of tests and maneuvers, instrumentation, and special considerations will be discussed. However, the reader must be aware that this Section is far from a complete description of all the factors which must be considered in establishing a rotorcraft flight envelope. Much of the material presented in Section 12 is pertinent to rotorcraft envelope definition.

Michael W Mosher↗
NASA NTRS2009

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Peters-Lidard, Christa D.↗
NASA NTRS2016

Effect of Satellite Formations and Imaging Modes on Global Albedo Estimation

We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static reference case. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/sq m or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than 70% ground spot overlap between the satellites is possible with 0.5deg of pointing accuracy, 2 Km of GPS accuracy and commands uplinked once a day. The formations can be maintained at less than 1 m/s of monthly (Delta)V per satellite.

BRDF↗
NASA NTRS2022

Defining and Characterizing Habitable Environments in Ocean World Systems

We explore the major characteristics of habitable environments on ocean worlds and how we can study them using Earth analogs and autonomous instru-mentation. Earth analogs for habitable regions on ocean worlds include interfaces (e.g., ice-water and seafloor-water boundaries), hydrothermal systems, and inside of ice, snow, clathrates, and crustal rocks. These analogs are best known in Earth’s ocean, but they may also exist on Earth’s land, particularly in polar regions. Importantly, ocean habitability requires that parts of the planetary body interact dynamically with the ocean. Probing the habitability of currently inaccessible extraterrestrial ocean worlds will require establishing biogenicity and abiotic reference frames for organic com-pounds on ocean worlds and technological advances to explore subsurface liquid water environments beyond Earth. Next generation studies of ocean world habitability will also require integrated modeling tools and coordination between the Earth/ocean sci-ences and the planetary science communities.

Jennifer B Glass↗
NASA NTRS1973

Satellite geological and geophysical remote sensing of Iceland: Preliminary results from analysis of MSS imagery

A binational, multidisciplinary research effort in Iceland is directed at an analysis of MSS imagery from ERTS-1 to study a variety of geologic, hydrologic, oceanographic, and agricultural phenomena. A preliminary evaluation of available MSS imagery of Iceland has yielded several significant results - some of which may have direct importance to the Icelandic economy. Initial findings can be summarized as follows: (1) recent lava flows can be delineated from older flows at Askja and Hekla; (2) MSS imagery from ERTS-1 and VHRR visible and infrared imagery from NOAA-2 recorded the vocanic eruption on Heimaey, Vestmann Islands; (3) coastline changes, particularly changes in the position of bars and beaches along the south coast are mappable; and (4) areas covered with new and residual snow can be mapped, and the appearance of newly fallen snow on ERTS-1, MSS band 7 appears dark where it is melting. ERTS-1 imagery provides a means of updating various types of maps of Iceland and will permit the compilation of special maps specifically aimed at those dynamic environmental phenomena which impact on the Icelandic economy.

Williams, R. S., Jr.↗
NASA NTRS1974

Microwave maps of the polar ice of the earth

Synoptic views of the entire polar regions of earth have been obtained free of the usual persistent cloud cover using a scanning microwave radiometer operating at a wavelength of 1.55 cm on board the Nimbus-5 satellite. Three different views at each pole are presented utilizing data obtained at approximately one-month intervals from December 1972 to February 1973. Large discrepancies exist between the long-term ice cover depicted in various atlases and the actual extent of the canopies. The distribution of multiyear ice in the north polar region is markedly different from that predicted by existing ice dynamics models. Irregularities in the edge of the Antarctic sea ice pack occur that have neither been observed previously nor anticipated. The brightness temperatures of the Greenland and Antarctic glaciers show interesting contours probably related to the ice and snow morphologic structure.

Gloersen, P.↗
NASA NTRS1979

Morphology and distribution of common 'sand' dunes on Mars - Comparison with the earth

A comparative study of Martian and terrestrial dunes was made based on Viking Orbiter pictures and aerial pictures of terrestrial deserts. The morphological similarity between the Martian dunes and terrestrial crescentic dunes implies that the dynamics of dune formation are similar on the two planets, despite Martian constraints on dune formation that include much higher velocity winds required to move 'sand' in saltation, the possible inhibition of sand movement by absorbed water vapor, the seasonal 'snow' cover in the north circumpolar erg, and a probably sparse sand supply. The absence of longitudinal dunes and the restriction of massive crescentic dunes to a few sites on Mars suggests that Mars may have a long eolian history in which much of the sand suitable for saltation has already been transported to the north polar erg and crater floor fields.

Breed, C. S.↗
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 NTRS1983

Photolysis of methane and the ionosphere of Uranus

Photochemical calculations for Uranus predict an extensive region of condensation of acetylene, ethane and methane in the vicinity of the temperature inversion layer. This could explain why ethane was not detected on Uranus, unlike Neptune which has a much warmer inversion layer. Subsequent snow-out of the condensibles is expected to result in reduced visibility in the troposphere. Ionospheric calculations for the equatorial region to be probed by Voyager, indicate peak electron concentrations on the order of 5,000 per cu cm, if dynamical effects are important. Upper limit to the electron peak is 30,000 per cu cm. Exospheric temperatures as high as 200-250K are conceivable.

Atreya, S. K.↗
NASA NTRS1984

Recent examples of mesoscale numerical forecasts of severe weather events along the east coast

Mesoscale numerical forecasts utilizing the Mesoscale Atmospheric Simulation System (MASS) are documented for two East Coast severe weather events. The two events are the thunderstorm and heavy snow bursts in the Washington, D.C. - Baltimore, MD region on 8 March 1984 and the devastating tornado outbreak across North and South Carolina on 28 March 1984. The forecasts are presented to demonstrate the ability of the model to simulate dynamical interactions and diabatic processes and to note some of the problems encountered when using mesoscale models for day-to-day forecasting.

Kocin, P. J.↗