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At least 703 records · Page 39
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NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering signi􀂦cant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

clouds↗
NASA NTRS2010

Investigation of Surface Flux Feedbacks for Coupled and Uncoupled Atmosphere-Ocean Anomalies

Variability in the atmosphere and ocean are linked through coupled processes via the surface exchanges of heat, moisture, and momentum. This coupling can occur predominantly via one-way (ocean forcing atmosphere or atmosphere forcing ocean) or two-way interactions. The dominant type of interaction can vary both regionally and with season. The existence of the coupled variability can act to enhance the persistence of anomalies and therefore may be important to seasonal (and longer) forecasts. The leading components of surface exchange that regulate the damping of the atmospheric and oceanic anomalies most likely also varies regionally and seasonally. This study seeks to elucidate the roles of the various surface flux components using satellite based data sets. Using dynamical relationships expected for one-way forcing regimes, coupled and uncoupled variability is isolated and used in conjunction with composite-type analyses to reveal the nature of these coupling mechanisms and their variation in space and time. Results of this study can be useful in examining the veracity of general circulation model output by understanding how the coupling mechanisms are replicated as found in satellite based observations.

Roberts, J. Brent↗
NASA NTRS2002

A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by rain decreases, as the size of a pixel becomes smaller. This means that within what looks like a patch of rainy area in a coarse resolution view with larger pixel size, one finds clusters of rainy and dry patches when viewed on a finer scale. The model makes definite predictions about how these and other related statistics depend on the pixel size. These predictions were found to agree well with data. In a subsequent second part of the work we plan to test the model with rain gauge data collected during the TRMM (Tropical Rainfall Measuring Mission) ground validation campaign.

Kundu, Prasun K.↗
NASA NTRS1999

Role of Ocean Currents and Bottom Pressure Variability on Seasonal Polar Motion

Changes in the ocean angular momentum (OAM) components about the equatorial axes, either due to fluctuations in currents or bottom pressure (mass redistribution), can induce movements of the Earth's pole of rotation, commonly referred to as polar motion or wobble. Output from a 1 deg resolution ocean model is used to calculate the effective equatorial OAM functions chi(sub 1, sup O) and chi(sub 2, sup O), corresponding to polar motion excitation about the equatorial axis pointing to the Greenwich and 90 deg E meridians, respectively. Time series of chi(sup O) are combined with similar atmospheric series chi(sup A), computed from the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalyses, to interpret the observed low-frequency polar motion excitation for the period 1985-1996. Results indicate that the oceans are a very important excitation source for the Chandler (approximately 433 days), annual, and semiannual wobbles, providing for much better amplitude and phase agreement with the observed excitation at these periods, in comparison with what is obtained when only the atmosphere is considered. Both oceanic mass and motion terms are found to be important but with mass signals having somewhat larger amplitudes. The role of regional variability in ocean currents and bottom pressure in contributing to chi(sup O) signals is quantified. Midlatitude regions (approximately 30 deg - 70 deg) figure prominently as places of strong local oceanic excitation signals. The North Pacific basin is found to be generally important for chi(sup O) excitation, while the Southern Ocean is important for both chi(sub 1, sup O) and chi(sub 2, sup O). The largest positive covariances of local with global chi(sup O) signals occur in the Kuroshio region near the western boundary of the North Pacific for chi(sub 1, sup O) and southwest of Australia for chi(sub 2, sup O).

Ponte, Rui M.↗
NASA NTRS2005

Computing Thermal Effects of Cavitation in Cryogenic Liquids

A computer program implements a numerical model of thermal effects of cavitation in cryogenic fluids. The model and program were developed for use in designing and predicting the performances of turbopumps for cryogenic fluids. Prior numerical models used for this purpose do not account for either the variability of properties of cryogenic fluids or the thermal effects (especially, evaporative cooling) involved in cavitation. It is important to account for both because in a cryogenic fluid, the thermal effects of cavitation are substantial, and the cavitation characteristics are altered by coupling between the variable fluid properties and the phase changes involved in cavitation. The present model accounts for both thermal effects and variability of properties by incorporating a generalized representation of the properties of cryogenic fluids into a generalized compressible-fluid formulation for a cavitating pump. The model has been extensively validated for liquid nitrogen and liquid hydrogen. Using the available data on the properties of these fluids, the model has been shown to predict accurate temperature-depression values.

Hosangadi, Ashvin↗
NASA NTRS2014

Configuration and Assessment of the GISS ModelE2 Contributions to the CMIP5 Archive

We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980-2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics.

ocean model↗
NASA NTRS2001

Determination of Interannual to Decadal Changes in Ice Sheet Mass Balance from Satellite Altimetry

A major uncertainty in predicting sea level rise is the sensitivity of ice sheet mass balance to climate change, as well as the uncertainty in present mass balance. Since the annual water exchange is about 8 mm of global sea level equivalent, the +/- 25% uncertainty in current mass balance corresponds to +/- 2 mm/yr in sea level change. Furthermore, estimates of the sensitivity of the mass balance to temperature change range from perhaps as much as - 10% to + 10% per K. Although the overall ice mass balance and seasonal and inter-annual variations can be derived from time-series of ice surface elevations from satellite altimetry, satellite radar altimeters have been limited in spatial coverage and elevation accuracy. Nevertheless, new data analysis shows mixed patterns of ice elevation increases and decreases that are significant in terms of regional-scale mass balances. In addition, observed seasonal and interannual variations in elevation demonstrate the potential for relating the variability in mass balance to changes in precipitation, temperature, and melting. From 2001, NASA's ICESat laser altimeter mission will provide significantly better elevation accuracy and spatial coverage to 86 deg latitude and to the margins of the ice sheets. During 3 to 5 years of ICESat-1 operation, an estimate of the overall ice sheet mass balance and sea level contribution will be obtained. The importance of continued ice monitoring after the first ICESat is illustrated by the variability in the area of Greenland surface melt observed over 17-years and its correlation with temperature. In addition, measurement of ice sheet changes, along with measurements of sea level change by a series of ocean altimeters, should enable direct detection of ice level and global sea level correlations.

Zwally, H. Jay↗
NASA NTRS2014

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.

Data Analytics↗
NASA NTRS1998

Adaptive Variable Bias Magnetic Bearing Control

Most magnetic bearing control schemes use a bias current with a superimposed control current to linearize the relationship between the control current and the force it delivers. With the existence of the bias current, even in no load conditions, there is always some power consumption. In aerospace applications, power consumption becomes an important concern. In response to this concern, an alternative magnetic bearing control method, called Adaptive Variable Bias Control (AVBC), has been developed and its performance examined. The AVBC operates primarily as a proportional-derivative controller with a relatively slow, bias current dependent, time-varying gain. The AVBC is shown to reduce electrical power loss, be nominally stable, and provide control performance similar to conventional bias control. Analytical, computer simulation, and experimental results are presented in this paper.

Johnson, Dexter↗
NASA NTRS2008

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Molnar, Gyula↗
NASA NTRS2015

Characterization of the Temporal-Spatial Variability of Trans-Atlantic Dust Transport Based on CALIPSO Lidar Measurements

The trans-Atlantic dust transport has important implications for human and ecosystem health, the terrestrial and oceanic biogeochemical cycle, weather systems, and climate. A reliable assessment of these influences requires the characterization of dust distributions in three dimensions and over long time periods. We provide an observation-based multiyear estimate of trans-Atlantic dust transport by using a 7-year (2007 - 2013) lidar record from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) in both cloud-free and above-cloud conditions. We estimate that on a basis of the 7-year average and integration over 10S - 30N, 182 Tg a-1 dust leaves the coast of North Africa at 15W, of which 132 Tg a-1 and 43 Tg a-1 reaches 35W and 75W, respectively. These flux estimates have an overall known uncertainty of (45 - 70). The 7-year average of dust deposition into the Amazon Basin is estimated to be 28 (8 - 48) Tg a-1 or 29 (8 - 50) kg ha-1 a-1. This imported dust could provide about 0.022 (0.006 - 0.037) Tg P of phosphorus per year, equivalent to 23 (7 - 39) g P ha-1 a-1 to fertilize the Amazon rainforest, which is comparable to the loss of phosphorus to rainfall. Significant seasonal variations are observed in both the magnitude of total dust transport and its meridional and vertical distributions. The observed large interannual variability of annual dust transport is highly anti-correlated with the prior-year Sahel Precipitation Index. Comparisons of CALIPSO measurements with surface-based observations and model simulations will also be discussed.

Transport↗
NASA NTRS1974

Convection in the moon - Effect of variable viscosity

This work determines criteria for stability of the lunar interior to thermal convection in the case of variable viscosity. The conditions necessary for solid convection to play an important role in the moon's revolution are determined by application of the calculated stability criteria to a variety of thermal history models. Most thermal history temperature profiles would be unstable to solid convection at the present time, if currently used estimates of the viscosity function are applicable. A possible explanation of lunar seismic data is that temperatures near the melting point of silicates exist at depths greater than 800 km. If this is the case, either the lunar interior is stable, or solid convection is occurring at a rate insufficient to cool the lunar interior substantially. If the former is true, the viscosity of lunar material is higher than that usually assumed.

Cassen, P.↗
NASA NTRS1979

Diffuse Jovian aurora influenced by plasma injection from Io

The paper demonstrates that the broad band of whistler-mode waves observed within the high density torus surrounding Io is consistent with electron cyclotron generation. Cyclotron resonant instability of Jovian energetic electrons is enhanced due to the lower resonant electron energy within the equatorial high density plasma torus surrounding the orbit of Io. The higher energy resonant electron scattering and the corresponding energetic electron lifetimes indicate that an efficient local acceleration process is required to replenish the precipitating relativistic electrons. Calculated energy deposition into the Jovian atmosphere should provide a dominant source of middle atmospheric ionization and excite a continuous band of diffuse auroral emission. It is suggested that the diffuse Jovian aurora should be influenced by the variable volcanic activity on Io which is thought to be an important source of plasma, since the cyclotron scattering process is strongly influenced by the ambient equatorial thermal plasma density.

Thorne, R. M.↗
NASA NTRS1981

The solar ultraviolet source for the ionosphere and its variation

Ion production in the ionospheric E and F regions is primarily due to solar EUV fluxes at wavelengths below 102.7 nm, where the flux ratios of maximum/minium for the present solar cycle were found to range from values around 3 for the dominant chromospheric emissions to much higher values for coronal emissions, resulting in a factor of about 4 in the integrated flux of the range 14-102.7 nm. The vertical distribution of ion production depends not only on the incident solar EUV fluxes but also on the structure of the absorbing neutral atmosphere (thermosphere). As the latter is strongly affected by solar EUV fluxes above 130 nm (production of atomic oxygen and heating), the observed increase, with ratios ranging from about 1.2 around 175-185 nm to about 2.3 around 140 nm, is at least indirectly important in the solar cycle variation of the ionosphere. The EUV variability models of the ionosphere using non EUV indices such as F sub 10.7, R sub Z or Ca2 plage indices are valuable as a crude guide only, but not for quantitative representations.

Hinteregger, H. E.↗
NASA NTRS1985

A systematic study of magnetic braking in low-mass binaries

A short summary is given of Rappaport et al. (1983) which described results of extending a simplified stellar evolution code covering the evolution of low-mass compact binaries. Magnetic braking is probably an important process in the evolution of such binaries (such as cataclysmic variables and low-mass X-ray sources). The initial simplified code describes the mass-losing star as an n = 3/2 polytrope and was developed to study the evolution of binaries with a secondary of low mass (between 0.01 and 0.4 solar mass) when the angular momentum losses are due to gravitational radiation. In the extended code, a composite polytrope model is used for the secondary, wherein the structure of the radiative core is described by an n = 3 polytrope and the convective envelope by an n = 3/2 polytrope.

Verbunt, F.↗
NASA NTRS1990

Global Models of Intermediate Timescale Variability on the Sun

In recent years a number of advances in both observation and theory have increased our understanding of the solar interior and how to model it. For climate studies, the timescale of interest for changes in the Sun ranges from decades to centuries. Some of the theoretical advances that will contribute to the building of global models of the Sun's variability on intermediate timescales are described. The current constraints on the important components are discussed. Finally a short discussion presenting some implications for input to climate modeling is presented.

Fox, Peter A.↗
NASA NTRS1990

Using KD(asterisk)P modulators for polarization measurements of the sun

Longitudinal KD(asterisk)Ps are used in ground-based solar magnetographs to eliminate seeing effects by rapidly changing their retardation characteristics. Although one of the main applications for longitudinal KD(asteriak)Ps has been their use as a variable retarder for 'imaging' applications, an understanding of their limitations is important when developing scientific instruments that make very accurate polarization measurements. This paper discusses some of the problems associated with the use of these devices in the Marshall Space Flight Center (MSFC) vector magnetograph, including temperature, field of view errors, and electrical characteristics.

West, E. A.↗
NASA NTRS1992

The multiple-function multi-input/multi-output digital controller system for the AFW wind-tunnel model

A real time multiple-function digital controller system was developed for the Active Flexible Wing (AFW) Program. The digital controller system (DCS) allowed simultaneous execution of two control laws: flutter suppression and either roll trim or a rolling maneuver load control. The DCS operated within, but independently of, a slower host operating system environment, at regulated speeds up to 200 Hz. It also coordinated the acquisition, storage, and transfer of data for near real time controller performance evaluation and both open- and closed-loop plant estimation. It synchronized the operation of four different processing units, allowing flexibility in the number, form, functionality, and order of control laws, and variability in the selection of the sensors and actuators employed. Most importantly, the DCS allowed for the successful demonstration of active flutter suppression to conditions approximately 26 percent (in dynamic pressure) above the open-loop boundary in cases when the model was fixed in roll and up to 23 percent when it was free to roll. Aggressive roll maneuvers with load control were achieved above the flutter boundary. The purpose here is to present the development, validation, and wind tunnel testing of this multiple-function digital controller system.

Hoadley, Sherwood T.↗