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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Analysis of the Global Microwave Polarization Data of Clouds

Two NASA microwave radiometers, the satellite-borne GPM (Global Precipitation Measurement) Microwave Imager (GMI) and the aircraft-borne CoSMIR (the Conical Scanning Millimeter-wave Imaging Radiometer), measure vertically- and horizontally-polarized microwaves emitted by cloud particles and the Earth below, providing unique information on ice crystal properties in clouds. Their data reveal that non-spherical ice crystals are common and they fall in a preferred horizontally aligned orientation in convective and optically thick clouds especially near cloud top. A bin (particle-size-resolving) microphysical model with an ice crystal shape representation is developed to simulate the evolution of ice crystal properties (i.e., size, shape and orientation), where the radiation effect on microphysics (REM) is taken into account. Since REM represents the effect of all (e.g., both infrared and solar) radiation on ice crystal temperature, it relies upon the ice crystal proprieties that determine how an ice crystal receives radiation. Definitely, REM is different from the radiative effects that cause sensitivity at the microwave frequencies in the GPM and CoSMIR observations. Model results show that horizontally-oriented ice crystals grow faster than vertically-oriented (or spherical) ones due to REM. When both horizontally- and vertically-oriented ice crystals coexist in an air parcel, the model results show that the former grow by vapor deposition whereas the latter shrink by sublimation and disappear eventually. These modeling results are supported by the GMI data and the CoSMIR observations from MC3E (Midlatitude Continental Convective Clouds Experiment) and OLYMPEX (Olympic Mountains Experiment) on the prevalence of horizontally-oriented ice crystals. Moreover, the REM-induced precipitation explains the CloudSat observations of rare thin clouds in the tropical mid-troposphere as well as the common diamond dust in the high latitudes.

Xiping Zeng↗
NASA NTRS1979

Martian wind activity detected by a seismometer at Viking lander 2 site

Since the Viking lander 2 seismometer (Anderson et al., 1977) located on top of the lander is extremely sensitive to Martian winds, it can provide a record of Martian wind activity. The seismograph continuously samples the wind-induced lander vibration, and its output complements meteorological data. Some pertinent seismic data are presented along with results of a preliminary spectral analysis of the data. Attention is given to wind speed/seismic noise correlation, and to long-term variation and periodicity. The results indicate that wind variations on Mars are very regular in the summer and winter seasons. Winds are light in summer and exhibit a strong diurnal periodicity, the strongest winds occurring in the early afternoon. Winds become stronger and more irregular in autumn. In all seasons nighttime conditions are usually very quiet. The high wind season correlates with the global dust storm duration. Spring is characterized by very strong though variable wind activity. Other details are also presented.

Nakamura, Y.↗
NASA NTRS1985

Variation objective analyses for cyclone studies

The objectives were to: (1) develop an objective analysis technique that will maximize the information content of data available from diverse sources, with particular emphasis on the incorporation of observations from satellites with those from more traditional immersion techniques; and (2) to develop a diagnosis of the state of the synoptic scale atmosphere on a much finer scale over a much broader region than is presently possible to permit studies of the interactions and energy transfers between global, synoptic and regional scale atmospheric processes. The variational objective analysis model consists of the two horizontal momentum equations, the hydrostatic equation, and the integrated continuity equation for a dry hydrostatic atmosphere. Preliminary tests of the model with the SESMAE I data set are underway for 12 GMT 10 April 1979. At this stage of purpose of the analysis is not the diagnosis of atmospheric structures but rather the validation of the model. Model runs for rawinsonde data and with the precision modulus weights set to force most of the adjustment of the wind field to the mass field have produced 90 to 95 percent reductions in the imbalance of the initial data after only 4-cycles through the Euler-Lagrange equations. Sensitivity tests for linear stability of the 11 Euler-Lagrange equations that make up the VASP Model 1 indicate that there will be a lower limit to the scales of motion that can be resolved by this method. Linear stability criteria are violated where there is large horizontal wind shear near the upper tropospheric jet.

Achtemeier, G. L.↗
NASA NTRS1988

Control of the flexible modes of an advanced technology geostationary platform

A controls analysis is conducted on an advanced technology geostationary platform. This spacecraft is a large flexible structure with a payload of Earth-sensing instruments which will collect data from Earth's oceans, land, and atmosphere as a part of the bold initiative mission to Planet Earth proposed by NASA. This program will provide a collection of data from a family of spacecraft in both low-Earth orbit and geostationary orbit, which will afford a global definition of the Earth as a system with the capability to predict future events resulting from human and natural forces. The platform concept studied here is a large flexible structure with a payload of eighteen instruments. Because the platform is in geostationary orbit, these instruments have sensitive pointing accuracy requirements, in the range of 0.1 to 0.0001 degrees, which must be satisfied. The structure housing the instruments is large and flexible with characteristic low natural frequencies, so active control is necessary for vibration suppression.

Dewalt, Diane V.↗
NASA NTRS2017

Diffusivities of Redox-Sensitive Elements in Basalt vs. Oxygen Fugacity Determined by LA-ICP-MS

Several diffusion experiments were conducted in a piston cylinder device across a range of oxygen fugacities (FMQ-3 FMQ-1.2, FMQ+6) at 1 GPa and 1300 C. This was done to explore the effects of oxygen fugacity (fO2) on diffusivity of redox sensitive trace elements. This allows investigation of how these elements diffuse across the fO2 range encountered in different reservoirs on planets and moons in our solar system. The University of Rochester LA-ICP-MS system was used for analysis of samples. Analyses were conducted using an Agilent 7900 quadrupole mass spectrometer connected to a Photon Machines 193 nm G2 laser ablation (LA) system equipped with a HelEx 2-volume sample chamber. Spots used were 35 micrometers circles spaced at 65 micrometers intervals. Laser fluence was 7.81 J/cm^2 with a rep rate of 10 Hz. The iolite software package was used to reduce data collected from laser ablation analysis of experiments with Si-29 used as the internal standard isotope. Iolite's global fit module was used to simultaneously fit elements' diffusivities in each experiment while keeping the Matano interface constant. Elements analysed include V, Nb, W, Mo, La, Ce, Pr, Sm, Eu, Gd, Ta, and W. Figures

Szumila, Ian↗
NASA NTRS1999

Interannual Variability of the Mosaic Land-Surface Model

Recently, NASA Goddard Earth Observing System (GEOS-1) reanalysis data has been used to provide forcing for the Koster and Suarez Mosaic Land-surface Model (LSM). The LSM was integrated off-line at all global land points for the period of 1983 - 1995 by the Off-line Land- surface GEOS Assimilation system (OLGA). Here, we compare the interannual variability of OLGA, GEOS-1 and surface observing stations temperature and moisture. Particular attention is given to the United States because of the extreme seasons of 1988 and 1993. Furthermore, the comparison of OLGA is extended to include the analysis of data on the'tiles' (different surface types) in the Mosaic LSM. Results indicate that the GEOS-1 near-surface temperature and moisture reasonably represents the interannual variability in more normal years. However, OLGA also simulates the extreme drought and floods years well. The analysis of the tile information shows that the "Bare soil" surface type is most sensitive to the climate extremes. Off-line testing has provided valuable information on the performance of the Mosaic LSM prior to its incorporation into the new version of the GEOS Data Assimilation System and the integration of a new long reanalysis.

Bosilovich, Michael G.↗
NASA NTRS2003

Estimating the k2 Tidal Gravity Love Number of Mars

Analysis of the orbits of spacecraft can be used to infer global tidal parameters. For Mars, the Mars Global Surveyor (MGS) spacecraft has been used to estimate the second degree Love number, k2 from the tracking DSN tracking Doppler and range data by several authors. Unfortunately, neither of the spacecraft presently in orbit are ideally suited to tidal recovery because they are in sun-synchronous orbits that vary only slightly in local time; and, further, the sub-solar location only varies by about 25 degrees in latitude. Never-the less respectable estimates of the k2 tide have been made by several authors. We present an updated solution of the degree 2 zonal Love number, compare with previous dues, and analyze the sensitivity of the solution to orbital parameters, spacecraft maneuvers, and solution methodology. Estimating the k2 Tidal Gravity Love Number of Mars.

Smith, David E.↗
NASA NTRS2010

Transfer of Satellite Rainfall Uncertainty from Gauged to Ungauged Regions at Regional and Seasonal Timescales

Hydrologists and other users need to know the uncertainty of the satellite rainfall data sets across the range of time/space scales over the whole domain of the data set. Here, uncertainty' refers to the general concept of the deviation' of an estimate from the reference (or ground truth) where the deviation may be defined in multiple ways. This uncertainty information can provide insight to the user on the realistic limits of utility, such as hydrologic predictability, that can be achieved with these satellite rainfall data sets. However, satellite rainfall uncertainty estimation requires ground validation (GV) precipitation data. On the other hand, satellite data will be most useful over regions that lack GV data, for example developing countries. This paper addresses the open issues for developing an appropriate uncertainty transfer scheme that can routinely estimate various uncertainty metrics across the globe by leveraging a combination of spatially-dense GV data and temporally sparse surrogate (or proxy) GV data, such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and the Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar. The TRMM Multi-satellite Precipitation Analysis (TMPA) products over the US spanning a record of 6 years are used as a representative example of satellite rainfall. It is shown that there exists a quantifiable spatial structure in the uncertainty of satellite data for spatial interpolation. Probabilistic analysis of sampling offered by the existing constellation of passive microwave sensors indicate that transfer of uncertainty for hydrologic applications may be effective at daily time scales or higher during the GPM era. Finally, a commonly used spatial interpolation technique (kriging), that leverages the spatial correlation of estimation uncertainty, is assessed at climatologic, seasonal, monthly and weekly timescales. It is found that the effectiveness of kriging is sensitive to the type of uncertainty metric, time scale of transfer and the density of GV data within the transfer domain. Transfer accuracy is lowest at weekly timescales with the error doubling from monthly to weekly.However, at very low GV data density (<20% of the domain), the transfer accuracy is too low to show any distinction as a function of the timescale of transfer.

Tang, Ling↗
NASA NTRS2010

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Sandford, Stephen P.↗
NASA NTRS1993

Cloud detection using satellite measurements of infrared and visible radiances for ISCCP

This paper, the first of three, describes the cloud detection part of the International Satellite Cloud Climatology Project (ISCCP) analysis. Key features of the cloud detection alogrithm are (1) use of space and time radiance variation tests over several different space and time domains to account for the global variety of cloudy and clear characteristics, (2) estimation of clear radiance values for every time and place, and, (3) use of radiance thresholds that vary with the type of surface and climate regime. Design of the detection algorithm was supported by global, multiyear surveys of the statistical behavior of satellite-measured infrared and visible radiances to determine those characteristics that differentiate cloudy and clear scenes and how these characteristics vary among climate regimes. A summary of these statistical results is presented to illustrate how the cloud detection method works in a variety of circumstances. The sensitivity of the results to changing test parameter values is determined to provide a first estimate of the uncertainty of ISCCP cloud amounts. These test results (which exclude polar regions) suggest detection uncertainties of about 10% with possible negative biases of 5% (especially at night).

Rossow, Illiam B.↗
NASA NTRS2007

Tropospheric Vertical Distribution of Tropical Atlantic Ozone Observed by TES during the Northern African Biomass Burning Season

We present vertical distributions of ozone from the Tropospheric Emission Spectrometer (TES) over the tropical Atlantic Ocean during January 2005. Between 10N and 20S, TES ozone retrievals have Degrees of Freedom for signal (DOF) around 0.7 - 0.8 each for tropospheric altitudes above and below 500 hPa. As a result, TES is able to capture for the first time from space a distribution characterized by two maxima: one in the lower troposphere north of the ITCZ and one in the middle and upper troposphere south of the ITCZ. We focus our analysis on the north tropical Atlantic Ocean, where most of previous satellite observations showed discrepancies with in-situ ozone observations and models. Trajectory analyses and a sensitivity study using the GEOS-Chem model confirm the influence of northern Africa biomass burning on the elevated ozone mixing ratios observed by TES over this region.

satellite observations↗
DOE OSTI2020

Interpreting and Stabilizing Machine-Learning Parametrizations of Convection

Neural networks are a promising technique for parameterizing subgrid-scale physics (e.g., moist atmospheric convection) in coarse-resolution climate models, but their lack of interpretability and reliability prevents widespread adoption. For instance, it is not fully understood why neural network parameterizations often cause dramatic instability when coupled to atmospheric fluid dynamics. This paper introduces tools for interpreting their behavior that are customized to the parameterization task. First, we assess the nonlinear sensitivity of a neural network to lower-tropospheric stability and the midtropospheric moisture, two widely studied controls of moist convection. Second, we couple the linearized response functions of these neural networks to simplified gravity wave dynamics, and analytically diagnose the corresponding phase speeds, growth rates, wavelengths, and spatial structures. To demonstrate their versatility, these techniques are tested on two sets of neural networks, one trained with a super-parameterized version of the Community Atmosphere Model (SPCAM) and the second with a near-global cloud-resolving model (GCRM). Additionally, even though the SPCAM simulation has a warmer climate than the cloud-resolving model, both neural networks predict stronger heating/drying in moist and unstable environments, which is consistent with observations. Moreover, the spectral analysis can predict that instability occurs when GCMs are coupled to networks that support gravity waves that are unstable and have phase speeds larger than 5 m s -1 . In contrast, standing unstable modes do not cause catastrophic instability. Using these tools, differences between the SPCAM-trained versus GCRM-trained neural networks are analyzed, and strategies to incrementally improve both of their coupled online performance unveiled.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Analysis of Composite Panels Subjected to Thermo-Mechanical Loads

The results of a detailed study of the effect of cutout on the nonlinear response of curved unstiffened panels are presented. The panels are subjected to combined temperature gradient through-the-thickness combined with pressure loading and edge shortening or edge shear. The analysis is based on a first-order, shear deformation, Sanders-Budiansky-type shell theory with the effects of large displacements, moderate rotations, transverse shear deformation, and laminated anisotropic material behavior included. A mixed formulation is used with the fundamental unknowns consisting of the generalized displacements and the stress resultants of the panel. The nonlinear displacements, strain energy, principal strains, transverse shear stresses, transverse shear strain energy density, and their hierarchical sensitivity coefficients are evaluated. The hierarchical sensitivity coefficients measure the sensitivity of the nonlinear response to variations in the panel parameters, as well as in the material properties of the individual layers. Numerical results are presented for cylindrical panels and show the effects of variations in the loading and the size of the cutout on the global and local response quantities as well as their sensitivity to changes in the various panel, layer, and micromechanical parameters.

Noor, Ahmed K.↗
NASA NTRS2001

Monitoring of MLS Measurements for Ozone Data Assimilation

The ozone data assimilation system at the NASA Goddard Space Flight Center Data Assimilation Office (DAO) has operationally provided near real time global three dimensional analyzed ozone fields since December 1999. Presently, 4 system assimilates both total column ozone and profile measurements from the NOAA - 16 SBUV/2 instrument into an off-line transport model using a physical space statistical analysis scheme (PS AS). Recently, this system was modified to investigate a possible impact from including MLS profile observations. Over a period from December 13, 1991 to March 1, 1992 the system assimilated both NOAA 11 SBUV/2 profile measurements and TOMS total column measurements. Short term ozone forecasts were produced and compared to MLS observations. The resulting observed -minus -forecast (O-F) residuals were studied regionally (by both latitude bands and pressure levels) in order to explore the potential impact of MLS observations on the assimilation and sensitivity to the UARS yaw maneuver and other instrument and algorithm characteristics. In addition, MLS profiles were compared to nearest neighbor SBUV and analysis profiles. In the tropics, analyzed ozone values tend to be too high from 1-3 hPa and too low from 10-20 hPa. MLS measurements in these regions tend be lower and higher (respectively) than forecast ozone values. This indicates that assimilating MLS measurements may improve, analysis results in these areas. Further, nearest neighbor profile comparisons in the southern high latitudes indicate that laminar features present in the analysis but not present in SBUV measurements, are also present in MLS measurements. This, together with the availability of MLS measurements in polar night regions indicates that assimilating MLS measurements in polar night regions indicates that assimilating MLS measurements may improve analyzed ozone values in high latitudes.

Winslow, Nathan↗
NASA NTRS1990

Summary of results and conclusions based on analysis of volume imaging and high spectral resolution lidar data acquired during FIRE phase 1, part 1

The collection of long term global statistics on cloud cover may be most easily accomplished with satellite based observations; however, measurements derived from passive satellite retrieval methods must be calibrated and verified by in situ or ground based remote sensor observations. Verification is not straight forward, however, because the highly variable nature of cloud altitude, morphology, and optical characteristics complicates the scaling of point measurements to satellite footprint sized areas. This is particularly evident for cirrus clouds which may be organized on horizontal scales of 10's of meters to 8 km or more, and have optical depths ranging from less than .003 to greater than 3. Cirrus clouds can strongly influence earths' radiative balance, but, because they are often transmissive, cirrus clouds are difficult to detect and characterize from satellite measurements. Because of its precise ranging capabilities, spatial resolution and sensitivity, lidar observations have played an important role in the detection, depiction, and characterization of cirrus clouds. Some of the characteristics of cirrus clouds are summarized which observed the High Spectral Resolution and Volume Imaging Lidars during the phase 1 IFO and ETO periods.

Grund, Christian J.↗
DOE OSTI2022

Differentially Private Synthesis and Sharing of Network Data Via Bayesian Exponential Random Graph Models

Abstract Network data often contain sensitive relational information. One approach to protecting sensitive information while offering flexibility for network analysis is to share synthesized networks based on the information in originally observed networks. We employ differential privacy (DP) and exponential random graph models (ERGMs) and propose the DP-ERGM method to synthesize network data. We apply DP-ERGM to two real-world networks. We then compare the utility of synthesized networks generated by DP-ERGM, the DyadWise Randomized Response (DWRR) approach, and the Synthesis through Conditional distribution of Edge given nodal Attribute (SCEA) approach. In general, the results suggest that DP-ERGM preserves the original information significantly better than two other approaches in network structural statistics and inference for ERGMs and latent space models. Furthermore, DP-ERGM satisfies node DP through modeling the global network structure with ERGM, a stronger notion of privacy than the edge DP under which DWRR and SCEA operate.

graph synthesis↗
NASA NTRS1999

The Prospect for Remote Sensing of Cirrus Clouds with a Submillimeter-Wave Spectrometer

Given the substantial radiative effects of cirrus clouds and the need to validate cirrus cloud mass in climate models, it is important to measure the global distribution of cirrus properties with satellite remote sensing. Existing cirrus remote sensing techniques, such as solar reflectance methods, measure cirrus ice water path (IWP) rather indirectly and with limited accuracy. Submillimeter/wave radiometry is an independent method of cirrus remote sensing based on ice particles scattering the upwelling radiance emitted by the lower atmosphere. A new aircraft instrument, the Far Infrared Sensor for Cirrus (FIRSC), is described. The FIRSC employs a Fourier Transform Spectrometer (FTS). which measures the upwelling radiance across the whole submillimeter region (0.1 1.0-mm wavelength). This wide spectral coverage gives high sensitivity to most cirrus particle sizes and allows accurate determination of the characteristic particle size. Radiative transfer modeling is performed to analyze the capabilities of the submillimeter FTS technique. A linear inversion analysis is done to show that cirrus IWP, particle size, and upper-tropospheric temperature and water vapor may be accurately measured, A nonlinear statistical algorithm is developed using a database of 20000 spectra simulated by randomly varying most relevant cirrus and atmospheric parameters. An empirical orthogonal function analysis reduces the 500-point spectrum (20 - 70/cm) to 15 "pseudo-channels" that are then input to a neural network to retrieve cirrus IWP and median particle diameter. A Monte Carlo accuracy study is performed with simulated spectra having realistic noise. The retrieval errors are low for IWP (rms less than a factor of 1.5) and for particle sizes (rins less than 30%) for IWP greater than 5 g/sq m and a wide range of median particle sizes. This detailed modeling indicates that there is good potential to accurately measure cirrus properties with a submillimeter FTS.

Evans, K. Franklin↗