SEARCH · Engineering Papers

Results for “Observation Data”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2015

Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet

The majority of research on efficient and scalable algorithms in computational science and engineering has focused on the forward problem : given parameter inputs, solve the governing equations to determine output quantities of interest. In contrast, in this paper, we consider the broader question: given a (large-scale) model containing uncertain parameters, (possibly) noisy observational data, and a prediction quantity of interest, how do we construct efficient and scalable algorithms to (1) infer the model parameters from the data (the deterministic inverse problem ), (2) quantify the uncertainty in the inferred parameters (the Bayesian inference problem), and (3) propagate the resulting uncertain parameters through the model to issue predictions with quantified uncertainties (the forward uncertainty propagation problem )? We present efficient and scalable algorithms for this end-to-end, data-to-prediction process under the Gaussian approximation and in the context of modeling the flow of the Antarctic ice sheet and its effect on loss of grounded ice to the ocean. The ice is modeled as a viscous, incompressible, creeping, shear-thinning fluid. The observational data come from satellite measurements of surface ice flow velocity, and the uncertain parameter field to be inferred is the basal sliding parameter, represented by a heterogeneous coefficient in a Robin boundary condition at the base of the ice sheet. The prediction quantity of interest is the present-day ice mass flux from the Antarctic continent to the ocean. We show that the work required for executing this data-to-prediction process—measured in number of forward (and adjoint) ice sheet model solves—is independent of the state dimension, parameter dimension, data dimension, and the number of processor cores. The key to achieving this dimension independence is to exploit the fact that, despite their large size, the observational data typically provide only sparse information on model parameters. This property can be exploited to construct a low rank approximation of the linearized parameter-to-observable map via randomized SVD methods and adjoint-based actions of Hessians of the data misfit functional.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

How Well do Earth System Models Capture Apparent Relationships Between Phytoplankton Biomass and Environmental Variables?

Abstract As phytoplankton form the base of the marine food web, understanding the controls on their abundance is fundamental to understanding marine ecology and its sensitivity to global climate change. While many Earth System Models (ESMs) predict phytoplankton biomass, it is unclear whether they properly capture the mechanistic relationships that control this quantity in the real ocean. We used Random Forest analysis to analyze the output of 13 ESMs as well as two observational data sets. The target variable was phytoplankton carbon and the predictors included environmental parameters known to influence phytoplankton, including nutrients, light, mixed layer depth, salinity, temperature, and upwelling. We examined the following: (a) What fractions of variability in ESMs and observations can be linked to the large‐scale environmental variables simulated by ESMs? (b) What are the dominant predictors and relationships affecting phytoplankton biomass? (c) How well do ESMs simulate phytoplankton carbon and do they simulate the relationships we see in observations? About 88%–96% of the variability in observational data sets and greater than 98% in the ESMs was accounted for by environmental variables known to influence phytoplankton biomass. The dominant predictors in the observational data sets were shortwave radiation and dissolved iron, with temperature and ammonium also relatively important. All the ESMs show that shortwave radiation is the most important variable and most of them predict the right sign of sensitivity to most variables. However, the models predict that biomass reaches maximum levels at unrealistically low levels of iron and unrealistically high levels of light.

Environmental Sciences & Ecology↗

NASA NTRS1979

International Planetary Patrol observations of Saturn's rings. I - Observations and data reduction

The paper describes the reduction procedure used for observations of Saturn's rings taken with the International Planetary Patrol Network in 1977. Corrections for atmospheric smearing are determined using an assumed ring model and performed by a two-dimensional Wiener filter developed at JPL's Image Processing Laboratory. These smearing corrections are shown to be consistent with the radial profile of the rings, not just on the major axis of the ring system, but over a range of azimuthal angle.

Lumme, K.↗

DOE OSTI2015

First Observation of C P Violation in B ¯ 0 → D C P ( * ) h 0 Decays by a Combined Time-Dependent Analysis of BABAR and Belle Data

We report a measurement of the time-dependent CP asymmetry of B¯ 0 → D$^{(*)}_{CP}$h 0 decays, where the light neutral hadron h 0 is a π 0 , η, or ω meson, and the neutral D meson is reconstructed in the CP eigenstates K + K – , K$^{0}_{S}$π 0 , or K$^{0}_{S}$ω. The measurement is performed combining the final data samples collected at the Υ(4S) resonance by the BABAR and Belle experiments at the asymmetric-energy B factories PEP-II at SLAC and KEKB at KEK, respectively. The data samples contain (471 ± 3) × 10 6 BB¯ pairs recorded by the BABAR detector and (772 ± 11) × 10 6 BB¯ pairs recorded by the Belle detector. We measure the CP asymmetry parameters –ηfS = +0.66 ± 0.10(stat) ± 0.06(syst) and C = –0.02 ± 0.07(stat) ± 0.03(syst). Here, these results correspond to the first observation of CP violation in B¯ 0 → D$^{(*)}_{CP}$h 0 decays. The hypothesis of no mixing-induced CP violation is excluded in these decays at the level of 5.4 standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1990

Identification of Cirrus over Wausau during the 1986 FIRE IFO from ground-based radiometer data

The potential of using irradiation data to indicate episodes of cirrus cloudiness during the daylight hours is explored. Thresholds separating cirrus from other clouds and clear skies are determined using four days of irradiation data, hourly weather observations, sky photographs, sky video, and occasional lidar observations. Data were gathered during the First International Satellite Cloud Climatology Program (ISCCP) Regional Experiment (FIRE) Intensive Field Observations (IFO) cirrus project. Thresholds are tested using data from the remaining 17 days of the IFO. Cirrus episodes are defined as intervals when the sky cover is primarily cirrus. Measurements of incoming shortwave and near infrared full hemispheric and diffuse irradiation, and atmospheric infrared irradiation were made at Wausau, Wisconsin Municipal Airport. Data were collected between October 13 and November 2, 1986 and are one minute averages of ten second samples. Data from October 23 and from October 27 to 29 were used for threshold determination. Using weather observations, lidar output, photographs and video, sky conditions were grouped into three categories: noncirrus cloudy, cirrus, and clear. Irradiation data from all periods falling under each of the sky categories were then examined and thresholds denoting a change from one sky category to another were determined. Variables with only a small amount of overlap between sky categories were selected as key indicators.

Robinson, David A.↗

DOE OSTI2023

Grounding our Understanding of the Impacts of Boreal Forest Expansion on Shallow Cumulus Clouds with a Simple Modeling Framework

Abstract The expansion of the boreal forest poleward is a potentially important driver of feedbacks between the land surface and Arctic climate. A growing body of work has highlighted the importance of differences in evaporative resistance between different possible future Arctic land covers, which in turn alters humidity and cloudiness in the boundary layer, for these feedbacks. While thus far this problem has been studied primarily with complex Earth system models, we turn to a locally focused, idealized model capable of diagnosing and testing the sensitivity of first-order processes connecting vegetation, the atmospheric boundary layer, and low clouds in this critical region. This allows us to benchmark the mechanisms and results at the center of predictions from larger-scale simulations. A surface dominated by broadleaf trees, characterized by higher albedo and lower surface evaporative resistance, drives cooling and moistening of the boundary layer relative to a surface of needleleaf trees, characterized by lower albedo and higher surface evaporative resistance. Differences in evaporative resistance between these hypothetical Arctic vegetation covers are of equal importance to changes in albedo for the initial response of the boundary layer to boreal expansion, even with our idealized approach. However, compensation between the elevation of the lifting condensation level (LCL) and more rapid growth of the mixed layer over higher evaporative resistance surfaces can minimize changes in the favorability of shallow clouds over different land cover types under some conditions. We then perform two tests on the sensitivity of this compensating effect, to changes in water availability, represented first by a reduction in boundary layer humidity and then by both a reduction in humidity and soil moisture available to our vegetation surface. Finally, given the importance of this potential LCL–mixed-layer height compensation in our idealized modeling results, we look to determine its relevance in observational data from a field campaign in boreal Finland. These observations do confirm that such a coupling plays an important role in cumulus-topped boundary layers over a needleleaf forest surface. While our results confirm some underlying mechanisms at the center of prior work with Earth system models, they also provide motivation for future work to constrain the impact of boreal forest expansion. This will include both large eddy simulations to examine the impact of processes and feedbacks not resolved by a mixed-layer model, as well as a more systematic evaluation and comparison of relevant observations at the site in Finland and sites from prior boreal field campaigns. Significance Statement Clouds and vegetation are both important components of the climate system that interact across a range of scales. These interactions are central to understanding how changes at the land surface feedback on climate. For example, if a forest expands or recedes, diagnosing how that will impact clouds will determine whether you predict warming or cooling temperatures from that shift in the forest area. These predictions are often made with complex Earth system models, but we look to a more idealized representation of the land–atmosphere system to diagnose how shallow clouds should respond to changes in surface properties with different scenarios of boreal forest expansion at a more foundational level. This both grounds our understanding of previous analysis and provides helpful direction for future studies of this relevant and impactful land cover change.

Meteorology & Atmospheric Sciences↗

NASA NTRS2011

Passage of Bolides Through the Atmosphere

Different fragmentation models are applied to a number of events, including the entry of TC3 2008 asteroid in order to reproduce existing observational data. Keywords meteoroid entry fragmentation modeling 1 Introduction Fragmentation is a very important phenomenon which occurs during the meteoroid entry into the atmosphere and adds more drastic effects than mere deceleration and ablation. Modeling of bolide fragmentation (100 106 kg in mass) may be divided into several approaches. Detail fitting of observational data (deceleration and/or light curves) allows the determination of some meteoroid parameters (ablation and shape-density coefficients, fragmentation points, amount of mass loss) (Ceplecha et al. 1993; Ceplecha and ReVelle 2005). Observational data with high accuracy are needed for the gross-fragmentation model (Ceplecha et al. 1993), which is used for the analysis of European and Desert bolide networks data. Hydrodynamical models, which describe the entry of the meteoroid including evolution of its material, are applied mainly for large bodies (>106 kg) (Boslough et al. 1994; Svetsov et al. 1995; Shuvalov and Artemieva 2002, and others). Numerous papers were devoted to the application of standard equations for large meteoroid entry in the attempts to reproduce dynamics and/or radiation for different bolides and to predict meteorite falls. These modeling efforts are often supplemented by different fragmentation models (Baldwin and Sheaffer, 1971; Borovi.ka et al. 1998; Artemieva and Shuvalov, 2001; Bland and Artemieva, 2006, and others). The fragmentation may occur in different ways. For example, few large fragments are formed. These pieces initially interact through their shock waves and then continue their flight independently. The progressive fragmentation model suggests that meteoroids are disrupted into fragments, which continue their flight as independent bodies and may be disrupted further. Similar models were suggested in numerous papers, beginning with Levin (1956) and initial interaction of fragments started to be taken into account after the paper by Passey and Melosh (1980). The progressive fragmentation model with lateral spreading of formed fragments is widely used (Artemieva and Shuvalov, 1996; Nemtchinov and Popova, 1997; Borovi.ka et al. 1998; Bland and Artemieva, 2006).

Popova, O.↗

NASA NTRS2010

Maintaining a Local Data Integration System in Support of Weather Forecast Operations

Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) have used a local data integration system (LDIS) as part of their forecast and warning operations. Each has benefited from 3-dimensional analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive and complete understanding of evolving fine-scale weather features. Recent efforts have been undertaken to update the LDIS through the formal tasking process of NASA's Applied Meteorology Unit. The goals include upgrading LDIS with the latest version of ADAS, incorporating new sources of observational data, and making adjustments to shell scripts written to govern the system. A series of scripts run a complete modeling system consisting of the preprocessing step, the main model integration, and the post-processing step. The preprocessing step prepares the terrain, surface characteristics data sets, and the objective analysis for model initialization. Data ingested through ADAS include (but are not limited to) Level II Weather Surveillance Radar- 1988 Doppler (WSR-88D) data from six Florida radars, Geostationary Operational Environmental Satellites (GOES) visible and infrared satellite imagery, surface and upper air observations throughout Florida from NOAA's Earth System Research Laboratory/Global Systems Division/Meteorological Assimilation Data Ingest System (MADIS), as well as the Kennedy Space Center ICape Canaveral Air Force Station wind tower network. The scripts provide NWS MLB and SMG with several options for setting a desirable runtime configuration of the LDIS to account for adjustments in grid spacing, domain location, choice of observational data sources, and selection of background model fields, among others. The utility of an improved LDIS will be demonstrated through postanalysis warm and cool season case studies that compare high-resolution model output with and without the ADAS analyses. Operationally, these upgrades will result in more accurate depictions of the current local environment to help with short-range weather forecasting applications, while also offering an improved initialization for local versions of the Weather Research and Forecasting model.

Watson, Leela R.↗

NASA NTRS2018

Sensitivity of Different Types of Observations to NASA GEOS Hurricane Analyses and Forecasts

The 2017 Atlantic hurricane season was the 5th most active, featuring 17 named storms, the highest number of major hurricanes since 2005, and by far the costliest season on record. African easterly waves often serve as the seeding circulation for a large portion of hurricanes (i.e. tropical storms with wind over 74mph in the Atlantic and Northeast Pacific). Warm SST, moist air, and low wind shear are the main requirements for tropical cyclones to develop and maintain hurricane strength. In terms of hurricane propagation (so called hurricane tracks), Atlantic hurricanes typically propagate around the periphery of the subtropical ridge called the Bermuda High (Azores High), riding along its strongest winds. If the high is positioned to the east, then hurricanes generally propagate northeastward around the high's western edge into the open Atlantic Ocean without making land fall. If the high is positioned to the west and extends far enough to the south, storms are blocked from curving north and forced to continue west towards Florida, Cuba, and the Gulf of Mexico. If we have accurate atmospheric temperature distribution, which is directly related to atmospheric wave patterns, wind distributions, moisture distribution, and SST distribution in the analyses, we will have better NWP skills in hurricane analyses including hurricane intensity and tracks. Assimilating various observation data are supposed to play these roles in the analyses. To examine impacts of different types of observation data on NASA Goddard Earth Observing System (GEOS) model hurricane analyses and forecasts during the period of 2017 summer, this study performs data denial experiments using GEOS Atmospheric Data Assimilation System (ADAS), which is based on the hybrid 4D-EnVar GSI algorithm. Various types of observations such as microwave sounders, infrared sounders, TCvitals, and conventional data are removed in the experiments. In addition, the interaction between the different observation groups as certain instruments are removed from the analysis is investigated in detail using adjoint based forecast sensitivity observation impact (FSOI).

Hurricane↗

NASA NTRS2010

Benefits of Using Remote Sensing for Health Alerts and Chronic Respiratory Exposures

Respiratory diseases such as asthma can be triggered by environmental conditions that can be monitored using Earth observing data and environmental forecast models. Frequent dust storms in the southwestern United States, the annual cycle of juniper pollen events in the spring, and increased aerosol and ozone concentrations in summer, are health concerns shared by the community at large. Being able to forecast the occurrence of these events would help the health care community prepare for increased visits to emergency rooms, as well as allow public health officials to issue alerts to affected persons. This information also is important to epidemiologists for analyzing long-term trends and impacts of these events on the health and well-being of the community. Earth observing data collected by remote sensing platforms are important for improving the performance of models that can forecast these events, and in turn, improve products and information for decision-making by public health authorities. This presentation will discuss the benefits of using remote sensing data for forecasting environmental events that can adversely affect individuals with respiratory ailments. The presentations will include a brief discussion on relevant Earth observing data, the forecast models used, and societal benefits of the resulting products and information. Several NASA-funded projects will be highlighted as examples

Luvall, J. C.↗

NASA NTRS2006

EV13 Genesis Reentry Observations and Data Analysis

The Genesis spacecraft reentry represented a unique opportunity to observe a "calibrated meteor" from northern Nevada. Knowing its speed, mass, composition, and precise trajectory made it a good subject to test some of the algorithms used to determine meteoroid mass from observed brightness. It was also a good test of an inexpensive set of cameras which could be deployed to observe future shuttle reentries. The utility of consumer grade video cameras was evident during the STS-107 accident investigation and the Genesis reentry gave us the opportunity to specify and test commercially available cameras which could be used during future reentries. This report describes the video observations and their analysis, compares the results with a simple photometric model, describes the forward scatter radar experiment, and lists lessons learned from the expedition and implications for the Stardust reentry in January 2006 as well as future shuttle reentries.

Swift, Wesley R.↗

NASA NTRS2005

Genesis Reentry Observations and Data Analysis

The Genesis spacecraft reentry represented a unique opportunity to observe a "calibrated meteor" from northern Nevada. Knowing its speed, mass, composition, and precise trajectory made it a good subject to test some of the algorithms used to determine meteoroid mass from observed brightness. It was also a good test of an inexpensive set of cameras that could be deployed to observe future shuttle reentries. The utility of consumer-grade video cameras was evident during the STS-107 accident investigation, and the Genesis reentry gave us the opportunity to specify and test commercially available cameras that could be used during future reentries. This Technical Memorandum describes the video observations and their analysis, compares the results with a simple photometric model, describes the forward scatter radar experiment, and lists lessons learned from the expedition and implications for the Stardust reentry in January 2006 as well as future shuttle reentries.

Suggs, R. M.↗

DOE OSTI2020

Gravitational Fluctuations as an Alternative to Inflation III. Numerical Results

Power spectra play an important role in the theory of inflation, and their ability to reproduce current observational data to high accuracy is often considered a triumph of inflation, largely because of a lack of credible alternatives. In previous work we introduced an alternative picture for the cosmological power spectra based on the nonperturbative features of the quantum version of Einstein’s gravity, instead of currently popular inflation models based on scalar fields. The key ingredients in this new picture are the appearance of a nontrivial gravitational vacuum condensate (directly related to the observed cosmological constant), and a calculable renormalization group running of Newton’s G on cosmological scales. More importantly, one notes the absence of any fundamental scalar fields in this approach. Results obtained previously were largely based on a semi-analytical treatment, and thus, while generally transparent in their implementation, often suffered from the limitations of various approximations and simplifying assumptions. In this work, we extend and refine our previous calculations by laying out an updated and extended analysis, which now utilizes a set of suitably modified state-of-the-art numerical programs (ISiTGR, MGCAMB and MGCLASS) developed for observational cosmology. As a result, we are able to remove some of the approximations employed in our previous studies, leading to a number of novel and detailed physical predictions. These should help in potentially distinguishing the vacuum condensate picture of quantum gravity from that of other models such as scalar field inflation. Here, besides the matter power spectrum P m (k) , we work out, in detail, predictions for what are referred to as the TT, TE, EE, BB angular spectra, as well as their closely related lensing spectra. However, the current limited precision of observational data today (especially on large angular scales) does not allow us yet to clearly prove or disprove either set of ideas. Nevertheless, by exploring in more details the relationship between gravity and cosmological matter and radiation both analytically and numerically, together with an expected future influx of increasingly accurate observational data, one can hope that the new quantum gravitational picture can be subjected to further stringent tests in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2008

'Towers in the Tempest' Computer Animation Submission

The following describes a computer animation that has been submitted to the ACM/SIGGRAPH 2008 computer graphics conference: 'Towers in the Tempest' clearly communicates recent scientific research into how hurricanes intensify. This intensification can be caused by a phenomenon called a 'hot tower.' For the first time, research meteorologists have run complex atmospheric simulations at a very fine temporal resolution of 3 minutes. Combining this simulation data with satellite observations enables detailed study of 'hot towers.' The science of 'hot towers' is described using: satellite observation data, conceptual illustrations, and a volumetric atmospheric simulation data. The movie starts by showing a 'hot tower' observed by NASA's Tropical Rainfall Measuring Mission (TRMM) spacecraft's three dimensional precipitation radar data of Hurricane Bonnie. Next, the dynamics of a hurricane and the formation of 'hot towers' are briefly explained using conceptual illustrations. Finally, volumetric cloud, wind, and vorticity data from a supercomputer simulation of Hurricane Bonnie are shown using volume techniques such as ray marching.

Shirah, Greg↗

DOE OSTI2015

THE NANOGRAV NINE-YEAR DATA SET: OBSERVATIONS, ARRIVAL TIME MEASUREMENTS, AND ANALYSIS OF 37 MILLISECOND PULSARS

We present high-precision timing observations spanning up to nine years for 37 millisecond pulsars monitored with the Green Bank and Arecibo radio telescopes as part of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) project. We describe the observational and instrumental setups used to collect the data, and methodology applied for calculating pulse times of arrival; these include novel methods for measuring instrumental offsets and characterizing low signal-to-noise ratio timing results. The time of arrival data are fit to a physical timing model for each source, including terms that characterize time-variable dispersion measure and frequency-dependent pulse shape evolution. In conjunction with the timing model fit, we have performed a Bayesian analysis of a parameterized timing noise model for each source, and detect evidence for excess low-frequency, or “red,” timing noise in 10 of the pulsars. For 5 of these cases this is likely due to interstellar medium propagation effects rather than intrisic spin variations. Subsequent papers in this series will present further analysis of this data set aimed at detecting or limiting the presence of nanohertz-frequency gravitational wave signals.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Bayesian Inversion of Seismic and Electromagnetic Data for Marine Gas Reservoir Characterization Using Multi-chain Markov Chain Monte Carlo Sampling

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

Ren, Huiying↗

NASA NTRS1994

The chemical and radiative effects of the Mount Pinatubo eruption

To clarify the mechanisms leading to effects on stratospheric ozone, time-dependent stratospheric aerosol and gas experiment II (SAGE II) and cryogenic limb array elaton spectrometer (CLAES) aerosol optical extinction data and SAGE II surface area density are used as parameters in a two-dimensional (2-D) zonally averaged chemical radiative transport model. The model was integrated with time from before the eruption through December 1993. The modeled impact on global ozone results from increased rates of heterogeneous reactions on sulfate aerosols and from the increased radiative heating and scattering caused by these aerosols. When the aerosol heating is allowed to modify the temperature distribution, the maximum change calculated in equatorial column ozone is -1.6%. The calculated equatorial temperature change and peak local ozone change in October 1991 are +6K and -4%, respectively. When aerosol heating perturbs the circulation in the model, the maximum change in equatorial column ozone is -6%. Increased heterogeneous processing on sulfate aerosols is calculated to have changed equatorial column ozone in late 1991 by -1.5%. Global column ozone in the model in 1992 and 1993 changed by -2.8% and -2.4%, respectively. The relationship of ozone-controlling processes in the lower stratosphere is altered as well; HO(x) becomes the most important catalytic cycle, followed by ClO(x) and NO(x). This is driven by significant changes in trace gas concentrations. In October 1991, lower stratospheric, equatorial NO(x) decreased by 40%, ClO(x) increased by 60%, and HO(x) increased by 25%. When the effect of heterogeneous chemical processing on sulfate aerosols is combined with aerosol heating, modifying either circulation or temperature, dramatically different ozone fingerprints with time and latitude are predicted. Model-derived changes in the equatorial region in column ozone best represented the observed data when perturbed circulation was combined with heterogeneous chemical effects. However, at high latitudes, the increased ozone production from the strengthening of the mean circulation tends to cancel the heterogeneous reduction of ozone. This is not in good agreement with observed data, especially in 1992 and 1993. When the circulation is held fixed and the temperature allowed to change, and heterogeneous chemical effects are included, the equatorial ozone decrease predicted was too small for 1991. However, the mid- to high-latitude decrease in 1992 and 1993 is in better agreement with observed data.

Kinneson, Douglas E.↗

NASA NTRS2005

Aerosol and Cloud Observations and Data Products by the GLAS Polar Orbiting Lidar Instrument

The Geoscience Laser Altimeter System (GLAS) launched in 2003 is the first polar orbiting satellite lidar. The instrument was designed for high performance observations of the distribution and optical scattering cross sections of clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. Both receiver channels meet and exceed their design goals, and beginning with a two month period through October and November 2003, an excellent global lidar data set now exists. The data products for atmospheric observations include the calibrated, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data sets are now in open release through the NASA data distribution system. The initial results on global statistics for cloud and aerosol distribution has been produced and in some cases compared to other satellite observations. The sensitivity of the cloud measurements is such that the 70% global cloud coverage result should be the most accurate to date. Results on the global distribution of aerosol are the first that produce the true height distribution for model inter-comparison.

Spinhirne, J. D.↗