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At least 73 records · Page 4

The use of Landsat-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

The MSS sensor on Landsat 4 is, in certain performance aspects, diferent from those of Landsats 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of Landsat 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using Landsat 4 and Landsat 2 data (33.35 meters) and the temporal data set constructed from two Landsat 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Anderson, J. E.

Regression Analysis of Long-term Profile Ozone Data Set from BUV Instruments

We have produced a profile merged ozone data set (MOD) based on the SBUV/SBUV2 series of nadir-viewing satellite backscatter instruments, covering the period from November 1978 - December 2003. In 2004, data from the Nimbus 7 SBUV and NOAA 9,11, and 16 SBUV/2 instruments were reprocessed using the Version 8 (V8) algorithm and most recent calibrations. More recently, data from the Nimbus 4 BUV instrument, which operated from 1970 - 1977, were also reprocessed using the V8 algorithm. As part of the V8 profile calibration, the Nimbus 7 and NOAA 9 (1993-1997 only) instrument calibrations have been adjusted to match the NOAA 11 calibration, which was established from comparisons with SSBUV shuttle flight data. Given the level of agreement between the data sets, we simply average the ozone values during periods of instrument overlap to produce the MOD profile data set. We use statistical time-series analysis of the MOD profile data set (1978-2003) to estimate the change in profile ozone due to changing stratospheric chlorine levels. The Nimbus 4 BUV data offer an opportunity to test the physical properties of our statistical model. We extrapolate our statistical model fit backwards in time and compare to the Nimbus 4 data. We compare the statistics of the residuals from the fit for the Nimbus 4 period to those obtained from the 1978-2003 period over which the statistical model coefficients were estimated.

Frith, Stacey

Restoration, Enhancement, and Distribution of the ATLAS-1 Imaging Spectrometric Observatory (ISO) Space Science Data Set

The primary goal of the funded task was to restore and distribute the ISO ATLAS-1 space science data set with enhanced software and database utilities. The first year was primarily dedicated to physically transferring the data from its original format to its initial CD archival format. The remainder of the first year was devoted to the verification of the restored data set and database. The second year was devoted to the enhancement of the data set, especially the development of IDL utilities and redesign of the database and search interface as needed. This period was also devoted to distribution of the rescued data set, principally the creation and maintenance of a web interface to the data set. The final six months was dedicated to working with NSSDC to create a permanent, off site, hive of the data set and supporting utilities. This time was also used to resolve last minute quality and design issues.

Germany, G. A.

Regression Analysis of Long-Term Profile Ozone Data Set from BUV Instruments

We have produced a profile merged ozone data set (MOD) based on the SBUV/SBUV2 series of nadir-viewing satellite backscatter instruments, covering the period from November 1978 - December 2003. In 2004, data from the Nimbus 7 SBUV and NOAA 9, ll, and 16 SBUV/2 instruments were reprocessed using the Version 8 (V8) algorithm and most recent calibrations. More recently, data from the Nimbus 4 BUT instrument, which was operational from 1970 - 1977, were also reprocessed using the V8 algorithm. As part of the V8 profile calibration, the Nimbus 7 and NOAA 9 (1993-1997 only) instrument calibrations have been adjusted to match the NOAA 11 calibration, which was established based on comparisons with SSBUV shuttle flight data. Differences between NOAA 11, Nimbus 7 and NOAA 9 profile zonal means are within plus or minus 5% at all levels when averaged over the respective periods of data overlap. NOAA 16 SBUV/2 data have insufficient overlap with NOAA 11, so its calibration is based on pre-flight information. Mean differences over 4 months of overlap are within plus or minus 7%. Given the level of agreement between the data sets, we simply average the ozone values during periods of instrument overlap to produce the MOD profile data set. Initial comparisons of coincident matches of N4 BUV and Arosa Umkehr data show mean differences of 0.5 (0.5)% at 30km; 7.5 (0.5)% at 35 km; and 11 (0.7)% at 40 km, where the number in parentheses is the standard error of the mean. In this study, we use the MOD profile data set (1978-2003) to estimate the change in profile ozone due to changing stratospheric chlorine levels. We use a standard linear regression model with proxies for the seasonal cycle, solar cycle, QBO, and ozone trend. To account for the non-linearity of stratospheric chlorine levels since the late 1990s, we use a time series of Effective Chlorine, defined as the global average of Chlorine + 50 * Bromine at 1 hPa, as the trend proxy. The Effective Chlorine data are taken from the 3-D Goddard CTM. We will show the latest trend results using this statistical model. In addition, the Nimbus 4 BUV data offer an opportunity to test the physical properties of our statistical model. From ground-based comparisons we will establish an uncertainty range for the Nimbus 4 data. We then extrapolate our statistical model fit backwards in time and compare to the Nimbus 4 data. We compare the characteristics of the residual, defined as the difference between the data and statistical regression fit, during the Nimbus 4 time period and the 1978-2003 period over which the statistical model coefficients were estimated, and present these results.

Stolarski, Richard S.

Calibration of the NOAA 11 solar backscatter ultraviolet (SBUV/2) ozone data set from 1989 to 1993 using in-flight calibration data and SSBUV

Total ozone and ozone profiles are currently being measured by solar backscatter ultraviolet (SBUV/2) instruments onboard NOAA polar orbiting spacecraft using the backscattered ultraviolet technique. The NOAA 11 SBUV/2 operational data set, reprocessed from January 1989 to May 1993 (version 6), includes an updated algorithm and revised prelaunch and postlaunch calibrations of the geometrical albedo observations used to derive ozone values. The postlaunch calibration revisions remove time dependent errors in the ozone amounts due to instrument drift, while the revised prelaunch calibration corrects the absolute value of retrieved ozone. The prelaunch corrections are a result of calibration checks from in-orbit comparisons of ultraviolet geometric albedos measured by shuttle SBUV (SSBUV) and the NOAA 11 SBUV/2. Geometric albedo comparison data are further corrected using a radiative transfer code to account for the small difference in observing conditions between the two spacecraft. The postlaunch corrections rely on in-flight calibration and solar irradiance data to account for time dependent changes in instrument gain, thermal response, and instrument diffuser degradation over time. Comparison of data from three SSBUV flights, which occurred about one year apart, with concurrent SBUV/2 data provided an independent check of the time dependent change derived from the in-flight calibration data. Time independent corrections result in an increase of about 1% for total ozone, 5% for ozone at 1 mbar, and near 0% at 15 mbar. The time dependent corrections amount to an increase of 2% for total ozone, 10% for ozone near 1 mbar, and 3% at 15 mbar at the end of the current record in May 1993. Recent laboratory studies indicate that the absolute radiance calibrations may still be in error by a few percent which results in ozone profile values that are too low. The SBUV/2 total and ozone profile data are compared to the Nimbus SBUV data during the period when the data overlapped. Total ozone values agree to about 1%, while ozone profile differences range from -4% to +6%, depending on latitude and altitude, relative to SBUV. These differences are not statistically significant given the uncertainties of the two data sets.

Hilsenrath, E.

Applications of the AVE-Sesame data sets to mesoscale studies

Data collected by the lightning data concentrator are available for research. The Mark 3 McIDAS capability provides greater flexibility for the Marshall user community and serves as a model of future UW McIDAS to remote computer links. Techniques were investigated for the display of dynamic 3-D data sets. To date the most promising display technology is a polarized two CRT perspective display which allows both dynamic 3-D images and graphics presentations with full color capability. Algorithms were for the preparation and display of conventional and satellite based weather data in 3-D. These include gridding, contouring, and streamlining processors which operate on both real time and case study data bases. An upper air trajectory model was implemented which creates a display of air parcel trajectories in perspective 3-D. A subsystem for the generation of 3-D solid surface display with shading and hidden surface display with shading and hidden surface removal was tested and its products are currently being evaluated. Motion parallax introduced by moving the point of observation during display is an important depth cue, which, when added to the perspective parallax creates a very realistic appearing display.

Suomi, V. E.

Intercomparisons of Total Precipitable Water from Satellite and Other Long Term Data Sets

Global water vapor data sets from satellite (NVAP) and reanalysis (NCEP and DAO) are intercompared for a 5 year period (1988-1992). Global average indicates that the NCEP and DAO reanalyses are dryer than NVAP over much of the period. Spatial patterns of the NCEP/NVAP and DAO/NVAP differences show regional variations in the 60 month climatogical fields. For example, in the Eastern Pacific just south of the equator NVAP is much dryer than the NCEP and more moist than DAO. Rather large discrepancies exist in other regions as well. North Africa, Saudi Arabia, India, and Australia show that NVAP TPW values are more moist than the NCEP and DAO model analyses by 4-8 mm. In general, the NCEP and DAO exhibits a tendency to be dryer than NVAP over the tropical ocean region. Over the Americas little differences exist except over the west coast. The shapes of the differences fields over the Eastern Pacific region are significantly different between NCEP/NVAP and DAO/NVAP differences. Over South America and Central Africa, DAO TPW values are significantly higher than those of NVAP. These difference fields show monthly and seasonal variability as well. These results will be highlighted in the paper and on the poster.

Chang, Fong-Chiau

Impact of CAMEX-4 Data Sets for Hurricane Forecasts using a Global Model

This study explores the impact on hurricane data assimilation and forecasts from the use of dropsondes and remote-sensed moisture profiles from the airborne Lidar Atmospheric Sensing Experiment (LASE) system. We show that the use of these additional data sets, above those from the conventional world weather watch, has a positive impact on hurricane predictions. The forecast tracks and intensity from the experiments show a marked improvement compared to the control experiment where such data sets were excluded. A study of the moisture budget in these hurricanes showed enhanced evaporation and precipitation over the storm area. This resulted in these data sets making a large impact on the estimate of mass convergence and moisture fluxes, which were much smaller in the control runs. Overall this study points to the importance of high vertical resolution humidity data sets for improved model results. We note that the forecast impact from the moisture profiling data sets for some of the storms is even larger than the impact from the use of dropwindsonde based winds.

Kamineni, Rupa

Production of long-term global water vapor and liquid water data set using ultra-fast methods to assimilate multi-satellite and radiosonde observations

During the next decade, many programs and experiments under the Global Energy and Water Cycle Experiment (GEWEX) will utilize present day and future data sets to improve our understanding of the role of moisture in climate, and its interaction with other variables such as clouds and radiation. An important element of GEWEX will be the GEWEX Water Vapor Project (GVaP), which will eventually initiate a routine, real-time assimilation of the highest quality, global water vapor data sets including information gained from future data collection systems, both ground and space based. The comprehensive global water vapor data set being produced by METSAT Inc. uses a combination of ground-based radiosonde data, and infrared and microwave satellite retrievals. This data is needed to provide the desired foundation from which future GEWEX-related research, such as GVaP, can build. The first year of this project was designed to use a combination of the best available atmospheric moisture data including: radiosonde (balloon/acft/rocket), HIRS/MSU (TOVS) retrievals, and SSM/I retrievals, to produce a one-year, global, high resolution data set of integrated column water vapor (precipitable water) with a horizontal resolution of 1 degree, and a temporal resolution of one day. The time period of this pilot product was to be det3ermined by the availability of all the input data sets. January 1988 through December 1988 were selected. In addition, a sample of vertically integrated liquid water content (LWC) was to be produced with the same temporal and spatial parameters. This sample was to be produced over ocean areas only. Three main steps are followed to produce a merged water vapor and liquid water product. Input data from Radiosondes, TOVS, and SSMI/I is quality checked in steps one and two. Processing is done in step two to generate individual total column water vapor and liquid water data sets. The third step, and final processing task, involves merging the individual output products to produce the integrated water vapor product. A final quality control is applied to the merged data sets.

Vonderhaar, T. H.

Validating a large geophysical data set: Experiences with satellite-derived cloud parameters

We are validating the global cloud parameters derived from the satellite-borne HIRS2 and MSU atmospheric sounding instrument measurements, and are using the analysis of these data as one prototype for studying large geophysical data sets in general. The HIRS2/MSU data set contains a total of 40 physical parameters, filling 25 MB/day; raw HIRS2/MSU data are available for a period exceeding 10 years. Validation involves developing a quantitative sense for the physical meaning of the derived parameters over the range of environmental conditions sampled. This is accomplished by comparing the spatial and temporal distributions of the derived quantities with similar measurements made using other techniques, and with model results. The data handling needed for this work is possible only with the help of a suite of interactive graphical and numerical analysis tools. Level 3 (gridded) data is the common form in which large data sets of this type are distributed for scientific analysis. We find that Level 3 data is inadequate for the data comparisons required for validation. Level 2 data (individual measurements in geophysical units) is needed. A sampling problem arises when individual measurements, which are not uniformly distributed in space or time, are used for the comparisons. Standard 'interpolation' methods involve fitting the measurements for each data set to surfaces, which are then compared. We are experimenting with formal criteria for selecting geographical regions, based upon the spatial frequency and variability of measurements, that allow us to quantify the uncertainty due to sampling. As part of this project, we are also dealing with ways to keep track of constraints placed on the output by assumptions made in the computer code. The need to work with Level 2 data introduces a number of other data handling issues, such as accessing data files across machine types, meeting large data storage requirements, accessing other validated data sets, processing speed and throughput for interactive graphical work, and problems relating to graphical interfaces.

Kahn, Ralph

ISCCP global radiance data set - A new resource for climate research

The operational data-collection phase of the International Satellite Cloud Climatology Project (ISCCP) began in July 1983 as an element of the World Climate Research Program (WCRP). Since then, raw images from an international network of operational geostationary and polar-orbiting meteorological satellites have been routinely processed to develop a global data set of calibrated radiances and derived cloud parameters for climate research. This report outlines the key steps involved in producing the basic ISCCP reduced-resolution global radiance (B3) data set, describes the main features of the data set, and indicates the principal point of contact for obtaining copies of the data tapes. A future paper will focus on the derived cloud properties and their utilization.

Schiffer, R. A.

Status of the Dobson total ozone data set

During deliberations of the International Ozone Trends Panel (IOTP) it became obvious that satellite determinations of global ozone amounts by themselves could not provide the necessary confidence in the measured trends. During the time of the deliberations of the IOTP, Bojkov re-examined the records of serveral North American Dobson stations and Degorska re-examined the records of the Belsk station. They were able to improve the quality of the data sets, thus improving the precision of their total ozone data sets. These improvements showed the greater potential of the world-wide Dobson total ozone data set in two primary areas. Firstly, the improvements showed that the existing data set when evaluated will become more valuable for comparisons with satellite determinations of total ozone. Secondly, the Dobson data set covers a greater period of time than the satellite data sets thus offering the possibility of extending improved information on ozone trends further back in time. An International Dobson Workshop was convened in September, 1991, under the auspices of the NOAA Climate and Global Change Program. It was part of the Information Management element of the C&GC Program. Further, it was considered as a 'data archaeology' project under the above. Clearly if the existing Dobson data set can be improved by re-evaluating all data records, we will be able to uncover the 'true' or 'best' data and fulfill the role of archaeologists.

Planet, Walter G.

Predicting Drug Effects from High-dimensional Asymmetric Drug Data Sets using Graph Neural Networks: A Comprehensive Analysis of Multi-target Drug Effect Prediction

Graph neural networks (GNNs) have emerged as one of the most effective Machine learning (ML) techniques for drug effect prediction from drug molecular graphs. Despite having immense potential, GNN models lack performance when using data sets that contain high dimensional asymmetrically co-occurrent drug effects as targets with complex correlations between them. Training individual learning models for each drug effect and incorporating every prediction result for a wide spectrum of drug effects is beyond practicality. Such an implication provides a testbed to address this challenge as multi-target prediction problems, aiming to predict all drug effects at a time. We develop standard and hybrid graph neural networks (GNNs)to perform two separate tasks that are multi-regression for continuous values and multi-label classification for categorical values contained in our data sets. Since this step makes the target data even more sparse and introduces asymmetric label co-occurrence, the learning of multi-label classification models becomes difficult and heavily impacts the GNN's performance. To address these challenges, we propose a new data oversampling technique to improve multi-label classification performances on all the given imbalanced molecular graph data sets. Using the technique, we improve the data imbalance ratio of the drug effects better than before while protecting the data set's integrity. Finally, we evaluate multi-label classification performance using the best-performant hybrid GNN model on all the oversampled data sets obtained from the proposed oversampling technique. These results outperform those of other ML models including GNN models when they are trained on the original data sets or oversampled data sets using MLSMOTE (a well-known oversampling technique) in all evaluation metrics precision, recall, and F1 score by a significant margin.

Bose, Avishek [ORNL]

Digital image data sets for remote sensing instruction

Several sets of LANDSAT image segments and a set of simple image processing programs operating in batch mode are being used to teach an introductory course in digital image analysis and classification. The image data sets contain only a small number of pixels and can be run quickly on most university computing systems. A number of image data sets derived from the raw spectral bands (smoothed data sets, band ratios and texture data sets) allows the student to examine and include these extracted variables in the classification process. Another data set consists of three registered LANDSAT image segments for three different dates so that the student may experiment with multitemporal data processing. The three LANDSAT scenes used in the class are described and the image data sets available for class exercises are listed.

Eyton, J. R.

Enclosed Sydney Swirl Burner Experimental Data Set - Release 1.0

This submission includes a comprehensive data set for the NETL Enclosed Sydney Swirl Burner, generated between 2012 and 2014. The data set includes global parametric data and advanced diagnostic data for (3) flames of interest to CFD model validation. The submission includes a companion summary document describing the data and associated references.

Diagnostics

Three dimensional turbulent boundary layers: Data sets for two-space coordinate flows

Sets of data (flows) from eight original sources on three-dimensional turbulent boundary layers were reevaluated and tabulated in a common format. The flows studied were all of the type describable in only two space coordinates, e.g., flow over a swept wing of infinite span. The principal data in each set are profiles of the main and crossflow components of mean velocity. Turbulent shear stress vector profiles were available for two flows, Bradshaw and Terrell (1969) and Johnson (1970). Free stream pressure gradient, wall shear stress coefficient and angle, integral thickness and left and right hand sides of the momentum integral equations were evaluated in a consistent manner for each flow.

Wheeler, A. J.

Greenhouse Effect Detection Experiment (GEDEX). Selected data sets

This CD-ROM contains selected data sets compiled by the participants of the Greenhouse Effect Detection Experiment (GEDEX) workshop on atmospheric temperature. The data sets include surface, upper air, and/or satellite-derived measurements of temperature, solar irradiance, clouds, greenhouse gases, fluxes, albedo, aerosols, ozone, and water vapor, along with Southern Oscillation Indices and Quasi-Biennial Oscillation statistics.

Olsen, Lola M.

Using Gaussian windows to explore a multivariate data set

In an earlier paper, I recounted an exploratory analysis, using Gaussian windows, of a data set derived from the Infrared Astronomical Satellite. Here, my goals are to develop strategies for finding structural features in a data set in a many-dimensional space, and to find ways to describe the shape of such a data set. After a brief review of Gaussian windows, I describe the current implementation of the method. I give some ways of describing features that we might find in the data, such as clusters and saddle points, and also extended structures such as a 'bar', which is an essentially one-dimensional concentration of data points. I then define a distance function, which I use to determine which data points are 'associated' with a feature. Data points not associated with any feature are called 'outliers'. I then explore the data set, giving the strategies that I used and quantitative descriptions of the features that I found, including clusters, bars, and a saddle point. I tried to use strategies and procedures that could, in principle, be used in any number of dimensions.

Jaeckel, Louis A.