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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Design tradeoff studies and sensitivity analysis, appendices B1 - B4

Documentation is presented for a program which separately computes fuel and energy consumption for the two modes of operation of a hybrid electric vehicle. The distribution of daily travel is specified as input data as well as the weights which the component driving cycles are given in each of the composite cycles. The possibility of weight reduction through the substitution of various materials is considered as well as the market potential for hybrid vehicles. Data relating to battery compartment weight distribution and vehicle handling analysis is tabulated.

Source record↗
NASA NTRS1989

Remote sensing information sciences research group: Browse in the EOS era

The problem of science data browse was examined. Given the tremendous data volumes that are planned for future space missions, particularly the Earth Observing System in the late 1990's, the need for access to large spatial databases must be understood. Work was continued to refine the concept of data browse. Further, software was developed to provide a testbed of the concepts, both to locate possibly interesting data, as well as view a small portion of the data. Build II was placed on a minicomputer and a PC in the laboratory, and provided accounts for use in the testbed. Consideration of the testbed software as an element of in-house data management plans was begun.

Estes, John E.↗
NASA NTRS1994

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation, final phase

In the final phase of the proposed research a complete top to down three dimensional object recognition scheme has been proposed. The various three dimensional objects included spheres, cones, cylinders, ellipsoids, paraboloids, and hyperboloids. Utilizing a newly developed blob determination technique, a given range scene with several non-cluttered quadric surfaces is segmented. Next, using the earlier (phase 1) developed alignment scheme, each of the segmented objects are then aligned in a desired coordinate system. For each of the quadric surfaces based upon their intersections with certain pre-determined planes, a set of distinct features (curves) are obtained. A database with entities such as the equations of the planes and angular bounds of these planes has been created for each of the quadric surfaces. Real range data of spheres, cones, cylinders, and parallelpipeds have been utilized for the recognition process. The developed algorithm gave excellent results for the real data as well as for several sets of simulated range data.

Mielke, Roland↗
NASA NTRS1994

Installed F/A-18 inlet flow calculations at 30 degrees angle-of-attack: A comparative study

NASA Lewis is currently engaged in a research effort as a team member of the High Alpha Technology Program (HATP) within NASA. This program utilizes a specially equipped F/A-18, the High Alpha Research Vehicle (HARV), in an ambitious effort to improve the maneuverability of high-performance military aircraft at low subsonic speed, high angle of attack conditions. The overall objective of the Lewis effort is to develop inlet technology that will ensure efficient airflow delivery to the engine during these maneuvers. One part of the Lewis approach utilizes computational fluid dynamics codes to predict the installed performance of inlets for these highly maneuverable aircraft. Full Navier-Stokes (FNS) calculations on the installed F/A-18 inlet at 30 degrees angle of attack, 0 degrees yaw, and a freestream Mach number of 0.2 have been obtained in this study using an algebraic turbulence model with two grids (original and revised). Results obtained with the original grid were used to determine where further grid refinements and additional geometry were needed. In order to account properly for the external effects, the forebody, leading edge extension (LEX), ramp, and wing were included with inlet geometry. In the original grid, the diverter, LEX slot, and leading edge flap were not included due to insufficient geometry definition, but were included in a revised grid. In addition, a thin-layer Navier-Stokes (TLNS) code is used with the revised grid and the numerical results are compared to those obtained with the FNS code. The TLNS code was used to evaluate the effects on the solution using a code with more recent CFD developments such as upwinding with TVD schemes versus central differencing with artificial dissipation. The calculations are compared to a limited amount of available experimental data. The predicted forebody/fuselage surface static pressures compared well with data of all solutions. The predicted trajectory of the vortex generated under the LEX was different for each solution. These discrepancies are attributed to differences in the grid resolution and turbulence modeling. All solutions predict that this vortex is ingested by the inlet. The predicted inlet total pressure recoveries are lower than data and the distortions are higher than data. The results obtained with the revised grid were significantly improved from the original grid results. The original grid results indicated the ingested vortex migrated to the engine face and caused additional distortions to those already present due to secondary flow development. The revised grid results indicate that the ingested vortex is dissipated along the inlet duct inboard wall. The TLNS results indicate the flow at the engine face was much more distorted than the FNS results and is attributed to the pole boundary condition introducing numerical distortions into the flow field.

Smith, C. Frederic↗
NASA NTRS1994

External comparisons of reprocessed SBUV/TOMS ozone data

Ozone Retrievals from the Solar Backscatter Ultraviolet (SBUV) Instrument on-board the Nimbus-7 Satellite have been reprocessed using an improved internal calibration. The resulting data set covering November, 1978 through January, 1987 has been archived at the National Space Science Data Center in Greenbelt, Maryland. The reprocessed SBUV total ozone data as well as recalibrated Total Ozone Mapping Spectrometer (TOMS) data are compared with total ozone measurements from a network of ground based Dobson spectrophotometers. The SBUV also measures the vertical distribution of ozone, and these measurements are compared with external measurements made by SAGE II, Umkehr, and Ozonesondes. Special attention is paid to long-term changes in ozone bias.

Wellemeyer, C. G.↗
NASA NTRS1995

Accurate estimation of sigma(exp 0) using AIRSAR data

During recent years signature analysis, classification, and modeling of Synthetic Aperture Radar (SAR) data as well as estimation of geophysical parameters from SAR data have received a great deal of interest. An important requirement for the quantitative use of SAR data is the accurate estimation of the backscattering coefficient sigma(exp 0). In terrain with relief variations radar signals are distorted due to the projection of the scene topography into the slant range-Doppler plane. The effect of these variations is to change the physical size of the scattering area, leading to errors in the radar backscatter values and incidence angle. For this reason the local incidence angle, derived from sensor position and Digital Elevation Model (DEM) data must always be considered. Especially in the airborne case, the antenna gain pattern can be an additional source of radiometric error, because the radar look angle is not known precisely as a result of the the aircraft motions and the local surface topography. Consequently, radiometric distortions due to the antenna gain pattern must also be corrected for each resolution cell, by taking into account aircraft displacements (position and attitude) and position of the backscatter element, defined by the DEM data. In this paper, a method to derive an accurate estimation of the backscattering coefficient using NASA/JPL AIRSAR data is presented. The results are evaluated in terms of geometric accuracy, radiometric variations of sigma(exp 0), and precision of the estimated forest biomass.

Holecz, Francesco↗
NASA NTRS2001

Automated Inspection of the RSRM Case O-Ring Seal Surface

An automated inspection system has been developed to inspect the o-ring sealing surfaces on the Space Shuttle reusable solid rocket motor (RSRM) case segment joints. A laser digitizing system is used to create a three dimensional map of the o-ring sealing surfaces. This data is analyzed for any irregularities, which are noted for further inspection and disposition. This paper describes both the hardware and the software used to gather data as well as the methods developed to analyze the data. The RSRM is assembled from four casting segments. Each of the field joints between these segments is sealed with three o-rings. These o-rings are critical for the proper operation of the motor. After launch the booster segments are recovered and reused. As part of the refurbishment process the o-ring sealing surfaces are inspected for any irregularities. The system developed uses a combination of commercial and customized hardware and software. The system uses two computer systems in a real time environment to control a laser, an XYZ precision table, and case rotation and position information. The system is capable of inspecting both the tang end and the clevis end of the RSRM field joint. The o-ring grooves and flat sealing surfaces are inspected.

ODell, Keith P.↗
NASA NTRS2001

A Multi-Band Analytical Algorithm for Deriving Absorption and Backscattering Coefficients from Remote-Sensing Reflectance of Optically Deep Waters

A multi-band analytical (MBA) algorithm is developed to retrieve absorption and backscattering coefficients for optically deep waters, which can be applied to data from past and current satellite sensors, as well as data from hyperspectral sensors. This MBA algorithm applies a remote-sensing reflectance model derived from the Radiative Transfer Equation, and values of absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. There are only limited empirical relationships involved in the algorithm, which implies that this MBA algorithm could be applied to a wide dynamic range of waters. Applying the algorithm to a simulated non-"Case 1" data set, which has no relation to the development of the algorithm, the percentage error for the total absorption coefficient at 440 nm a (sub 440) is approximately 12% for a range of 0.012 - 2.1 per meter (approximately 6% for a (sub 440) less than approximately 0.3 per meter), while a traditional band-ratio approach returns a percentage error of approximately 30%. Applying it to a field data set ranging from 0.025 to 2.0 per meter, the result for a (sub 440) is very close to that using a full spectrum optimization technique (9.6% difference). Compared to the optimization approach, the MBA algorithm cuts the computation time dramatically with only a small sacrifice in accuracy, making it suitable for processing large data sets such as satellite images. Significant improvements over empirical algorithms have also been achieved in retrieving the optical properties of optically deep waters.

Lee, Zhong-Ping↗
NASA NTRS1998

Ion-Molecule Reactions and Ion Kinetics in DC Townsend Discharges in Dielectric Gases

In gas discharges the identify, transport, relative intensities, and kinetic energy distributions (KEDs) of ions may be dominated by ion-molecule reactions. In order to understand these discharges, there is a need for cross section data for various ion-molecule reactions, including symmetric and asymmetric charge-transfer, collisional detachment, and ion conversion reactions, especially for low to intermediate ion-impact energies. In view of the importance of dielectric gases, we have recently measured the KEDs of various positive and negative ions produced in DC Townsend discharges in SF6, CF4, CHF3, O2, and CO2. The relative abundance and mean energies of ions are obtained from the measured KEDs. The effective cross sections (Qeff) describing the KEDs of various ions can be derived by using the mean ion energies and the electric field-to-gas density ratios (E/N). In the case of SF6 and O2 discharges, the determined cross sections (Qeff) for the negative-ion molecule reactions are consistent with previously measured cross section data obtained by crossed-beam experiment. The availability of these cross section values enabled us to understand the ion data reasonably well. However, the lack of adequate cross section data for positive ions in all of the above gases is a major obstacle in understanding ion transport in these gas discharges.

Rao, M. V. V. S.↗
NASA NTRS2002

Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

Bell, Thomas L.↗
NASA NTRS2004

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗
NASA NTRS2004

A Multi-Wavelength Study of the X-Ray Sources in the NGC 5018

The E3 giant elliptical galaxy NGC-5018 was observed with the cxo X-ray Observatory's Advanced CCD Imaging Spectrometer for 30-h on 14 April 2001. Results of analysis of these X-ray data as well as of complementary optical, infrared, and radio data are reported. Seven X-ray point sources, including the nucleus, were detected. If they are intrinsic to NGC-5018, then all six non-nuclear sources have luminosities exceeding 10(exp 39)-ergl in the 0.5-8.0-keV energy band; placing them in the class of Ultra- luminous X-ray sources. Comparison of X-ray source positions to archival Hubble Space Telescope/Wide Field Planetary Camera 2 (hst/WFPC2) images reveal four of the six non-nuclear sources are spatially--coincident with bright, M$(sub V)LA -8.6 mag, objects. These four objects have optical magnitudes and (V-I) colors consistent with globular clusters in NGC-5018. However, one of these objects was observed to vary by siml mag in both V and I between observations taken 28 July 1997 and 04 Feb 1999 indicating this source is a background active galactic nucleus (AGN). The nature of the other three optically-bright objects cannot be determined from the available optical data but all have X-ray-to-optical flux ratios consistent with background AGNs. Strong, unpolarized, radio emission has been detected from another of the optically-bright counterparts. It displays an inverted radio spectrum and is the most absorbed of the seven sources in the X-ray band. It, too, is most readily explained as a background AGN, though alternative explanations cannot be ruled out. Extended X-ray emission is detected within a siml5 arcsec radius of the galaxy center at a luminosity of sim lO(exp 40)-ergl in the X-ray band. Its thermal X-ray spectrum (kT sim0.4-keV) and its spatial coincidence with strong H(alpha) emission are consistent with a hot gas origin. The nucleus itself is a weak X-ray source, LA-5 times 10(exp 39)-ergl, but displays a radio spectrum typical of AGN.

Ghosh, Kajal K.↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_TRMM-PFM_Edition1)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2000-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

SHORTWAVE FILTERED RADIANCE UPWARDS↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Terra-FM1_Edition1)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-11-02] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

WINDOW DETECTOR OUTPUT↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Terra-FM2_Edition1)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-11-02] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

TOTAL DETECTOR OUTPUT↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Terra-FM1_Edition2)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

SW FILTERED RADIANCE UPWARDS↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Terra-FM2_Edition2)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

TOTAL DETECTOR OUTPUT↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Aqua-FM4_Edition1)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-04-02] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

WN FILTERED RADIANCE UPWARDS↗