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NASA NTRS2012

Achieving Accuracy Requirements for Forest Biomass Mapping: A Spaceborne Data Fusion Method for Estimating Forest Biomass and Lidar Sampling Error

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission (+/-20 Mg/ha or 20%, the greater of the two, for at least 80% of grid cells). A data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional-global extents. A general framework for mapping above ground live forest biomass density (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify contiguous areas (>0.5 ha) that are relatively homogenous in remote sensing metrics (forest patches). We used this image-derived data with simulated spaceborne LiDAR derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (LVIS) to compute AGB and estimate LiDAR sampling error for forest patches and 100 m, 250 m, 500 m, and 1 km grid cells. At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. First, this data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting. Second, a data fusion approach for estimating AGB using simulated spaceborne LiDAR with SAR and passive optical image combinations reduced forest AGB sampling errors 12%-38% from those where LiDAR is used with SAR or passive optical alone. In absolute terms, sampling errors were reduced from 14-40 Mg/ha to 11-28 Mg/ha across all grid scales and prediction methods, where minimum sampling errors were 11, 15, 18, and 22 Mg/ha for 1 km, 500 m, 250 m, and 100 m grid scales, respectively. Third, spaceborne global scale accuracy requirements were achieved whereby at least 80% of the grid cells at 100 m, 250 m, 500 m, and 1 km grid levels met AGB accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500 m and 250 m grid level, respectively..

LiDAR↗

NASA NTRS1990

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Source record↗

NASA NTRS1973

Remote Measurement of Atmospheric Temperatures By Raman Lidar

The Raman shifted return of a lidar, or optical radar, system has been utilized to make atmospheric temperature measurements. These measurements were made along a horizontal path at temperatures between -20 C and +30 C and at ranges of about 100 meters. The temperature data were acquired by recording the intensity ratio of two portions of the Raman spectrum which were simultaneously sampled from a preset range. The lidar unit employed in this testing consisted of a 4 joule-10ppm laser operating at 694.3 nm, a 10-inch Schmidt-Cassegrain telescope, and a system of time-gated detection and signal processing electronics. The detection system processed three return signal wavelength intervals - two intervals along the rotational Raman scattered spectrum and one interval centered at the Rayleigh-Mie scattered wavelength. The wavelength intervals were resolved by using a pellicle beam splitter and three optical interference filters. Raman return samples were taken from one discrete range segment during each test shot and the signal intensities were displayed in digital format. The Rayleigh-Mie techniques. The test site utilized to evaluate this measurement technique encompassed a total path length of 200 meters. Major components of the test site included a trailer-van housing the lidar unit, a controlled environment test zone, and a beam terminator. The control zone which was located about 100 meters from the trailer was 12 meters in length, 2.4 meters in diameter, and was equipped with hinged doors at each end. The temperature of the air inside the zone could be either raised or lowered with respect to ambient air through the use of infrared heaters or a liquid-nitrogen cooling system. Conditions inside the zone were continuously monitored with a thermocouple rake assembly. The test path length was terminated by a 1.2 meter square array of energy absorbing cones and a flat black screen. Tests were initially conducted at strictly ambient conditions utilizing the normal outside air temperatures as a test parameter. These tests provided a calibration of the Raman intensity ratio as a function of' temperature for the particular optical-filter arrangement used in this system while also providing a test of' the theoretical prediction formulated in the design of the system. Later tests utilized zone temperatures above and below ambient to provide temperature gradient data. These tests indicate that ten shots, or one minute of' data acquisition, from a 100 meter range can provide absolute temperature measurements with an accuracy of + 30 C and a range resolution of about 5 meters. Because this measurement accuracy compares well with that predicted for this particular unit, it is suggested that a field-application system could be built with signif'icant improvements in both absolute accuracy and range.

Salzman, Jack A.↗

NASA NTRS2002

Ship Radar Observations of a Developing Hurricane in the East Pacific

During the recently completed East Pacific Investigation of Climate Processes in the Coupled Ocean-Atmosphere System (EPIC) field program, the NOAA research vessel Ronald H. Brown (RHB) was deployed in the east Pacific Inter Tropical Convergence Zone (ITCZ) for approximately 3 weeks near 10 deg. N, 95 deg. W. One of the principal objectives of the EPIC-ITCZ program was to observe the modulation of convection by synoptic-scale easterly waves and the air-sea coupling process in this poorly sampled region of the east Pacific. Data from the experiment will be used as validation to improve forecast models. The RHB carried a variety of platforms during EPIC to sample atmospheric and oceanic phenomena, including a scanning C-band Doppler radar, radiation flux instrumentation, air-sea flux system, Doppler lidar, 35 GHz cloud radar, UHF wind profiler, sea surface temperature (SST) sensors, as well as standard surface meteorological instrumentation and a suite of rain gauges. This presentation will focus on the analysis of C-band radar data that was collected on 10 September, 2001 as the ship passed through an easterly wave which later developed into hurricane Ivo. The ship captured approximately 12 hours of convection associated with the tropical disturbance. During this period, the domain sampled by the radar (approximately 71,000 sq km) contained a significant number of echo features. Specifically, the fraction of the domain containing radar echo above 10 dBZ reached 80% for over 2 hours and remained near 60% for a continuous six hour period. Animation of radar images showed distinct rotation in echo features associated with the easterly wave passage. Despite an approximate 4 C drop in surface air temperature and sustained winds approaching 20 m/ s, the SST remained nearly constant throughout the observation period (approx. 29.5 C). Peak values of latent and sensible heat flux exceeded 400 and 100 W /sq m, respectively. The radar documented the change in precipitation vertical structure as the ship passed through regions of significant convection with echo tops approaching 14 km and 30 dBZ echo tops extending to near 9 km embedded in regions that were predominantly stratiform in nature. Single Doppler retrievals (Extended Velocity Azimuth Display) were conducted continuously at 10-minute resolution for approximately 4 hours in the latter part of the observation period, and documented the transition from convection (low-level convergence, upper level divergence) to stratiform (mid-level convergence sandwiched between upper and lower level divergence) kinematic structure.

Cifelli, Robert↗

NASA NTRS1992

Phase noise in pulsed Doppler lidar and limitations on achievable single-shot velocity accuracy

The smaller sampling volumes afforded by Doppler lidars compared to radars allows for spatial resolutions at and below some sheer and turbulence wind structure scale sizes. This has brought new emphasis on achieving the optimum product of wind velocity and range resolutions. Several recent studies have considered the effects of amplitude noise, reduction algorithms, and possible hardware related signal artifacts on obtainable velocity accuracy. We discuss here the limitation on this accuracy resulting from the incoherent nature and finite temporal extent of backscatter from aerosols. For a lidar return from a hard (or slab) target, the phase of the intermediate frequency (IF) signal is random and the total return energy fluctuates from shot to shot due to speckle; however, the offset from the transmitted frequency is determinable with an accuracy subject only to instrumental effects and the signal to noise ratio (SNR), the noise being determined by the LO power in the shot noise limited regime. This is not the case for a return from a media extending over a range on the order of or greater than the spatial extent of the transmitted pulse, such as from atmospheric aerosols. In this case, the phase of the IF signal will exhibit a temporal random walk like behavior. It will be uncorrelated over times greater than the pulse duration as the transmitted pulse samples non-overlapping volumes of scattering centers. Frequency analysis of the IF signal in a window similar to the transmitted pulse envelope will therefore show shot-to-shot frequency deviations on the order of the inverse pulse duration reflecting the random phase rate variations. Like speckle, these deviations arise from the incoherent nature of the scattering process and diminish if the IF signal is averaged over times greater than a single range resolution cell (here the pulse duration). Apart from limiting the high SNR performance of a Doppler lidar, this shot-to-shot variance in velocity estimates has a practical impact on lidar design parameters. In high SNR operation, for example, a lidar's efficiency in obtaining mean wind measurements is determined by its repetition rate and not pulse energy or average power. In addition, this variance puts a practical limit on the shot-to-shot hard target performance required of a lidar.

Mcnicholl, P.↗

NASA NTRS1974

International Symposium on Remote Sensing of Environment, 9th, University of Michigan, Ann Arbor, Mich., April 15-19, 1974, Proceedings. Volumes 1, 2 & 3

The present work gathers together numerous papers describing the use of remote sensing technology for mapping, monitoring, and management of earth resources and man's environment. Studies using various types of sensing equipment are described, including multispectral scanners, radar imagery, spectrometers, lidar, and aerial photography, and both manual and computer-aided data processing techniques are described. Some of the topics covered include: estimation of population density in Tokyo districts from ERTS-1 data, a clustering algorithm for unsupervised crop classification, passive microwave sensing of moist soils, interactive computer processing for land use planning, the use of remote sensing to delineate floodplains, moisture detection from Skylab, scanning thermal plumes, electrically scanning microwave radiometers, oil slick detection by X-band synthetic aperture radar, and the use of space photos for search of oil and gas fields. Individual items are announced in this issue.

Source record↗

NASA NTRS1991

Coherent Doppler lidar for automated space vehicle rendezvous, stationkeeping and capture

The inherent spatial resolution of laser radar makes ladar or lidar an attractive candidate for Automated Rendezvous and Capture application. Previous applications were based on incoherent lidar techniques, requiring retro-reflectors on the target vehicle. Technology improvements (reduced size, no cryogenic cooling requirement) have greatly enhanced the construction of coherent lidar systems. Coherent lidar permits the acquisition of non-cooperative targets at ranges that are limited by the detection capability rather than by the signal-to-noise ratio (SNR) requirements. The sensor can provide translational state information (range, velocity, and angle) by direct measurement and, when used with any array detector, also can provide attitude information by Doppler imaging techniques. Identification of the target is accomplished by scanning with a high pulse repetition frequency (dependent on the SNR). The system performance is independent of range and should not be constrained by sun angle. An initial effort to characterize a multi-element detection system has resulted in a system that is expected to work to a minimum range of 1 meter. The system size, weight and power requirements are dependent on the operating range; 10 km range requires a diameter of 3 centimeters with overall size at 3 x 3 x 15 to 30 cm, while 100 km range requires a 30 cm diameter.

Bilbro, James A.↗

NASA NTRS1989

Dynamics of the upper middle atmosphere (80-110 km) at Tromsoe, June-December 1987, using the Tromsoe/Saskatoon M.F. radar

A real time winds (RTW) system from Saskatoon operated with the Tromsoe M.F. (partial reflection) radar on a continuous basis, June to December 1987. Profiles with 3 km resolution were obtained every 5 minutes with weak ionization, and few geomagnetic disturbances limited the observations normally to 80 to 110 km. However, daily mean winds, tidal characteristics (24, 12 h) such as amplitudes, phases and wavelengths, and gravity wave characteristics (intensities, mean directions) are available throughout this interval, which includes MAC-SINE and Epsilon. This is particularly valuable in defining the background state for some experiments, e.g., rockets, and for comparison with related parameters from the lidar and other radars (EISCAT, SOUSY-VHF). Comparisons with dynamical parameters from Saskatoon (52 N) are made: the zonal circulation was weaker at Tromsoe, tidal amplitudes smaller, and summer 12 h tidal wavelengths shorter (approx. 80 km vs approx. 100 km). The fall transition for this tide occurred in September, earlier than observed elsewhere. Initial comparisons with other experimental systems are also made.

Manson, A. H.↗

NASA NTRS2020

Evaluation of the MODIS Collection 6 Multilayer Cloud Detection Algorithm Through Comparisons with Cloudsat Cloud Profiling Radar and CALIPSO CALIOP Products

Since multilayer cloud scenes are common in the atmosphere and can be an important source of uncertainty in passive satellite sensor cloud retrievals, the MODIS MOD06 and MYD06 standard cloud optical property products include a multilayer cloud detection algorithm to assist with data quality assessment. This paper presents an evaluation of the Aqua MODIS MYD06 Collection 6 multilayer cloud detection algorithm through comparisons with active Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products that have the ability to provide cloud vertical distributions and directly classify multilayer cloud scenes and layer properties. To compare active sensor products with an imager such as MODIS, it is first necessary to define multilayer clouds in the context of their radiative impact on cloud retrievals. Three main parameters have thus been considered in this evaluation: (1) the maximum separation distance between two cloud layers, (2) the thermodynamic phase of those layers and (3) the upper-layer cloud optical thickness. The impact of including the Pavolonis–Heidinger multilayer cloud detection algorithm, introduced in Collection 6, to assist with multilayer cloud detection has also been assessed. For the year 2008, the MYD06 C6 multilayer cloud detection algorithm identifies roughly 20% of all cloudy pixels as multilayer (decreasing to about 13% if the Pavolonis–Heidinger algorithm output is not used). Evaluation against the merged CPR and CALIOP2B-CLDCLASS-lidar product shows that the MODIS multilayer detection results are quite sensitive to how multilayer clouds are defined in the radar and lidar product and that the algorithm performs better when the optical thickness of the upper cloud layer is greater than about 1.2 with a minimum layer separation distance of 1 km. Finally, we find that filtering the MYD06 cloud optical properties retrievals using the multilayer cloud flag improves aggregated statistics, particularly for ice cloud effective radius.

MODIS↗

NASA NTRS1989

Mesoscale and microscale structure of cirrus clouds - Three case studies

The structure and composition of various types of cirrus clouds were examined using coordinated aircraft and on-ground polarization lidar and Doppler radar measurements carried out during three case studies conducted during autumn or spring in Colorado, Wisconsin, and Utah states. A variety of cirrus cloud types observed included a multilayered orographic cirrus, a 6-km-deep cirrostratus overcast, and a group of fibrous cirrus cloud bands associated with tropopause generating cells, representing three basic cirrus-cloud types. The results on the structure and composition of these clouds provide insights into the microphysical processes and characteristic physical scales involved in the generation of cirrus clouds.

Sassen, Kenneth↗

NASA NTRS1990

Regional conditions during the 25 October 1986 FIRE cirrus/altocumulus case study

The regional cloud and meteorological conditions are described for this case using satellite imagery (GOES), dual polarization lidar data, NWS radar, NMC analyses, rawinsonde data including special soundings, and analyzed vertical motions. These observations are interpreted with respect to relationships between the observed cloud characteristics and corresponding atmospheric structure. Similarities with the 27 to 28 Oct. FIRE Cirrus Case Study are noted.

Starr, David↗

NASA NTRS1990

Wind shear predictive detector technology study status

Among the different elements to be investigated when considering the Wind Shear hazard, the Aeronautical Navigation Technical Service (STNA/3E), whose task is to participate in the development of new technologies and equipments, focused its effort on airborne and ground sensors for the detection of low-level wind shear. The first task, initiated in 1986, consists in the evaluation of three candidate techniques for forward-looking sensors: lidar, sodar, and radar. No development is presently foreseen for an infrared based air turbulence advance warning system although some flight experiments took place in the 70's. A Thomson infrared radiometer was then installed on an Air France Boeing 707 to evaluate its capability of detecting clear air turbulence. The conclusion showed that this technique was apparently able to detect cloud layers but that additional experiments were needed; on the other hand, the rarity of the phenomenon and the difficulty in operating on a commercial aircraft were also mentioned.

Gandolfi, C.↗

NASA NTRS2003

Preliminary Analysis and Simulations of July 23rd Extended Anvil Case

A key focus of CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers - Florida Area Cirrus Experiment) was the generation and subsequent evolution of cirrus outflow from deep convective cloud systems. A preliminary integrated look at the observations of an extended cirrus anvil cloud system observed on 23 July 2002 will be presented, including lidar and millimeter radar observations from NASA's ER-2 and in- situ observations from NASA's WB-57 and University of North Dakota Citation. The observations will be compared to preliminary results of simulations using 1-D and 2-D high-resolution (100 meter) cloud resolving models. The CRMs explicitly account for cirrus microphysical development by resolving the evolving ice crystal size distribution (bin model) in time and space. Both homogeneous and heterogeneous nucleation are allowed in the model. The CRM simulations are driven using the output of regional simulations using MM5 that produces deep convection similar to what was observed. The MM5 model employs a 2 km inner grid (32 layers) over a 360 km domain, nested within a 6 km grid over a 600 km domain. Initial and boundary conditions for the 36- hour MM5 simulation are taken from NCEP Eta model analysis at 32 km resolution. Key issues to be explored are the settling of the observed anvil versus the model simulations, and comparisons of dynamical properties, such as vertical motions, occurring in the observations and models. The former provides an integrated measure of the validity of the model microphysics (fallspeed) while the latter is the key factor in forcing continued ice generation.

Lin, R.-F.↗

NASA NTRS2003

Atmospheric Boundary Layer Sensors for Application in a Wake Vortex Advisory System

Remote sensing of the atmospheric boundary layer has advanced in recent years with the development of commercial off-the-shelf (COTS) radar, sodar, and lidar wind profiling technology. Radio acoustic sounding systems for vertical temperature profiles of high temporal scales (when compared to routine balloon soundings- (radiosondes) have also become increasingly available as COTS capabilities. Aircraft observations during landing and departures are another source of available boundary layer data. This report provides an updated assessment of available sensors, their performance specifications and rough order of magnitude costs for a potential future aircraft Wake Vortex Avoidance System (WakeVAS). Future capabilities are also discussed. Vertical profiles of wind, temperature, and turbulence are anticipated to be needed at airports in any dynamic wake avoidance system. Temporal and spatial resolution are dependent on the selection of approach and departure corridors to be protected. Recommendations are made for potential configurations of near-term sensor technologies and for testing some of the sensor systems in order to validate performance in field environments with adequate groundtruth.

Zak, J. Allen↗

NASA NTRS2003

HARLIE Aerosol and Cloud Structure and Wind Observations during HARGLO and IHOP

The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) is a conical-scanning, 1-micron wavelength lidar that has been adapted for ground-based applications and used to infer horizontal wind information by tracking the motions of aerosol and cloud scattering structures. In addition, HARLIE's rapid continuous scanning enables boundary layer statistics and a new cloud lidar data product that gives cloud coverage as a function of altitude with high temporal resolution. HARLIE has been used in several field campaigns while developing the techniques for wind, boundary layer (BL), and cloud data products. These campaigns involved a variety of wind measuring instruments including rawindsondes, cloud-tracked winds from video imagery, Doppler lidars and Doppler radars. HARGLO-2 was one of these campaigns and was dedicated to wind profile intercomparisons over a 1-week period in November of 2001. The most recent of these campaigns was the International H20 Project (IHOP) located in the Southern Great Plains of the US during May and June of 2002.

Schwemmer, Geary K.↗

NASA NTRS2003

CRYSTAL-FACE Analysis and Simulations of the July 23rd Extended Anvil Case

A key focus of CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers - Florida Area Cirrus Experiment) was the generation and subsequent evolution of cirrus outflow from deep convective cloud systems. Present theoretical background and motivations will be discussed. An integrated look at the observations of an extended cirrus anvil cloud system observed on 23 July 2002 will be presented, including lidar and millimeter radar observation; from NASA s ER-2 and in-situ observations from NASA s WB-57 and University of North Dakota Citation. The observations will be compared to results of simulations using 1-D and 2-D high-resolution (100 meter) cloud resolving models. The CRMs explicitly account for cirrus microphysical development by resolving the evolving ice crystal size distribution (bin model) in time and space. Both homogeneous and heterogeneous nucleation are allowed in the model. The CRM simulations are driven using the output of regional simulations using MM5 that produces deep convection similar to what was observed. The MM5 model employs a 2 km inner grid (32 layers) over a 360 km domain, nested within a 6-km grid over a 600-km domain. Initial and boundary conditions for the 36-hour MM5 simulation are taken from NCEP Eta model analysis at 32 km resolution. Key issues to be explored are the settling of the observed anvil versus the model simulations, and comparisons of dynamical properties, such as vertical motions, occurring in the observations and models. The former provides an integrated measure of the validity of the model microphysics (fallspeed) while the latter is the key factor in forcing continued ice generation.

Starr, David↗

NASA NTRS2006

A-Train Data Depot: Integrating and Visualizing Atmospheric Measurements Along the A-Train Tracks

The succession of US and international satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000) The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot, to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The A-Train Data Depot (ATDD) will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth s Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archwing for fast data access, and Cooperative Institute for Research in the Atmosphere (CRA) data co-registration tools. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be followed by associated measurements from MLS, OMI, HIRDLS, and TES. Given the independent nature of instrument/platform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be discussed. The project s resulting visualizations and analysis illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗

NASA NTRS2006

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗