A Visual Guide to the GRACE Data Assimilation for Drought Monitoring (GRACE-DA-DM) Data Products
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Stephanie Stettz↗
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Forecasting Plant Productivity and Health Using Diffuse-to-Global Irradiance Ratios Extracted from the OMI Aerosol Product
Atmospheric aerosols are a major contributor to diffuse irradiance. This Candidate Solution suggests using the OMI (Ozone Monitoring Instrument) aerosol product as input into a radiative transfer model, which would calculate the ratio of diffuse to global irradiance at the Earth s surface. This ratio can significantly influence the rate of photosynthesis in plants; increasing the ratio of diffuse to global irradiance can accelerate photosynthesis, resulting in greater plant productivity. Accurate values of this ratio could be useful in predicting crop productivity, thereby improving forecasts of regional food resources. However, disagreements exist between diffuse-to-global irradiance values measured by different satellites and ground sensors. OMI, with its unique combination of spectral bands, high resolution, and daily global coverage, may be able to provide more accurate aerosol measurements than other comparable sensors.
Knowlton, Kelly↗
Monitoring the Flow of the Greenland Ice Sheet: the PROMICE Ice Velocity Product and Recent Updates
We present the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) ice velocity product, which is a time series of ice velocity mosaics derived using offset tracking on Sentinel-1 SAR data. The time series starting in January 2016 is continuously updated with a new mosaic every 12 days and is posted at 500 m grid resolution. Within PROMICE, the ice velocity product is used directly as input to estimate the solid ice discharge from the Greenland Ice Sheet as well as to study ice dynamic processes on seasonal and multi-annual time scales. Recently, we have made changes to the processing chain due to spurious cases of slow down detected in a few glaciers in Southeast Greenland. In this contribution, we discuss how this was resolved as well as other recent improvements to the product.
Greenland ice sheet↗
Global crop forecasting
The needs for and remote sensing means of global crop forecasting are discussed, and key results of the Large Area Crop Inventory Experiment (LACIE) are presented. Current crop production estimates provided by foreign countries are shown often to be inadequate, and the basic elements of crop production forecasts are reviewed. The LACIE project is introduced as a proof-of-concept experiment designed to assimilate remote sensing technology, monitor global wheat production, evaluate key technical problems, modify the technique accordingly and demonstrate the feasibility of a global agricultural monitoring system. The global meteorological data, sampling and aggregation techniques, Landsat data analysis procedures and yield forecast procedures used in the experiment are outlined. Accuracy assessment procedures employed to evaluate LACIE technology performance are presented, and improvements in system efficiency and capacity during the three years of operation are pointed out. Results of LACIE estimates of Soviet, U.S. and Canadian wheat production are presented which demonstrate the feasibility and accuracy of the remote-sensing approach for global food and fiber monitoring.
Macdonald, R. B.↗
Biomedical Monitoring and Countermeasures Facility
The Space Station Freedom Program (SSFP) represents the transition within the US Space program from the 'heroic' era of space flight (characterized most vividly by the Mercury and Apollo programs) to an epoch characterized by routine access to the space environment. In this new era, the unique characteristics of the microgravity environment will enable new types of research activities, primarily in the life sciences, materials science, and biotechnology fields. In addition to its role as a'microgravity science laboratory,' Space Station Freedom (SSF) constitutes the operational platform on which the knowledge and skills needed to continue our exploration of space will be acquired. In the area of spacecraft operations, these skills include the ability to assemble, operate, and maintain large structures in space. In the area of crew operations, the potentially harmful effects of extended exposure to microgravity must be understood in order to keep the crew mission capable. To achieve this goal, the complex process of physiological deconditioning must be monitored, and countermeasures utilized as needed to keep the individual crew members within acceptable physiological limits. The countermeasures program under development for the SSF Program is titled the Biomedical Monitoring and Countermeasures (BMAC) program. As implied by the name, this activity has two primary products, a biomedical monitoring element and a countermeasures development effort. The program is a critical path element in the overall SSF Program, and should be considered an essential element of operations on board the space station. It is readily apparent that the capability to both protect and optimize the health and performance of the human operators on board SSF will be a critical element in the overall success of the SSFP. Previous experience within the Russian space program has demonstrated that the time required for countermeasures on extended missions can become a monumental operational burden. Therefore, one of the primary objectives of the countermeasures development activity will be to design and implement countermeasures which are significantly more effective than the existing generation. Other primary objectives include the following: to set health and human performance standards for all mission phases; to determine critical issues that affect performance or return to flight status; to develop and implement monitoring systems to follow health and performance status; and to understand risk, and balance the resource costs of countermeasures vs. the benefit gained.
Stewart, Donald F.↗
The Unusual Evolution of Hurricane Arthur 2014
Hurricane Arthur (2014) was an early season hurricane that had its roots in a convective complex in the Southern Plains of the U.S. As the complex moved into northern Texas, a Mesoscale Convective Vortex (MCV) formed and drifted towards the east of the southern U.S. for a few days before emerging over the southwest Atlantic near South Carolina. The MCV drifted south and slowly acquired tropical characteristics, eventually becoming a Category 2 hurricane that would affect much of eastern North Carolina prior to the 4th of July holiday weekend. Arthur continued up the coast, brushing portions of southeast New England and merged with an upper-level low, completing a full tropical to extratropical-transition in the process, producing damaging wind gusts in portions of the Canadian Maritimes. As part of the GOES-R and JPSS Satellite Proving Grounds, multiple proxy and operational products were available to analyze and forecast this complex evolution. The Storm Prediction Center had products available to monitor the initial severe thunderstorm aspect, while the National Hurricane Center and Ocean Prediction Center were able to monitor the tropical and extratropical transition of Arthur using various convective and red, green, blue (RGB) products that have been introduced in recent years. This paper will discuss Arthur's evolution through the eyes of the various Satellite Proving Ground demonstrations.
Folmer, Michael↗
Assessing the Uncertainty Impact of CERES Fast Longwave and SHortwave Radiative Flux (FLASHFlux) Level 3 Product With and Without Terra Observations
The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave And SHortwave radiative Flux (FLASHFlux) data product was developed to provide data for applied science research involving the renewable energy and agricultural sectors within a week of observation. FLASHFlux achieves this by using simplified calibration, an operational meteorological product from Global Monitoring and Assimilation Office (GMAO), and a surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Terra and NOAA-20 observations. 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) gridded data that combines NOAA-20 and Terra observations on a one-degree equal angle grid. FLASHFlux TISA data product interpolate on a diurnal model that assumes a satellite equilateral crossing time of 10:30 AM and 1:30 PM from Terra and Aqua, respectively. Aqua was replaced by NOAA-20 starting on September 2022. Terra is planned to be replace by the Satellite ClOud and Radiation Property retrieval System (SatCORPS) soon. We are currently using the Terra observations as it continues to drift. We assess the impact of FLASHFlux TISA data when Terra is removed. An uncertainty estimate of the Top-Of-Atmosphere (TOA) fluxes are given of FLASHFlux Version4A (before Terra drift) and Version4B (current), and Version4B (no Terra) in comparison to the CERES EBAF and SYN1deg. In addition, we compare FLASHFlux Version4B and Version4B (no Terra) surface radiative fluxes to ground base measurements to determine the impact of running without Terra data.
PC Sawaengphokhai↗
Space Technology for Patient Monitoring
A contract for the development of an astronaut monitoring system in the early days of the space program provided Mennen Medical, Inc. with a foundation in telemetry that led to the development of a computerized medical electronic system used by hospitals. Mennen was the first company to adopt solid state design in patient monitoring and to offer multipatient telemetry monitoring. Telemetry converts instrument data to electrical signals and relays them to a remote receiver where they are displayed. From a central station, a nurse can monitor several patients. Company products include VISTA systems and Horizon 2000 Monitor.
Source record↗
Blowout Monitor
C Language Integrated Production System (CLIPS), a NASA-developed software shell for developing expert systems, has been embedded in a PC-based expert system for training oil rig personnel in monitoring oil drilling. Oil drilling rigs if not properly maintained for possible blowouts pose hazards to human life, property and the environment may be destroyed. CLIPS is designed to permit the delivery of artificial intelligence on computer. A collection of rules is set up and, as facts become known, these rules are applied. In the Well Site Advisor, CLIPS provides the capability to accurately process, predict and interpret well data in a real time mode. CLIPS was provided to INTEQ by COSMIC.
Source record↗
Using LIDAR and Quickbird Data to Model Plant Production and Quantify Uncertainties Associated with Wetland Detection and Land Cover Generalizations
Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.
Cook, Bruce D.↗
TRMM-based Merged Data Products Compared to Global Precipitation Climatology Project (GPCP) Analyses
This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) (launched in November 1997) information as the key calibration tool; in a merged analysis on a 1 degree x l degree latitude/longitude monthly scale based on multiple satellite sources and raingauge analyses. The TRMM-based product will be compared with the community-based Global Precipitation Climatology Project (GPCP) results. The long-term GPCP analysis is compared to the new TRMM-based analysis which uses the most accurate TRMM information to calibrate the estimates from the Special Sensor Microwave/Imager (SSM/I) and geosynchronous IR observations and merges those estimates together with the TRMM and gauge information to produce accurate rainfall estimates with the increased sampling provided by the combined satellite information. The comparison with TRMM results on a month-to-month basis should clarify the strengths and weaknesses of the long-term GPCP product in the tropics and point to how to improve the monitoring analysis. Preliminary results from the TRMM merged satellite analysis indicates close agreement with the GPCP estimates. By the time of the meeting over a year of TRMM products will be available for comparison. Global tropical and regional values will be compared. Seasonal variations, and variations associated with the 1998 El Nino/Southern Oscillation ENSO event will be examined and compared between the two analyses. These variations will be examined carefully and validated where possible from surface-based radar and gauge observations. The role of TRMM observations in the refinement of the long-term monitoring product will be outlined.
Adler, Robert F.↗
Simulation of the Ozone Monitoring Instrument Aerosol Index Using the NASA Goddard Earth Observing System Aerosol Reanalysis Products
We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI aerosol retrieval algorithms, and its retrieved AI (OMAERUV AI) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600hPa and 1013.25hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.
remote sensing↗
Remote sensing investigations of wetland biomass and productivity for global biosystems research
Monitoring biomass of wetlands ecosystems can provide information on net primary production and on the chemical and physical status of wetland soils relative to anaerobic microbial transformation of key elements. Multispectral remote sensing techniques successfully estimated macrophytic biomass in wetlands systems. Regression models developed from ground spectral data for predicting Spartina alterniflora biomass over an entire growing season include seasonal variations in biomass density and illumination intensity. An independent set of biomass and spectral data were collected and the standing crop biomass and net primary productivity were estimated. The improved spatial, radiometric and spectral resolution of th LANDSAT-4 Thematic Mapper over the LANDSAT MSS can greatly enhance multispectral techniques for estimating wetlands biomass over large areas. These techniques can provide the biomass data necessary for global ecology studies.
Harkisky, M.↗
Electrochemical Detection of Multiple Bioprocess Analytes
An apparatus that includes highly miniaturized thin-film electrochemical sensor array has been demonstrated as a prototype of instruments for simultaneous detection of multiple substances of interest (analytes) and measurement of acidity or alkalinity in bioprocess streams. Measurements of pH and of concentrations of nutrients and wastes in cell-culture media, made by use of these instruments, are to be used as feedback for optimizing the growth of cells or the production of desired substances by the cultured cells. The apparatus is designed to utilize samples of minimal volume so as to minimize any perturbation of monitored processes. The apparatus can function in a potentiometric mode (for measuring pH), an amperometric mode (detecting analytes via oxidation/reduction reactions), or both. The sensor array is planar and includes multiple thin-film microelectrodes covered with hydrous iridium oxide. The oxide layer on each electrode serves as both a protective and electrochemical transducing layer. In its transducing role, the oxide provides electrical conductivity for amperometric measurement or pH response for potentiometric measurement. The oxide on an electrode can also serve as a matrix for one or more enzymes that render the electrode sensitive to a specific analyte. In addition to transducing electrodes, the array includes electrodes for potential control. The array can be fabricated by techniques familiar to the microelectronics industry. The sensor array is housed in a thin-film liquid-flow cell that has a total volume of about 100 mL. The flow cell is connected to a computer-controlled subsystem that periodically draws samples from the bioprocess stream to be monitored. Before entering the cell, each 100-mL sample is subjected to tangential-flow filtration to remove particles. In the present version of the apparatus, the electrodes are operated under control by a potentiostat and are used to simultaneously measure the pH and the concentration of glucose. It is anticipated that development of procedures for trapping more enzymes into hydrous iridium oxide (and possibly into other electroactive metal oxides) and of means for imparting long-term stability to the transducer layers should make it possible to monitor concentrations of products of many enzyme reactions for example, such key bioprocess analytes as amino acids, vitamins, lactose, and acetate.
Rauh, R. David↗
Newly Released TRMM Version 7 Products, Other Precipitation Datasets and Data Services at NASA GES DISC
The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is home of global precipitation product archives, in particular, the Tropical Rainfall Measuring Mission (TRMM) products. TRMM is a joint U.S.-Japan satellite mission to monitor tropical and subtropical (40 S - 40 N) precipitation and to estimate its associated latent heating. The TRMM satellite provides the first detailed and comprehensive dataset on the four dimensional distribution of rainfall and latent heating over vastly undersampled tropical and subtropical oceans and continents. The TRMM satellite was launched on November 27, 1997. TRMM data products are archived at and distributed by GES DISC. The newly released TRMM Version 7 consists of several changes including new parameters, new products, meta data, data structures, etc. For example, hydrometeor profiles in 2A12 now have 28 layers (14 in V6). New parameters have been added to several popular Level-3 products, such as, 3B42, 3B43. Version 2.2 of the Global Precipitation Climatology Project (GPCP) dataset has been added to the TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/), allowing online analysis and visualization without downloading data and software. The GPCP dataset extends back to 1979. Version 3 of the Global Precipitation Climatology Centre (GPCC) monitoring product has been updated in TOVAS as well. The product provides global gauge-based monthly rainfall along with number of gauges per grid. The dataset begins in January 1986. To facilitate data and information access and support precipitation research and applications, we have developed a Precipitation Data and Information Services Center (PDISC; URL: http://disc.gsfc.nasa.gov/precipitation). In addition to TRMM, PDISC provides current and past observational precipitation data. Users can access precipitation data archives consisting of both remote sensing and in-situ observations. Users can use these data products to conduct a wide variety of activities, including case studies, model evaluation, uncertainty investigation, etc. To support Earth science applications, PDISC provides users near-real-time precipitation products over the Internet. At PDISC, users can access tools and software. Documentation, FAQ and assistance are also available. Other capabilities include: 1) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Mirador is designed to be fast and easy to learn; 2)TOVAS; 3) NetCDF data download for the GIS community; 4) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/). The OPeNDAP provides remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; 5) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml). The WMS is an interface that allows the use of data and enables clients to build customized maps with data coming from a different network.
Liu, Zhong↗
A quantum yield determination of O/1D/ production from ozone via laser flash photolysis
The quantum yield of electronically excited atomic oxygen produced from ozone photolysis was measured at 298 K from wavelengths of 293.0 to 316.5 nm. The reaction of the atomic oxygen with N2O to form excited NO2 was used to monitor the O production; a frequency-doubled flashlamp-pumped dye laser which provided tunable ultraviolet in the desired spectral region with 0.1-nm linewidth served as the photolysis source. The atomic oxygen quantum yield was found to be constant below 300 nm, with a sharp decrease centered at 308 nm and a diminution to less than one tenth of the constant value by 313.5 nm.
Philen, D. L.↗
Potential of VIIRS Data for Regional Monitoring of Gypsy Moth Defoliation: Implications for Forest Threat Early Warning System
A NASA RPC (Rapid Prototyping Capability) experiment was conducted to assess the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) data for monitoring non-native gypsy moth (Lymantria dispar) defoliation of forests. This experiment compares defoliation detection products computed from simulated VIIRS and from MODIS (Moderate Resolution Imaging Spectroradiometer) time series products as potential inputs to a forest threat EWS (Early Warning System) being developed for the USFS (USDA Forest Service). Gypsy moth causes extensive defoliation of broadleaved forests in the United States and is specifically identified in the Healthy Forest Restoration Act (HFRA) of 2003. The HFRA mandates development of a national forest threat EWS. This system is being built by the USFS and NASA is aiding integration of needed satellite data products into this system, including MODIS products. This RPC experiment enabled the MODIS follow-on, VIIRS, to be evaluated as a data source for EWS forest monitoring products. The experiment included 1) assessment of MODIS-simulated VIIRS NDVI products, and 2) evaluation of gypsy moth defoliation mapping products from MODIS-simulated VIIRS and from MODIS NDVI time series data. This experiment employed MODIS data collected over the approximately 15 million acre mid-Appalachian Highlands during the annual peak defoliation time frame (approximately June 10 through July 27) during 2000-2006. NASA Stennis Application Research Toolbox software was used to produce MODIS-simulated VIIRS data and NASA Stennis Time Series Product Tool software was employed to process MODIS and MODIS-simulated VIIRS time series data scaled to planetary reflectance. MODIS-simulated VIIRS data was assessed through comparison to Hyperion-simulated VIIRS data using data collected during gypsy moth defoliation. Hyperion-simulated MODIS data showed a high correlation with actual MODIS data (NDVI R2 of 0.877 and RMSE of 0.023). MODIS-simulated VIIRS data for the same date showed moderately high correlation with Hyperion-simulated VIIRS data (NDVI R2 of 0.62 and RMSE of 0.035), even though the datasets were collected about a half an hour apart during changing weather conditions. MODIS products (MOD02, MOD09, and MOD13) and MOD02-simulated VIIRS time series data were used to generate defoliation mapping products based on image classification and image differencing change detection techniques. Accuracy of final defoliation mapping products was assessed by image interpreting over 170 randomly sampled locations found on Landsat and ASTER data in conjunction with defoliation map data from the USFS. The MOD02-simulated VIIRS 400-meter NDVI classification produced a similar overall accuracy (87.28 percent with 0.72 Kappa) to the MOD02 250-meter NDVI classification (86.71 percent with 0.71 Kappa). In addition, the VIIRS 400-meter NDVI, MOD02 250-meter NDVI, and MOD02 500-meter NDVI showed good user and producer accuracies for the defoliated forest class (70 percent) and acceptable Kappa values (0.66). MOD02 and MOD02-simulated VIIRS data both showed promise as data sources for regional monitoring of forest disturbance due to insect defoliation.
Spruce, Joseph P.↗
Production and Distribution of NASA MODIS Remote Sensing Products
The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.
Wolfe, Robert↗