Coronae on Venus: An Updated Global Database and Insights Into Morphology, Spatial Distribution, Geological Setting, and Lithospheric Properties
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This is the fourth of a set of five volumes which describe the software architecture for the Computational Structural Mechanics Testbed. Derived from NICE, an integrated software system developed at Lockheed Palo Alto Research Laboratory, the architecture is composed of the command language CLAMP, the command language interpreter CLIP, and the data manager GAL. Volumes 1, 2, and 3 (NASA CR's 178384, 178385, and 178386, respectively) describe CLAMP and CLIP and the CLIP-processor interface. Volumes 4 and 5 (NASA CR's 178387 and 178388, respectively) describe GAL and its low-level I/O. CLAMP, an acronym for Command Language for Applied Mechanics Processors, is designed to control the flow of execution of processors written for NICE. Volume 4 describes the nominal-record data management component of the NICE software. It is intended for all users.
Earth-based radar data remain an important part of the information set used to select and certify spacecraft landing sites on Mars. Constraints on robotic landings on Mars include: terrain elevation, radar reflectivity, regional and local slopes, rock distribution and coverage, and surface roughness, all of which are addressed by radar data. Indeed, the usefulness of radar data for Mars exploration has been demonstrated in the past. Radar data were critical in assessing the Viking Lander, and more recently, the Mars Pathfinder landing.
Earth-based radar data remain an important part of the information set used to select and certify spacecraft landing sites on Mars. Constraints on robotic landings on Mars include: terrain elevation, radar reflectivity, regional and local slopes, rock distribution and coverage, and surface roughness, all of which are addressed by radar data. Indeed, the usefulness of radar data for Mars exploration has been demonstrated in the past. Radar data were critical in assessing the Viking Lander 1 site, and more recently, the Mars Pathfinder landing site.
Now that the Galileo spacecraft s tour of the Jupiter system is over, we seek to integrate all available datasets in the hopes of understanding Io as completely as possible. We have compiled information about the morphologies and locations of paterae (volcano-tectonic depressions), mountains, and hotspots on Io in a single database. It is our hope that an analysis of the spatial and temporal relationships between these features will provide more indications of the nature of the crust of Io and the mechanisms leading to these features formation. Since Io s tidal heat escapes through its crust, more knowledge about the crust will lead to an understanding of internal processes, such as magma generation and delivery to the surface, and magnitude and orientation of internal stresses.
This paper will describe the production of the Ancillary Geographic Product (AGP) in support of the Earth Observing System (EOS) Multi-angle Imaging SpectroRadiometer (MISR) instrument data processing. The AGP is essentially a global database of geographic properties, tailored to the needs of the MISR mission.
Aerosols are highly variable in space, time and properties. Global assessment from satellite platforms and model predictions rely on validation from AERONET, a highly accurate ground-based network. Ver. 3 represents a significant improvement in accuracy and quality.
This paper describes the Global Resources Information Database (GRID), which is part of the Global Environmental Monitoring (GEM) Program. The following four objectives were established for GRID: (1) to collect and disseminate geographical information; (2) to construct within developing countries a geographical information system (GIS); (3) to demonstrate the ability of GIS to fuse global and national data sets for resource and environment management and planning at the national level; and (4) to train individuals from developing countries in remote sensing technology. The activities of GRID are coordinated at the GEM center at Nairobi (Kenya).
The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5 latitude by 2-3 longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded data sets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia,Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DCD1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously identified in MERRAs precipitation, and they reinforce the need to consider alternative sources of precipitation data. GFWED can be used for analyzing historical relationships between fire weather and fire activity at continental and global scales, in identifying large-scale atmosphereocean controls on fire weather, and calibration of FWI-based fire prediction models.
Seasonal forecasting of fire weather is examined based on a recently produced global database of the Fire Weather Index (FWI) system beginning in 1980. Seasonal average values of the FWI are examined in relation to measures of the El Nino-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). The results are used to examine seasonal forecasts of fire weather conditions throughout the world.
Fire plays a significant role on both national and global scales, profoundly impacting landscapes shaped by human activity as well as those left wild. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes. Fires can also serve to reduce fuels to mitigate wildfire risk and maintain healthy ecosystem functions. However, the smoke produced by fires, regardless of their size or purpose, can pose adverse effects on human health when inhaled downwind. Understanding the influence of smoke on air quality and human well-being necessitates the quantification of emissions that fires release into the atmosphere. In response to this need, we have established a comprehensive global consumption database directly linked to distinct fuels within various fire danger categories. This database, featuring a spatial resolution of approximately 300 meters, builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized Fuel Characteristic Classification System (FCCS) biomass parameters. Consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. We define ‘residual burned area’ as area burning in a region that has burned on a previous day for the same fire season, and ‘new burned area’ as area burning in a region that has not recently burned. This product serves as a valuable tool when used in conjunction with burned area data to rapidly estimate the carbon consumed and released into the atmosphere. Previously, we developed a similar emissions method utilizing satellite information, in conjunction with the FCCS 30-meter United States fuelbed dataset. We implemented this approach on fires, documented during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to estimate daily carbon emissions. Our emissions estimates were rigorously compared against in-situ measurements of CO2, CO, and black carbon aerosols, revealing a robust agreement between the two datasets.
A distributed Ada program library is a key element in a distributed Ada Program Support Environment (APSE). To implement this successfully, the program library universe as defined by the Ada Reference Manual must be broken up into independently manageable pieces. This in turn requires the support of a distributed database system, as well as a mechanism for identifying compilation units, linkable subprograms, and Ada types in a decentralized way, to avoid falling victim to the bottlenecks of a global database and/or global unique-identifier manager. It was found that the ability to decentralize Ada program library activity is a major advantage in the management of large Ada programs. Currently, there are 18 resource-catalog revision sets, each in its own Host Interface (HIF) partition, plus 18 partitions for testing each of these, plus 11 partitions for the top-level compiler/linker/program library manager components. Compiling and other development work can proceed in parallel in each of these partitions, without suffering the performance bottlenecks of global locks or global unique-identifier generation.
Fire plays a significant role on both national and global scales, profoundly impacting landscapes shaped by human activity as well as wildlands. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes. Fires can also serve to reduce fuels to mitigate wildfire risk and maintain healthy ecosystem functions. However, the smoke produced by fires, regardless of their size or purpose, can pose adverse effects on human health when inhaled downwind. Understanding the influence of smoke on air quality and human well-being necessitates the quantification of emissions that fires release into the atmosphere. In response to this need, we have developed a carbon consumption database for the Continental United States (CONUS) and are developing a global carbon consumption database, both of which are directly link to distinct fuels within various fire danger categories. Fuel Characteristic Classification System (FCCS) fuels are used to parameterize biomass, and consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. Residual burned area is defined as burning in areas that have recently burned. We implemented the FCCS 30-meter CONUS fuelbed dataset during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to estimate daily carbon emissions. Our emissions estimates were rigorously compared against in-situ measurements of CO2, CO, and black carbon aerosols, revealing a robust agreement between the two datasets. The 300-meter global database builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized FCCS biomass parameters. These products can serve as valuable tools when used in conjunction with burned area data to rapidly and accurately estimate carbon consumed and released into the atmosphere.
The primary goal of this collaborative project, lead by Nicholas Gruber at UCLA, is to better quantify the air-sea fluxes of pre-industrial and anthropogenic carbon dioxide CO2 for the global ocean with a newly developed inverse method. The method involves using ocean general circulation models (OGCMs) to characterize the subsurface distribution of tracers injected for different regions of the ocean surface. By linearly combining a series of these basis (or Greens) functions, one should be able to recreate any arbitrary ocean tracer field. In our case, we are using the global database of ocean dissolved inorganic carbon (DIC) from the WOCE/JGOFS global CO2 survey from the 1990s. The observed DIC field has been partitioned into pre-industrial and anthropogenic components using the empirical C* technique. We then solve for an optimal combination of the regional basis functions that best match the two sets observations in a least-squares sense with singular value decomposition. This in turn provides solutions for the regional air-sea CO2 fluxes (pre-industrial and anthropogenic) that are independent of more traditional estimates derived from surface water disequilibria in the partial pressure of CO2 and wind speed gas exchange parameterizations. We are apply the method to a suite of nine different OGCMs to test the robustness of the derived surface fluxes fields to differences in ocean circulation. Together with a collegue Keith Lindsay at NCAR, S. Doney's role in this project was to create the appropriate steady-state and temporally evolving basis functions from the NCAR CSM-1 ocean circulation model. Because of a slow start across the project in defining a common set of experimental protocols, we requested and were given a one year, no cost extension. Both the steady-state and temporally evolving basis functions were delivered to the UCLA group for further analysis. Additional information is included in the original extended abstract.
The AeroMACS (Aeronautical Mobile Airport Communications System), which is based on the IEEE 802.16-2009 mobile wireless standard, is envisioned as the wireless network which will cover all areas of airport surfaces for next generation air transportation. It is expected to be implemented in the 5091-5150 MHz frequency band which is also occupied by mobile satellite service uplinks. Thus the AeroMACS must be designed to avoid interference with this incumbent service. Simulations using Visualyse software were performed utilizing a global database of 6207 airports. Variations in base station and subscriber antenna distribution and gain pattern were examined. Based on these simulations, recommendations for global airport base station and subscriber antenna power transmission limitations are provided.
The AeroMACS (Aeronautical Mobile Airport Communications System), which is based on the IEEE 802.16-2009 mobile wireless standard, is envisioned as the wireless network which will cover all areas of airport surfaces for next generation air transportation. It is expected to be implemented in the 5091-5150 MHz frequency band which is also occupied by mobile satellite service uplinks. Thus the AeroMACS must be designed to avoid interference with this incumbent service. Simulations using Visualyse software were performed utilizing a global database of 6207 airports. Variations in base station and subscriber antenna distribution and gain pattern were examined. Based on these simulations, recommendations for global airport base station and subscriber antenna power transmission limitations are provided.
State-of-the-art cloud computing platforms such as Google Earth Engine (GEE) enable regional-to-global land cover and land cover change mapping with machine learning algorithms. However, collection of high-quality training data, which is necessary for accurate land cover mapping, remains costly and labor-intensive. To address this need, we created a global database of nearly 2 million training units spanning the period from 1984 to 2020 for seven primary and nine secondary land cover classes. Our training data collection approach leveraged GEE and machine learning algorithms to ensure data quality and biogeographic representation. We sampled the spectral-temporal feature space from Landsat imagery to efficiently allocate training data across global ecoregions and incorporated publicly available and collaborator-provided datasets to our database. To reflect the underlying regional class distribution and post-disturbance landscapes, we strategically augmented the database. We used a machine learning-based cross-validation procedure to remove potentially mis-labeled training units. Our training database is relevant for a wide array of studies such as land cover change, agriculture, forestry, hydrology, urban development, among many others.