Using Quality Attributes to Bridge Systems Engineering Gaps : a Juno Ground Data Systems Case Study
No abstract available
Ground Data Systems (GDS)↗
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Global Scale Attribution of Anthropogenic and Natural Dust Sources and their Emission Rates Based on MODIS Deep Blue Aerosol Products
Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Here we present a global-scale high-resolution (0.1 deg) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.
aerosols↗
Attribution of Trends and Variability in Surface Ozone over the United States
Concentrations of tropospheric ozone, a greenhouse gas and air pollutant, are impacted by changes in precursor emissions as well meteorology and influx from the stratosphere. Observations show a decreasing trend in summertime surface ozone at rural stations in the eastern United States, while some western stations show increasing trends, particularly in springtime. We use the Global Modeling Initiative (GMI) global chemical transport model to investigate the roles of precursor emission changes, meteorological variability, and stratosphere-troposphere exchange (STE) in explaining observed trends in surface ozone from rural sites in the United States from 1991-2010. The model's interannual variability shows significant correlations with observations from many of the surface sites. We also compare the simulated ozone to ozonesonde data for several locations with sufficiently long records. We compare a simulation with time-dependent precursor emissions, including emission reductions over the United States and Europe and increases over Asia, to a simulation with fixed emissions to quantify the impact of changing emissions on the surface trends. The simulation with varying emissions reproduces much of the east-west difference in summertime ozone over the U.S., although it generally underestimates the negative trend in the East. In contrast, the fixed-emission simulation shows increasing ozone at both eastern and western sites. We will discuss possible causes of this behavior, including long-range transport and STE.
ozone↗
Source Attributions of Pollution to the Western Arctic During the NASA ARCTAS Field Campaign
We use the NASA GEOS-5 transport model with tagged tracers to investigate the contributions of different regional sources of CO and black carbon (BC) to their concentrations in the Western Arctic (i.e., 50-90 deg N and 190- 320 deg E) in spring and summer 2008. The model is evaluated by comparing the results with airborne measurements of CO and BC from the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaigns to demonstrate the strengths and limitations of our simulations. We also examine the reliability of tagged CO tracers in characterizing air mass origins using the measured fossil fuel tracer of dichloromethane and the biomass burning tracer of acetonitrile. Our tagged CO simulations suggest that most of the enhanced CO concentrations (above background level from CH4 production) observed during April originate from Asian anthropogenic emissions. Boreal biomass burning emissions and Asian anthropogenic emissions are of similar importance in July domain wise, although the biomass burning CO fraction is much larger in the area of the ARCTAS field experiments. The fraction of CO from Asian anthropogenic emissions is larger in spring than in summer. European sources make up no more than 10% of CO levels in the campaign domain during either period. Comparisons of CO concentrations along the flight tracks with regional averages from GEOS-5 show that the alongtrack measurements are representative of the concentrations within the large domain of the Western Arctic in April but not in July.
Black Carbon↗
Large Fluvial Fans: Aspects of the Attribute Array
In arguing for a strict definition of the alluvial fan (coarse‐grained with radii less than10 km, in mountain‐front settings), Blair and McPherson (1994) proposed that there is no meaningful difference between large fluvial fans (LFF) and floodplains, because the building blocks of both are channel‐levee‐overbank deposits. Sediment bodies at the LFF scale (greater than 100 km long, fan‐shaped in planform), are relatively unstudied although greater than 160 are now identified globally. The following perspectives suggest that the significance of LFF needs to be reconsidered.
Wilkinson, Justin M.↗
A New Look at Data Usage by Using Metadata Attributes as Indicators of Data Quality
This study reviews the key metrics (users, distributed volume, and files) in multiple ways to gain an understanding of the significance of the metadata. Characterizing the usability of data by key metadata elements, such as discipline and study area, will assist in understanding how the user needs have evolved over time. The data usage pattern based on product level provides insight into the level of data quality. In addition, the data metrics by various services, such as the Open-source Project for a Network Data Access Protocol (OPeNDAP) and subsets, address how these services have extended the usage of data. Over-all, this study presents the usage of data and metadata by metrics analyses, which may assist data centers in better supporting the needs of the users.
metadata↗
Tropospheric Ozone Source Attribution in Southern California during Summer 2014 Based on Lidar Measurements and Model Simulations
In the past decades, significant efforts have been made to increase tropospheric ozone long-term monitoring. A large number of ground-based, airborne and space-borne instruments are currently providing valuable data to contribute to better understand tropospheric ozone budget and variability. Nonetheless, most of these instruments provide in-situ surface and column-integrated data, whereas vertically resolved measurements are still scarce. Besides ozonesondes and aircraft, lidar measurements have proven to be valuable tropospheric ozone profilers. Using the measurements from the tropospheric ozone differential absorption lidar (DIAL) located at the JPL Table Mountain Facility, California, and the GEOS-Chem and GEOS-5 model outputs, the impact of the North American monsoon on tropospheric ozone during summer 2014 is investigated. The influence of the Monsoon lightning-induced NOx will be evaluated against other sources (e.g. local anthropogenic emissions and the stratosphere) using also complementary data such as backward-trajectories analysis, coincident water vapor lidar measurements, and surface ozone in-situ measurements.
Lidar↗
Comparison of Two Bioinformatics Tools Used to Characterize the Microbial Diversity and Predictive Functional Attributes of Microbial Mats from Lake Obersee, Antarctica
In this study, using NextGen sequencing of the collective 16S rRNA genes obtained from two sets of samples collected from Lake Obersee, Antarctica, we compared and contrasted two bioinformatics tools, PICRUSt and Tax4Fun. We then developed an R script to assess the taxonomic and predictive functional profiles of the microbial communities within the samples. Taxa such as Pseudoxanthomonas, Planctomycetaceae, Cyanobacteria Subsection III, Nitrosomonadaceae, Leptothrix, and Rhodobacter were exclusively identified by Tax4Fun that uses SILVA database; whereas PICRUSt that uses Greengenes database uniquely identified Pirellulaceae, Gemmatimonadetes A1-B1, Pseudanabaena, Salinibacterium and Sinibacteraceae. Predictive functional profiling of the microbial communities using Tax4Fun and PICRUSt separately revealed common metabolic capabilities, while also showing specific functional IDs not shared between the two approaches. Combining these functional predictions using a customized R script revealed a more inclusive metabolic profile, such as hydrolases, oxidoreductases, transferases; enzymes involved in carbohydrate and amino acid metabolisms; and membrane transport proteins known for nutrient uptake from the surrounding environment. Our results present the first molecular-phylogenetic characterization and predictive functional profiles of the microbial mat communities in Lake Obersee, while demonstrating the efficacy of combining both the taxonomic assignment information and functional IDs using the R script created in this study for a more streamlined evaluation of predictive functional profiles of microbial communities.
Hyunmin Koo↗
Attribution of Flux Partitioning Variations Between Land Surface Models over the Continental U.S.
Accurate quantification of the terrestrial evapotranspiration (ET) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total ET. As these models are often used in data assimilation environments for incorporating and extending ET relevant remote sensing measurements, understanding the sources of inter-model differences in ET components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total ET: (1) contribution of the local partitioning and (2) regional distribution of ET. The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the ET partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of ET over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total ET errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial.
uncertainty↗
Attribution of Flux Partitioning Variations Between Land Surface Models Over the Continental U.S.
Accurate quantification of the terrestrial evapotranspiration (ET) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total ET. As these models are often used in data assimilation environments for incorporating and extending ET relevant remote sensing measurements, understanding the sources of inter-model differences in ET components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total ET: (1) contribution of the local partitioning and (2) regional distribution of ET. The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the ET partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of ET over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total ET errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial.
evapotranspiration partitioning; transpiration; so↗
Synthetic Aperture Radar and Optical Remote Sensing of Crop Damage Attributed to Severe Weather in the Central United States
Damaging hail and wind from severe thunderstorms threatens agricultural areas annually, especially across the central United States where agriculture is prevalent. On average, these storms produce $160 to $580 million worth of damage in the US every year and contribute significantly to food prices, crop insurance, and agricultural related stocks. However, hail damage is not regularly ground-surveyed like tornadoes. Optical (visible, NIR (Near Infra-Red), and SWIR (Short-Wave Infra-Red) remote sensing techniques have been shown to successfully identify and monitor hail damage swaths. Techniques of identification and monitoring hail damage swaths from synthetic aperture radar (SAR) are currently unexplored. We hypothesize that hail-damaged cropland will exhibit lower power return than surrounding healthy vegetation due to changes in the geometry of the targets. Further analysis is needed to determine a threshold for future automated monitoring of hail damage swaths.
Bell, Jordan↗
Observation and Attribution of Temperature Trends near the Stratopause from HALOE
This study considers time series of temperature versus pressure, T(p), from the Halogen Occultation Experiment (HALOE) across the stratopause region, where the effects of radiative forcings from the greenhouse gases (CO2 and H2O) and from ozone are most pronounced. Trend analyses are from 1993-2005 for HALOE T(p) values at seven levels from 3.0 to 0.3 hPa with a vertical resolution of about 4 km and for eight latitude zones from 65°S to 65°N. The HALOE trends at 2.0 hPa are of the order of -1.0 K/decade across the tropics and subtropics, but then become smaller (-0.5 K/decade) at the middle latitudes. The near-global HALOE trend profile has a minimum cooling rate of -0.2 K/decade at 1.0 hPa, although it is more negative in the southern hemisphere and slightly positive in the northern hemisphere. The combined radiative forcings from CO2, H2O, and ozone are from -0.4 to -0.6 K/decade for 1993-2005 and are hemispherically symmetric. HALOE temperature trend and total radiative cooling profiles differ from those reported from observations and calculations for 1980-2000, mainly because the ozone trends changed from clearly negative in the 1980s through mid-1990s to slightly positive during the time of HALOE. Trends for the tracer, HALOE methane (CH4), increase from 2 to 4 %/decade from 50 hPa to 10 hPa, indicating an acceleration of the Brewer/Dobson circulation. Analyses of time series of CH4 across the stratopause reveal more variability in the northern hemisphere, where wave dissipation likely contributes to the heating.
Remsberg, Ellis↗
Quality Attributes for Mission Flight Software: A Reference for Architects
No abstract available
Dvorak, Dan↗
Interannual Variability in MLS Trace Gas Observations in the Antarctic Polar Vortex: Issues in Detection and Attribution of Trends
No abstract available
Schwartz, Michael J.↗
Interannual Variability in MLS Trace Gas Observations in the Antarctic Polar Vortex: Issues in Detection and Attribution of Trends
No abstract available
Schwartz, Michael J.↗
Mapping the Capabilities and Attributes of Solid Oxide Electrochemical Systems to Human Spaceflight Needs
NASA is sponsoring the development of a solid oxide electrochemical oxygen separation and compression system. This system is capable of extracting oxygen from a process stream of spacecraft cabin air, and compressing it to >27,000 kPa without mechanical compressors. Process temperatures are >650C, but the materials in contact with the oxygen do not burn. The system is called eCOG-C, Electrochemical Oxygen Generator and Compressor. A system capable of producing high pressure, high purity oxygen may have application as a method of recharging space suit oxygen tanks during human exploration missions. This paper describes the key performance parameters of a space suit oxygen tank recharge system, and places the key performance parameters of eCOG-c in the context of other methods of space suit oxygen tank recharge. This paper compares the eCOG-c configuration to an earlier electrochemical oxygen generator that has been prototyped and tested. Areas of emphasis for eCOG-C development are listed and described.
John Graf↗