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At least 181 records · Page 10

Cloud regimes over the Amazon Basin: perspectives from the GoAmazon2014/5 campaign

Abstract. Radiosonde observations collected during the GoAmazon2014/5 campaign are analyzed to identify the primary thermodynamic regimes accompanying different modes of convection over the Amazon. This analysis identifies five thermodynamic regimes that are consistent with traditional Amazon calendar definitions of seasonal shifts, which include one wet, one transitional, and three dry season regimes based on a k-means cluster analysis. A multisensor ground-based approach is used to project associated bulk cloud and precipitation properties onto these regimes. This is done to assess the propensity for each regime to be associated with different characteristic cloud frequency, cloud types, and precipitation properties. Additional emphasis is given to those regimes that promote deep convective precipitation and organized convective systems. Overall, we find reduced cloud cover and precipitation rates to be associated with the three dry regimes and those with the highest convective inhibition. While approximately 15 % of the dataset is designated as organized convection, these events are predominantly contained within the transitional regime.

54 ENVIRONMENTAL SCIENCES↗

Effect of scene illumination conditions on digital enhancement techniques of multispectral scanner LANDSAT images

Two sets of MSS/LANDSAT data with solar elevation ranging from 22 deg to 41 deg were used at the Image-100 System to implement the Eliason et alii technique for extracting the topographic modulation component. An unsupervised cluster analysis was used to obtain an average brightness image for each channel. Analysis of the enhanced imaged shows that the technique for extracting topographic modulation component is more appropriated to MSS data obtained under high sun elevation ngles. Low sun elevation increases the variance of each cluster so that the average brightness doesn't represent its albedo proprties. The topographic modulation component applied to low sun elevation angle damages rather than enhance topographic information. Better results were produced for channels 4 and 5 than for channels 6 and 7.

Parada, N. D. J.↗

Possible identification of a cluster of galaxies at redshift z = 3.4

We report the possible detection of a cluster of 16 radio-quiet galaxies at z = 3.4, identified in the field around the optically thick absorption system toward Q0000-263 at z(sub abs) = 3.390. Two of them, a Lyman alpha emitter at z = 3.428 and the galaxy responsible for the absorption system, have redshifts spectroscopically confirmed. The other 14 galaxies identified using a multicolor imaging technique designed to detect sources in the redshift interval 3 approximately less than z approximately less than 3.5 which are characterized by a Lyman discontinuity in an otherwise flat spectrum, have broad-band spectral energy distributions identical to the two galaxies with known redshift. They are spatially distributed in two apparent clumps, around the damped absorber and the Lyman alpha galaxy, respectively. A clustering analysis excludes with 98.8% confidence that this association is a realization of a Poissonian distribution and confirms that the observed clumps are real. The implications are that the 16 galaxies are members of a cluster at z approximately equals 3.4, by far the most distant ever detected. An estimate of the mass bounded in stars of this cluster is 3 x 10(exp 12) solar mass (q(sub 0) = 0 and H(sub 0) = 50 km/s/Mpc throughout this Letter), while the total mass (baryonic + dark) is 6 x 10(exp 14) solar mass. We also estimate that at z = 3.4 the correlation length is 2.2 Mpc, which, compared to the present value of 11 Mpc, suggests that the clustering evolution is still close to the linear regime.

Giavalisco, Mauro↗

Nasa Space Flight Instruments: Cost Time Trends

Are NASA’s space flight instruments becoming cheaper or more expensive as time marches forward? After analyzing the costs of hundreds of instruments launched over the last 30 years, the short answer to this question is no… and yes. This paper gives a visual analysis of the cost time trends for various NASA space flight instrument types, such as optical, particles detectors, fields detectors and microwave instruments. In addition to the statistical approaches utilized, such as significance tests, cluster analysis and principle components analysis (PCA), we will also discuss the intangibles which are likely at play, including technological progress, NASA policy and the luck of the draw associated with mission manifests. This analysis was performed as the main driver for the NASA Instrument Cost Model (NICM) recent cost estimating model redesign. Started in 2004, the first version of NICM was based off of instruments launched from 1985-2005, or 20 years’ worth of data. As NICM hit its 10-year anniversary, we wanted to know: should NICM continue to only use the most recent 20 years’ worth of data (1995-2015)? Are instruments becoming cheaper or more expensive as time marches forward? There is evidence in favor of a drop in the median dollar-per-kg value across some instrument types, but little in others. Whereas further research is needed to substantiate, Particles and Optical-Planetary instrument types show moderate to strong evidence of a downward trend in dollar-per-kg. Further research is required to study the nature of this trend (shift, taper, cyclic, etc.). Little evidence for a similar downward trend was detected for Fields or Microwave instruments, or Optical instruments on Earth Orbiting spacecraft. We presented evidence in favor of a drop in the median dollar-per-kg value for Particles and Optical-Planetary instrument types. While similar evidence was weak at best for Fields and Microwave instruments. We can speculate as to the causes for this effect, but we are also equipped to begin to rule out, or at least prioritize, some of the suspected drivers. We observed, for Particles and Optical-Planetary instruments, that perhaps a launch manifest effect was playing part of the role in the observed decrease in dollar-per-kg over the years, noting that the more flagship class missions, which have more money to spend on their instruments, were seen in the earlier years in our data, versus the later years which were dominated by less expensive class missions. However, if this were a dominating driver, would we not have seen the downward trend in the Fields and Microwave instruments as well, which were drawn from that same launch manifest? The fact that we did not observe this helps us rule out the launch manifest effect, and other drivers, such as advances in technology, that seem to be more likely suspects. In that case, however, why would technology advances be helping the Particles and Optical-Planetary instruments only? Why would it not be impacting Optical-Earth Orbiting instruments? Further suspects were looked at as well and ruled out, such as the “Faster, Better, Cheaper”era of NASA development which did not seem to actually impact trends by instrument type on a dollar-perkg scale. VI. Future Work A. Time Series Detailed Statistical Assessment The analysis discussed above sets the foundation for a more rigorous time series analysis of the data. Time series analysis will further explore evidence to-date of time trends for the instrument types which showed the strongest indicators for a decrease in dollar-per-kg: Optical (Planetary) and Particles instruments. More than providing evidence and top-level significance tests, time series analysis would help elucidate what kind of trend that exists in the data, their significance and allow statistically based forecasting (see Figure 10)

Mrozinksi, Joseph↗

The environmental dependence of the stellar mass of active galactic nucleus host galaxies and dependence of the clustering properties of active galactic nucleus host galaxies on the stellar mass

Abstract We used two volume‐limited active galactic nucleus (AGN) host galaxy samples constructed by Deng & Wen (2020, RMxAA , 56, 87), and explored the environmental dependence of the stellar mass of AGN host galaxies. In the luminous volume‐limited AGN host galaxy sample, the stellar mass of AGN host galaxies apparently depends on local environments: high mass AGN host galaxies exist preferentially in the dense regions of the universe, while low mass AGN host galaxies are located preferentially in low density regions. But in the faint volume‐limited AGN host galaxy sample, this dependence is fairly weak. We also examined the dependence of the clustering properties of AGN host galaxies on the stellar mass by cluster analysis, and found that in the luminous volume‐limited AGN host galaxy sample, low mass AGN host galaxies preferentially form isolated galaxies, close pairs, and small groups, while high mass AGN host galaxies preferentially inhabit the dense groups and clusters. A substantial dependence of the clustering properties of AGN host galaxies on the stellar mass is also observed in the faint volume‐limited AGN host galaxy sample, which is inconsistent with the environmental dependence of the stellar mass of AGN host galaxies in the faint volume‐limited AGN host galaxy sample. This is likely due to the galaxy number of the faint volume‐limited AGN host galaxy sample being too small to ensure an ideal statistical analysis.

Deng, Xin‐Fa↗

Feasibility Analyses for the Microgrid of the Mountain in the Cordillera Central Region of Puerto Rico

Distributed energy resource (DER) development can benefit communities through improvement of access to reliable electricity and a resilient energy system. Many place-specific considerations must be accounted for when designing electrical systems with co-located generation and loads. This paper presents an overview of four studies focusing on different aspects for regional DER development in the Cordillera Central region of Puerto Rico, including a grid and load stability study with the introduction of solar energy generation, microgrid design based on the solar resource in the area, resilience considerations during power outage scenarios, and qualitative risk aspects for components in the microgrid. Additionally, a conceptual substation microgrid analysis is conducted using the Microgrid Design Toolkit (MDT) to evaluate trade-offs between cost and energy availability, providing insights into optimal design strategies. A microgrid resilience assessment is performed using the Resilient Nodal Cluster Analysis Tool (ReNCAT) to identify critical loads and evaluates their accessibility during outages, emphasizing the importance of community needs. Finally, a qualitative risk assessment utilizing Hazard and Operability Analysis (HAZOP) methods highlights potential hazards and mitigations for microgrid components, ensuring robust system design and operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mimas: Preliminary Evidence For Amorphous Water Ice from VIMS

We have conducted a statistical clustering analysis (1,2) on a mosaic of VIMS data cubes obtained on February 13, 2010, for Saturn s satellite Mimas. Seven VIMS cubes were geometrically projected and re-sampled to a common spatial resolution. The clustering technique consists of a partitioning algorithm coupled to a criterion that prevents sub-optimal solutions and tests for the influence of random noise in the measurements. The clustering technique is agnostic about the meaning of the clusters, and scientific interpretation requires their a posteriori evaluation. The preliminary results yielded five clusters, demonstrating that spectral variability across Mimas surface is statistically significant. The ratios of the means calculated for each of the clusters show structure within the 1.6- micron water ice band, as well as the shape and the central wavelength of the strong ice band at 2 micron, that map spatially in patterns apparently related to the topography of Mimas, in particular certain regions in and around Herschel crater. The mean spectra of the five clusters, show similarities with laboratory spectra of amorphous and crystalline H2O ice (3) that are suggestive of the presence of an amorphous ice component in certain regions of Mimas, notably on the central peak of Herschel, on the crater floor, and in faults surrounding the crater. This may represent a mixture of both ice phases, or perhaps a layer of amorphous ice on a base of crystalline ice. Another possible occurrence of amorphous ice appears southwest of Herschel, close to the south pole.

Cruikshank, Dale P.↗

Relating Molecular Properties to the Persistence of Marine Dissolved Organic Matter with Liquid Chromatography–Ultrahigh-Resolution Mass Spectrometry

Marine dissolved organic matter (DOM) contains a complex mixture of small molecules that eludes rapid biological degradation. Spatial and temporal variations in the abundance of DOM reflect the existence of fractions that are removed from the ocean over different time scales, ranging from seconds to millennia. However, it remains unknown whether the intrinsic chemical properties of these organic components relate to their persistence. Here, we elucidate and compare the molecular compositions of distinct DOM fractions with different lability along a water column in the North Atlantic Gyre. Our analysis utilized ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry at 21 T coupled to liquid chromatography and a novel data pipeline developed in CoreMS that generates molecular formula assignments and metrics of isomeric complexity. Clustering analysis binned 14 857 distinct molecular components into groups that correspond to the depth distribution of semilabile, semirefractory, and refractory fractions of DOM. The more labile fractions were concentrated near the ocean surface and contained more aliphatic, hydrophobic, and reduced molecules than the refractory fraction, which occurred uniformly throughout the water column. These findings suggest that processes that selectively remove hydrophobic compounds, such as aggregation and particle sorption, contribute to variable removal rates of marine DOM.

54 ENVIRONMENTAL SCIENCES↗

Analysis of xylem formation in pine by cDNA sequencing

Secondary xylem (wood) formation is likely to involve some genes expressed rarely or not at all in herbaceous plants. Moreover, environmental and developmental stimuli influence secondary xylem differentiation, producing morphological and chemical changes in wood. To increase our understanding of xylem formation, and to provide material for comparative analysis of gymnosperm and angiosperm sequences, ESTs were obtained from immature xylem of loblolly pine (Pinus taeda L.). A total of 1,097 single-pass sequences were obtained from 5' ends of cDNAs made from gravistimulated tissue from bent trees. Cluster analysis detected 107 groups of similar sequences, ranging in size from 2 to 20 sequences. A total of 361 sequences fell into these groups, whereas 736 sequences were unique. About 55% of the pine EST sequences show similarity to previously described sequences in public databases. About 10% of the recognized genes encode factors involved in cell wall formation. Sequences similar to cell wall proteins, most known lignin biosynthetic enzymes, and several enzymes of carbohydrate metabolism were found. A number of putative regulatory proteins also are represented. Expression patterns of several of these genes were studied in various tissues and organs of pine. Sequencing novel genes expressed during xylem formation will provide a powerful means of identifying mechanisms controlling this important differentiation pathway.

Non-NASA Center↗

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom probe tomography (APT) has enabled the direct visualization of solute clusters, providing valuable insights into material structures. This clustering is crucial for understanding the nanoscale composition and behavior of materials, which can significantly influence their mechanical and physical properties. However, the widely used clustering methods in the APT community face challenges such as subjective parametric selection and limited applicability, particularly in dealing with overlapping clusters, nested clusters, and artifacts across different scales, such as precipitates and dislocations. To address these challenges, we present a framework based on density-based cluster analysis that aims to be less dependent on user input, reproducible, and robust.

Density-based clustering↗

Adaptive on-line classification of multi-spectral scanner data

A possible solution to the analysis of the massive amounts of multi-spectral scanner data from the Earth Resource Technical Satellite (ERTS) program is proposed. This solution is offered as an adaptive on-line classification scheme. The classifier is described as well as its controller which is based on ground truth data. Cluster analysis is presented as an alternative approach to the ground truth data. Adaptive feature selection is discussed and possible mini-computer implementations are offered.

Fromm, F. R.↗

An Assessment of Non-Powered Dam Hydropower Development Opportunities in the United States

Retrofitting non-powered dams (NPDs) to add hydropower offers multiple benefits over traditional, new hydropower development. Since much of the civil works infrastructure already exists, many retrofits require minimal new construction and can leverage existing water conveyances and discharge for generation. Although NPDs vary considerably in terms of their defining characteristics, identifying similarities helps support targeted investment and find opportunities to develop solutions for common challenges. With the publication of NPD-related data in 2022 (Hansen et al. 2022b), the US Department of Energy and relevant stakeholders are equipped with key information across roughly 89,000 US NPDs. These data represent the best-available information to date and extend beyond previous assessments of potential power capacity by describing design, operational, socioeconomic, environmental aspects of NPDs (Hadjerioua et al. 2012). To capitalize on these efforts to improve breadth and depth of NPD data access, this study uses a data-driven approach to assess NPD hydropower development opportunities in the United States. To help describe project feasibility drivers for NPDs, recent NPD retrofits were reviewed to examine variability with respect to a variety of characteristics. Based on the assessment of recent retrofits and data availability, several attributes were selected to characterize the remaining NPD population: (1) owner type, (2) 30% exceedance flow (a common design flow that describes the flow that is exceeded by 30% of the flow in the record), (3) hydraulic head, and (4) maximum reservoir storage. These four characteristics were used as inputs to a statistical clustering analysis (a common technique for grouping individuals of a population based on similarities or how closely associated individuals are to one another) of a set of 2,709 NPDs with at least 100 kW potential capacity and recently retrofit dams with available data. With the large dataset of NPDs, the clusters help describe how the population breaks down into different types (i.e., how many types of dams there are and what portion of the population belongs to each cluster).

13 HYDRO ENERGY↗

Latest NASA Instrument Cost Model (NICM): Version VI

The NASA Instrument Cost Model, NICM, is a suite of tools which allow for probabilistic cost estimation of NASA's space-flight instruments at both the system and subsystem level. NICM also includes the ability to perform cost by analogy as well as joint confidence level (JCL) analysis. The latest version of NICM, Version VI, was released in Spring 2014. This paper will focus on the new features released with NICM VI, which include: 1) The NICM-E cost estimating relationship, which is applicable for instruments flying on Explorer-like class missions; 2) The new cluster analysis ability which, alongside the results of the parametric cost estimation for the user's instrument, also provides a visualization of the user's instrument's similarity to previously flown instruments; and 3) includes new cost estimating relationships for in-situ instruments.

Mrozinski, Joe↗

Supporting data for climatic clustering and longitudinal analysis with impacts on food, bioenergy, and pandemics

This data supports the conclusions found in climatic clustering and longitudinal analysis with impacts on food, bioenergy, and pandemics. Included here are (i) the binarized geolocation vectors used for exhaustive vector comparisons, (ii) the resulting climatic networks, (iii) the results of applying Markov clustering to the climatic networks, and (iv) the results of applying Correlation-of-Correlations (cor-cor) to the climatic networks. The set of binarized geolocation vectors that are used as inputs for the Combinatorial Metrics library (CoMet) are of the form comet-UUUUUxVVVVV-XXXX-YYYY.shuffled.tped where UUUUU is the number of vectors, VVVVV is the length of each vector, XXXX is the starting year, and YYYY is the ending year. Each line corresponds to a geolocation vector of binary elements A (i.e., 0) and T (i.e., 1). The set of climatic networks that are used for downstream network analysis are of the form network-U-way-XXXX-YYYY.parsed.txt where U is the order of the comparison (2-way or 3-way), XXXX is the starting year, and YYYY is the ending year. Each line corresponds to an edge linking two geolocations (defined by latitude and longitude) with its corresponding edge weight (i.e., DUO score). The set of cluster results are of the form clusters-U-way-XXXX-YYYY-thresh-VVVV-inflation-WWW.clustered.txt where U is the order of the comparison (2-way or 3-way), XXXX is the starting year, YYYY is the ending year, VVVV is the similarity threshold, and WWW is the Markov clustering inflation rate. Each line corresponds to a single cluster and is composed of a number of corresponding geolocations (defined by latitude and longitude). The set of cor-cor results are of the form corcor-U-way-XXXX-YYYY.cumulative.txt where U is the order of the comparison (2-way or 3-way), XXXX is the starting year, and YYYY is the ending year. Each line corresponds to a single geolocation with it's corresponding cor-cor value.

54 ENVIRONMENTAL SCIENCES↗

Making the most of missing values : object clustering with partial data in astronomy

We demonstrate a clustering analysis algorithm, KSC, that a) uses all observed values and b) does not discard the partially observed objects. KSC uses soft constraints defined by the fully observed objects to assist in the grouping of objects with missing values. We present an analysis of objects taken from the Sloan Digital Sky Survey to demonstrate how imputing the values can be misleading and why the KSC approach can produce more appropriate results.

clustering↗

The optimization of model ensemble composition and size can enhance the robustness of crop yield projections

Linked climate and crop simulation models are widely used to assess the impact of climate change on agriculture. However, it is unclear how ensemble configurations (model composition and size) influence crop yield projections and uncertainty. Here, we investigate the influences of ensemble configurations on crop yield projections and modeling uncertainty from Global Gridded Crop Models and Global Climate Models under future climate change. We performed a cluster analysis to identify distinct groups of ensemble members based on their projected outcomes, revealing unique patterns in crop yield projections and corresponding uncertainty levels, particularly for wheat and soybean. Furthermore, our findings suggest that approximately six Global Gridded Crop Models and 10 Global Climate Models are sufficient to capture modeling uncertainty, while a cluster-based selection of 3-4 Global Gridded Crop Models effectively represents the full ensemble. The contribution of individual Global Gridded Crop Models to overall uncertainty varies depending on region and crop type, emphasizing the importance of considering the impact of specific models when selecting models for local-scale applications. Our results emphasize the importance of model composition and ensemble size in identifying the primary sources of uncertainty in crop yield projections, offering valuable guidance for optimizing ensemble configurations in climate-crop modeling studies tailored to specific applications.

Agriculture↗

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Steyaert, Lou↗

The Cocytos Stream: A Disrupted Globular Cluster from our Last Major Merger?

The census of stellar streams and dwarf galaxies in the Milky Way provides direct constraints on galaxy formation models and the nature of dark matter. The DESI Milky Way survey (with a footprint of 14,000$~deg{^2}$ and a depth of $r<19$ mag) delivers the largest sample of distant metal-poor stars compared to previous optical fiber-fed spectroscopic surveys. This makes DESI an ideal survey to search for previously undetected streams and dwarf galaxies. We present a detailed characterization of the Cocytos stream, which was re-discovered using a clustering analysis with a catalog of giants in the DESI year 3 data, supplemented with Magellan/MagE spectroscopy. Our analysis reveals a relatively metal-rich ([Fe/H]$=-1.3$) and thick stream (width$=1.5^\circ$) at a heliocentric distance of $\approx 25$ kpc, with an internal velocity dispersion of 6.5-9 km s$^{-1}$. The stream's metallicity, radial orbit, and proximity to the Virgo stellar overdensities suggest that it is most likely a disrupted globular cluster that came in with the Gaia-Enceladus merger. We also confirm its association with the Pyxis globular cluster. Our result showcases the ability of wide-field spectroscopic surveys to kinematically discover faint disrupted dwarfs and clusters, enabling constraints on the dark matter distribution in the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗