Attribution of regional flood changes based on scaling fingerprints

PubMed Central

Merz, Bruno; Viet Dung, Nguyen; Parajka, Juraj; Nester, Thomas; Blöschl, Günter

2016-01-01

Abstract Changes in the river flood regime may be due to atmospheric processes (e.g., increasing precipitation), catchment processes (e.g., soil compaction associated with land use change), and river system processes (e.g., loss of retention volume in the floodplains). This paper proposes a new framework for attributing flood changes to these drivers based on a regional analysis. We exploit the scaling characteristics (i.e., fingerprints) with catchment area of the effects of the drivers on flood changes. The estimation of their relative contributions is framed in Bayesian terms. Analysis of a synthetic, controlled case suggests that the accuracy of the regional attribution increases with increasing number of sites and record lengths, decreases with increasing regional heterogeneity, increases with increasing difference of the scaling fingerprints, and decreases with an increase of their prior uncertainty. The applicability of the framework is illustrated for a case study set in Austria, where positive flood trends have been observed at many sites in the past decades. The individual scaling fingerprints related to the atmospheric, catchment, and river system processes are estimated from rainfall data and simple hydrological modeling. Although the distributions of the contributions are rather wide, the attribution identifies precipitation change as the main driver of flood change in the study region. Overall, it is suggested that the extension from local attribution to a regional framework, including multiple drivers and explicit estimation of uncertainty, could constitute a similar shift in flood change attribution as the extension from local to regional flood frequency analysis. PMID:27609996

Topographic controls on the regional-scale biodiversity of the south-western USA

Treesearch

David D. Coblentz; Kurt H. Riitters

2004-01-01

Aim Topography is a fundamental geophysical observable that contains valuable information about the geodynamic, tectonic and climatic history of a region. Here, we extend the traditional uses of topographic analysis to evaluate the role played by topography in the distribution of regional-scale biodiversity in the south-western USA. An important aspect of our study is...

Analysis of regional-scale vegetation dynamics of Mexico using stratified AVHRR NDVI data. [Normalized Difference Vegetaion Index

NASA Technical Reports Server (NTRS)

Turcotte, Kevin M.; Kramber, William J.; Venugopal, Gopalan; Lulla, Kamlesh

1989-01-01

Previous studies have shown that a good relationship exists between AVHRR Normalized Difference Vegetation Index (NDVI) measurements, and both regional-scale patterns of vegetation seasonality and productivity. Most of these studies used known samples of vegetation types. An alternative approach, and the objective was to examine the above relationships by analyzing one year of AVHRR NDVI data that was stratified using a small-scale vegetation map of Mexico. The results show that there is a good relationship between AVHRR NDVI measurements and regional-scale vegetation dynamics of Mexico.

Regional Scale Meteorological Analysis and Prediction Using GPS Occultation and EOS Data

NASA Technical Reports Server (NTRS)

Bromwich, David H.; Shum, C. K.; Zhao, Changyin; Kuo, Bill; Rocken, Chris

2004-01-01

The main objective of the research under this award is to improve regional meteorological analysis and prediction for traditionally data limited regions, particularly over the Southern Ocean and Antarctica, using the remote sensing observations from current and upcoming GPS radio occultation missions and the EOS instrument suite. The major components of this project are: 1.Develop and improve the methods for retrieving temperature, moisture, and pressure profiles from GPS radio occultation data and EOS radiometer data. 2. Develop and improve a regional scale data assimilation system (MM5 4DVAR). 3. Perform case studies involving data analysis and numerical modeling to investigate the impact of different data for regional meteorological analysis and the importance of data assimilation for regional meteorological simulation over the Antarctic region. 4. Apply the findings and improvements from the above studies to weather forecasting experiments. 5. In the third year of the award we made significant progress toward the remaining goals of the project. The work included carefully evaluating the performance of an atmospheric mesoscale model, the Polar MM5 in Antarctic applications and improving the upper boundary condition.

Validation of the ANOCOVA model for regional scale ECa-ECe calibration

USDA-ARS?s Scientific Manuscript database

Over the past decade two approaches have emerged as the preferred means for assessing salinity at regional scale: (1) vegetative indices from satellite imagery (e.g., MODIS enhanced vegetative index, NDVI, etc.) and (2) analysis of covariance (ANOCOVA) calibration of apparent soil electrical conduct...

Investigating the Nexus of Climate, Energy, Water, and Land at Decision-Relevant Scales: The Platform for Regional Integrated Modeling and Analysis (PRIMA)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kraucunas, Ian P.; Clarke, Leon E.; Dirks, James A.

2015-04-01

The Platform for Regional Integrated Modeling and Analysis (PRIMA) is an innovative modeling system developed at Pacific Northwest National Laboratory (PNNL) to simulate interactions among natural and human systems at scales relevant to regional decision making. PRIMA brings together state-of-the-art models of regional climate, hydrology, agriculture, socioeconomics, and energy systems using a flexible coupling approach. The platform can be customized to inform a variety of complex questions and decisions, such as the integrated evaluation of mitigation and adaptation options across a range of sectors. Research into stakeholder decision support needs underpins the platform's application to regional issues, including uncertainty characterization.more » Ongoing numerical experiments are yielding new insights into the interactions among human and natural systems on regional scales with an initial focus on the energy-land-water nexus in the upper U.S. Midwest. This paper focuses on PRIMA’s functional capabilities and describes some lessons learned to date about integrated regional modeling.« less

Wavelet analysis applied to the IRAS cirrus

NASA Technical Reports Server (NTRS)

Langer, William D.; Wilson, Robert W.; Anderson, Charles H.

1994-01-01

The structure of infrared cirrus clouds is analyzed with Laplacian pyramid transforms, a form of non-orthogonal wavelets. Pyramid and wavelet transforms provide a means to decompose images into their spatial frequency components such that all spatial scales are treated in an equivalent manner. The multiscale transform analysis is applied to IRAS 100 micrometer maps of cirrus emission in the north Galactic pole region to extract features on different scales. In the maps we identify filaments, fragments and clumps by separating all connected regions. These structures are analyzed with respect to their Hausdorff dimension for evidence of the scaling relationships in the cirrus clouds.

Geographical Scale Effects on the Analysis of Leptospirosis Determinants

PubMed Central

Gracie, Renata; Barcellos, Christovam; Magalhães, Mônica; Souza-Santos, Reinaldo; Barrocas, Paulo Rubens Guimarães

2014-01-01

Leptospirosis displays a great diversity of routes of exposure, reservoirs, etiologic agents, and clinical symptoms. It occurs almost worldwide but its pattern of transmission varies depending where it happens. Climate change may increase the number of cases, especially in developing countries, like Brazil. Spatial analysis studies of leptospirosis have highlighted the importance of socioeconomic and environmental context. Hence, the choice of the geographical scale and unit of analysis used in the studies is pivotal, because it restricts the indicators available for the analysis and may bias the results. In this study, we evaluated which environmental and socioeconomic factors, typically used to characterize the risks of leptospirosis transmission, are more relevant at different geographical scales (i.e., regional, municipal, and local). Geographic Information Systems were used for data analysis. Correlations between leptospirosis incidence and several socioeconomic and environmental indicators were calculated at different geographical scales. At the regional scale, the strongest correlations were observed between leptospirosis incidence and the amount of people living in slums, or the percent of the area densely urbanized. At the municipal scale, there were no significant correlations. At the local level, the percent of the area prone to flooding best correlated with leptospirosis incidence. PMID:25310536

a Region-Based Multi-Scale Approach for Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.

2016-06-01

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

Cross-Scale Analysis of the Region Effect on Vascular Plant Species Diversity in Southern and Northern European Mountain Ranges

PubMed Central

Lenoir, Jonathan; Gégout, Jean-Claude; Guisan, Antoine; Vittoz, Pascal; Wohlgemuth, Thomas; Zimmermann, Niklaus E.; Dullinger, Stefan; Pauli, Harald; Willner, Wolfgang; Grytnes, John-Arvid; Virtanen, Risto; Svenning, Jens-Christian

2010-01-01

Background The divergent glacial histories of southern and northern Europe affect present-day species diversity at coarse-grained scales in these two regions, but do these effects also penetrate to the more fine-grained scales of local communities? Methodology/Principal Findings We carried out a cross-scale analysis to address this question for vascular plants in two mountain regions, the Alps in southern Europe and the Scandes in northern Europe, using environmentally paired vegetation plots in the two regions (n = 403 in each region) to quantify four diversity components: (i) total number of species occurring in a region (total γ-diversity), (ii) number of species that could occur in a target plot after environmental filtering (habitat-specific γ-diversity), (iii) pair-wise species compositional turnover between plots (plot-to-plot β-diversity) and (iv) number of species present per plot (plot α-diversity). We found strong region effects on total γ-diversity, habitat-specific γ-diversity and plot-to-plot β-diversity, with a greater diversity in the Alps even towards distances smaller than 50 m between plots. In contrast, there was a slightly greater plot α-diversity in the Scandes, but with a tendency towards contrasting region effects on high and low soil-acidity plots. Conclusions/Significance We conclude that there are strong regional differences between coarse-grained (landscape- to regional-scale) diversity components of the flora in the Alps and the Scandes mountain ranges, but that these differences do not necessarily penetrate to the finest-grained (plot-scale) diversity component, at least not on acidic soils. Our findings are consistent with the contrasting regional Quaternary histories, but we also consider alternative explanatory models. Notably, ecological sorting and habitat connectivity may play a role in the unexpected limited or reversed region effect on plot α-diversity, and may also affect the larger-scale diversity components. For instance, plot connectivity and/or selection for high dispersal ability may increase plot α-diversity and compensate for low total γ-diversity. PMID:21203521

Regional climates in the GISS global circulation model - Synoptic-scale circulation

NASA Technical Reports Server (NTRS)

Hewitson, B.; Crane, R. G.

1992-01-01

A major weakness of current general circulation models (GCMs) is their perceived inability to predict reliably the regional consequences of a global-scale change, and it is these regional-scale predictions that are necessary for studies of human-environmental response. For large areas of the extratropics, the local climate is controlled by the synoptic-scale atmospheric circulation, and it is the purpose of this paper to evaluate the synoptic-scale circulation of the Goddard Institute for Space Studies (GISS) GCM. A methodology for validating the daily synoptic circulation using Principal Component Analysis is described, and the methodology is then applied to the GCM simulation of sea level pressure over the continental United States (excluding Alaska). The analysis demonstrates that the GISS 4 x 5 deg GCM Model II effectively simulates the synoptic-scale atmospheric circulation over the United States. The modes of variance describing the atmospheric circulation of the model are comparable to those found in the observed data, and these modes explain similar amounts of variance in their respective datasets. The temporal behavior of these circulation modes in the synoptic time frame are also comparable.

Survival analysis for a large scale forest health issue: Missouri oak decline

Treesearch

C.W. Woodall; P.L. Grambsch; W. Thomas; W.K. Moser

2005-01-01

Survival analysis methodologies provide novel approaches for forest mortality analysis that may aid in detecting, monitoring, and mitigating of large-scale forest health issues. This study examined survivor analysis for evaluating a regional forest health issue - Missouri oak decline. With a statewide Missouri forest inventory, log-rank tests of the effects of...

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

U.S. Regional Aquifer Analysis Program

NASA Astrophysics Data System (ADS)

Johnson, Ivan

As a result of the severe 1976-1978 drought, Congress in 1978 requested that the U.S. Geological Survey (USGS) initiate studies of the nation's aquifers on a regional scale. This continuing USGS project, the Regional Aquifer System Analysis (RASA) Program, consists of systematic studies of the quality and quantity of water in the regional groundwater systems that supply a large part of the nation's water.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-04-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-06-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

NASA Technical Reports Server (NTRS)

Shen, Suhung; Kempler, Steven J.; Gerasimov, Irina V.

2013-01-01

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

PubMed Central

Scottá, Fernando C.; da Fonseca, Eliana L.

2015-01-01

This study aimed to evaluate changes in the aboveground net primary productivity (ANPP) of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration) were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing. PMID:26197320

Spontaneous alterations of regional brain activity in patients with adult generalized anxiety disorder

PubMed Central

Xia, Likun; Li, Shumei; Wang, Tianyue; Guo, Yaping; Meng, Lihong; Feng, Yunping; Cui, Yu; Wang, Fan; Ma, Jian; Jiang, Guihua

2017-01-01

Objective We aimed to examine how spontaneous brain activity might be related to the pathophysiology of generalized anxiety disorder (GAD). Patients and methods Using resting-state functional MRI, we examined spontaneous regional brain activity in 31 GAD patients (mean age, 36.87±9.16 years) and 36 healthy control participants (mean age, 39.53±8.83 years) matched for age, education, and sex from December 2014 to October 2015. We performed a two-sample t-test on the voxel-based analysis of the regional homogeneity (ReHo) maps. We used Pearson correlation analysis to compare scores from the Hamilton Anxiety Rating Scale, Hamilton Depression Rating Scale, State–Trait Anxiety Scale-Trait Scale, and mean ReHo values. Results We found abnormal spontaneous activity in multiple regions of brain in GAD patients, especially in the sensorimotor cortex and emotional regions. GAD patients showed decreased ReHo values in the right orbital middle frontal gyrus, left anterior cingulate cortex, right middle frontal gyrus, and bilateral supplementary motor areas, with increased ReHo values in the left middle temporal gyrus, left superior temporal gyrus, and right superior occipital gyrus. The ReHo value of the left middle temporal gyrus correlated positively with the Hamilton Anxiety Rating Scale scores. Conclusion These results suggest that altered local synchronization of spontaneous brain activity may be related to the pathophysiology of GAD. PMID:28790831

Evolutionary conservation of the polyproline II conformation surrounding intrinsically disordered phosphorylation sites.

PubMed

Elam, W Austin; Schrank, Travis P; Campagnolo, Andrew J; Hilser, Vincent J

2013-04-01

Intrinsically disordered (ID) proteins function in the absence of a unique stable structure and appear to challenge the classic structure-function paradigm. The extent to which ID proteins take advantage of subtle conformational biases to perform functions, and whether signals for such mechanism can be identified in proteome-wide studies is not well understood. Of particular interest is the polyproline II (PII) conformation, suggested to be highly populated in unfolded proteins. We experimentally determine a complete calorimetric propensity scale for the PII conformation. Projection of the scale into representative eukaryotic proteomes reveals significant PII bias in regions coding for ID proteins. Importantly, enrichment of PII in ID proteins, or protein segments, is also captured by other PII scales, indicating that this enrichment is robustly encoded and universally detectable regardless of the method of PII propensity determination. Gene ontology (GO) terms obtained using our PII scale and other scales demonstrate a consensus for molecular functions performed by high PII proteins across the proteome. Perhaps the most striking result of the GO analysis is conserved enrichment (P < 10(-8) ) of phosphorylation sites in high PII regions found by all PII scales. Subsequent conformational analysis reveals a phosphorylation-dependent modulation of PII, suggestive of a conserved "tunability" within these regions. In summary, the application of an experimentally determined polyproline II (PII) propensity scale to proteome-wide sequence analysis and gene ontology reveals an enrichment of PII bias near disordered phosphorylation sites that is conserved throughout eukaryotes. Copyright © 2013 The Protein Society.

The pyramid system for multiscale raster analysis

USGS Publications Warehouse

De Cola, L.; Montagne, N.

1993-01-01

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

Attribution of regional flood changes based on scaling fingerprints

NASA Astrophysics Data System (ADS)

Viglione, A.; Merz, B.; Dung, N.; Parajka, J.; Nester, T.; Bloeschl, G.

2017-12-01

Changes in the river flood regime may be due to atmospheric processes (e.g., increasing precipitation), catchment processes (e.g., soil compaction associated with land use change), and river system processes (e.g., loss of retention volume in the floodplains). We propose a framework for attributing flood changes to these drivers based on a regional analysis. We exploit the scaling characteristics (i.e., fingerprints) with catchment area of the effects of the drivers on flood changes. The estimation of their relative contributions is framed in Bayesian terms. Analysis of a synthetic, controlled case suggests that the accuracy of the regional attribution increases with increasing number of sites and record lengths, decreases with increasing regional heterogeneity, increases with increasing difference of the scaling fingerprints, and decreases with an increase of their prior uncertainty. The applicability of the framework is illustrated for a case study set in Austria, where positive flood trends have been observed at many sites in the past decades. The individual scaling fingerprints related to the atmospheric, catchment, and river system processes are estimated from rainfall data and simple hydrological modeling. Although the distributions of the contributions are rather wide, the attribution identifies precipitation change as the main driver of flood change in the study region.

Recent Regional Climate State and Change - Derived through Downscaling Homogeneous Large-scale Components of Re-analyses

NASA Astrophysics Data System (ADS)

Von Storch, H.; Klehmet, K.; Geyer, B.; Li, D.; Schubert-Frisius, M.; Tim, N.; Zorita, E.

2015-12-01

Global re-analyses suffer from inhomogeneities, as they process data from networks under development. However, the large-scale component of such re-analyses is mostly homogeneous; additional observational data add in most cases to a better description of regional details and less so on large-scale states. Therefore, the concept of downscaling may be applied to homogeneously complementing the large-scale state of the re-analyses with regional detail - wherever the condition of homogeneity of the large-scales is fulfilled. Technically this can be done by using a regional climate model, or a global climate model, which is constrained on the large scale by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional risks - in particular marine risks - was identified. While the data density in Europe is considerably better than in most other regions of the world, even here insufficient spatial and temporal coverage is limiting risk assessments. Therefore, downscaled data-sets are frequently used by off-shore industries. We have run this system also in regions with reduced or absent data coverage, such as the Lena catchment in Siberia, in the Yellow Sea/Bo Hai region in East Asia, in Namibia and the adjacent Atlantic Ocean. Also a global (large scale constrained) simulation has been. It turns out that spatially detailed reconstruction of the state and change of climate in the three to six decades is doable for any region of the world.The different data sets are archived and may freely by used for scientific purposes. Of course, before application, a careful analysis of the quality for the intended application is needed, as sometimes unexpected changes in the quality of the description of large-scale driving states prevail.

SIGN SINGULARITY AND FLARES IN SOLAR ACTIVE REGION NOAA 11158

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sorriso-Valvo, L.; De Vita, G.; Kazachenko, M. D.

Solar Active Region NOAA 11158 has hosted a number of strong flares, including one X2.2 event. The complexity of current density and current helicity are studied through cancellation analysis of their sign-singular measure, which features power-law scaling. Spectral analysis is also performed, revealing the presence of two separate scaling ranges with different spectral index. The time evolution of parameters is discussed. Sudden changes of the cancellation exponents at the time of large flares and the presence of correlation with Extreme-Ultra-Violet and X-ray flux suggest that eruption of large flares can be linked to the small-scale properties of the current structures.

Segmentation-based wavelet transform for still-image compression

NASA Astrophysics Data System (ADS)

Mozelle, Gerard; Seghier, Abdellatif; Preteux, Francoise J.

1996-10-01

In order to address simultaneously the two functionalities, content-based scalability required by MPEG-4, we introduce a segmentation-based wavelet transform (SBWT). SBWT takes into account both the mathematical properties of multiresolution analysis and the flexibility of region-based approaches for image compression. The associated methodology has two stages: 1) image segmentation into convex and polygonal regions; 2) 2D-wavelet transform of the signal corresponding to each region. In this paper, we have mathematically studied a method for constructing a multiresolution analysis (VjOmega)j (epsilon) N adapted to a polygonal region which provides an adaptive region-based filtering. The explicit construction of scaling functions, pre-wavelets and orthonormal wavelets bases defined on a polygon is carried out by using scaling functions is established by using the theory of Toeplitz operators. The corresponding expression can be interpreted as a location property which allow defining interior and boundary scaling functions. Concerning orthonormal wavelets and pre-wavelets, a similar expansion is obtained by taking advantage of the properties of the orthogonal projector P(V(j(Omega )) perpendicular from the space Vj(Omega ) + 1 onto the space (Vj(Omega )) perpendicular. Finally the mathematical results provide a simple and fast algorithm adapted to polygonal regions.

Projected changes to precipitation extremes over the Canadian Prairies using multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2016-12-01

Information on projected changes to precipitation extremes is needed for future planning of urban drainage infrastructure and storm water management systems and to sustain socio-economic activities and ecosystems at local, regional and other scales of interest. This study explores the projected changes to seasonal (April-October) precipitation extremes at daily, hourly and sub-hourly scales over the Canadian Prairie Provinces of Alberta, Saskatchewan, and Manitoba, based on the North American Regional Climate Change Assessment Program multi-Regional Climate Model (RCM) ensemble and regional frequency analysis. The performance of each RCM is evaluated regarding boundary and performance errors to study various sources of uncertainties and the impact of large-scale driving fields. In the absence of RCM-simulated short-duration extremes, a framework is developed to derive changes to extremes of these durations. Results from this research reveal that the relative changes in sub-hourly extremes are higher than those in the hourly and daily extremes. Overall, projected changes in precipitation extremes are larger for southeastern parts of this region than southern and northern areas, and smaller for southwestern and western parts of the study area. Keywords: climate change, precipitation extremes, regional frequency analysis, NARCCAP, Canadian Prairie provinces

Environmental analysis of groundwater in Mecosta County, Michigan.

PubMed

Steinman, Alan D; Biddanda, Bopi; Chu, Xuefeng; Thompson, Kurt; Rediske, Rick

2007-11-01

Groundwater withdrawal has major economic, social, and environmental implications. In Michigan, recent legislative activity has begun to address the issue of groundwater sustainability. However, more hydrologic data are needed to help inform policy and legislation. A study was conducted in Mecosta County, Michigan to: (1) determine if a relationship could be established between land use/land cover and groundwater quality; and (2) develop a conceptual model for the shallow groundwater system of the study region. In general, groundwater quality was good, with below detection levels of E. coli, low total bacterial counts, and relatively low nutrient concentrations. No statistically significant associations were found between the bacterial numbers and either land use or the physical/chemical attributes measured, which may be because the scale of our spatial analysis was too coarse to detect patterns. Finer-scale, localized processes may have a greater influence on microorganism growth and abundance than coarser-scale, regional processes in this area. Our groundwater analysis suggested that shallow groundwater flow paths are generally consistent with regional surface water flow networks, and that shallow groundwater levels in most of the region have fluctuated within 1-2 m over the past 30 years, with no obvious increasing or decreasing trend.

Large Scale Processes and Extreme Floods in Brazil

NASA Astrophysics Data System (ADS)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

Quantification of scaling exponent with Crossover type phenomena for different types of forcing in DC glow discharge plasma

NASA Astrophysics Data System (ADS)

Saha, Debajyoti; Shaw, Pankaj Kumar; Ghosh, Sabuj; Janaki, M. S.; Sekar Iyengar, A. N.

2018-01-01

We have carried out a detailed study of scaling region using detrended fractal analysis test by applying different forcing likewise noise, sinusoidal, square on the floating potential fluctuations acquired under different pressures in a DC glow discharge plasma. The transition in the dynamics is observed through recurrence plot techniques which is an efficient method to observe the critical regime transitions in dynamics. The complexity of the nonlinear fluctuation has been revealed with the help of recurrence quantification analysis which is a suitable tool for investigating recurrence, an ubiquitous feature providing a deep insight into the dynamics of real dynamical system. An informal test for stationarity which checks for the compatibility of nonlinear approximations to the dynamics made in different segments in a time series has been proposed. In case of sinusoidal, noise, square forcing applied on fluctuation acquired at P = 0.12 mbar only one dominant scaling region is observed whereas the forcing applied on fluctuation (P = 0.04 mbar) two prominent scaling regions have been explored reliably using different forcing amplitudes indicating the signature of crossover phenomena. Furthermore a persistence long range behavior has been observed in one of these scaling regions. A comprehensive study of the quantification of scaling exponents has been carried out with the increase in amplitude and frequency of sinusoidal, square type of forcings. The scalings exponent is envisaged to be the roughness of the time series. The method provides a single quantitative idea of the scaling exponent to quantify the correlation properties of a signal.

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

PubMed

Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

2018-09-01

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

SRM Internal Flow Tests and Computational Fluid Dynamic Analysis. Volume 2; CFD RSRM Full-Scale Analyses

NASA Technical Reports Server (NTRS)

2001-01-01

This document presents the full-scale analyses of the CFD RSRM. The RSRM model was developed with a 20 second burn time. The following are presented as part of the full-scale analyses: (1) RSRM embedded inclusion analysis; (2) RSRM igniter nozzle design analysis; (3) Nozzle Joint 4 erosion anomaly; (4) RSRM full motor port slag accumulation analysis; (5) RSRM motor analysis of two-phase flow in the aft segment/submerged nozzle region; (6) Completion of 3-D Analysis of the hot air nozzle manifold; (7) Bates Motor distributed combustion test case; and (8) Three Dimensional Polysulfide Bump Analysis.

Variation in the macrofaunal community over large temporal and spatial scales in the southern Yellow Sea

NASA Astrophysics Data System (ADS)

Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin

2017-09-01

To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables may be more responsible for the long-term changes in the macrofaunal community.

Agro-biodiversity has increased over a 95 year period at sub-regional and regional scales in southern Quebec, Canada

NASA Astrophysics Data System (ADS)

Renard, D.; Bennett, E. M.; Rhemtulla, J. M.

2016-12-01

Decline in agricultural biodiversity (cultivated species and wild species used for food or that support agro-ecosystem functioning) at the farm scale has fueled concerns about potential negative effects of this biodiversity loss on the ecological and economic sustainability of agro-ecosystems. Despite these concerns, formal assessment of how agro-biodiversity has historically changed at scales larger than individual farms is fragmented. We quantified the changes in the abundance of 10 crop and livestock species, their overall diversity, and the way they were mixed in ‘baskets’ of agricultural products from 1911 to 2006, at a sub-regional (15 Regional County Municipalities) and regional scales. We found that the diversity of agricultural products increased at the regional scale. From 1911 to 1966, the region produced fodder, milk and maple, mixed in two low-diversity baskets. After 1966, the region provided a greater variety of baskets composed of newly introduced cash crops and high-value livestock. All baskets provided were themselves more diverse than historically and varied greatly in composition across space. Increasing regional diversity was related to changes in agricultural policy, while the variation in the composition of baskets produced was related to biophysical and socioeconomic characteristics. Our results indicate that agricultural transformations of the 21th century did not invariably lead to agro-biodiversity loss at large scales. We have also demonstrated that combining diversity measures at multiple scales with the analysis of compositional change of agricultural products over long time periods could improve research on the links between agro-biodiversity dynamics and resilience.

The regionalization of national-scale SPARROW models for stream nutrients

USGS Publications Warehouse

Schwarz, Gregory E.; Alexander, Richard B.; Smith, Richard A.; Preston, Stephen D.

2011-01-01

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national-scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national-scale and regional-scale information to estimate a hybrid model that imposes cross-region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Intermediate scale plasma density irregularities in the polar ionosphere inferred from radio occultation

NASA Astrophysics Data System (ADS)

Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O. P.; Butala, M.; Mannucci, A. J.

2014-12-01

In this research, we report intermediate scale plasma density irregularities in the high-latitude ionosphere inferred from high-resolution radio occultation (RO) measurements in the CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) - GPS (Global Positioning System) satellites radio link. The high inclination of the CASSIOPE satellite and high rate of signal receptionby the occultation antenna of the GPS Attitude, Positioning and Profiling (GAP) instrument on the Enhanced Polar Outflow Probe platform on CASSIOPE enable a high temporal and spatial resolution investigation of the dynamics of the polar ionosphere, magnetosphere-ionospherecoupling, solar wind effects, etc. with unprecedented details compared to that possible in the past. We have carried out high spatial resolution analysis in altitude and geomagnetic latitude of scintillation-producing plasma density irregularities in the polar ionosphere. Intermediate scale, scintillation-producing plasma density irregularities, which corresponds to 2 to 40 km spatial scales were inferred by applying multi-scale spectral analysis on the RO phase delay measurements. Using our multi-scale spectral analysis approach and Polar Operational Environmental Satellites (POES) and Defense Meteorological Satellite Program (DMSP) observations, we infer that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap regions. In specific terms, we found that large length scales and and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap region. Hence, the irregularity scales and phase scintillation characteristics are a function of the solar wind and the magnetospheric forcing. Multi-scale analysis may become a powerful diagnostic tool for characterizing how the ionosphere is dynamically driven by these factors.

Analysis of the temporal-spatial distribution of ionosphere scale height based on COSMIC occultation data

NASA Astrophysics Data System (ADS)

Ma, Xin-Xin; Lin, Zhan; Jin, Hong-Lin; Chen, Hua-Ran; Jiao, Li-Guo

2017-11-01

In this study, the distribution characteristics of scale height at various solar activity levels were statistically analyzed using the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation data for 2007-2013. The results show that: (1) in the mid-high latitude region, the daytime (06-17LT) scale height exhibits annual variations in the form of a single peak structure with the crest appearing in summer. At the high latitude region, an annual variation is also observed for nighttime (18-05LT) scale height; (2) changes in the spatial distribution of the scale height occur. The crests are deflected towards the north during daytime (12-14LT) at a geomagnetic longitude of 60°W-180°W, and they are distributed roughly along the geomagnetic equator at 60°W-180°E. In the approximate region of 120°W-150°E and 50°S-80°S, the scale height values are significantly higher than those in other mid-latitude areas. This region enlarges with increased solar activity, and shows an approximately symmetric distribution about 0° geomagnetic longitude. Nighttime (00-02LT) scale height values in the high-latitude region are larger than those in the low-mid latitude region. These results could serve as reference for the study of ionosphere distribution and construction of the corresponding profile model.

An Automatic Method for Generating an Unbiased Intensity Normalizing Factor in Positron Emission Tomography Image Analysis After Stroke.

PubMed

Nie, Binbin; Liang, Shengxiang; Jiang, Xiaofeng; Duan, Shaofeng; Huang, Qi; Zhang, Tianhao; Li, Panlong; Liu, Hua; Shan, Baoci

2018-06-07

Positron emission tomography (PET) imaging of functional metabolism has been widely used to investigate functional recovery and to evaluate therapeutic efficacy after stroke. The voxel intensity of a PET image is the most important indicator of cellular activity, but is affected by other factors such as the basal metabolic ratio of each subject. In order to locate dysfunctional regions accurately, intensity normalization by a scale factor is a prerequisite in the data analysis, for which the global mean value is most widely used. However, this is unsuitable for stroke studies. Alternatively, a specified scale factor calculated from a reference region is also used, comprising neither hyper- nor hypo-metabolic voxels. But there is no such recognized reference region for stroke studies. Therefore, we proposed a totally data-driven automatic method for unbiased scale factor generation. This factor was generated iteratively until the residual deviation of two adjacent scale factors was reduced by < 5%. Moreover, both simulated and real stroke data were used for evaluation, and these suggested that our proposed unbiased scale factor has better sensitivity and accuracy for stroke studies.

Development of lichen response indexes using a regional gradient modeling approach for large-scale monitoring of forests

Treesearch

Susan Will-Wolf; Peter Neitlich

2010-01-01

Development of a regional lichen gradient model from community data is a powerful tool to derive lichen indexes of response to environmental factors for large-scale and long-term monitoring of forest ecosystems. The Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture Forest Service includes lichens in its national inventory of forests of...

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D.; Kiem, A. S.

2008-10-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Analysis of surface scale on the Ni-based superalloy CMSX-10N and proposed mechanism of formation

NASA Astrophysics Data System (ADS)

Simmonds, S.; D'Souza, N.; Ryder, K. S.; Dong, H.

2012-01-01

There is a continuing demand to raise the operating temperature of jet engine turbine blades to meet the need for higher turbine entry temperatures (TET) in order to increase thermal efficiency and thrust. Modern, high-pressure turbine blades are made from Ni-based superalloys in single-crystal form via the investment casting process. One important post-cast surface defect, known as 'surface scale', has been investigated on the alloy CMSX-10N. This is an area of distinct discolouration of the aerofoil seen after casting. Auger electron and X-ray photoelectron spectroscopy analysis were carried out on both scaled and un-scaled areas. In the scaled region, a thin layer (~800nm) of Ni oxide is evident. In the un-scaled regions there is a thicker Al2O3 layer. It is shown that, as the blade cools during casting, differential thermal contraction of mould and alloy causes the solid blade to 'detach' from the mould in these scaled areas. The formation of Ni Oxides is facilitated by this separation.

Regional Climate Change across North America in 2030 Projected from RCP6.0

NASA Astrophysics Data System (ADS)

Otte, T.; Nolte, C. G.; Faluvegi, G.; Shindell, D. T.

2012-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. In this research, downscaling techniques that we developed with historical data are now applied to GCM fields. Results from downscaling NASA/GISS ModelE2 simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model has been used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 over North America and illustrate potential changes in regional climate that are projected by ModelE2 and WRF under RCP6.0. The analysis focuses on regional climate fields that most strongly influence the interactions between climate change and air quality. In particular, an analysis of extreme temperature and precipitation events will be presented.

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, A.B.; McMahon, G.

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States - higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, Anne B.; McMahon, Gerard

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States—higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Metallurgical Analysis of Cracks Formed on Coal Fired Boiler Tube

NASA Astrophysics Data System (ADS)

Kishor, Rajat; Kyada, Tushal; Goyal, Rajesh K.; Kathayat, T. S.

2015-02-01

Metallurgical failure analysis was carried out for cracks observed on the outer surface of a boiler tube made of ASME SA 210 GR A1 grade steel. The cracks on the surface of the tube were observed after 6 months from the installation in service. A careful visual inspection, chemical analysis, hardness measurement, detailed microstructural analysis using optical and scanning electron microscopy coupled with energy dispersive X-ray spectroscopy were carried out to ascertain the cause for failure. Visual inspection of the failed tube revealed the presence of oxide scales and ash deposits on the surface of the tube exposed to fire. Many cracks extending longitudinally were observed on the surface of the tube. Bulging of the tube was also observed. The results of chemical analysis, hardness values and optical micrographs did not exhibit any abnormality at the region of failure. However, detailed SEM with EDS analysis confirmed the presence of various oxide scales. These scales initiated corrosion at both the inner and outer surfaces of the tube. In addition, excessive hoop stress also developed at the region of failure. It is concluded that the failure of the boiler tube took place owing to the combined effect of the corrosion caused by the oxide scales as well as the excessive hoop stress.

Ecological Regional Analysis Applied to Campus Sustainability Performance

ERIC Educational Resources Information Center

Weber, Shana; Newman, Julie; Hill, Adam

2017-01-01

Purpose: Sustainability performance in higher education is often evaluated at a generalized large scale. It remains unknown to what extent campus efforts address regional sustainability needs. This study begins to address this gap by evaluating trends in performance through the lens of regional environmental characteristics.…

Assessing Hydrological and Energy Budgets in Amazonia through Regional Downscaling, and Comparisons with Global Reanalysis Products

NASA Astrophysics Data System (ADS)

Nunes, A.; Ivanov, V. Y.

2014-12-01

Although current global reanalyses provide reasonably accurate large-scale features of the atmosphere, systematic errors are still found in the hydrological and energy budgets of such products. In the tropics, precipitation is particularly challenging to model, which is also adversely affected by the scarcity of hydrometeorological datasets in the region. With the goal of producing downscaled analyses that are appropriate for a climate assessment at regional scales, a regional spectral model has used a combination of precipitation assimilation with scale-selective bias correction. The latter is similar to the spectral nudging technique, which prevents the departure of the regional model's internal states from the large-scale forcing. The target area in this study is the Amazon region, where large errors are detected in reanalysis precipitation. To generate the downscaled analysis, the regional climate model used NCEP/DOE R2 global reanalysis as the initial and lateral boundary conditions, and assimilated NOAA's Climate Prediction Center (CPC) MORPHed precipitation (CMORPH), available at 0.25-degree resolution, every 3 hours. The regional model's precipitation was successfully brought closer to the observations, in comparison to the NCEP global reanalysis products, as a result of the impact of a precipitation assimilation scheme on cumulus-convection parameterization, and improved boundary forcing achieved through a new version of scale-selective bias correction. Water and energy budget terms were also evaluated against global reanalyses and other datasets.

Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations

NASA Astrophysics Data System (ADS)

Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.

2010-12-01

There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.

Image Patch Analysis of Sunspots and Active Regions

NASA Astrophysics Data System (ADS)

Moon, K.; Delouille, V.; Hero, A.

2017-12-01

The flare productivity of an active region has been observed to be related to its spatial complexity. Separating active regions that are quiet from potentially eruptive ones is a key issue in space weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature does not use all of the information present in the observations. In our work, we present an image patch analysis for characterizing sunspots and active regions. We first propose fine-scale quantitative descriptors for an active region's complexity such as intrinsic dimension, and we relate them to the Mount Wilson classification. Second, we introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. To obtain this local geometry, we use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches using the singular value decomposition. The resulting factorizations of active regions can be compared via the definition of appropriate metrics on the factors. The distances obtained from these metrics are then used to cluster the active regions. Results. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the R-value.

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

Forest Ecosystem Analysis Using a GIS

Treesearch

S.G. McNulty; W.T. Swank

1996-01-01

Forest ecosystem studies have expanded spatially in recent years to address large scale environmental issues. We are using a geographic information system (GIS) to understand and integrate forest processes at landscape to regional spatial scales. This paper presents three diverse research studies using a GIS. First, we used a GIS to develop a landscape scale model to...

Comparison of the Scaling Properties of EUV Intensity Fluctuations in Coronal Holes to those in Regions of Quiet Sun

NASA Astrophysics Data System (ADS)

Cadavid, Ana Cristina; Lawrence, John K.; Jennings, Peter John

2017-08-01

We investigate the scaling properties of EUV intensity fluctuations seen in low-latitude coronal holes (CH) and in regions of Quiet Sun (QS), in signals obtained with the SDO/AIA instrument in the 193 Å waveband. Contemporaneous time series in the 171 and 211 Å wavebands are used for comparison among emissions at different heights in the transition region and low corona. Potential-field extrapolations of contemporaneous SDO/HMI line-of-sight magnetic fields provide a context in the physical environment. Detrended fluctuation analysis (DFA) shows that the variance of the fluctuations obeys a power-law as a function of temporal scales with periods in the range ~15-60 min. This scaling is characterized by a generalized Hurst exponent α. In QS regions, and in regions within CHs that include magnetic bipoles, the scaling exponent lies in the range 1.0 < α < 1.5, and it thus corresponds to anti-correlated, turbulent-like, dynamical processes. Regions inside the coronal holes primarily associated with magnetic field of a dominant single polarity, have a generalized exponent (0.5 < α < 1) corresponding to positively correlated (“persistent”) processes. The results indicate the influence of the magnetic fields on the dynamics of the emission.

Local-scale topoclimate effects on treeline elevations: a country-wide investigation of New Zealand's southern beech treelines.

PubMed

Case, Bradley S; Buckley, Hannah L

2015-01-01

Although treeline elevations are limited globally by growing season temperature, at regional scales treelines frequently deviate below their climatic limit. The cause of these deviations relate to a host of climatic, disturbance, and geomorphic factors that operate at multiple scales. The ability to disentangle the relative effects of these factors is currently hampered by the lack of reliable topoclimatic data, which describe how regional climatic characteristics are modified by topographic effects in mountain areas. In this study we present an analysis of the combined effects of local- and regional-scale factors on southern beech treeline elevation variability at 28 study areas across New Zealand. We apply a mesoscale atmospheric model to generate local-scale (200 m) meteorological data at these treelines and, from these data, we derive a set of topoclimatic indices that reflect possible detrimental and ameliorative influences on tree physiological functioning. Principal components analysis of meteorological data revealed geographic structure in how study areas were situated in multivariate space along gradients of topoclimate. Random forest and conditional inference tree modelling enabled us to tease apart the relative effects of 17 explanatory factors on local-scale treeline elevation variability. Overall, modelling explained about 50% of the variation in treeline elevation variability across the 28 study areas, with local landform and topoclimatic effects generally outweighing those from regional-scale factors across the 28 study areas. Further, the nature of the relationships between treeline elevation variability and the explanatory variables were complex, frequently non-linear, and consistent with the treeline literature. To our knowledge, this is the first study where model-generated meteorological data, and derived topoclimatic indices, have been developed and applied to explain treeline variation. Our results demonstrate the potential of such an approach for ecological research in mountainous environments.

Local-scale topoclimate effects on treeline elevations: a country-wide investigation of New Zealand’s southern beech treelines

PubMed Central

Buckley, Hannah L.

2015-01-01

Although treeline elevations are limited globally by growing season temperature, at regional scales treelines frequently deviate below their climatic limit. The cause of these deviations relate to a host of climatic, disturbance, and geomorphic factors that operate at multiple scales. The ability to disentangle the relative effects of these factors is currently hampered by the lack of reliable topoclimatic data, which describe how regional climatic characteristics are modified by topographic effects in mountain areas. In this study we present an analysis of the combined effects of local- and regional-scale factors on southern beech treeline elevation variability at 28 study areas across New Zealand. We apply a mesoscale atmospheric model to generate local-scale (200 m) meteorological data at these treelines and, from these data, we derive a set of topoclimatic indices that reflect possible detrimental and ameliorative influences on tree physiological functioning. Principal components analysis of meteorological data revealed geographic structure in how study areas were situated in multivariate space along gradients of topoclimate. Random forest and conditional inference tree modelling enabled us to tease apart the relative effects of 17 explanatory factors on local-scale treeline elevation variability. Overall, modelling explained about 50% of the variation in treeline elevation variability across the 28 study areas, with local landform and topoclimatic effects generally outweighing those from regional-scale factors across the 28 study areas. Further, the nature of the relationships between treeline elevation variability and the explanatory variables were complex, frequently non-linear, and consistent with the treeline literature. To our knowledge, this is the first study where model-generated meteorological data, and derived topoclimatic indices, have been developed and applied to explain treeline variation. Our results demonstrate the potential of such an approach for ecological research in mountainous environments. PMID:26528407

The Nurturant Fathering Scale: A Confirmatory Factor Analysis with an African American Sample of College Students

ERIC Educational Resources Information Center

Doyle, Otima; Pecukonis, Edward; Harrington, Donna

2011-01-01

Objective: The objective of this study was to test the factor structure of the "Nurturant Fathering Scale" (NFS) among an African American sample in the mid-Atlantic region that have neither Caribbean heritage nor immigration experiences but who do have diverse family structures (N = 212). Method: A confirmatory factor analysis (CFA) was conducted…

Deliberation and Scale in Mekong Region Water Governance

NASA Astrophysics Data System (ADS)

Dore, John; Lebel, Louis

2010-07-01

Understanding the politics of deliberation, scales, and levels is crucial to understanding the social complexity of water-related governance. Deliberative processes might complement and inform more conventional representational and bureaucratic approaches to planning and decision-making. However, they are also subject to scale and level politics, which can confound institutionalized decision-making. Scale and level contests arise in dialogues and related arenas because different actors privilege particular temporal or spatial scales and levels in their analysis, arguments, and responses. Scale contests might include whether to privilege administrative, hydrological, ecosystem, or economic boundaries. Level contests might include whether to privilege the subdistrict or the province, the tributary watershed or the international river basin, a river or a biogeographic region, and the local or the regional economy. In the Mekong Region there is a recurrent demand for water resources development projects and major policies proposed by governments and investors to be scrutinized in public. Deliberative forms of engagement are potentially very helpful because they encourage supporters and critics to articulate assumptions and reasoning about the different opportunities and risks associated with alternative options, and in doing so, they often traverse and enable higher-quality conversations within and across scales and within and between levels. Six case studies from the Mekong Region are examined. We find evidence that scale and level politics affects the context, process, content, and outcomes of deliberative engagement in a region where public deliberation is still far from being a norm, particularly where there are sensitive and far-reaching choices to be made about water use and energy production.

Deliberation and scale in Mekong region water governance.

PubMed

Dore, John; Lebel, Louis

2010-07-01

Understanding the politics of deliberation, scales, and levels is crucial to understanding the social complexity of water-related governance. Deliberative processes might complement and inform more conventional representational and bureaucratic approaches to planning and decision-making. However, they are also subject to scale and level politics, which can confound institutionalized decision-making. Scale and level contests arise in dialogues and related arenas because different actors privilege particular temporal or spatial scales and levels in their analysis, arguments, and responses. Scale contests might include whether to privilege administrative, hydrological, ecosystem, or economic boundaries. Level contests might include whether to privilege the subdistrict or the province, the tributary watershed or the international river basin, a river or a biogeographic region, and the local or the regional economy. In the Mekong Region there is a recurrent demand for water resources development projects and major policies proposed by governments and investors to be scrutinized in public. Deliberative forms of engagement are potentially very helpful because they encourage supporters and critics to articulate assumptions and reasoning about the different opportunities and risks associated with alternative options, and in doing so, they often traverse and enable higher-quality conversations within and across scales and within and between levels. Six case studies from the Mekong Region are examined. We find evidence that scale and level politics affects the context, process, content, and outcomes of deliberative engagement in a region where public deliberation is still far from being a norm, particularly where there are sensitive and far-reaching choices to be made about water use and energy production.

Segmentation of the Speaker's Face Region with Audiovisual Correlation

NASA Astrophysics Data System (ADS)

Liu, Yuyu; Sato, Yoichi

The ability to find the speaker's face region in a video is useful for various applications. In this work, we develop a novel technique to find this region within different time windows, which is robust against the changes of view, scale, and background. The main thrust of our technique is to integrate audiovisual correlation analysis into a video segmentation framework. We analyze the audiovisual correlation locally by computing quadratic mutual information between our audiovisual features. The computation of quadratic mutual information is based on the probability density functions estimated by kernel density estimation with adaptive kernel bandwidth. The results of this audiovisual correlation analysis are incorporated into graph cut-based video segmentation to resolve a globally optimum extraction of the speaker's face region. The setting of any heuristic threshold in this segmentation is avoided by learning the correlation distributions of speaker and background by expectation maximization. Experimental results demonstrate that our method can detect the speaker's face region accurately and robustly for different views, scales, and backgrounds.

Insight on invasions and resilience derived from spatiotemporal discontinuities of biomass at local and regional scales

USGS Publications Warehouse

Angeler, David G.; Allen, Criag R.; Johnson, Richard K.

2012-01-01

Understanding the social and ecological consequences of species invasions is complicated by nonlinearities in processes, and differences in process and structure as scale is changed. Here we use discontinuity analyses to investigate nonlinear patterns in the distribution of biomass of an invasive nuisance species that could indicate scale-specific organization. We analyze biomass patterns in the flagellate Gonyostomum semen (Raphidophyta) in 75 boreal lakes during an 11-year period (1997-2007). With simulations using a unimodal null model and cluster analysis, we identified regional groupings of lakes based on their biomass patterns. We evaluated the variability of membership of individual lakes in regional biomass groups. Temporal trends in local and regional discontinuity patterns were analyzed using regressions and correlations with environmental variables that characterize nutrient conditions, acidity status, temperature variability, and water clarity. Regionally, there was a significant increase in the number of biomass groups over time, indicative of an increased number of scales at which algal biomass organizes across lakes. This increased complexity correlated with the invasion history of G. semen and broad-scale environmental change (recovery from acidification). Locally, no consistent patterns of lake membership to regional biomass groups were observed, and correlations with environmental variables were lake specific. The increased complexity of regional biomass patterns suggests that processes that act within or between scales reinforce the presence of G. semen and its potential to develop high-biomass blooms in boreal lakes. Emergent regional patterns combined with locally stochastic dynamics suggest a bleak future for managing G. semen, and more generally why invasive species can be ecologically successful.

Parameter Uncertainty Analysis Using Monte Carlo Simulations for a Regional-Scale Groundwater Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Pohlmann, K.

2016-12-01

Regional-scale grid-based groundwater models for flow and transport often contain multiple types of parameters that can intensify the challenge of parameter uncertainty analysis. We propose a Monte Carlo approach to systematically quantify the influence of various types of model parameters on groundwater flux and contaminant travel times. The Monte Carlo simulations were conducted based on the steady-state conversion of the original transient model, which was then combined with the PEST sensitivity analysis tool SENSAN and particle tracking software MODPATH. Results identified hydrogeologic units whose hydraulic conductivity can significantly affect groundwater flux, and thirteen out of 173 model parameters that can cause large variation in travel times for contaminant particles originating from given source zones.

Combining tower mixing ratio and community model data to estimate regional-scale net ecosystem carbon exchange by boundary layer inversion over four flux towers in the United States

Treesearch

Xueri Dang; Chun-Ta Lai; David Y. Hollinger; Andrew J. Schauer; Jingfeng Xiao; J. William Munger; Clenton Owensby; James R. Ehleringer

2011-01-01

We evaluated an idealized boundary layer (BL) model with simple parameterizations using vertical transport information from community model outputs (NCAR/NCEP Reanalysis and ECMWF Interim Analysis) to estimate regional-scale net CO2 fluxes from 2002 to 2007 at three forest and one grassland flux sites in the United States. The BL modeling...

A pilot application of regional scale risk assessment to the forestry management of the upper Grand Ronde watershed, Oregon

Treesearch

Suzanne M. Anderson; Wayne G. Landis

2012-01-01

An issue in forestry management has been the integration of a variety of different information into a threat analysis or risk assessment. In this instance, regional scale risk assessment was applied to the Upper Grande Ronde watershed in eastern Oregon to examine the potential of risk assessment for use in the management of broad landscapes. The site was a focus of...

Attribution of spring snow water equivalent (SWE) changes over the northern hemisphere to anthropogenic effects

NASA Astrophysics Data System (ADS)

Jeong, Dae Il; Sushama, Laxmi; Naveed Khaliq, M.

2017-06-01

Snow is an important component of the cryosphere and it has a direct and important influence on water storage and supply in snowmelt-dominated regions. This study evaluates the temporal evolution of snow water equivalent (SWE) for the February-April spring period using the GlobSnow observation dataset for the 1980-2012 period. The analysis is performed for different regions of hemispherical to sub-continental scales for the Northern Hemisphere. The detection-attribution analysis is then performed to demonstrate anthropogenic and natural effects on spring SWE changes for different regions, by comparing observations with six CMIP5 model simulations for three different external forcings: all major anthropogenic and natural (ALL) forcings, greenhouse gas (GHG) forcing only, and natural forcing only. The observed spring SWE generally displays a decreasing trend, due to increasing spring temperatures. However, it exhibits a remarkable increasing trend for the southern parts of East Eurasia. The six CMIP5 models with ALL forcings reproduce well the observed spring SWE decreases at the hemispherical scale and continental scales, whereas important differences are noted for smaller regions such as southern and northern parts of East Eurasia and northern part of North America. The effects of ALL and GHG forcings are clearly detected for the spring SWE decline at the hemispherical scale, based on multi-model ensemble signals. The effects of ALL and GHG forcings, however, are less clear for the smaller regions or with single-model signals, indicating the large uncertainty in regional SWE changes, possibly due to stronger influence of natural climate variability.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Simulating Nationwide Pandemics: Applying the Multi-scale Epidemiologic Simulation and Analysis System to Human Infectious Diseases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dombroski, M; Melius, C; Edmunds, T

2008-09-24

This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to humanmore » epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future work including validating the model against reliable historical disease data, improving contact rates, spread methods, and disease parameters through discussions with epidemiological experts, and incorporating realistic behavioral assumptions.« less

Effect of scaling and root planing on alveolar bone as measured by subtraction radiography.

PubMed

Hwang, You-Jeong; Fien, Matthew Jonas; Lee, Sam-Sun; Kim, Tae-Il; Seol, Yang-Jo; Lee, Yong-Moo; Ku, Young; Rhyu, In-Chul; Chung, Chong-Pyoung; Han, Soo-Boo

2008-09-01

Scaling and root planing of diseased periodontal pockets is fundamental to the treatment of periodontal disease. Although various clinical parameters have been used to assess the efficacy of this therapy, radiographic analysis of changes in bone density following scaling and root planing has not been extensively researched. In this study, digital subtraction radiography was used to analyze changes that occurred in the periodontal hard tissues following scaling and root planing. Thirteen subjects with a total of 39 sites that presented with >3 mm of vertical bone loss were included in this study. Clinical examinations were performed and radiographs were taken prior to treatment and were repeated 6 months following scaling and root planing. Radiographic analysis was performed with computer-assisted radiographic evaluation software. Three regions of interest (ROI) were defined as the most coronal, middle, and apical portions of each defect. A fourth ROI was used for each site as a control region and was placed at a distant, untreated area. Statistical analysis was carried out to evaluate changes in the mean gray level at the coronal, middle, and apical region of each treated defect. Digital subtraction radiography revealed an increase in radiographic density in 101 of the 117 test regions (83.3%). A 256 gray level was used, and a value >128 was assumed to represent a density gain in the ROI. The average gray level increase was 18.65. Although the coronal, middle, and apical regions displayed increases in bone density throughout this study, the bone density of the apical ROI (gray level = 151.27 +/- 20.62) increased significantly more than the bone density of the coronal ROI (gray level = 139.19 +/- 21.78). A significant increase in bone density was seen in probing depths >5 mm compared to those <5 mm in depth. No significant difference was found with regard to bone-density changes surrounding single- versus multiple-rooted teeth. Scaling and root planing of diseased periodontal pockets can significantly increase radiographic alveolar bone density as demonstrated through the use of digital subtraction radiography.

Coronal Heating and the Magnetic Flux Content of the Network

NASA Technical Reports Server (NTRS)

Falconer, D. A.; Moore, R. L.; Porter, J. G.; Hathaway, D. H.; Rose, M. Franklin (Technical Monitor)

2001-01-01

Previously, from analysis of SOHO coronal images in combination with Kitt Peak magnetograms, we found that the quiet corona is the sum of two components: the large-scale corona and the coronal network. The large-scale corona consists of all coronal-temperature (T approximately 10(exp 6) K) structures larger than supergranules (greater than approximately 30,000 kilometers). The coronal network (1) consists of all coronal-temperature structures smaller than supergranules, (2) is rooted in and loosely traces the photospheric magnetic network, (3) has its brightest features seated on polarity dividing lines (neutral lines) in the network magnetic flux, and (4) produces only about 5% of the total coronal emission in quiet regions. The heating of the coronal network is apparently magnetic in origin. Here, from analysis of EIT coronal images of quiet regions in combination with magnetograms of the same quiet regions from SOHO/MDI and from Kitt Peak, we examine the other 95% of the quiet corona and its relation to the underlying magnetic network. We find: (1) Dividing the large-scale corona into its bright and dim halves divides the area into bright "continents" and dark "oceans" having spans of 2-4 supergranules. (2) These patterns are also present in the photospheric magnetograms: the network is stronger under the bright half and weaker under the dim half. (3) The radiation from the large-scale corona increases roughly as the cube root of the magnetic flux content of the underlying magnetic network. In contrast, the coronal radiation from an active region increases roughly linearly with the magnetic flux content of the active region. We assume, as is widely held, that nearly all of the large-scale corona is magnetically rooted in the network. Our results suggest that either the coronal heating in quiet regions has a large non-magnetic component, or, if the heating is predominantly produced via the magnetic field, the mechanism is significantly different than in active regions.

Species richness at the guild level: effects of species pool and local environmental conditions on stream macroinvertebrate communities.

PubMed

Grönroos, Mira; Heino, Jani

2012-05-01

1. A fundamental question in ecology is which factors determine species richness. Here, we studied the relative importance of regional species pool and local environmental characteristics in determining local species richness (LSR). Typically, this question has been studied using whole communities or a certain taxonomic group, although including species with widely varying biological traits in the same analysis may hinder the detection of ecologically meaningful patterns. 2. We studied the question above for whole stream macroinvertebrate community and within functional feeding guilds. We defined the local scale as a riffle site and the regional scale (i.e. representing the regional species pool) as a stream. Such intermediate-sized regional scale is rarely studied in this context. 3. We sampled altogether 100 sites, ten riffles (local scale) in each of ten streams (regional scale). We used the local-regional richness regression plots to study the overall effect of regional species pool on LSR. Variation partitioning was used to determine the relative importance of regional species pool and local environmental conditions for species richness. 4. The local-regional richness relationship was mainly linear, suggesting strong species pool effects. Only one guild showed some signs of curvilinearity. However, variation partitioning showed that local environmental characteristics accounted for a larger fraction of variance in LSR than regional species pool. Also, the relative importance of the fractions differed between the whole community and guilds, as well as among guilds. 5. This study indicates that the importance of the local and regional processes may vary depending on feeding guild and trophic level. We conclude that both the size of the regional species pool and local habitat characteristics are important in determining LSR of stream macroinvertebrates. Our results are in agreement with recent large-scale studies conducted in highly different study systems and complement the previous findings by showing that the interplay of regional and local factors is also important at intermediate regional scales. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Local Helioseismology of Emerging Active Regions: A Case Study

NASA Astrophysics Data System (ADS)

Kosovichev, Alexander G.; Zhao, Junwei; Ilonidis, Stathis

2018-04-01

Local helioseismology provides a unique opportunity to investigate the subsurface structure and dynamics of active regions and their effect on the large-scale flows and global circulation of the Sun. We use measurements of plasma flows in the upper convection zone, provided by the Time-Distance Helioseismology Pipeline developed for analysis of solar oscillation data obtained by Helioseismic and Magnetic Imager (HMI) on Solar Dynamics Observatory (SDO), to investigate the subsurface dynamics of emerging active region NOAA 11726. The active region emergence was detected in deep layers of the convection zone about 12 hours before the first bipolar magnetic structure appeared on the surface, and 2 days before the emergence of most of the magnetic flux. The speed of emergence determined by tracking the flow divergence with depth is about 1.4 km/s, very close to the emergence speed in the deep layers. As the emerging magnetic flux becomes concentrated in sunspots local converging flows are observed beneath the forming sunspots. These flows are most prominent in the depth range 1-3 Mm, and remain converging after the formation process is completed. On the larger scale converging flows around active region appear as a diversion of the zonal shearing flows towards the active region, accompanied by formation of a large-scale vortex structure. This process occurs when a substantial amount of the magnetic flux emerged on the surface, and the converging flow pattern remains stable during the following evolution of the active region. The Carrington synoptic flow maps show that the large-scale subsurface inflows are typical for active regions. In the deeper layers (10-13 Mm) the flows become diverging, and surprisingly strong beneath some active regions. In addition, the synoptic maps reveal a complex evolving pattern of large-scale flows on the scale much larger than supergranulation

Assessment and Mitigation of PM pollution in the border regions of Austria and Slovenia

NASA Astrophysics Data System (ADS)

Uhrner, Ulrich; Reifeltshammer, Rafael; Lackner, Bettina; Forkel, Renate; Sturm, Peter

2017-04-01

Many cities, towns and regions located at the southern fringe of the Alps face remarkably high PM levels particularly during the winter period. The project PMinter aimed 1) to analyse the air quality in S-Styria, S-Carinthia and N-Slovenia, 2) to evaluate local and regional measures to develop effective air quality management plans and finally 3) to support a sustainable improvement of air quality in the project region. Using wood for residential heating is very popular in Austria and in Slovenia. To assess the contribution from wood smoke to the total PM burden and the impact of regional and large scale transport as well as the impact of secondary aerosols were major goals of PMinter. Due to the complex terrain air quality and exposure assessment is challenging. To resolve sources which are located in valleys and basins, emissions were computed or processed on 1 km x 1 km resolution for the entire program area. A new combined model approach was developed and tested successfully using a state-of-the-art CTM (WRF/Chem) on the regional scale and the Lagrangian particle model GRAL on the local scale. A detailed analysis and comparisons with measurements and regional/local scale scenario simulations were carried out. Residential heating using wood was identified as the major source and PM component dominant on the "local scale" ( 10 km), secondary inorganic aerosol was the dominant PM component on the regional scale ( 10 km - 150 km) and above. Various mitigation scenarios for PM were computed. A "local" scenario where individual heating facilities using solid fuels were replaced by district heating and a regional scenario with 35% reduced ammonia emissions from agriculture proved to be most effective.

Multi-scale Quantitative Precipitation Forecasting Using ...

EPA Pesticide Factsheets

Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals difficult to be detected at a local scale as it could cause large uncertainties when using linear correlation analysis only. This paper explores the relationship between global SST and terrestrial precipitation with respect to long-term non-stationary teleconnection signals during 1981-2010 over three regions in North America and one in Central America. Empirical mode decomposition as well as wavelet analysis is utilized to extract the intrinsic trend and the dominant oscillation of the SST and precipitation time series in sequence. After finding possible associations between the dominant oscillation of seasonal precipitation and global SST through lagged correlation analysis, the statistically significant SST regions are extracted based on the correlation coefficient. With these characterized associations, individual contribution of these SST forcing regions linked to the related precipitation responses are further quantified through nonlinear modeling with the aid of extreme learning machine. Results indicate that the non-leading SST regions also contribute a salient portion to the terrestrial precipitation variability compared to some known leading SST regions. In some cases, these

REGIONAL-SCALE WIND FIELD CLASSIFICATION EMPLOYING CLUSTER ANALYSIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glascoe, L G; Glaser, R E; Chin, H S

2004-06-17

The classification of time-varying multivariate regional-scale wind fields at a specific location can assist event planning as well as consequence and risk analysis. Further, wind field classification involves data transformation and inference techniques that effectively characterize stochastic wind field variation. Such a classification scheme is potentially useful for addressing overall atmospheric transport uncertainty and meteorological parameter sensitivity issues. Different methods to classify wind fields over a location include the principal component analysis of wind data (e.g., Hardy and Walton, 1978) and the use of cluster analysis for wind data (e.g., Green et al., 1992; Kaufmann and Weber, 1996). The goalmore » of this study is to use a clustering method to classify the winds of a gridded data set, i.e, from meteorological simulations generated by a forecast model.« less

Parameter uncertainty and nonstationarity in regional extreme rainfall frequency analysis in Qu River Basin, East China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Gu, H.

2014-12-01

Traditionally, regional frequency analysis methods were developed for stationary environmental conditions. Nevertheless, recent studies have identified significant changes in hydrological records, leading to the 'death' of stationarity. Besides, uncertainty in hydrological frequency analysis is persistent. This study aims to investigate the impact of one of the most important uncertainty sources, parameter uncertainty, together with nonstationarity, on design rainfall depth in Qu River Basin, East China. A spatial bootstrap is first proposed to analyze the uncertainty of design rainfall depth estimated by regional frequency analysis based on L-moments and estimated on at-site scale. Meanwhile, a method combining the generalized additive models with 30-year moving window is employed to analyze non-stationarity existed in the extreme rainfall regime. The results show that the uncertainties of design rainfall depth with 100-year return period under stationary conditions estimated by regional spatial bootstrap can reach 15.07% and 12.22% with GEV and PE3 respectively. On at-site scale, the uncertainties can reach 17.18% and 15.44% with GEV and PE3 respectively. In non-stationary conditions, the uncertainties of maximum rainfall depth (corresponding to design rainfall depth) with 0.01 annual exceedance probability (corresponding to 100-year return period) are 23.09% and 13.83% with GEV and PE3 respectively. Comparing the 90% confidence interval, the uncertainty of design rainfall depth resulted from parameter uncertainty is less than that from non-stationarity frequency analysis with GEV, however, slightly larger with PE3. This study indicates that the spatial bootstrap can be successfully applied to analyze the uncertainty of design rainfall depth on both regional and at-site scales. And the non-stationary analysis shows that the differences between non-stationary quantiles and their stationary equivalents are important for decision makes of water resources management and risk management.

The Regionalization of National-Scale SPARROW Models for Stream Nutrients

USGS Publications Warehouse

Schwarz, G.E.; Alexander, R.B.; Smith, R.A.; Preston, S.D.

2011-01-01

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national-scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national-scale and regional-scale information to estimate a hybrid model that imposes cross-region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ??100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

Method for identifying subsurface fluid migration and drainage pathways in and among oil and gas reservoirs using 3-D and 4-D seismic imaging

DOEpatents

Anderson, R.N.; Boulanger, A.; Bagdonas, E.P.; Xu, L.; He, W.

1996-12-17

The invention utilizes 3-D and 4-D seismic surveys as a means of deriving information useful in petroleum exploration and reservoir management. The methods use both single seismic surveys (3-D) and multiple seismic surveys separated in time (4-D) of a region of interest to determine large scale migration pathways within sedimentary basins, and fine scale drainage structure and oil-water-gas regions within individual petroleum producing reservoirs. Such structure is identified using pattern recognition tools which define the regions of interest. The 4-D seismic data sets may be used for data completion for large scale structure where time intervals between surveys do not allow for dynamic evolution. The 4-D seismic data sets also may be used to find variations over time of small scale structure within individual reservoirs which may be used to identify petroleum drainage pathways, oil-water-gas regions and, hence, attractive drilling targets. After spatial orientation, and amplitude and frequency matching of the multiple seismic data sets, High Amplitude Event (HAE) regions consistent with the presence of petroleum are identified using seismic attribute analysis. High Amplitude Regions are grown and interconnected to establish plumbing networks on the large scale and reservoir structure on the small scale. Small scale variations over time between seismic surveys within individual reservoirs are identified and used to identify drainage patterns and bypassed petroleum to be recovered. The location of such drainage patterns and bypassed petroleum may be used to site wells. 22 figs.

Method for identifying subsurface fluid migration and drainage pathways in and among oil and gas reservoirs using 3-D and 4-D seismic imaging

DOEpatents

Anderson, Roger N.; Boulanger, Albert; Bagdonas, Edward P.; Xu, Liqing; He, Wei

1996-01-01

The invention utilizes 3-D and 4-D seismic surveys as a means of deriving information useful in petroleum exploration and reservoir management. The methods use both single seismic surveys (3-D) and multiple seismic surveys separated in time (4-D) of a region of interest to determine large scale migration pathways within sedimentary basins, and fine scale drainage structure and oil-water-gas regions within individual petroleum producing reservoirs. Such structure is identified using pattern recognition tools which define the regions of interest. The 4-D seismic data sets may be used for data completion for large scale structure where time intervals between surveys do not allow for dynamic evolution. The 4-D seismic data sets also may be used to find variations over time of small scale structure within individual reservoirs which may be used to identify petroleum drainage pathways, oil-water-gas regions and, hence, attractive drilling targets. After spatial orientation, and amplitude and frequency matching of the multiple seismic data sets, High Amplitude Event (HAE) regions consistent with the presence of petroleum are identified using seismic attribute analysis. High Amplitude Regions are grown and interconnected to establish plumbing networks on the large scale and reservoir structure on the small scale. Small scale variations over time between seismic surveys within individual reservoirs are identified and used to identify drainage patterns and bypassed petroleum to be recovered. The location of such drainage patterns and bypassed petroleum may be used to site wells.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Classification as a generic tool for characterising status and changes of regional scale groundwater systems

NASA Astrophysics Data System (ADS)

Barthel, Roland; Haaf, Ezra

2016-04-01

Regional hydrogeology is becoming increasingly important, but at the same time, scientifically sound, universal solutions for typical groundwater problems encountered on the regional scale are hard to find. While managers, decision-makers and state agencies operating on regional and national levels have always shown a strong interest in regional scale hydrogeology, researchers from academia tend to avoid the subject, focusing instead on local scales. Additionally, hydrogeology has always had a tendency to regard every problem as unique to its own site- and problem-specific context. Regional scale hydrogeology is therefore pragmatic rather than aiming at developing generic methodology (Barthel, 2014; Barthel and Banzhaf, 2016). One of the main challenges encountered on the regional scale in hydrogeology is the extreme heterogeneity that generally increases with the size of the studied area - paired with relative data scarcity. Even in well-monitored regions of the world, groundwater observations are usually clustered, leaving large areas without any direct data. However, there are many good reasons for assessing the status and predicting the behavior of groundwater systems under conditions of global change even for those areas and aquifers without observations. This is typically done by using rather coarsely discretized and / or poorly parameterized numerical models, or by using very simplistic conceptual hydrological models that do not take into account the complex three-dimensional geological setup. Numerical models heavily rely on local data and are resource-demanding. Conceptual hydrological models only deliver reliable information on groundwater if the geology is extremely simple. In this contribution, we present an approach to derive statistically relevant information for un-monitored areas, making use of existing information from similar localities that are or have been monitored. The approach combines site-specific knowledge with conceptual assumptions on the behavior of groundwater systems. It is based on the hypothesis that similar groundwater systems respond similarly to similar impacts. At its core is the classification of (i) static hydrogeological characteristics (such as aquifer geometry and hydraulic properties), (ii) dynamic changes of the boundary conditions (such as recharge, water levels in surface waters), and (iii) dynamic groundwater system responses (groundwater head and chemical parameters). The dependencies of system responses on explanatory variables are used to map knowledge from observed locations to areas without measurements. Classification of static and dynamic system features combined with information about known system properties and their dependencies provide insight into system behavior that cannot be directly derived through the analysis of raw data. Classification and dependency analysis could finally lead to a new framework for groundwater system assessment on the regional scale as a replacement or supplement to numerical groundwater models and catchment scale hydrological models. This contribution focusses on the main hydrogeological concepts underlying the approach while another EGU contribution (Haaf and Barthel, 2016) explains the methodologies used to classify groundwater systems. References: Barthel, R., 2014. A call for more fundamental science in regional hydrogeology. Hydrogeol J, 22(3): 507-510. Barthel, R., Banzhaf, S., 2016. Groundwater and Surface Water Interaction at the Regional-scale - A Review with Focus on Regional Integrated Models. Water Resour Manag, 30(1): 1-32. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs. Abstract submitted to EGU General Assembly 2016, Vienna, Austria.

Tony Jimenez | NREL

Science.gov Websites

pre-feasibility analysis; wind data analysis; the small wind turbine certification process; economic Regional Test Center effort, analysis of the potential economic impact of large-scale MHK deployment off pre-feasibility analysis. Tony is an engineer officer in the Army Reserve. He has deployed twice

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Spatial structures of stream and hillslope drainage networks following gully erosion after wildfire

USGS Publications Warehouse

Moody, J.A.; Kinner, D.A.

2006-01-01

The drainage networks of catchment areas burned by wildfire were analysed at several scales. The smallest scale (1-1000 m2) representative of hillslopes, and the small scale (1000 m2 to 1 km2), representative of small catchments, were characterized by the analysis of field measurements. The large scale (1-1000 km2), representative of perennial stream networks, was derived from a 30-m digital elevation model and analysed by computer analysis. Scaling laws used to describe large-scale drainage networks could be extrapolated to the small scale but could not describe the smallest scale of drainage structures observed in the hillslope region. The hillslope drainage network appears to have a second-order effect that reduces the number of order 1 and order 2 streams predicted by the large-scale channel structure. This network comprises two spatial patterns of rills with width-to-depth ratios typically less than 10. One pattern is parallel rills draining nearly planar hillslope surfaces, and the other pattern is three to six converging rills draining the critical source area uphill from an order 1 channel head. The magnitude of this critical area depends on infiltration, hillslope roughness and critical shear stress for erosion of sediment, all of which can be substantially altered by wildfire. Order 1 and 2 streams were found to constitute the interface region, which is altered by a disturbance, like wildfire, from subtle unchannelized drainages in unburned catchments to incised drainages. These drainages are characterized by gullies also with width-to-depth ratios typically less than 10 in burned catchments. The regions (hillslope, interface and chanel) had different drainage network structures to collect and transfer water and sediment. Copyright ?? 2005 John Wiley & Sons, Ltd.

Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

PubMed Central

Guo, Bin; Chen, Zhongsheng; Guo, Jinyun; Liu, Feng; Chen, Chuanfa; Liu, Kangli

2016-01-01

Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD). Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years) and inter-decadal scale (quasi-12 and quasi-23 years). Moreover, the 2–3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements. PMID:27007388

Spatial, temporal and frequency based climate change assessment in Columbia River Basin using multi downscaled-scenarios

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid

2016-07-01

Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070-2099 with respect to historical period of 1970-2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the potential predictability of the broad-scale and regional monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both Sea Surface Temperatures (SST) and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. However, for regional monsoons, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

Analyzing energy-water exchange dynamics in the Thar desert

NASA Astrophysics Data System (ADS)

Raja, P.; Singh, Nilendu; Srinivas, C. V.; Singhal, Mohit; Chauhan, Pankaj; Singh, Maharaj; Sinha, N. K.

2017-07-01

Regions of strong land-atmosphere coupling will be more susceptible to the hydrological impacts in the intensifying hydrological cycle. In this study, micrometeorological experiments were performed to examine the land-atmosphere coupling strength over a heat low region (Thar desert, NW India), known to influence the Indian summer monsoon (ISM). Within the vortex of Thar desert heat low, energy-water exchange and coupling behavior were studied for 4 consecutive years (2011-2014) based on sub-hourly measurements of radiative-convective flux, state parameters and sub-surface thermal profiles using lead-lag analysis between various E-W balance components. Results indicated a strong (0.11-0.35) but variable monsoon season (July-September) land-atmosphere coupling events. Coupling strength declined with time, becomes negative beyond 10-day lag. Evapotranspiration (LE) influences rainfall at the monthly time-scale (20-40 days). Highly correlated monthly rainfall and LE anomalies (r = 0.55, P < 0.001) suggested a large precipitation memory linked to the local land surface state. Sensible heating (SH) during March and April are more strongly (r = 0.6-0.7) correlated to ISM rainfall than heating during May or June (r = 0.16-0.36). Analyses show strong and weak couplings among net radiation (Rn)-vapour pressure deficit (VPD), LE-VPD and Rn-LE switching between energy-limited to water-limited conditions. Consistently, +ve and -ve residual energy [(dE) = (Rn - G) - (SH + LE)] were associated with regional wet and dry spells respectively with a lead of 10-40 days. Dew deposition (18.8-37.9 mm) was found an important component in the annual surface water balance. Strong association of variation of LE and rainfall was found during monsoon at local-scale and with regional-scale LE (MERRA 2D) but with a lag which was more prominent at local-scale than at regional-scale. Higher pre-monsoon LE at local-scale as compared to low and monotonous variation in regional-scale LE led to hypothesize that excess energy and water vapour brought through advection caused by pre-monsoon rainfall might have been recycled through rainfall to compensate for early part of monsoon rainfall at local-scale. However, long-term measurements and isotope analysis would be able to strengthen this hypothesis. This study would fill the key gaps in the global flux studies and improve understanding on local E-W exchange pathways, responses and feedbacks.

Assessing the accuracy of a regional land cover classification

Treesearch

William Clerke; Raymond Czaplewski; Jeff Campbell; Janet Fahringer

1996-01-01

The Southern Region USDA Forest Service recently completed the Southern Appalachian Assessment (SAA). The Assessment is a broad scale interagency analysis and sharing of existing information relative to the natural and human resources of the region. The SAA encompasses over 36 million acres extending from Northern Virginia to Northern Alabama. It was clear early in the...

AQMEII3: the EU and NA regional scale program of the ...

EPA Pesticide Factsheets

The presentation builds on the work presented last year at the 14th CMAS meeting and it is applied to the work performed in the context of the AQMEII-HTAP collaboration. The analysis is conducted within the framework of the third phase of AQMEII (Air Quality Model Evaluation International Initiative) and encompasses the gauging of model performance through measurement-to-model comparison, error decomposition and time series analysis of the models biases. Through the comparison of several regional-scale chemistry transport modelling systems applied to simulate meteorology and air quality over two continental areas, this study aims at i) apportioning the error to the responsible processes through time-scale analysis, and ii) help detecting causes of models error, and iii) identify the processes and scales most urgently requiring dedicated investigations. The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while the apportioning of the error into its constituent parts (bias, variance and covariance) can help assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the previous phases of AQMEII. The National Exposure Research Laboratory (NERL) Computational Exposur

A holistic approach for large-scale derived flood frequency analysis

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Apel, Heiko; Hundecha, Yeshewatesfa; Guse, Björn; Sergiy, Vorogushyn; Merz, Bruno

2017-04-01

Spatial consistency, which has been usually disregarded because of the reported methodological difficulties, is increasingly demanded in regional flood hazard (and risk) assessments. This study aims at developing a holistic approach for deriving flood frequency at large scale consistently. A large scale two-component model has been established for simulating very long-term multisite synthetic meteorological fields and flood flow at many gauged and ungauged locations hence reflecting the spatially inherent heterogeneity. The model has been applied for the region of nearly a half million km2 including Germany and parts of nearby countries. The model performance has been multi-objectively examined with a focus on extreme. By this continuous simulation approach, flood quantiles for the studied region have been derived successfully and provide useful input for a comprehensive flood risk study.

SMALL-SCALE FUEL ALCOHOL PRODUCTION TO MEET UNIVERSITY VEHICLE FUEL NEEDS AND PROMOTE REGIONAL SUSTAINABLE DEVELOPMENT

EPA Science Inventory

1. The small scale sweet sorghum ethanol production system in Iowa has good potential for development based on an economic analysis with rates of return ranging from 12% to 32 % for ethanol prices ranging from $1.66/gal to $2.20/gal. A scale of 300 acres (121 ha) for produ...

2. Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

   NASA Astrophysics Data System (ADS)

   Harris, B.; McDougall, K.; Barry, M.

   2012-07-01

   Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

3. Regional- and local-scale variations in benthic megafaunal composition at the Arctic deep-sea observatory HAUSGARTEN

   NASA Astrophysics Data System (ADS)

   Taylor, J.; Krumpen, T.; Soltwedel, T.; Gutt, J.; Bergmann, M.

   2016-02-01

   The Long-Term Ecological Research (LTER) observatory HAUSGARTEN, in the eastern Fram Strait, provides us the valuable ability to study the composition of benthic megafaunal communities through the analysis of seafloor photographs. This, in combination with extensive sampling campaigns, which have yielded a unique data set on faunal, bacterial, biogeochemical and geological properties, as well as on hydrography and sedimentation patterns, allows us to address the question of why variations in megafaunal community structure and species distribution exist within regional (60-110 km) and local (<4 km) scales. Here, we present first results from the latitudinal HAUSGARTEN gradient, consisting of three different stations (N3, HG-IV, S3) between 78°30‧N and 79°45‧N (2351-2788 m depth), obtained via the analysis of images acquired by a towed camera (OFOS-Ocean Floor Observation System) in 2011. We assess variability in megafaunal densities, species composition and diversity as well as biotic and biogenic habitat features, which may cause the patterns observed. While there were significant regional-scale differences in megafaunal composition and densities between the stations (N3=26.74±0.63; HG-IV=11.21±0.25; S3=18.34±0.39 individuals m-2), significant local differences were only found at HG-IV. Regional-scale variations may be due to the significant differences in ice coverage at each station as well as the different quantities of protein available, whereas local-scale differences at HG-IV may be a result of variation in bottom topography or factors not yet identified.

4. Analysis of Thermal Structure of Arctic Lakes at Local and Regional Scales Using in Situ and Multidate Landsat-8 Data

   NASA Astrophysics Data System (ADS)

   Huang, Yan; Liu, Hongxing; Hinkel, Kenneth; Yu, Bailang; Beck, Richard; Wu, Jianping

   2017-11-01

   The Arctic coastal plain is covered with numerous thermokarst lakes. These lakes are closely linked to climate and environmental change through their heat and water budgets. We examined the intralake thermal structure at the local scale and investigated the water temperature pattern of lakes at the regional scale by utilizing extensive in situ measurements and multidate Landsat-8 remote sensing data. Our analysis indicates that the lake skin temperatures derived from satellite thermal sensors during most of the ice-free summer period effectively represent the lake bulk temperature because the lakes are typically well-mixed and without significant vertical stratification. With the relatively high-resolution Landsat-8 thermal data, we were able to quantitatively examine intralake lateral temperature differences and gradients in relation to geographical location, topography, meteorological factors, and lake morphometry for the first time. Our results suggest that wind speed and direction not only control the vertical stratification but also influences lateral differences and gradients of lake surface temperature. Wind can considerably reduce the intralake temperature gradient. Interestingly, we found that geographical location (latitude, longitude, distance to the ocean) and lake morphometry (surface size, depth, volume) not only control lake temperature regionally but also affect the lateral temperature gradient and homogeneity level within each individual lake. For the Arctic coastal plain, at regional scales, inland and southern lakes tend to have larger horizontal temperature differences and gradients compared to coastal and northern lakes. At local scales, large and shallow lakes tend to have large lateral temperature differences relative to small and deep lakes.

5. Application of regional climate models to the Indian winter monsoon over the western Himalayas.

   PubMed

   Dimri, A P; Yasunari, T; Wiltshire, A; Kumar, P; Mathison, C; Ridley, J; Jacob, D

   2013-12-01

   The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies. Copyright © 2013 Elsevier B.V. All rights reserved.

6. Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations

   PubMed Central

   Losch, Martin; Menemenlis, Dimitris

   2018-01-01

   Abstract Sea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data. PMID:29576996

7. Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations

   NASA Astrophysics Data System (ADS)

   Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

   2018-01-01

   Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

8. Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations.

   PubMed

   Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

   2018-01-01

   Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

9. Rockfall hazard and risk assessments along roads at a regional scale: example in Swiss Alps

   NASA Astrophysics Data System (ADS)

   Michoud, C.; Derron, M.-H.; Horton, P.; Jaboyedoff, M.; Baillifard, F.-J.; Loye, A.; Nicolet, P.; Pedrazzini, A.; Queyrel, A.

   2012-03-01

   Unlike fragmental rockfall runout assessments, there are only few robust methods to quantify rock-mass-failure susceptibilities at regional scale. A detailed slope angle analysis of recent Digital Elevation Models (DEM) can be used to detect potential rockfall source areas, thanks to the Slope Angle Distribution procedure. However, this method does not provide any information on block-release frequencies inside identified areas. The present paper adds to the Slope Angle Distribution of cliffs unit its normalized cumulative distribution function. This improvement is assimilated to a quantitative weighting of slope angles, introducing rock-mass-failure susceptibilities inside rockfall source areas previously detected. Then rockfall runout assessment is performed using the GIS- and process-based software Flow-R, providing relative frequencies for runout. Thus, taking into consideration both susceptibility results, this approach can be used to establish, after calibration, hazard and risk maps at regional scale. As an example, a risk analysis of vehicle traffic exposed to rockfalls is performed along the main roads of the Swiss alpine valley of Bagnes.

10. Multi-Scale Drought Analysis using Thermal Remote Sensing: A Case Study in Georgia’s Altamaha River Watershed

    NASA Astrophysics Data System (ADS)

    Jacobs, J. M.; Bhat, S.; Choi, M.; Mecikalski, J. R.; Anderson, M. C.

    2009-12-01

    The unprecedented recent droughts in the Southeast US caused reservoir levels to drop dangerously low, elevated wildfire hazard risks, reduced hydropower generation and caused severe economic hardships. Most drought indices are based on recent rainfall or changes in vegetation condition. However in heterogeneous landscapes, soils and vegetation (type and cover) combine to differentially stress regions even under similar weather conditions. This is particularly true for the heterogeneous landscapes and highly variable rainfall in the Southeastern United States. This research examines the spatiotemperal evolution of watershed scale drought using a remotely sensed stress index. Using thermal-infrared imagery, a fully automated inverse model of Atmosphere-Land Exchange (ALEXI), GIS datasets and analysis tools, modeled daily surface moisture stress is examined at a 10-km resolution grid covering central to southern Georgia. Regional results are presented for the 2000-2008 period. The ALEXI evaporative stress index (ESI) is compared to existing regional drought products and validated using local hydrologic measurements in Georgia’s Altamaha River watershed at scales from 10 to 10,000 km2.

11. Manufacturing Analysis | Energy Analysis | NREL

    Science.gov Websites

    , state, and community levels. Solar photovoltaic manufacturing cost analysis Examining the regional competitiveness of solar photovoltaic manufacturing points to access to capital as a critical component for scale of rare material-based photovoltaic PV technology deployment may influence the United States

Finding stability regions for preserving efficiency classification of variable returns to scale technology in data envelopment analysis

NASA Astrophysics Data System (ADS)

Zamani, P.; Borzouei, M.

2016-12-01

This paper addresses issue of sensitivity of efficiency classification of variable returns to scale (VRS) technology for enhancing the credibility of data envelopment analysis (DEA) results in practical applications when an additional decision making unit (DMU) needs to be added to the set being considered. It also develops a structured approach to assisting practitioners in making an appropriate selection of variation range for inputs and outputs of additional DMU so that this DMU be efficient and the efficiency classification of VRS technology remains unchanged. This stability region is simply specified by the concept of defining hyperplanes of production possibility set of VRS technology and the corresponding halfspaces. Furthermore, this study determines a stability region for the additional DMU within which, in addition to efficiency classification, the efficiency score of a specific inefficient DMU is preserved and also using a simulation method, a region in which some specific efficient DMUs become inefficient is provided.

Multi-dimension and Comprehensive Assessment on the Utilizing and Sharing of Regional Large-Scale Scientific Equipment

PubMed Central

Li, Chen; Yongbo, Lv; Chi, Chen

2015-01-01

Based on the data from 30 provincial regions in China, an assessment and empirical analysis was carried out on the utilizing and sharing of the large-scale scientific equipment with a comprehensive assessment model established on the three dimensions, namely, equipment, utilization and sharing. The assessment results were interpreted in light of relevant policies. The results showed that on the whole, the overall development level in the provincial regions in eastern and central China is higher than that in western China. This is mostly because of the large gap among the different provincial regions with respect to the equipped level. But in terms of utilizing and sharing, some of the Western provincial regions, such as Ningxia, perform well, which is worthy of our attention. Policy adjustment targeting at the differentiation, elevation of the capacity of the equipment management personnel, perfection of the sharing and cooperation platform, and the promotion of the establishment of open sharing funds, are all important measures to promote the utilization and sharing of the large-scale scientific equipment and to narrow the gap among different regions. PMID:25937850

Large-scale data analysis of power grid resilience across multiple US service regions

NASA Astrophysics Data System (ADS)

Ji, Chuanyi; Wei, Yun; Mei, Henry; Calzada, Jorge; Carey, Matthew; Church, Steve; Hayes, Timothy; Nugent, Brian; Stella, Gregory; Wallace, Matthew; White, Joe; Wilcox, Robert

2016-05-01

Severe weather events frequently result in large-scale power failures, affecting millions of people for extended durations. However, the lack of comprehensive, detailed failure and recovery data has impeded large-scale resilience studies. Here, we analyse data from four major service regions representing Upstate New York during Super Storm Sandy and daily operations. Using non-stationary spatiotemporal random processes that relate infrastructural failures to recoveries and cost, our data analysis shows that local power failures have a disproportionally large non-local impact on people (that is, the top 20% of failures interrupted 84% of services to customers). A large number (89%) of small failures, represented by the bottom 34% of customers and commonplace devices, resulted in 56% of the total cost of 28 million customer interruption hours. Our study shows that extreme weather does not cause, but rather exacerbates, existing vulnerabilities, which are obscured in daily operations.

Negative Symptom Dimensions of the Positive and Negative Syndrome Scale Across Geographical Regions

PubMed Central

Liharska, Lora; Harvey, Philip D.; Atkins, Alexandra; Ulshen, Daniel; Keefe, Richard S.E.

2017-01-01

Objective: Recognizing the discrete dimensions that underlie negative symptoms in schizophrenia and how these dimensions are understood across localities might result in better understanding and treatment of these symptoms. To this end, the objectives of this study were to 1) identify the Positive and Negative Syndrome Scale negative symptom dimensions of expressive deficits and experiential deficits and 2) analyze performance on these dimensions over 15 geographical regions to determine whether the items defining them manifest similar reliability across these regions. Design: Data were obtained for the baseline Positive and Negative Syndrome Scale visits of 6,889 subjects across 15 geographical regions. Using confirmatory factor analysis, we examined whether a two-factor negative symptom structure that is found in schizophrenia (experiential deficits and expressive deficits) would be replicated in our sample, and using differential item functioning, we tested the degree to which specific items from each negative symptom subfactor performed across geographical regions in comparison with the United States. Results: The two-factor negative symptom solution was replicated in this sample. Most geographical regions showed moderate-to-large differential item functioning for Positive and Negative Syndrome Scale expressive deficit items, especially N3 Poor Rapport, as compared with Positive and Negative Syndrome Scale experiential deficit items, showing that these items might be interpreted or scored differently in different regions. Across countries, except for India, the differential item functioning values did not favor raters in the United States. Conclusion: These results suggest that the Positive and Negative Syndrome Scale negative symptom factor can be better represented by a two-factor model than by a single-factor model. Additionally, the results show significant differences in responses to items representing the Positive and Negative Syndrome Scale expressive factors, but not the experiential factors, across regions. This could be due to a lack of equivalence between the original and translated versions, cultural differences with the interpretation of items, dissimilarities in rater training, or diversity in the understanding of scoring anchors. Knowing which items are challenging for raters across regions can help to guide Positive and Negative Syndrome Scale training and improve the results of international clinical trials aimed at negative symptoms. PMID:29410935

Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

Treesearch

Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

2006-01-01

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

Woody Species Diversity in Forest Plantations in a Mountainous Region of Beijing, China: Effects of Sampling Scale and Species Selection

PubMed Central

Zhang, Yuxin; Zhang, Shuang; Ma, Keming; Fu, Bojie; Anand, Madhur

2014-01-01

The role of forest plantations in biodiversity conservation has gained more attention in recent years. However, most work on evaluating the diversity of forest plantations focuses only on one spatial scale; thus, we examined the effects of sampling scale on diversity in forest plantations. We designed a hierarchical sampling strategy to collect data on woody species diversity in planted pine (Pinus tabuliformis Carr.), planted larch (Larix principis-rupprechtii Mayr.), and natural secondary deciduous broadleaf forests in a mountainous region of Beijing, China. Additive diversity partition analysis showed that, compared to natural forests, the planted pine forests had a different woody species diversity partitioning pattern at multi-scales (except the Simpson diversity in the regeneration layer), while the larch plantations did not show multi-scale diversity partitioning patterns that were obviously different from those in the natural secondary broadleaf forest. Compare to the natural secondary broadleaf forests, the effects of planted pine forests on woody species diversity are dependent on the sampling scale and layers selected for analysis. Diversity in the planted larch forest, however, was not significantly different from that in the natural forest for all diversity components at all sampling levels. Our work demonstrated that the species selected for afforestation and the sampling scales selected for data analysis alter the conclusions on the levels of diversity supported by plantations. We suggest that a wide range of scales should be considered in the evaluation of the role of forest plantations on biodiversity conservation. PMID:25545860

Scale Dependence of Land Atmosphere Interactions in Wet and Dry Regions as Simulated with NU-WRF over the Southwestern and Southeast US

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Wu, Di; Lau, K.- M.; Tao, Wei-Kuo

2016-01-01

Large-scale forcing and land-atmosphere interactions on precipitation are investigated with NASA-Unified WRF (NU-WRF) simulations during fast transitions of ENSO phases from spring to early summer of 2010 and 2011. The model is found to capture major precipitation episodes in the 3-month simulations without resorting to nudging. However, the mean intensity of the simulated precipitation is underestimated by 46% and 57% compared with the observations in dry and wet regions in the southwestern and south-central United States, respectively. Sensitivity studies show that large-scale atmospheric forcing plays a major role in producing regional precipitation. A methodology to account for moisture contributions to individual precipitation events, as well as total precipitation, is presented under the same moisture budget framework. The analysis shows that the relative contributions of local evaporation and large-scale moisture convergence depend on the dry/wet regions and are a function of temporal and spatial scales. While the ratio of local and large-scale moisture contributions vary with domain size and weather system, evaporation provides a major moisture source in the dry region and during light rain events, which leads to greater sensitivity to soil moisture in the dry region and during light rain events. The feedback of land surface processes to large-scale forcing is well simulated, as indicated by changes in atmospheric circulation and moisture convergence. Overall, the results reveal an asymmetrical response of precipitation events to soil moisture, with higher sensitivity under dry than wet conditions. Drier soil moisture tends to suppress further existing below-normal precipitation conditions via a positive soil moisture-land surface flux feedback that could worsen drought conditions in the southwestern United States.

Field-aligned currents' scale analysis performed with the Swarm constellation

NASA Astrophysics Data System (ADS)

Lühr, Hermann; Park, Jaeheung; Gjerloev, Jesper W.; Rauberg, Jan; Michaelis, Ingo; Merayo, Jose M. G.; Brauer, Peter

2015-01-01

We present a statistical study of the temporal- and spatial-scale characteristics of different field-aligned current (FAC) types derived with the Swarm satellite formation. We divide FACs into two classes: small-scale, up to some 10 km, which are carried predominantly by kinetic Alfvén waves, and large-scale FACs with sizes of more than 150 km. For determining temporal variability we consider measurements at the same point, the orbital crossovers near the poles, but at different times. From correlation analysis we obtain a persistent period of small-scale FACs of order 10 s, while large-scale FACs can be regarded stationary for more than 60 s. For the first time we investigate the longitudinal scales. Large-scale FACs are different on dayside and nightside. On the nightside the longitudinal extension is on average 4 times the latitudinal width, while on the dayside, particularly in the cusp region, latitudinal and longitudinal scales are comparable.

Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques

DTIC Science & Technology

Koopman Mode Analysis was newly applied to southern hemisphere sea ice concentration data. The resulting Koopman modes from analysis of both the...southern and northern hemisphere sea ice concentration data shows geographical regions where sea ice coverage has decreased over multiyear time scales.

Quantification of scaling exponents and dynamical complexity of microwave refractivity in a tropical climate

NASA Astrophysics Data System (ADS)

Fuwape, Ibiyinka A.; Ogunjo, Samuel T.

2016-12-01

Radio refractivity index is used to quantify the effect of atmospheric parameters in communication systems. Scaling and dynamical complexities of radio refractivity across different climatic zones of Nigeria have been studied. Scaling property of the radio refractivity across Nigeria was estimated from the Hurst Exponent obtained using two different scaling methods namely: The Rescaled Range (R/S) and the detrended fluctuation analysis(DFA). The delay vector variance (DVV), Largest Lyapunov Exponent (λ1) and Correlation Dimension (D2) methods were used to investigate nonlinearity and the results confirm the presence of deterministic nonlinear profile in the radio refractivity time series. The recurrence quantification analysis (RQA) was used to quantify the degree of chaoticity in the radio refractivity across the different climatic zones. RQA was found to be a good measure for identifying unique fingerprint and signature of chaotic time series data. Microwave radio refractivity was found to be persistent and chaotic in all the study locations. The dynamics of radio refractivity increases in complexity and chaoticity from the Coastal region towards the Sahelian climate. The design, development and deployment of robust and reliable microwave communication link in the region will be greatly affected by the chaotic nature of radio refractivity in the region.

Controls on mineralisation in the Sierra Foothills gold province, central California, USA: A GIS-based reconnaissance prospectivity analysis

USGS Publications Warehouse

Bierlein, F.P.; Northover, H.J.; Groves, D.I.; Goldfarb, R.J.; Marsh, E.E.

2008-01-01

The assessment of spatial relationships between the location, abundance and size of orogenic-gold deposits in the highly endowed Sierra Foothills gold province in California, via the combination of field studies and a GIS-based analysis, illustrates the power of such an approach to the characterisation of important parameters of mineral systems, and the prediction of districts likely to host economic mineralisation. Regional- to deposit-scale reconnaissance mapping suggests that deposition of gold-bearing quartz veins occurred in second- and third-order, east-over-west thrusts during regional east - west compression and right-lateral transpression. At the district-scale, significant zones of mineralisation correspond with such transpressional reactivation zones and dilational jogs that developed during the Late Jurassic - Early Cretaceous along the misaligned segments of first-order faults throughout the Sierra Nevada Foothills Metamorphic Belt. Field-based observations and interpretation of GIS data (including solid geology, structural elements, deposit locations, magnetics, gravity) also highlight the importance of structural permeability contrasts, rheological gradients, and variations in fault orientation for localising mineralisation. Although this approach confirms empirical findings and produces promising results at the province scale, enhanced geological, structural, geophysical and geochronological data density is required to generate regionally consistent, high-quality input layers that improve predictive targeting at the goldfield to deposit-scale.

Latitude delineates patterns of biogeography in terrestrial Streptomyces.

PubMed

Choudoir, Mallory J; Doroghazi, James R; Buckley, Daniel H

2016-12-01

The biogeography of Streptomyces was examined at regional spatial scales to identify factors that govern patterns of microbial diversity. Streptomyces are spore forming filamentous bacteria which are widespread in soil. Streptomyces strains were isolated from perennial grass habitats sampled across a spatial scale of more than 6000 km. Previous analysis of this geographically explicit culture collection provided evidence for a latitudinal diversity gradient in Streptomyces species. Here the hypothesis that this latitudinal diversity gradient is a result of evolutionary dynamics associated with historical demographic processes was evaluated. Historical demographic phenomena have genetic consequences that can be evaluated through analysis of population genetics. Population genetic approaches were applied to analyze population structure in six of the most numerically abundant and geographically widespread Streptomyces phylogroups from our culture collection. Streptomyces population structure varied at regional spatial scales, and allelic diversity correlated with geographic distance. In addition, allelic diversity and gene flow are partitioned by latitude. Finally, it was found that nucleotide diversity within phylogroups was negatively correlated with latitude. These results indicate that phylogroup diversification is constrained by dispersal limitation at regional spatial scales, and they are consistent with the hypothesis that historical demographic processes have influenced the contemporary biogeography of Streptomyces. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown

EPA Science Inventory

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) hel...

Wildlife

Treesearch

Bryce Rickel

2005-01-01

This volume addresses the wildlife and fish of the grasslands in the Southwestern Region of the USDA Forest Service. Our intent is to provide information that will help resource specialists and decisionmakers manage wildlife populations within grassland ecosystems in the Southwestern United States. The information and analysis presented is at a Regional scale.

Catchment scale water resource constraints on UK policies for low-carbon energy system transition

NASA Astrophysics Data System (ADS)

Konadu, D. D.; Fenner, R. A.

2017-12-01

Long-term low-carbon energy transition policy of the UK presents national scale propositions of different low-carbon energy system options that lead to meeting GHG emissions reduction target of 80% on 1990 levels by 2050. Whilst national-scale assessments suggests that water availability may not be a significant constrain on future thermal power generation systems in this pursuit, these analysis fail to capture the appropriate spatial scale where water resource decisions are made, i.e. at the catchment scale. Water is a local resource, which also has significant spatio-temporal regional and national variability, thus any policy-relevant water-energy nexus analysis must be reflective of these characteristics. This presents a critical challenge for policy relevant water-energy nexus analysis. This study seeks to overcome the above challenge by using a linear spatial-downscaling model to allocate nationally projected water-intensive energy system infrastructure/technologies to the catchment level, and estimating the water requirements for the deployment of these technologies. The model is applied to the UK Committee on Climate Change Carbon Budgets to 2030 as a case study. The paper concludes that whilst national-scale analyses show minimal long-term water related impacts, catchment level appraisal of water resource requirements reveal significant constraints in some locations. The approach and results presented in this study thus, highlights the importance of bringing together scientific understanding, data and analysis tools to provide better insights for water-energy nexus decisions at the appropriate spatial scale. This is particularly important for water stressed regions where the water-energy nexus must be analysed at appropriate spatial resolution to capture the full water resource impact of national energy policy.

Transverse Dimensions of Chorus in the Source Region

NASA Technical Reports Server (NTRS)

Santolik, O.; Gurnett, D. A.

2003-01-01

We report measurement of whistler-mode chorus by the four Cluster spacecraft at close separations. We focus our analysis on the generation region close to the magnetic equatorial plane at a radial distance of 4.4 Earth's radii. We use both linear and rank correlation analysis to define perpendicular dimensions of the sources of chorus elements below one half of the electron cyclotron frequency. Correlation is significant throughout the range of separation distances of 60-260 km parallel to the field line and 7-100 km in the perpendicular plane. At these scales, the correlation coefficient is independent for parallel separations, and decreases with perpendicular separation. The observations are consistent with a statistical model of the source region assuming individual sources as gaussian peaks of radiated power with a common half-width of 35 km perpendicular to the magnetic field. This characteristic scale is comparable to the wavelength of observed waves.

Evolution of anthropogenic emissions at the global and regional scale during the past three decades

NASA Astrophysics Data System (ADS)

Granier, C.; Bessagnet, B. B.; Bond, T. C.; D'Angiola, A.; Denier van der Gon, H.; Frost, G. J.; Heil, A.; Kaiser, J.; Kinne, S. A.; Klimont, Z.; Kloster, S.; Lamarque, J.; Liousse, C.; Masui, T.; Meleux, F.; Mieville, A.; Ohara, T.; Raut, J.; Riahi, K.; Schultz, M. G.; Smith, S.; Thomson, A. M.; van Aardenne, J.; van der Werf, G.; van Vuuren, D.

2010-12-01

The knowledge of the distributions of surface emissions of gases and aerosols is essential for an accurate modeling and analysis of the distribution and evolution of the concentration of gaseous and particulate chemical species. The quantification of surface fluxes by source of origin is furthermore central to the assessment of effects and the development of control measures. Over the past few years, different ranges of emission fluxes have been proposed by several studies, which have provided emissions at different spatial and temporal scales. We have compared the emissions of several chemical compounds, i.e. carbon monoxide, nitrogen oxides, sulfur dioxide and black carbon, as provided by global and regional emissions inventories in different regions of the world for the past thirty years. The presentation will focus on the United States, Europe and China. Significant differences between the datasets providing emissions in these regions have been identified, reaching for example 60% and 35% for anthropogenic emissions of carbon monoxide and nitrogen oxides in both regions, respectively. We will assess the current uncertainties on surface emissions and their recent trends. This analysis is often hindered because of differences in base years and in species considered in the different datasets. Current work aiming at compiling comparable metrics for such species for the analysis of regional and global emission datasets will be discussed.

Scaling properties of Arctic sea ice deformation in high-resolution viscous-plastic sea ice models and satellite observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2017-04-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Impact of the 1997-1998 El-Nino of Regional Hydrology

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1998-01-01

The 1997-1998 El-Nino brought with it a range of severe local-regional hydrological phenomena. Record high temperatures and extremely dry soil conditions in Texas is an example of this regional effect. The El-Nino and La-Nina change the continental weather patterns considerably. However, connections between continental weather anomalies and regional or local anomalies have not been established to a high degree of confidence. There are several unique features of the recent El-Nino and La-Nina. Due to the recognition of the present El-Nino well in advance, there have been several coupled model studies on global and regional scales. Secondly, there is a near real-time monitoring of the situation using data from satellite sensors, namely, SeaWIFS, TOVS, AVHRR and GOES. Both observations and modeling characterize the large scale features of this El-Nino fairly well. However the connection to the local and regional hydrological phenomenon still needs to be made. This paper will use satellite observations and analysis data to establish a relation between local hydrology and large scale weather patterns. This will be the first step in using satellite data to perform regional hydrological simulations of surface temperature and soil moisture.

Evaluating Water Budget Closure Across Spatial Scales: An Observational Approach through Texas Water Observatory

NASA Astrophysics Data System (ADS)

Gaur, N.; Jaimes, A.; Vaughan, S.; Morgan, C.; Moore, G. W.; Miller, G. R.; Everett, M. E.; Lawing, M.; Mohanty, B.

2017-12-01

Applications varying from improving water conservation practices at the field scale to predicting global hydrology under a changing climate depend upon our ability to achieve water budget closure. 1) Prevalent heterogeneity in soils, geology and land-cover, 2) uncertainties in observations and 3) space-time scales of our control volume and available data are the main factors affecting the percentage of water budget closure that we can achieve. The Texas Water Observatory presents a unique opportunity to observe the major components of the water cycle (namely precipitation, evapotranspiration, root zone soil moisture, streamflow and groundwater) in varying eco-hydrological regions representative of the lower Brazos River basin at multiple scales. The soils in these regions comprise of heavy clays that swell and shrink to create complex preferential pathways in the sub-surface, thus, making the hydrology in this region difficult to quantify. This work evaluates the water budget of the region by varying the control volume in terms of 3 temporal (weekly, monthly and seasonal) and 3 different spatial scales. The spatial scales are 1) Point scale - that is typical for process understanding of water dynamics, 2) Eddy Covariance footprint scale - that is typical of most eco-hydrological applications at the field scale and, 3) Satellite footprint scale- that is typically used in regional and global hydrological analysis. We employed a simple water balance model to evaluate the water budget at all scales. The point scale water budget was assessed using direct observations from hydro-geo-thematically located observation locations within different eddy covariance footprints. At the eddy covariance footprint scale, the sub-surface of each eddy covariance footprint was intensively characterized using electromagnetic induction (EM 38) and the resultant data was used to calculate the inter-point variability to upscale the sub-surface storage while the satellite scale water budget was evaluated using SMAP satellite observations supplemented with reanalysis products. At the point scale, we found differences in sub-surface storage in the same land-cover depending on the landscape position of the observation point while land-cover significantly affected water budget at the larger scales.

Identifying regions of strong scattering at the core-mantle boundary from analysis of PKKP precursor energy

USGS Publications Warehouse

Rost, S.; Earle, P.S.

2010-01-01

We detect seismic scattering from the core-mantle boundary related to the phase PKKP (PK. KP) in data from small aperture seismic arrays in India and Canada. The detection of these scattered waves in data from small aperture arrays is new and allows a better characterization of the fine-scale structure of the deep Earth especially in the southern hemisphere. Their slowness vector is determined from array processing allowing location of the heterogeneities at the core-mantle boundary using back-projection techniques through 1D Earth models. We identify strong scattering at the core-mantle boundary (CMB) beneath the Caribbean, Patagonia and the Antarctic Peninsula as well as beneath southern Africa. An analysis of the scattering regions relative to sources and receivers indicates that these regions represent areas of increased scattering likely due to increased heterogeneities close to the CMB. The 1. Hz array data used in this study is most sensitive to heterogeneity with scale lengths of about 10. km. Given the small size of the scatterers, a chemical origin of the heterogeneities is likely. By comparing the location of the fine-scale heterogeneity to geodynamical models and tomographic images, we identify different scattering mechanisms in regions related to subduction (Caribbean and Patagonia) and dense thermo chemical piles (Southern Africa). ?? 2010 Elsevier B.V.

Satellite Based Analysis of Wood Biomass and Fuelwood Sustainability in Senegal: Developing Approaches for Long-Term Monitoring in the SERVIR-West Africa Region

NASA Astrophysics Data System (ADS)

Hanan, N. P.; Anchang, J.; Dieye, A. M.; Yero, K.; Tredennick, A. T.

2017-12-01

Rural populations in most of Africa are highly dependent on woody biomass (wood or charcoal) for cooking and heating. Many rural families gather wood locally, while urban populations often rely on small-scale commercial charcoal producers, who make charcoal in rural areas for transport to urban centers. Given that cooking is essential for conversion of inedible protein and carbohydrate substrates into edible food, fuelwood is an essential part of the food security puzzle for most African families. The SERVIR program is a partnership between USAID, NASA and regional institutions designed to enhance access to, and application of, earth observation data for economic development and natural resource management in less developed countries. In this paper, we report on a SERVIR West Africa collaboration to develop above-ground wood biomass estimates using moderate resolution ( 20 m) data from Sentinel-1 and Sentinel-2 satellites, incorporating field data for calibration and validation, and using data retrieval and analysis workflows that can be replicated by SERVIR partners across the region. Using the country of Senegal as a test case, we analyze the spatial distribution of biomass stocks in relation to fuelwood demand to assess supply-demand patterns across scales from local (village), to district, regional and national scales.

The interplanetary magnetic field B sub y -dependent field-aligned current in the dayside polar cap under quiet conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamauchi, M.; Araki, T.

1989-03-01

Spatial distribution and temporal variation of the interplanetary magnetic field (IMF) B{sub y}-dependent cusp region field-aligned currents (FACs) during quiet periods were studied by use of magnetic data observed by Magsat. The analysis was made for 11 events (each event lasts more than one and a half days) when the IMF B{sub y} component was steadily large and B{sub x} was relatively small ({vert bar}B{sub z}{vert bar} < {vert bar}B{sub y}{vert bar}). Results of the analysis of total 62 half-day periods for the IMF B{sub y}-dependent cusp region FAC are summarized as follows: (1) the IMF B{sub y}-dependent cusp regionmore » FAC is located at around 86{degree}-87{degree} invariant latitude local noon, which is more poleward than the location of the IMF B{sub z}-dependent cusp region FAC; (2) the current density of this FAC is greater than previous studies ({ge} 4 {mu}A/m{sup 2} for IMF B{sub y} = 6 nT); (3) there are two time scales for the IMF B{sub y}-dependent cusp region FAC to appear: the initial rise of the current is on a short time scale, {approximately} 10 min, and it is followed by a gradual increase on a time scale of several hours to a half day; (4) the seasonal change of this FAC is greater than that of the nightside region 1 or region 2 FACs; (5) the IMF B{sub z}-dependent cusp region FAC is not well observed around the cusp when the IMF B{sub y}-dependent cusp region FAC is intense.« less

Small beetle, large-scale drivers: how regional and landscape factors affect outbreaks of the European spruce bark beetle

PubMed Central

Seidl, Rupert; Müller, Jörg; Hothorn, Torsten; Bässler, Claus; Heurich, Marco; Kautz, Markus

2016-01-01

Summary 1. Unprecedented bark beetle outbreaks have been observed for a variety of forest ecosystems recently, and damage is expected to further intensify as a consequence of climate change. In Central Europe, the response of ecosystem management to increasing infestation risk has hitherto focused largely on the stand level, while the contingency of outbreak dynamics on large-scale drivers remains poorly understood. 2. To investigate how factors beyond the local scale contribute to the infestation risk from Ips typographus (Col., Scol.), we analysed drivers across seven orders of magnitude in scale (from 103 to 1010 m2) over a 23-year period, focusing on the Bavarian Forest National Park. Time-discrete hazard modelling was used to account for local factors and temporal dependencies. Subsequently, beta regression was applied to determine the influence of regional and landscape factors, the latter characterized by means of graph theory. 3. We found that in addition to stand variables, large-scale drivers also strongly influenced bark beetle infestation risk. Outbreak waves were closely related to landscape-scale connectedness of both host and beetle populations as well as to regional bark beetle infestation levels. Furthermore, regional summer drought was identified as an important trigger for infestation pulses. Large-scale synchrony and connectivity are thus key drivers of the recently observed bark beetle outbreak in the area. 4. Synthesis and applications. Our multiscale analysis provides evidence that the risk for biotic disturbances is highly dependent on drivers beyond the control of traditional stand-scale management. This finding highlights the importance of fostering the ability to cope with and recover from disturbance. It furthermore suggests that a stronger consideration of landscape and regional processes is needed to address changing disturbance regimes in ecosystem management. PMID:27041769

Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA

USGS Publications Warehouse

Delin, G.N.; Healy, R.W.; Lorenz, D.L.; Nimmo, J.R.

2007-01-01

Regional ground-water recharge estimates for Minnesota were compared to estimates made on the basis of four local- and basin-scale methods. Three local-scale methods (unsaturated-zone water balance, water-table fluctuations (WTF) using three approaches, and age dating of ground water) yielded point estimates of recharge that represent spatial scales from about 1 to about 1000 m2. A fourth method (RORA, a basin-scale analysis of streamflow records using a recession-curve-displacement technique) yielded recharge estimates at a scale of 10–1000s of km2. The RORA basin-scale recharge estimates were regionalized to estimate recharge for the entire State of Minnesota on the basis of a regional regression recharge (RRR) model that also incorporated soil and climate data. Recharge rates estimated by the RRR model compared favorably to the local and basin-scale recharge estimates. RRR estimates at study locations were about 41% less on average than the unsaturated-zone water-balance estimates, ranged from 44% greater to 12% less than estimates that were based on the three WTF approaches, were about 4% less than the age dating of ground-water estimates, and were about 5% greater than the RORA estimates. Of the methods used in this study, the WTF method is the simplest and easiest to apply. Recharge estimates made on the basis of the UZWB method were inconsistent with the results from the other methods. Recharge estimates using the RRR model could be a good source of input for regional ground-water flow models; RRR model results currently are being applied for this purpose in USGS studies elsewhere.

Statistical analysis of the time and space characteristic scales for large precipitating systems in the equatorial, tropical, sahelian and mid-latitude regions.

NASA Astrophysics Data System (ADS)

Duroure, Christophe; Sy, Abdoulaye; Baray, Jean luc; Van baelen, Joel; Diop, Bouya

2017-04-01

Precipitation plays a key role in the management of sustainable water resources and flood risk analyses. Changes in rainfall will be a critical factor determining the overall impact of climate change. We propose to analyse long series (10 years) of daily precipitation at different regions. We present the Fourier densities energy spectra and morphological spectra (i.e. probability repartition functions of the duration and the horizontal scale) of large precipitating systems. Satellite data from the Global precipitation climatology project (GPCP) and local pluviometers long time series in Senegal and France are used and compared in this work. For mid-latitude and Sahelian regions (North of 12°N), the morphological spectra are close to exponential decreasing distribution. This fact allows to define two characteristic scales (duration and space extension) for the precipitating region embedded into the large meso-scale convective system (MCS). For tropical and equatorial regions (South of 12°N) the morphological spectra are close to a Levy-stable distribution (power law decrease) which does not allow to define a characteristic scale (scaling range). When the time and space characteristic scales are defined, a "statistical velocity" of precipitating MCS can be defined, and compared to observed zonal advection. Maps of the characteristic scales and Levy-stable exponent over West Africa and south Europe are presented. The 12° latitude transition between exponential and Levy-stable behaviors of precipitating MCS is compared with the result of ECMWF ERA-Interim reanalysis for the same period. This morphological sharp transition could be used to test the different parameterizations of deep convection in forecast models.

Influence of Land Cover Heterogeneity, Land-Use Change and Management on the Regional Carbon Cycle in the Upper Midwest USA as Evaluated by High-Density Observations and a Dynamic Ecosystem Model

NASA Astrophysics Data System (ADS)

Desai, A. R.; Bolstad, P. V.; Moorcroft, P. R.; Davis, K. J.

2005-12-01

The interplay between land use change, forest management and land cover variability complicates the ability to characterize regional scale (10-1000 km) exchange of carbon dioxide between the land surface and atmosphere in heterogeneous landscapes. An attempt was made to observe and model these factors and their influence on the regional carbon cycle across the upper Midwest USA. A high density of eddy-covariance carbon flux, micrometeorology, carbon dioxide mixing ratio, stand-scale biometry and canopy component flux observations have been occurring in this area as part of the Chequamegon Ecosystem-Atmosphere Study. Observations limited to sampling only dominant stands and coarse-resolution biogeochemical models limited to biome-scale parameterization neither accurately capture the variability of carbon fluxes measured by the network of eddy covariance towers nor match the regional-scale carbon flux inferred from very tall tower eddy covariance measurements and multi-site upscaling. Analysis of plot level biometric data, U.S. Forest Service Forest Inventory Analysis data and high-resolution land cover data around the tall tower revealed significant variations in vegetation type, stand age, canopy stocking and structure. Wetlands, clearcuts and recent natural disturbances occur in characteristic small non-uniformly distributed patches that aggregate to form more than 30% of the landscape. The Ecosystem Demography model, a dynamic ecosystem model that incorporates vegetation heterogeneity, canopy structure, stand age, disturbance, land use change and forest management, was parameterized with regional biometric data and meteorology, historical records of land management and high-resolution satellite land cover maps. The model will be used to examine the significance of past land use change, natural disturbance history and current forest management in explaining landscape structure and regional carbon fluxes observed in the region today.

Cross-scale dynamics of a regional urban system through time

EPA Science Inventory

In this work, we conducted an analysis of a regional urban system (southeastern United States) that has been the subject of research in the series of papers reviewed in the preceding sections. We used a U.S. census dataset incorporating the urbanized area (UA) definition. A UA co...

Chapter 9: Carbon fluxes across regions.

Treesearch

Beverly E. Law; Dave Turner; John Campbell; Michael Lefsky; Michael Guzy; Osbert Sun; Steve Van Tuyl; Warren Cohen

2006-01-01

Scaling biogeochemical processes to regions, continents, and the globe is critical for understanding feedbacks between the biosphere and atmosphere in the analysis of global change. This includes the effects of changing atmospheric carbon dioxide, climate, disturbances, and increasing nitrogen deposition from air pollution (Ehleringer and Field 1993, Vitousek et al....

Influence of Boundary Conditions on Regional Air Quality Simulations—Analysis of AQMEII Phase 3 Results

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary con...

Large-scale derived flood frequency analysis based on continuous simulation

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

Regional precipitation trend analysis at the Langat River Basin, Selangor, Malaysia

NASA Astrophysics Data System (ADS)

Palizdan, Narges; Falamarzi, Yashar; Huang, Yuk Feng; Lee, Teang Shui; Ghazali, Abdul Halim

2014-08-01

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982-2011 were examined at the 95 % level of significance using the regional average Mann-Kendall (RAMK) test and the regional average Mann-Kendall coupled with bootstrap (RAMK-bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km × 5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.

Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors

USGS Publications Warehouse

Pervez, Md Shahriar; Henebry, Geoffrey M.

2014-01-01

Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change. Precipitation during and after the monsoon is likely to increase in both basins under the A1B and A2 emission scenarios; whereas, the pre-monsoon precipitation is likely to decrease. Peak monsoon precipitation is likely to shift from July to August, and may impact the livelihoods of large rural populations linked to subsistence agriculture in the basins. Uncertainty analysis of the downscaled precipitation indicated that the uncertainty in the downscaled precipitation was less than the uncertainty in the original CGCM3.1 precipitation; hence, the CGCM3.1 downscaled precipitation was a better input for the regional hydrological impact studies. However, downscaled precipitation from multiple GCMs is suggested for comprehensive impact studies.

Characterizing the Severe Turbulence Environments Associated With Commercial Aviation Accidents. Part 1; 44 Case Study Synoptic Observational Analyses

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Huffman, Allan W.; Lux, Kevin M.; Charney, Joseph J.; Riordan, Allan J.; Lin, Yuh-Lang; Proctor, Fred H. (Technical Monitor)

2002-01-01

A 44 case study analysis of the large-scale atmospheric structure associated with development of accident-producing aircraft turbulence is described. Categorization is a function of the accident location, altitude, time of year, time of day, and the turbulence category, which classifies disturbances. National Centers for Environmental Prediction Reanalyses data sets and satellite imagery are employed to diagnose synoptic scale predictor fields associated with the large-scale environment preceding severe turbulence. These analyses indicate a predominance of severe accident-producing turbulence within the entrance region of a jet stream at the synoptic scale. Typically, a flow curvature region is just upstream within the jet entrance region, convection is within 100 km of the accident, vertical motion is upward, absolute vorticity is low, vertical wind shear is increasing, and horizontal cold advection is substantial. The most consistent predictor is upstream flow curvature and nearby convection is the second most frequent predictor.

Multiplex ligation-dependent probe amplification analysis on capillary electrophoresis instruments for a rapid gene copy number study.

PubMed

Jankowski, Stéphane; Currie-Fraser, Erica; Xu, Licen; Coffa, Jordy

2008-09-01

Annotated DNA samples that had been previously analyzed were tested using multiplex ligation-dependent probe amplification (MLPA) assays containing probes targeting BRCA1, BRCA2, and MMR (MLH1/MSH2 genes) and the 9p21 chromosomal region. MLPA polymerase chain reaction products were separated on a capillary electrophoresis platform, and the data were analyzed using GeneMapper v4.0 software (Applied Biosystems, Foster City, CA). After signal normalization, loci regions that had undergone deletions or duplications were identified using the GeneMapper Report Manager and verified using the DyeScale functionality. The results highlight an easy-to-use, optimal sample preparation and analysis workflow that can be used for both small- and large-scale studies.

Central Atlantic regional ecological test site

NASA Technical Reports Server (NTRS)

Alexander, R. H.

1972-01-01

The work of the Central Atlantic Regional Ecological Test Site (CARETS) project is discussed. The primary aim of CARETS is to test the hypothesis that data from ERTS-A can be made an integral part of a regional land resources information system, encompassing both inventory of the resource base and monitoring of changes, along with their effects on the quality of the environment. Another objective of the project is to determine scaling factors for developing land use information and regional analysis for regions of any given size.

Multi objective climate change impact assessment using multi downscaled climate scenarios

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid

2016-04-01

Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional and global scale. In the present study, we have analyzed the changes in precipitation and temperature for future scenario period of 2070-2099 with respect to historical period of 1970-2000 from a set of statistically downscaled GCM projections for Columbia River Basin (CRB). Analysis is performed using 2 different statistically downscaled climate projections namely the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. Analysis is performed on spatial, temporal and frequency based parameters in the future period at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice-versa for temperature. Frequency analysis provided insights into possible explanation to changes in precipitation.

Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2014-06-01

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and issue.

Spatially Resolved Distribution of Fe Species around Microbes at the Submicron Scale in Natural Bacteriogenic Iron Oxides.

PubMed

Suga, Hiroki; Kikuchi, Sakiko; Takeichi, Yasuo; Miyamoto, Chihiro; Miyahara, Masaaki; Mitsunobu, Satoshi; Ohigashi, Takuji; Mase, Kazuhiko; Ono, Kanta; Takahashi, Yoshio

2017-09-27

Natural bacteriogenic iron oxides (BIOS) were investigated using local-analyzable synchrotron-based scanning transmission X-ray microscopy (STXM) with a submicron-scale resolution. Cell, cell sheath interface (EPS), and sheath in the BIOS were clearly depicted using C-, N-, and O- near edge X-ray absorption fine structure (NEXAFS) obtained through STXM measurements. Fe-NEXAFS obtained from different regions of BIOS indicated that the most dominant iron mineral species was ferrihydrite. Fe(II)- and/or Fe(III)-acidic polysaccharides accompanied ferrihydrite near the cell and EPS regions. Our STXM/NEXAFS analysis showed that Fe species change continuously between the cell, EPS, and sheath under several 10-nm scales.

Non-linear characteristics and long-range correlations in Asian stock markets

NASA Astrophysics Data System (ADS)

Jiang, J.; Ma, K.; Cai, X.

2007-05-01

We test several non-linear characteristics of Asian stock markets, which indicates the failure of efficient market hypothesis and shows the essence of fractal of the financial markets. In addition, by using the method of detrended fluctuation analysis (DFA) to investigate the long range correlation of the volatility in the stock markets, we find that the crossover phenomena exist in the results of DFA. Further, in the region of small volatility, the scaling behavior is more complicated; in the region of large volatility, the scaling exponent is close to 0.5, which suggests the market is more efficient. All these results may indicate the possibility of characteristic multifractal scaling behaviors of the financial markets.

Quantifying the impact of human mobility on malaria

PubMed Central

Wesolowski, Amy; Eagle, Nathan; Tatem, Andrew J.; Smith, David L.; Noor, Abdisalan M.; Snow, Robert W.; Buckee, Caroline O.

2013-01-01

Human movements contribute to the transmission of malaria on spatial scales that exceed the limits of mosquito dispersal. Identifying the sources and sinks of imported infections due to human travel and locating high-risk sites of parasite importation could greatly improve malaria control programs. Here we use spatially explicit mobile phone data and malaria prevalence information from Kenya to identify the dynamics of human carriers that drive parasite importation between regions. Our analysis identifies specific importation routes that contribute to malaria epidemiology on regional spatial scales. PMID:23066082

Air Emissions Inventories

EPA Pesticide Factsheets

This site provides access to emissions data, regulations and guidance, electronic system access, resources and tools to support trends analysis, regional, and local scale air quality modeling, regulatory impact assessments.

Low regional cerebral blood flow in burning mouth syndrome patients with depression.

PubMed

Liu, B-L; Yao, H; Zheng, X-J; Du, G-H; Shen, X-M; Zhou, Y-M; Tang, G-Y

2015-07-01

The main aims of this study were to (i) investigate the emotional disorder status of patients with burning mouth syndrome (BMS) and (ii) detect regional cerebral blood flow in BMS patients with the application of combined single-photon emission computed tomography and computed tomography (SPECT/CT). The degree of pain was measured using the visual analysis scale, and emotional disorder with the self-rating anxiety scale, self-rating depression scale, and Hamilton depression rating scale in 29 patients with BMS and 10 healthy controls. SPECT/CT was performed in 29 patients with BMS and 10 healthy controls, and statistical parametric mapping method was used for between-group analyses. The incidence rate of depression in patients with BMS was 31.0%. Compared to the control group, patients with BMS displayed significantly different depression and anxiety scales (P < 0.05). Significantly lower regional cerebral blood flow in the left parietal and left temporal lobes was recorded for BMS patients with depression (P < 0.05). Patients with BMS experience more depression and anxious emotion. Moreover, depression in patients with BMS may be associated with lower regional cerebral blood flow in the left temporal and left parietal lobes. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multi-scale comparison of source parameter estimation using empirical Green's function approach

NASA Astrophysics Data System (ADS)

Chen, X.; Cheng, Y.

2015-12-01

Analysis of earthquake source parameters requires correction of path effect, site response, and instrument responses. Empirical Green's function (EGF) method is one of the most effective methods in removing path effects and station responses by taking the spectral ratio between a larger and smaller event. Traditional EGF method requires identifying suitable event pairs, and analyze each event individually. This allows high quality estimations for strictly selected events, however, the quantity of resolvable source parameters is limited, which challenges the interpretation of spatial-temporal coherency. On the other hand, methods that exploit the redundancy of event-station pairs are proposed, which utilize the stacking technique to obtain systematic source parameter estimations for a large quantity of events at the same time. This allows us to examine large quantity of events systematically, facilitating analysis of spatial-temporal patterns, and scaling relationship. However, it is unclear how much resolution is scarified during this process. In addition to the empirical Green's function calculation, choice of model parameters and fitting methods also lead to biases. Here, using two regional focused arrays, the OBS array in the Mendocino region, and the borehole array in the Salton Sea geothermal field, I compare the results from the large scale stacking analysis, small-scale cluster analysis, and single event-pair analysis with different fitting methods to systematically compare the results within completely different tectonic environment, in order to quantify the consistency and inconsistency in source parameter estimations, and the associated problems.

Soil organic matter dynamics and CO2 fluxes in relation to landscape scale processes: linking process understanding to regional scale carbon mass-balances

NASA Astrophysics Data System (ADS)

Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas

2014-05-01

In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.

Contextual Compression of Large-Scale Wind Turbine Array Simulations: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gruchalla, Kenny M; Brunhart-Lupo, Nicholas J; Potter, Kristin C

Data sizes are becoming a critical issue particularly for HPC applications. We have developed a user-driven lossy wavelet-based storage model to facilitate the analysis and visualization of large-scale wind turbine array simulations. The model stores data as heterogeneous blocks of wavelet coefficients, providing high-fidelity access to user-defined data regions believed the most salient, while providing lower-fidelity access to less salient regions on a block-by-block basis. In practice, by retaining the wavelet coefficients as a function of feature saliency, we have seen data reductions in excess of 94 percent, while retaining lossless information in the turbine-wake regions most critical to analysismore » and providing enough (low-fidelity) contextual information in the upper atmosphere to track incoming coherent turbulent structures. Our contextual wavelet compression approach has allowed us to deliver interactive visual analysis while providing the user control over where data loss, and thus reduction in accuracy, in the analysis occurs. We argue this reduced but contexualized representation is a valid approach and encourages contextual data management.« less

Contextual Compression of Large-Scale Wind Turbine Array Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gruchalla, Kenny M; Brunhart-Lupo, Nicholas J; Potter, Kristin C

Data sizes are becoming a critical issue particularly for HPC applications. We have developed a user-driven lossy wavelet-based storage model to facilitate the analysis and visualization of large-scale wind turbine array simulations. The model stores data as heterogeneous blocks of wavelet coefficients, providing high-fidelity access to user-defined data regions believed the most salient, while providing lower-fidelity access to less salient regions on a block-by-block basis. In practice, by retaining the wavelet coefficients as a function of feature saliency, we have seen data reductions in excess of 94 percent, while retaining lossless information in the turbine-wake regions most critical to analysismore » and providing enough (low-fidelity) contextual information in the upper atmosphere to track incoming coherent turbulent structures. Our contextual wavelet compression approach has allowed us to deliver interative visual analysis while providing the user control over where data loss, and thus reduction in accuracy, in the analysis occurs. We argue this reduced but contextualized representation is a valid approach and encourages contextual data management.« less

Development of Activity-based Cost Functions for Cellulase, Invertase, and Other Enzymes

NASA Astrophysics Data System (ADS)

Stowers, Chris C.; Ferguson, Elizabeth M.; Tanner, Robert D.

As enzyme chemistry plays an increasingly important role in the chemical industry, cost analysis of these enzymes becomes a necessity. In this paper, we examine the aspects that affect the cost of enzymes based upon enzyme activity. The basis for this study stems from a previously developed objective function that quantifies the tradeoffs in enzyme purification via the foam fractionation process (Cherry et al., Braz J Chem Eng 17:233-238, 2000). A generalized cost function is developed from our results that could be used to aid in both industrial and lab scale chemical processing. The generalized cost function shows several nonobvious results that could lead to significant savings. Additionally, the parameters involved in the operation and scaling up of enzyme processing could be optimized to minimize costs. We show that there are typically three regimes in the enzyme cost analysis function: the low activity prelinear region, the moderate activity linear region, and high activity power-law region. The overall form of the cost analysis function appears to robustly fit the power law form.

Finite element solutions for crack-tip behavior in small-scale yielding

NASA Technical Reports Server (NTRS)

Tracey, D. M.

1976-01-01

The subject considered is the stress and deformation fields in a cracked elastic-plastic power law hardening material under plane strain tensile loading. An incremental plasticity finite element formulation is developed for accurate analysis of the complete field problem including the extensively deformed near tip region, the elastic-plastic region, and the remote elastic region. The formulation has general applicability and was used to solve the small scale yielding problem for a set of material hardening exponents. Distributions of stress, strain, and crack opening displacement at the crack tip and through the elastic-plastic zone are presented as a function of the elastic stress intensity factor and material properties.

Meteorological Contribution to Variability in Particulate Matter Concentrations

NASA Astrophysics Data System (ADS)

Woods, H. L.; Spak, S. N.; Holloway, T.

2006-12-01

Local concentrations of fine particulate matter (PM) are driven by a number of processes, including emissions of aerosols and gaseous precursors, atmospheric chemistry, and meteorology at local, regional, and global scales. We apply statistical downscaling methods, typically used for regional climate analysis, to estimate the contribution of regional scale meteorology to PM mass concentration variability at a range of sites in the Upper Midwestern U.S. Multiple years of daily PM10 and PM2.5 data, reported by the U.S. Environmental Protection Agency (EPA), are correlated with large-scale meteorology over the region from the National Centers for Environmental Prediction (NCEP) reanalysis data. We use two statistical downscaling methods (multiple linear regression, MLR, and analog) to identify which processes have the greatest impact on aerosol concentration variability. Empirical Orthogonal Functions of the NCEP meteorological data are correlated with PM timeseries at measurement sites. We examine which meteorological variables exert the greatest influence on PM variability, and which sites exhibit the greatest response to regional meteorology. To evaluate model performance, measurement data are withheld for limited periods, and compared with model results. Preliminary results suggest that regional meteorological processes account over 50% of aerosol concentration variability at study sites.

Rainfall trends in the South Asian summer monsoon and its related large-scale dynamics with focus over Pakistan

NASA Astrophysics Data System (ADS)

Latif, M.; Syed, F. S.; Hannachi, A.

2017-06-01

The study of regional rainfall trends over South Asia is critically important for food security and economy, as both these factors largely depend on the availability of water. In this study, South Asian summer monsoon rainfall trends on seasonal and monthly (June-September) time scales have been investigated using three observational data sets. Our analysis identify a dipole-type structure in rainfall trends over the region north of the Indo-Pak subcontinent, with significant increasing trends over the core monsoon region of Pakistan and significant decreasing trends over the central-north India and adjacent areas. The dipole is also evident in monthly rainfall trend analyses, which is more prominent in July and August. We show, in particular, that the strengthening of northward moisture transport over the Arabian Sea is a likely reason for the significant positive trend of rainfall in the core monsoon region of Pakistan. In contrast, over the central-north India region, the rainfall trends are significantly decreasing due to the weakening of northward moisture transport over the Bay of Bengal. The leading empirical orthogonal functions clearly show the strengthening (weakening) patterns of vertically integrated moisture transport over the Arabian Sea (Bay of Bengal) in seasonal and monthly interannual time scales. The regression analysis between the principal components and rainfall confirm the dipole pattern over the region. Our results also suggest that the extra-tropical phenomena could influence the mean monsoon rainfall trends over Pakistan by enhancing the cross-equatorial flow of moisture into the Arabian Sea.

SEISMIC SOURCE SCALING AND DISCRIMINATION IN DIVERSE TECTONIC ENVIRONMENTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abercrombie, R E; Mayeda, K; Walter, W R

2007-07-10

The objectives of this study are to improve low-magnitude regional seismic discrimination by performing a thorough investigation of earthquake source scaling using diverse, high-quality datasets from varied tectonic regions. Local-to-regional high-frequency discrimination requires an estimate of how earthquakes scale with size. Walter and Taylor (2002) developed the MDAC (Magnitude and Distance Amplitude Corrections) method to empirically account for these effects through regional calibration. The accuracy of these corrections has a direct impact on our ability to identify clandestine explosions in the broad regional areas characterized by low seismicity. Unfortunately our knowledge of source scaling at small magnitudes (i.e., m{sub b}more » < {approx}4.0) is poorly resolved. It is not clear whether different studies obtain contradictory results because they analyze different earthquakes, or because they use different methods. Even in regions that are well studied, such as test sites or areas of high seismicity, we still rely on empirical scaling relations derived from studies taken from half-way around the world at inter-plate regions. We investigate earthquake sources and scaling from different tectonic settings, comparing direct and coda wave analysis methods. We begin by developing and improving the two different methods, and then in future years we will apply them both to each set of earthquakes. Analysis of locally recorded, direct waves from events is intuitively the simplest way of obtaining accurate source parameters, as these waves have been least affected by travel through the earth. But there are only a limited number of earthquakes that are recorded locally, by sufficient stations to give good azimuthal coverage, and have very closely located smaller earthquakes that can be used as an empirical Green's function (EGF) to remove path effects. In contrast, coda waves average radiation from all directions so single-station records should be adequate, and previous work suggests that the requirements for the EGF event are much less stringent. We can study more earthquakes using the coda-wave methods, while using direct wave methods for the best recorded subset of events so as to investigate any differences between the results of the two approaches. Finding 'perfect' EGF events for direct wave analysis is difficult, as is ascertaining the quality of a particular EGF event. We develop a multi-taper method to obtain time-domain source-time-functions by frequency division. If an earthquake and EGF event pair are able to produce a clear, time-domain source pulse then we accept the EGF event. We then model the spectral (amplitude) ratio to determine source parameters from both direct P and S waves. We use the well-recorded sequence of aftershocks of the M5 Au Sable Forks, NY, earthquake to test the method and also to obtain some of the first accurate source parameters for small earthquakes in eastern North America. We find that the stress drops are high, confirming previous work suggesting that intraplate continental earthquakes have higher stress drops than events at plate boundaries. We simplify and improve the coda wave analysis method by calculating spectral ratios between different sized earthquakes. We first compare spectral ratio performance between local and near-regional S and coda waves in the San Francisco Bay region for moderate-sized events. The average spectral ratio standard deviations using coda are {approx}0.05 to 0.12, roughly a factor of 3 smaller than direct S-waves for 0.2 < f < 15.0 Hz. Also, direct wave analysis requires collocated pairs of earthquakes whereas the event-pairs (Green's function and target events) can be separated by {approx}25 km for coda amplitudes without any appreciable degradation. We then apply coda spectral ratio method to the 1999 Hector Mine mainshock (M{sub w} 7.0, Mojave Desert) and its larger aftershocks. We observe a clear departure from self-similarity, consistent with previous studies using similar regional datasets.« less

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, B. C.

1991-01-01

A new diagnostic tool is developed for examining relationships between the synoptic scale circulation and regional temperature distributions in GCMs. The 4 x 5 deg GISS GCM is shown to produce accurate simulations of the variance in the synoptic scale sea level pressure distribution over the U.S. An analysis of the observational data set from the National Meteorological Center (NMC) also shows a strong relationship between the synoptic circulation and grid point temperatures. This relationship is demonstrated by deriving transfer functions between a time-series of circulation parameters and temperatures at individual grid points. The circulation parameters are derived using rotated principal components analysis, and the temperature transfer functions are based on multivariate polynomial regression models. The application of these transfer functions to the GCM circulation indicates that there is considerable spatial bias present in the GCM temperature distributions. The transfer functions are also used to indicate the possible changes in U.S. regional temperatures that could result from differences in synoptic scale circulation between a 1XCO2 and a 2xCO2 climate, using a doubled CO2 version of the same GISS GCM.

Multi-Scale Surface Descriptors

PubMed Central

Cipriano, Gregory; Phillips, George N.; Gleicher, Michael

2010-01-01

Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190

Scale-up of ecological experiments: Density variation in the mobile bivalve Macomona liliana

USGS Publications Warehouse

Schneider, Davod C.; Walters, R.; Thrush, S.; Dayton, P.

1997-01-01

At present the problem of scaling up from controlled experiments (necessarily at a small spatial scale) to questions of regional or global importance is perhaps the most pressing issue in ecology. Most of the proposed techniques recommend iterative cycling between theory and experiment. We present a graphical technique that facilitates this cycling by allowing the scope of experiments, surveys, and natural history observations to be compared to the scope of models and theory. We apply the scope analysis to the problem of understanding the population dynamics of a bivalve exposed to environmental stress at the scale of a harbour. Previous lab and field experiments were found not to be 1:1 scale models of harbour-wide processes. Scope analysis allowed small scale experiments to be linked to larger scale surveys and to a spatially explicit model of population dynamics.

Geographic Information for Analysis of Highway Runoff-Quality Data on a National or Regional Scale in the Conterminous United States

USGS Publications Warehouse

Smieszek, Tomas W.; Granato, Gregory E.

2000-01-01

Spatial data are important for interpretation of water-quality information on a regional or national scale. Geographic information systems (GIS) facilitate interpretation and integration of spatial data. The geographic information and data compiled for the conterminous United States during the National Highway Runoff Water-Quality Data and Methodology Synthesis project is described in this document, which also includes information on the structure, file types, and the geographic information in the data files. This 'geodata' directory contains two subdirectories, labeled 'gisdata' and 'gisimage.' The 'gisdata' directory contains ArcInfo coverages, ArcInfo export files, shapefiles (used in ArcView), Spatial Data Transfer Standard Topological Vector Profile format files, and meta files in subdirectories organized by file type. The 'gisimage' directory contains the GIS data in common image-file formats. The spatial geodata includes two rain-zone region maps and a map of national ecosystems originally published by the U.S. Environmental Protection Agency; regional estimates of mean annual streamflow, and water hardness published by the Federal Highway Administration; and mean monthly temperature, mean annual precipitation, and mean monthly snowfall modified from data published by the National Climatic Data Center and made available to the public by the Oregon Climate Service at Oregon State University. These GIS files were compiled for qualitative spatial analysis of available data on a national and(or) regional scale and therefore should be considered as qualitative representations, not precise geographic location information.

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

Multiscale object-based drought monitoring and comparison in rainfed and irrigated agriculture from Landsat 8 OLI imagery

NASA Astrophysics Data System (ADS)

Ozelkan, Emre; Chen, Gang; Ustundag, Burak Berk

2016-02-01

Drought is a rapidly rising environmental issue that can cause hardly repaired or unrepaired damages to the nature and socio-economy. This is especially true for a region that features arid/semi-arid climate, including the Turkey's most important agricultural district - Southeast Anatolia. In this area, we examined the uncertainties of applying Landsat 8 Operational Land Imager (OLI) NDVI data to estimate meteorological drought - Standardized Precipitation Index (SPI) - measured from 31 in-situ agro-meteorological monitoring stations during spring and summer of 2013 and 2014. Our analysis was designed to address two important, yet under-examined questions: (i) how does the co-existence of rainfed and irrigated agriculture affect remote sensing drought monitoring in an arid/semi-arid region? (ii) What is the role of spatial scale in drought monitoring using a GEOBIA (geographic object-based image analysis) framework? Results show that spatial scale exerted a higher impact on drought monitoring especially in the drier year 2013, during which small scales were found to outperform large scales in general. In addition, consideration of irrigated and rainfed areas separately ensured a better performance in drought analysis. Compared to the positive correlations between SPI and NDVI over the rainfed areas, negative correlations were determined over the irrigated agricultural areas. Finally, the time lag effect was evident in the study, i.e., strong correlations between spring SPI and summer NDVI in both 2013 and 2014. This reflects the fact that spring watering is crucial for the growth and yield of the major crops (i.e., winter wheat, barley and lentil) cultivated in the region.

Optical differentiation between malignant and benign lymphadenopathy by grey scale texture analysis of endobronchial ultrasound convex probe images.

PubMed

Nguyen, Phan; Bashirzadeh, Farzad; Hundloe, Justin; Salvado, Olivier; Dowson, Nicholas; Ware, Robert; Masters, Ian Brent; Bhatt, Manoj; Kumar, Aravind Ravi; Fielding, David

2012-03-01

Morphologic and sonographic features of endobronchial ultrasound (EBUS) convex probe images are helpful in predicting metastatic lymph nodes. Grey scale texture analysis is a well-established methodology that has been applied to ultrasound images in other fields of medicine. The aim of this study was to determine if this methodology could differentiate between benign and malignant lymphadenopathy of EBUS images. Lymph nodes from digital images of EBUS procedures were manually mapped to obtain a region of interest and were analyzed in a prediction set. The regions of interest were analyzed for the following grey scale texture features in MATLAB (version 7.8.0.347 [R2009a]): mean pixel value, difference between maximal and minimal pixel value, SEM pixel value, entropy, correlation, energy, and homogeneity. Significant grey scale texture features were used to assess a validation set compared with fluoro-D-glucose (FDG)-PET-CT scan findings where available. Fifty-two malignant nodes and 48 benign nodes were in the prediction set. Malignant nodes had a greater difference in the maximal and minimal pixel values, SEM pixel value, entropy, and correlation, and a lower energy (P < .0001 for all values). Fifty-one lymph nodes were in the validation set; 44 of 51 (86.3%) were classified correctly. Eighteen of these lymph nodes also had FDG-PET-CT scan assessment, which correctly classified 14 of 18 nodes (77.8%), compared with grey scale texture analysis, which correctly classified 16 of 18 nodes (88.9%). Grey scale texture analysis of EBUS convex probe images can be used to differentiate malignant and benign lymphadenopathy. Preliminary results are comparable to FDG-PET-CT scan.

78 FR 29314 - Approval and Promulgation of State Implementation Plans; State of Utah; Interstate Transport of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-20

...) SIP submissions an adequate technical analysis to support their conclusions regarding interstate... acceptable modeling technical analyses are available, but EPA does not believe that modeling is required if... regional scale technical analysis, and Utah will point to that analysis in order to conclude that there are...

Geology of the Icy Galilean Satellites: Understanding Crustal Processes and Geologic Histories Through the JIMO Mission

NASA Technical Reports Server (NTRS)

Figueredo, P. H.; Tanaka, K.; Senske, D.; Greeley, R.

2003-01-01

Knowledge of the geology, style and time history of crustal processes on the icy Galilean satellites is necessary to understanding how these bodies formed and evolved. Data from the Galileo mission have provided a basis for detailed geologic and geo- physical analysis. Due to constrained downlink, Galileo Solid State Imaging (SSI) data consisted of global coverage at a -1 km/pixel ground sampling and representative, widely spaced regional maps at -200 m/pixel. These two data sets provide a general means to extrapolate units identified at higher resolution to lower resolution data. A sampling of key sites at much higher resolution (10s of m/pixel) allows evaluation of processes on local scales. We are currently producing the first global geological map of Europa using Galileo global and regional-scale data. This work is demonstrating the necessity and utility of planet-wide contiguous image coverage at global, regional, and local scales.

Multi-level structure in the large scale distribution of optically luminous galaxies

NASA Astrophysics Data System (ADS)

Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen

1992-04-01

Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.

Characterizing and modelling river channel migration rates at a regional scale: Case study of south-east France.

PubMed

Alber, Adrien; Piégay, Hervé

2017-11-01

An increased awareness by river managers of the importance of river channel migration to sediment dynamics, habitat complexity and other ecosystem functions has led to an advance in the science and practice of identifying, protecting or restoring specific erodible corridors across which rivers are free to migrate. One current challenge is the application of these watershed-specific goals at the regional planning scales (e.g., the European Water Framework Directive). This study provides a GIS-based spatial analysis of the channel migration rates at the regional-scale. As a case study, 99 reaches were sampled in the French part of the Rhône Basin and nearby tributaries of the Mediterranean Sea (111,300 km 2 ). We explored the spatial correlation between the channel migration rate and a set of simple variables (e.g., watershed area, channel slope, stream power, active channel width). We found that the spatial variability of the channel migration rates was primary explained by the gross stream power (R 2  = 0.48) and more surprisingly by the active channel width scaled by the watershed area. The relationship between the absolute migration rate and the gross stream power is generally consistent with the published empirical models for freely meandering rivers, whereas it is less significant for the multi-thread reaches. The discussion focused on methodological constraints for a regional-scale modelling of the migration rates, and the interpretation of the empirical models. We hypothesize that the active channel width scaled by the watershed area is a surrogate for the sediment supply which may be a more critical factor than the bank resistance for explaining the regional-scale variability of the migration rates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Negative Symptom Dimensions of the Positive and Negative Syndrome Scale Across Geographical Regions: Implications for Social, Linguistic, and Cultural Consistency.

PubMed

Khan, Anzalee; Liharska, Lora; Harvey, Philip D; Atkins, Alexandra; Ulshen, Daniel; Keefe, Richard S E

2017-12-01

Objective: Recognizing the discrete dimensions that underlie negative symptoms in schizophrenia and how these dimensions are understood across localities might result in better understanding and treatment of these symptoms. To this end, the objectives of this study were to 1) identify the Positive and Negative Syndrome Scale negative symptom dimensions of expressive deficits and experiential deficits and 2) analyze performance on these dimensions over 15 geographical regions to determine whether the items defining them manifest similar reliability across these regions. Design: Data were obtained for the baseline Positive and Negative Syndrome Scale visits of 6,889 subjects across 15 geographical regions. Using confirmatory factor analysis, we examined whether a two-factor negative symptom structure that is found in schizophrenia (experiential deficits and expressive deficits) would be replicated in our sample, and using differential item functioning, we tested the degree to which specific items from each negative symptom subfactor performed across geographical regions in comparison with the United States. Results: The two-factor negative symptom solution was replicated in this sample. Most geographical regions showed moderate-to-large differential item functioning for Positive and Negative Syndrome Scale expressive deficit items, especially N3 Poor Rapport, as compared with Positive and Negative Syndrome Scale experiential deficit items, showing that these items might be interpreted or scored differently in different regions. Across countries, except for India, the differential item functioning values did not favor raters in the United States. Conclusion: These results suggest that the Positive and Negative Syndrome Scale negative symptom factor can be better represented by a two-factor model than by a single-factor model. Additionally, the results show significant differences in responses to items representing the Positive and Negative Syndrome Scale expressive factors, but not the experiential factors, across regions. This could be due to a lack of equivalence between the original and translated versions, cultural differences with the interpretation of items, dissimilarities in rater training, or diversity in the understanding of scoring anchors. Knowing which items are challenging for raters across regions can help to guide Positive and Negative Syndrome Scale training and improve the results of international clinical trials aimed at negative symptoms.

The Functional Arm Scale for Throwers (FAST)-Part I: The Design and Development of an Upper Extremity Region-Specific and Population-Specific Patient-Reported Outcome Scale for Throwing Athletes.

PubMed

Sauers, Eric L; Bay, R Curtis; Snyder Valier, Alison R; Ellery, Traci; Huxel Bliven, Kellie C

2017-03-01

Upper extremity (UE) region-specific, patient-reported outcome (PRO) scales assess injuries to the UE but do not account for the demands of overhead throwing athletes or measure patient-oriented domains of health-related quality of life (HRQOL). To develop the Functional Arm Scale for Throwers (FAST), a UE region-specific and population-specific PRO scale that assesses multiple domains of disablement in throwing athletes with UE injuries. In stage I, a beta version of the scale was developed for subsequent factor identification, final item reduction, and construct validity analysis during stage II. Descriptive laboratory study. Three-stage scale development was utilized: Stage I (item generation and initial item reduction) and stage II (factor analysis, final item reduction, and construct validity) are reported herein, and stage III (establishment of measurement properties [reliability and validity]) will be reported in a companion paper. In stage I, a beta version was developed, incorporating National Center for Medical Rehabilitation Research disablement domains and ensuring a blend of sport-related and non-sport-related items. An expert panel and focus group assessed importance and interpretability of each item. During stage II, the FAST was reduced, preserving variance characteristics and factor structure of the beta version and construct validity of the final FAST scale. During stage I, a 54-item beta version and a separate 9-item pitcher module were developed. During stage II, a 22-item FAST and 9-item pitcher module were finalized. The factor solution for FAST scale items included pain (n = 6), throwing (n = 10), activities of daily living (n = 5), psychological impact (n = 4), and advancement (n = 3). The 6-item pain subscale crossed factors. The remaining subscales and pitcher module are distinctive, correlated, and internally consistent and may be interpreted individually or combined. This article describes the development of the FAST, which assesses clinical outcomes and HRQOL of throwing athletes after UE injury. The FAST encompasses multiple domains of disability and demonstrates excellent construct validity. The FAST provides a single UE region-specific and population-specific PRO scale for high-demand throwers to facilitate measurement of impact of UE injuries on HRQOL and clinical outcomes while quantifying recovery for comparative effectiveness studies.

Assessment of the 1997-1998 Asian Monsoon Anomalies

NASA Technical Reports Server (NTRS)

Lau, William K.-M.; Wu, H.-T.

1999-01-01

Using State-of-the-art satellite-gauge monthly rainfall estimate and optimally interpolated sea surface temperature (SST) data, we have assessed the 1997-98 Asian monsoon anomalies in terms of three basic causal factors: basin-scale SST, regional coupling, and internal variability. Singular Value Decomposition analysis of rainfall and SST are carried out globally over the entire tropics and regionally over the Asian monsoon domain. Contributions to monsoon rainfall predictability by various factors are evaluated from cumulative anomaly correlation with dominant regional SVD modes. Results reveal a dominant, large-scale monsoon-El Nino coupled mode with well-defined centers of action in the near-equatorial monsoon regions. it is noted that some subcontinental regions such as all-India, or arbitrarily chosen land regions over East Asia, while important socio-economically, are not near the centers of influence from El Nino, hence are not necessarily representative of the response of the entire monsoon region to El Nino. The observed 1997-98 Asian monsoon anomalies are found to be very complex with approximately 34% of the anomalies attributable to basin- scale SST influence associated with El Nino. Regional coupled processes contribute an additional 19%, leaving about 47% due to internal dynamics. Also noted is that the highest monsoon predictability is not necessary associated with major El Nino events (e.g. 1997, 1982) but rather in non-El Nino years (e.g. 1980, 1988) when contributions from the regional coupled modes far exceed those from the basin-scale SST. The results suggest that in order to improve monsoon seasonal-to-interannual predictability, there is a need to exploit not only monsoon-El Nino relationship, but also monsoon regional coupled processes and their modulation by long-term climate change.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications.

PubMed

Silvestro, Paolo Cosmo; Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio; Casa, Raffaele

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications

PubMed Central

Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations. PMID:29107963

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

PubMed

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

The 2014 southeast Brazil austral summer drought: regional scale mechanisms and teleconnections

NASA Astrophysics Data System (ADS)

Coelho, Caio A. S.; de Oliveira, Cristiano Prestrelo; Ambrizzi, Tércio; Reboita, Michelle Simões; Carpenedo, Camila Bertoletti; Campos, José Leandro Pereira Silveira; Tomaziello, Ana Carolina Nóbile; Pampuch, Luana Albertani; Custódio, Maria de Souza; Dutra, Lívia Marcia Mosso; Da Rocha, Rosmeri P.; Rehbein, Amanda

2016-06-01

The southeast region of Brazil experienced in austral summer 2014 a major drought event leading to a number of impacts in water availability for human consumption, agricultural irrigation and hydropower production. This study aims to perform a diagnostic analysis of the observed climate conditions during this event, including an inspection of the occurred precipitation anomalies in the context of previous years, and an investigation of possible relationships with sea surface temperatures and atmospheric circulation patterns. The sea surface temperature analysis revealed that the southwestern South Atlantic Ocean region near the coast of southeast Brazil showed strong negative association with precipitation over southeast Brazil, indicating that increased sea temperatures in this ocean region are consistent with reduced precipitation as observed in summer 2014. The circulation analysis revealed prevailing anti-cyclonic anomalies at lower levels (850 hPa) with northerly anomalies to the west of southeast Brazil, channeling moisture from the Amazon towards Paraguay, northern Argentina and southern Brazil, and drier than normal air from the South Atlantic Ocean towards the southeast region of Brazil. This circulation pattern was found to be part of a large-scale teleconnection wave train linked with the subsidence branch of the Walker circulation in the tropical east Pacific, which in turn was generated by an anomalous tropical heat source in north/northeastern Australia. A regional Hadley circulation with an ascending branch to the south of the subsidence branch of the Walker circulation in the tropical east Pacific was identified as an important component connecting the tropical and extratropical circulation. The ascending branch of this Hadley circulation in the south Pacific coincided with an identified Rossby wave source region, which contributed to establishing the extratropical component of the large-scale wave train connecting the south Pacific and the Atlantic region surrounding southeast Brazil. This connection between the Pacific and the Atlantic was confirmed with Rossby ray tracing analyses. The local circulation response was associated to downward air motion (subsidence) over Southeast Brazil, contributing to the expressive negative precipitation anomalies observed during summer 2014, and leading to a major drought event in the historical context. The analysis of atmospheric and oceanic patterns of this event helped defining a schematic framework leading to the observed drought conditions in southeast Brazil, including the involved teleconnections, blocking high pressure, radiative and humidity transport effects.

Regional climates in the GISS general circulation model: Surface air temperature

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

Floating Offshore Wind in Oregon: Potential for Jobs and Economic Impacts in Oregon Coastal Counties from Two Future Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jimenez, Tony; Keyser, David; Tegen, Suzanne

This analysis examines the employment and potential economic impacts of large-scale deployment of offshore wind technology off the coast of Oregon. This analysis examines impacts within the seven Oregon coastal counties: Clatsop, Tillamook, Lincoln, Lane, Douglas, Coos, and Curry. The impacts highlighted here can be used in county, state, and regional planning discussions and can be scaled to get a general sense of the economic development opportunities associated with other deployment scenarios.

Analysis of central enterprise architecture elements in models of six eHealth projects.

PubMed

Virkanen, Hannu; Mykkänen, Juha

2014-01-01

Large-scale initiatives for eHealth services have been established in many countries on regional or national level. The use of Enterprise Architecture has been suggested as a methodology to govern and support the initiation, specification and implementation of large-scale initiatives including the governance of business changes as well as information technology. This study reports an analysis of six health IT projects in relation to Enterprise Architecture elements, focusing on central EA elements and viewpoints in different projects.

Regional hydro-climatic impacts of contemporary Amazonian deforestation

NASA Astrophysics Data System (ADS)

Khanna, Jaya

More than 17% of the Amazon rainforest has been cleared in the past three decades triggering important climatological and societal impacts. This thesis is devoted to identifying and explaining the regional hydroclimatic impacts of this change employing multidecadal satellite observations and numerical simulations providing an integrated perspective on this topic. The climatological nature of this study motivated the implementation and application of a cloud detection technique to a new geostationary satellite dataset. The resulting sub daily, high spatial resolution, multidecadal time series facilitated the detection of trends and variability in deforestation triggered cloud cover changes. The analysis was complemented by satellite precipitation, reanalysis and ground based datasets and attribution with the variable resolution Ocean-Land-Atmosphere-Model. Contemporary Amazonian deforestation affects spatial scales of hundreds of kilometers. But, unlike the well-studied impacts of a few kilometers scale deforestation, the climatic response to contemporary, large scale deforestation is neither well observed nor well understood. Employing satellite datasets, this thesis shows a transition in the regional hydroclimate accompanying increasing scales of deforestation, with downwind deforested regions receiving 25% more and upwind deforested regions receiving 25% less precipitation from the deforested area mean. Simulations robustly reproduce these shifts when forced with increasing deforestation alone, suggesting a negligible role of large-scale decadal climate variability in causing the shifts. Furthermore, deforestation-induced surface roughness variations are found necessary to reproduce the observed spatial patterns in recent times illustrating the strong scale-sensitivity of the climatic response to Amazonian deforestation. This phenomenon, inconsequential during the wet season, is found to substantially affect the regional hydroclimate in the local dry and parts of transition seasons, hence occurring in atmospheric conditions otherwise less conducive to thermal convection. Evidence of this phenomenon is found at two large scale deforested areas considered in this thesis. Hence, the 'dynamical' mechanism, which affects the seasons most important for regional ecology, emerges as an impactful convective triggering mechanism. The phenomenon studied in this thesis provides context for thinking about the climate of a future, more patchily forested Amazonia, by articulating relationships between climate and spatial scales of deforestation.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

Can Regional Climate Models be used in the assessment of vulnerability and risk caused by extreme events?

NASA Astrophysics Data System (ADS)

Nunes, Ana

2015-04-01

Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme events also helps the development of a system for decision-making, regarding natural and social disasters, and reducing impacts. Numerical experiments using this regional modeling system successfully modeled severe weather events in Brazil. Comparisons with the NCEP Climate Forecast System Reanalysis outputs were made at resolutions of about 40- and 25-km of the regional climate model.

Landscape-scale analysis of aboveground tree carbon stocks affected by mountain pine beetles in Idaho

Treesearch

Benjamin Bright; J. A. Hicke; A. T. Hudak

2012-01-01

Bark beetle outbreaks kill billions of trees in western North America, and the resulting tree mortality can significantly impact local and regional carbon cycling. However, substantial variability in mortality occurs within outbreak areas. Our objective was to quantify landscape-scale effects of beetle infestations on aboveground carbon (AGC) stocks using field...

Multiplex Ligation-Dependent Probe Amplification Analysis on Capillary Electrophoresis Instruments for a Rapid Gene Copy Number Study

PubMed Central

Jankowski, Stéphane; Currie-Fraser, Erica; Xu, Licen; Coffa, Jordy

2008-01-01

Annotated DNA samples that had been previously analyzed were tested using multiplex ligation-dependent probe amplification (MLPA) assays containing probes targeting BRCA1, BRCA2, and MMR (MLH1/MSH2 genes) and the 9p21 chromosomal region. MLPA polymerase chain reaction products were separated on a capillary electrophoresis platform, and the data were analyzed using GeneMapper v4.0 software (Applied Biosystems, Foster City, CA). After signal normalization, loci regions that had undergone deletions or duplications were identified using the GeneMapper Report Manager and verified using the DyeScale functionality. The results highlight an easy-to-use, optimal sample preparation and analysis workflow that can be used for both small- and large-scale studies. PMID:19137113

The spectroscopic (FT-IR, FT-Raman, UV) and first order hyperpolarizability, HOMO and LUMO analysis of 3-aminobenzophenone by density functional method

NASA Astrophysics Data System (ADS)

Karabacak, M.; Kurt, M.; Cinar, M.; Ayyappan, S.; Sudha, S.; Sundaraganesan, N.

In this work, experimental and theoretical study on the molecular structure and the vibrational spectra of 3-aminobenzophenone (3-ABP) is presented. The vibrational frequencies of the title compound were obtained theoretically by DFT/B3LYP calculations employing the standard 6-311++G(d,p) basis set for optimized geometry and were compared with Fourier transform infrared spectrum (FTIR) in the region of 400-4000 cm-1 and with Fourier Transform Raman spectrum in the region of 50-4000 cm-1. Complete vibrational assignments, analysis and correlation of the fundamental modes for the title compound were carried out. The vibrational harmonic frequencies were scaled using scale factor, yielding a good agreement between the experimentally recorded and the theoretically calculated values.

Spatial feature analysis of a cosmic-ray sensor for measuring the soil water content: Comparison of four weighting methods

NASA Astrophysics Data System (ADS)

Cai, Jingya; Pang, Zhiguo; Fu, Jun'e.

2018-04-01

To quantitatively analyze the spatial features of a cosmic-ray sensor (CRS) (i.e., the measurement support volume of the CRS and the weight of the in situ point-scale soil water content (SWC) in terms of the regionally averaged SWC derived from the CRS) in measuring the SWC, cooperative observations based on CRS, oven drying and frequency domain reflectometry (FDR) methods are performed at the point and regional scales in a desert steppe area of the Inner Mongolia Autonomous Region. This region is flat with sparse vegetation cover consisting of only grass, thereby minimizing the effects of terrain and vegetation. Considering the two possibilities of the measurement support volume of the CRS, the results of four weighting methods are compared with the SWC monitored by FDR within an appropriate measurement support volume. The weighted average calculated using the neutron intensity-based weighting method (Ni weighting method) best fits the regionally averaged SWC measured by the CRS. Therefore, we conclude that the gyroscopic support volume and the weights determined by the Ni weighting method are the closest to the actual spatial features of the CRS when measuring the SWC. Based on these findings, a scale transformation model of the SWC from the point scale to the scale of the CRS measurement support volume is established. In addition, the spatial features simulated using the Ni weighting method are visualized by developing a software system.

Regional and local species richness in an insular environment: Serpentine plants in California

USGS Publications Warehouse

Harrison, S.; Safford, H.D.; Grace, J.B.; Viers, J.H.; Davies, K.F.

2006-01-01

We asked how the richness of the specialized (endemic) flora of serpentine rock outcrops in California varies at both the regional and local scales. Our study had two goals: first, to test whether endemic richness is affected by spatial habitat structure (e.g., regional serpentine area, local serpentine outcrop area, regional and local measures of outcrop isolation), and second, to conduct this test in the context of a broader assessment of environmental influences (e.g., climate, soils, vegetation, disturbance) and historical influences (e.g., geologic age, geographic province) on local and regional species richness. We measured endemic and total richness and environmental variables in 109 serpentine sites (1000-m2 paired plots) in 78 serpentine-containing regions of the state. We used structural equation modeling (SEM) to simultaneously relate regional richness to regionalscale predictors, and local richness to both local-scale and regional-scale predictors. Our model for serpentine endemics explained 66% of the variation in local endemic richness based on local environment (vegetation, soils, rock cover) and on regional endemic richness. It explained 73% of the variation in regional endemic richness based on regional environment (climate and productivity), historical factors (geologic age and geographic province), and spatial structure (regional total area of serpentine, the only significant spatial variable in our analysis). We did not find a strong influence of spatial structure on species richness. However, we were able to distinguish local vs. regional influences on species richness to a novel extent, despite the existence of correlations between local and regional conditions. ?? 2006 by the Ecological Society of America.

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region

PubMed Central

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-01

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management. PMID:29342852

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region.

PubMed

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-13

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management.

Modeling the Impact of Uganda's Safe Male Circumcision Program: Implications for Age and Regional Targeting.

PubMed

Kripke, Katharine; Vazzano, Andrea; Kirungi, William; Musinguzi, Joshua; Opio, Alex; Ssempebwa, Rhobbinah; Nakawunde, Susan; Kyobutungi, Sheila; Akao, Juliet N; Magala, Fred; Mwidu, George; Castor, Delivette; Njeuhmeli, Emmanuel

2016-01-01

Uganda aims to provide safe male circumcision (SMC) to 80% of men ages 15-49 by 2016. To date, only 2 million men have received SMC of the 4.2 million men required. In response to age and regional trends in SMC uptake, the country sought to re-examine its targets with respect to age and subnational region, to assess the program's progress, and to refine the implementation approach. The Decision Makers' Program Planning Tool, Version 2.0 (DMPPT 2.0), was used in conjunction with incidence projections from the Spectrum/AIDS Impact Module (AIM) to conduct this analysis. Population, births, deaths, and HIV incidence and prevalence were used to populate the model. Baseline male circumcision prevalence was derived from the 2011 AIDS Indicator Survey. Uganda can achieve the most immediate impact on HIV incidence by circumcising men ages 20-34. This group will also require the fewest circumcisions for each HIV infection averted. Focusing on men ages 10-19 will offer the greatest impact over a 15-year period, while focusing on men ages 15-34 offers the most cost-effective strategy over the same period. A regional analysis showed little variation in cost-effectiveness of scaling up SMC across eight regions. Scale-up is cost-saving in all regions. There is geographic variability in program progress, highlighting two regions with low baseline rates of circumcision where additional efforts will be needed. Focusing SMC efforts on specific age groups and regions may help to accelerate Uganda's SMC program progress. Policy makers in Uganda have already used model outputs in planning efforts, proposing males ages 10-34 as a priority group for SMC in the 2014 application to the Global Fund's new funding model. As scale-up continues, the country should also consider a greater effort to expand SMC in regions with low MC prevalence.

Modeling the Impact of Uganda’s Safe Male Circumcision Program: Implications for Age and Regional Targeting

PubMed Central

Kripke, Katharine; Vazzano, Andrea; Kirungi, William; Musinguzi, Joshua; Opio, Alex; Ssempebwa, Rhobbinah; Nakawunde, Susan; Kyobutungi, Sheila; Akao, Juliet N.; Magala, Fred; Mwidu, George; Castor, Delivette

2016-01-01

Background Uganda aims to provide safe male circumcision (SMC) to 80% of men ages 15–49 by 2016. To date, only 2 million men have received SMC of the 4.2 million men required. In response to age and regional trends in SMC uptake, the country sought to re-examine its targets with respect to age and subnational region, to assess the program’s progress, and to refine the implementation approach. Methods and Findings The Decision Makers’ Program Planning Tool, Version 2.0 (DMPPT 2.0), was used in conjunction with incidence projections from the Spectrum/AIDS Impact Module (AIM) to conduct this analysis. Population, births, deaths, and HIV incidence and prevalence were used to populate the model. Baseline male circumcision prevalence was derived from the 2011 AIDS Indicator Survey. Uganda can achieve the most immediate impact on HIV incidence by circumcising men ages 20–34. This group will also require the fewest circumcisions for each HIV infection averted. Focusing on men ages 10–19 will offer the greatest impact over a 15-year period, while focusing on men ages 15–34 offers the most cost-effective strategy over the same period. A regional analysis showed little variation in cost-effectiveness of scaling up SMC across eight regions. Scale-up is cost-saving in all regions. There is geographic variability in program progress, highlighting two regions with low baseline rates of circumcision where additional efforts will be needed. Conclusion Focusing SMC efforts on specific age groups and regions may help to accelerate Uganda’s SMC program progress. Policy makers in Uganda have already used model outputs in planning efforts, proposing males ages 10–34 as a priority group for SMC in the 2014 application to the Global Fund’s new funding model. As scale-up continues, the country should also consider a greater effort to expand SMC in regions with low MC prevalence. PMID:27410234

Landslide Hazard Assessment In Mountaneous Area of Uzbekistan

NASA Astrophysics Data System (ADS)

Nyazov, R. A.; Nurtaev, B. S.

Because of the growth of population and caretaking of the flat areas under agricul- ture, mountain areas have been intensively mastered, producing increase of natural and technogenic processes in Uzbekistan last years. The landslides are the most dan- gerous phenomena and 7240 of them happened during last 40 years. More than 50 % has taken place in the term of 1991 - 2000 years. The situation is aggravated be- cause these regions are situated in zones, where disastrous earthquakes with M> 7 occurred in past and are expected in the future. Continuing seismic gap in Uzbek- istan during last 15-20 years and last disastrous earthquakes occurred in Afghanistan, Iran, Turkey, Greece, Taiwan and India worry us. On the basis of long-term observa- tions the criteria of landslide hazard assessment (suddenness, displacement interval, straight-line directivity, kind of residential buildings destruction) are proposed. This methodology was developed on two geographic levels: local (town scale) and regional (region scale). Detailed risk analysis performed on a local scale and extrapolated to the regional scale. Engineering-geologic parameters content of hazard estimation of landslides and mud flows also is divided into regional and local levels. Four degrees of danger of sliding processes are distinguished for compiling of small-scale, medium- and large-scale maps. Angren industrial area in Tien-Shan mountain is characterized by initial seismic intensity of 8-9 (MSC scale). Here the human technological activity (open-cast mining) has initiated the forming of the large landslide that covers more- over 8 square kilometers and corresponds to a volume of 800 billion cubic meters. In turn the landslide influence can become the source of industrial emergencies. On an example of Angren industrial mining region, the different scenarios on safety control of residing of the people and motion of transport, regulating technologies definition of field improvement and exploitation of mountain water reservoirs are proposed for prevention of dangerous geological processes.

Links between global meat trade and organic river pollution

NASA Astrophysics Data System (ADS)

Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick

2017-04-01

Rising demand of meat boosts livestock farming intensification. Due to international meat trade, the environmental costs of production are becoming increasingly separated from where the meat is consumed. However, little is known about the impact of trade on the environment for both importers and exporters. Combining multi-scale (national, regional and gridded) data, we present a new method to quantify the impacts of international meat trade on global river organic pollution. We computed spatially distributed organic pollution in global river networks with and without meat trade, where the without-trade scenario assumes that meat imports are replaced by local production. Our analysis indicates high potential savings of livestock population and pollutants production at the global scale due to the international meat trade. The spatially detailed analysis shows that current trade contributes to organic pollution reductions in meat importing regions, especially in rich nations. The deterioration of river water quality, especially in developing regions, points to an urgent need for affordable infrastructure and technology development and wastewater solutions.

Multi-scale landslide hazard assessment: Advances in global and regional methodologies

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Peters-Lidard, Christa; Adler, Robert; Hong, Yang

2010-05-01

The increasing availability of remotely sensed surface data and precipitation provides a unique opportunity to explore how smaller-scale landslide susceptibility and hazard assessment methodologies may be applicable at larger spatial scales. This research first considers an emerging satellite-based global algorithm framework, which evaluates how the landslide susceptibility and satellite derived rainfall estimates can forecast potential landslide conditions. An analysis of this algorithm using a newly developed global landslide inventory catalog suggests that forecasting errors are geographically variable due to improper weighting of surface observables, resolution of the current susceptibility map, and limitations in the availability of landslide inventory data. These methodological and data limitation issues can be more thoroughly assessed at the regional level, where available higher resolution landslide inventories can be applied to empirically derive relationships between surface variables and landslide occurrence. The regional empirical model shows improvement over the global framework in advancing near real-time landslide forecasting efforts; however, there are many uncertainties and assumptions surrounding such a methodology that decreases the functionality and utility of this system. This research seeks to improve upon this initial concept by exploring the potential opportunities and methodological structure needed to advance larger-scale landslide hazard forecasting and make it more of an operational reality. Sensitivity analysis of the surface and rainfall parameters in the preliminary algorithm indicates that surface data resolution and the interdependency of variables must be more appropriately quantified at local and regional scales. Additionally, integrating available surface parameters must be approached in a more theoretical, physically-based manner to better represent the physical processes underlying slope instability and landslide initiation. Several rainfall infiltration and hydrological flow models have been developed to model slope instability at small spatial scales. This research investigates the potential of applying a more quantitative hydrological model to larger spatial scales, utilizing satellite and surface data inputs that are obtainable over different geographic regions. Due to the significant role that data and methodological uncertainties play in the effectiveness of landslide hazard assessment outputs, the methodology and data inputs are considered within an ensemble uncertainty framework in order to better resolve the contribution and limitations of model inputs and to more effectively communicate the model skill for improved landslide hazard assessment.

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

NASA Astrophysics Data System (ADS)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Species turnover drives β-diversity patterns across multiple spatial scales of plant-galling interactions in mountaintop grasslands.

PubMed

Coelho, Marcel Serra; Carneiro, Marco Antônio Alves; Branco, Cristina Alves; Borges, Rafael Augusto Xavier; Fernandes, Geraldo Wilson

2018-01-01

This study describes differences in species richness and composition of the assemblages of galling insects and their host plants at different spatial scales. Sampling was conducted along altitudinal gradients composed of campos rupestres and campos de altitude of two mountain complexes in southeastern Brazil: Espinhaço Range and Mantiqueira Range. The following hypotheses were tested: i) local and regional richness of host plants and galling insects are positively correlated; ii) beta diversity is the most important component of regional diversity of host plants and galling insects; and iii) Turnover is the main mechanism driving beta diversity of both host plants and galling insects. Local richness of galling insects and host plants increased with increasing regional richness of species, suggesting a pattern of unsaturated communities. The additive partition of regional richness (γ) into local and beta components shows that local richnesses (α) of species of galling insects and host plants are low relative to regional richness; the beta (β) component incorporates most of the regional richness. The multi-scale analysis of additive partitioning showed similar patterns for galling insects and host plants with the local component (α) incorporated a small part of regional richness. Beta diversity of galling insects and host plants were mainly the result of turnover, with little contribution from nesting. Although the species composition of galling insects and host plant species varied among sample sites, mountains and even mountain ranges, local richness remained relatively low. In this way, the addition of local habitats with different landscapes substantially affects regional richness. Each mountain contributes fundamentally to the composition of regional diversity of galling insects and host plants, and so the design of future conservation strategies should incorporate multiple scales.

Development of a composite repair and the associated inspection intervals for the F-111C stiffener runout region

NASA Technical Reports Server (NTRS)

Jones, R.; Molent, L.; Paul, J.; Saunders, T.; Chiu, W. K.

1994-01-01

This paper presents an overview of the structural aspects of the design and development of a local reinforcement designed to lower the stresses in a region of the F-111C wing fitting which is prone to cracking. The stress analysis, with particular emphasis on the use of a unified constitutive model for the cyclic inelastic response of the structure, representative specimen testing, thermal analysis and full scale static testing of this design are summarized.

Multiple-length-scale deformation analysis in a thermoplastic polyurethane

PubMed Central

Sui, Tan; Baimpas, Nikolaos; Dolbnya, Igor P.; Prisacariu, Cristina; Korsunsky, Alexander M.

2015-01-01

Thermoplastic polyurethane elastomers enjoy an exceptionally wide range of applications due to their remarkable versatility. These block co-polymers are used here as an example of a structurally inhomogeneous composite containing nano-scale gradients, whose internal strain differs depending on the length scale of consideration. Here we present a combined experimental and modelling approach to the hierarchical characterization of block co-polymer deformation. Synchrotron-based small- and wide-angle X-ray scattering and radiography are used for strain evaluation across the scales. Transmission electron microscopy image-based finite element modelling and fast Fourier transform analysis are used to develop a multi-phase numerical model that achieves agreement with the combined experimental data using a minimal number of adjustable structural parameters. The results highlight the importance of fuzzy interfaces, that is, regions of nanometre-scale structure and property gradients, in determining the mechanical properties of hierarchical composites across the scales. PMID:25758945

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Three-dimensional constrained variational analysis: Approach and application to analysis of atmospheric diabatic heating and derivative fields during an ARM SGP intensive observational period

NASA Astrophysics Data System (ADS)

Tang, Shuaiqi; Zhang, Minghua

2015-08-01

Atmospheric vertical velocities and advective tendencies are essential large-scale forcing data to drive single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulations (LESs). However, they cannot be directly measured from field measurements or easily calculated with great accuracy. In the Atmospheric Radiation Measurement Program (ARM), a constrained variational algorithm (1-D constrained variational analysis (1DCVA)) has been used to derive large-scale forcing data over a sounding network domain with the aid of flux measurements at the surface and top of the atmosphere (TOA). The 1DCVA algorithm is now extended into three dimensions (3DCVA) along with other improvements to calculate gridded large-scale forcing data, diabatic heating sources (Q1), and moisture sinks (Q2). Results are presented for a midlatitude cyclone case study on 3 March 2000 at the ARM Southern Great Plains site. These results are used to evaluate the diabatic heating fields in the available products such as Rapid Update Cycle, ERA-Interim, National Centers for Environmental Prediction Climate Forecast System Reanalysis, Modern-Era Retrospective Analysis for Research and Applications, Japanese 55-year Reanalysis, and North American Regional Reanalysis. We show that although the analysis/reanalysis generally captures the atmospheric state of the cyclone, their biases in the derivative terms (Q1 and Q2) at regional scale of a few hundred kilometers are large and all analyses/reanalyses tend to underestimate the subgrid-scale upward transport of moist static energy in the lower troposphere. The 3DCVA-gridded large-scale forcing data are physically consistent with the spatial distribution of surface and TOA measurements of radiation, precipitation, latent and sensible heat fluxes, and clouds that are better suited to force SCMs, CRMs, and LESs. Possible applications of the 3DCVA are discussed.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

On The Evidence For Large-Scale Galactic Conformity In The Local Universe

NASA Astrophysics Data System (ADS)

Sin, Larry P. T.; Lilly, Simon J.; Henriques, Bruno M. B.

2017-10-01

We re-examine the observational evidence for large-scale (4 Mpc) galactic conformity in the local Universe, as presented in Kauffmann et al. We show that a number of methodological features of their analysis act to produce a misleadingly high amplitude of the conformity signal. These include a weighting in favour of central galaxies in very high density regions, the likely misclassification of satellite galaxies as centrals in the same high-density regions and the use of medians to characterize bimodal distributions. We show that the large-scale conformity signal in Kauffmann et al. clearly originates from a very small number of central galaxies in the vicinity of just a few very massive clusters, whose effect is strongly amplified by the methodological issues that we have identified. Some of these 'centrals' are likely misclassified satellites, but some may be genuine centrals showing a real conformity effect. Regardless, this analysis suggests that conformity on 4 Mpc scales is best viewed as a relatively short-range effect (at the virial radius) associated with these very large neighbouring haloes, rather than a very long-range effect (at tens of virial radii) associated with the relatively low-mass haloes that host the nominal central galaxies in the analysis. A mock catalogue constructed from a recent semi-analytic model shows very similar conformity effects to the data when analysed in the same way, suggesting that there is no need to introduce new physical processes to explain galactic conformity on 4 Mpc scales.

Regional Data Assimilation of AIRS Profiles and Radiances at the SPoRT Center

NASA Technical Reports Server (NTRS)

Zavodsky, Brad; Chou, Shih-hung; Jedlovec, Gary

2009-01-01

This slide presentation reviews the Short Term Prediction Research and Transition (SPoRT) Center's mission to improve short-term weather prediction at the regional and local scale. It includes information on the cold bias in Weather Research and Forcasting (WRF), troposphere recordings from the Atmospheric Infrared Sounder (AIRS), and vertical resolution of analysis grid.

Scaling analysis of the non-Abelian quasiparticle tunneling in Z}}_k FQH states

NASA Astrophysics Data System (ADS)

Li, Qi; Jiang, Na; Wan, Xin; Hu, Zi-Xiang

2018-06-01

Quasiparticle tunneling between two counter propagating edges through point contacts could provide information on its statistics. Previous study of the short distance tunneling displays a scaling behavior, especially in the conformal limit with zero tunneling distance. The scaling exponents for the non-Abelian quasiparticle tunneling exhibit some non-trivial behaviors. In this work, we revisit the quasiparticle tunneling amplitudes and their scaling behavior in a full range of the tunneling distance by putting the electrons on the surface of a cylinder. The edge–edge distance can be smoothly tuned by varying the aspect ratio for a finite size cylinder. We analyze the scaling behavior of the quasiparticles for the Read–Rezayi states for and 4 both in the short and long tunneling distance region. The finite size scaling analysis automatically gives us a critical length scale where the anomalous correction appears. We demonstrate this length scale is related to the size of the quasiparticle at which the backscattering between two counter propagating edges starts to be significant.

Coronal Heating and the Magnetic Flux Content of the Network

NASA Technical Reports Server (NTRS)

Falconer, D. A.; Moore, R. L.; Porter, J. G.; Hathaway, D. H.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

Previously, from analysis of SOHO/EIT coronal images in combination with Kitt Peak magnetograms (Falconer et al 1998, ApJ, 501, 386-396), we found that the quiet corona is the sum of two components: the e-scale corona and the coronal network. The large-scale corona consists of all coronal-temperature (T approx. 10(exp 6) K) structures larger than supergranules (>approx.30,000 km). The coronal network (1) consists of all coronal-temperature structures smaller than supergranules, (2) is rooted in and loosely traces the photospheric magnetic network, (3) has its brightest features seated on polarity dividing fines (neutral lines) in the network magnetic flux, and (4) produces only about 5% of the total coronal emission in quiet regions. The heating of the coronal network is apparently magnetic in origin. Here, from analysis of EIT coronal images of quiet regions in combination with magnetograms of the same quiet regions from SOHO/MDI and from Kitt Peak, we examine the other 95% of the quiet corona and its relation to the underlying magnetic network. We find: (1) Dividing the large-scale corona into its bright and dim halves divides the area into bright "continents" and dark "oceans" having spans of 2-4 supergranules. (2) These patterns are also present in the photospheric magnetograms: the network is stronger under the bright half and weaker under the dim half. (3) The radiation from the large-scale corona increases roughly as the cube root of the magnetic flux content of the underlying magnetic network. In contrast, Fisher et A (1998, ApJ, 508, 985-998) found that the coronal radiation from an active region increases roughly linearly with the magnetic flux content of the active region. We assume, as is widely held, that nearly all of the large-scale corona is magnetically rooted in the network. Our results, together with the result of Fisher et al (1999), suggest that either the coronal heating in quiet regions has a large non-magnetic component, or, if the heating is predominantly produced via the magnetic field, the mechanism is significantly different than in active regions. This work is funded by NASA's Office of Space Science through the Solar Physics Supporting Research and Technology Program and the Sun-Earth Connection Guest Investigator Program.

Developing a high-resolution regional atmospheric reanalysis for Australia

NASA Astrophysics Data System (ADS)

White, Christopher; Fox-Hughes, Paul; Su, Chun-Hsu; Jakob, Dörte; Kociuba, Greg; Eisenberg, Nathan; Steinle, Peter; Harris, Rebecca; Corney, Stuart; Love, Peter; Remenyi, Tomas; Chladil, Mark; Bally, John; Bindoff, Nathan

2017-04-01

A dynamically consistent, long-term atmospheric reanalysis can be used to support high-quality assessments of environmental risk and likelihood of extreme events. Most reanalyses are presently based on coarse-scale global systems that are not suitable for regional assessments in fire risk, water and natural resources, amongst others. The Australian Bureau of Meteorology is currently working to close this gap by producing a high-resolution reanalysis over the Australian and New Zealand region to construct a sequence of atmospheric conditions at sub-hourly intervals over the past 25 years from 1990. The Australia reanalysis consists of a convective-scale analysis nested within a 12 km regional-scale reanalysis, which is bounded by a coarse-scale ERA-Interim reanalysis that provides the required boundary and initial conditions. We use an unchanging atmospheric modelling suite based on the UERRA system used at the UK Met Office and the more recent version of the Bureau of Meteorology's operational numerical prediction model used in ACCESS-R (Australian Community Climate and Earth-System Simulator-Regional system). An advanced (4-dimensional variational) data assimilation scheme is used to optimally combine model physics with multiple observations from aircrafts, sondes, surface observations and satellites to create a best estimate of state of the atmosphere over a 6-hour moving window. This analysis is in turn used to drive a higher-resolution (1.5 km) downscaling model over selected subdomains within Australia, currently eastern New South Wales and Tasmania, with the capability to support this anywhere in the Australia-New Zealand domain. The temporal resolution of the gridded analysis fields for both the regional and higher-resolution subdomains are generally one hour, with many fields such as 10 m winds and 2 m temperatures available every 10 minutes. The reanalysis also produces many other variables that include wind, temperature, moisture, pressure, cloud cover, precipitation, evaporation, soil water, and energy fluxes. In this presentation, we report on the implementation of the Australia regional reanalysis and results from first stages of the project, with a focus on the Tasmanian subdomain. An initial benchmarking 1.5 km data set - referred to as the 'Initial Analysis' - has been constructed over the subdomains consisting of regridded and harmonised analysis and short-term forecast fields from the operational ACCESS-C model using the past 5 years (2011-2015) of archived data. Evaluation of the Initial Analysis against surface observations from automatic weather stations indicate changes in model skills over time that may be attributed to changes in NWP and assimilation systems, and model cycling frequency. Preliminary evaluations of the reanalysis across Tasmania and its inter-comparisons with the Initial Analysis and the ERA-Interim reanalysis products will be presented, including some features across the Tasmanian subdomain such as means and extremes of analysed weather variables. Finally, we describe a number of applications across Tasmania of the reanalysis of immediate interest to meteorologists, fire and landscape managers and other members of the emergency management community, including the use of the data to create post-processed fields such as soil dryness, tornados and fire danger indices for forest fire danger risk assessment, including a climatology of Continuous Haines Index.

A Scaling Analysis of Frequency Dependent Energy Partition for Local and Regional Seismic Phases from Explosions

DTIC Science & Technology

2007-08-31

explosions at the former Soviet Semipalatinsk test site (STS). Labeled stations are those for which high resolution digital data are available. 12 8...characteristics of regional phase observations from underground nuclear explosions at the former Soviet Semipalatinsk and Novaya Zemlya test sites , the...various regional phases observed from underground nuclear explosions at the former Soviet Semipalatinsk test site (STS). Labeled stations are those for

Remote sensing applied to prospecting of thermomineral water in the county of Caldas Novas-Goias

NASA Technical Reports Server (NTRS)

Veneziani, P.; Eustaquiodosanjos, C.

1978-01-01

LANDSAT imagery of the region were studied allowing the placement of the area of study in the regional geological context. A geological mapping of the 1.60.000 scale was done. A methodology was developed which consisted in a regional temperature mapping using trend surface analysis. Through the correlation of all these data, four different areas were localized with a high potential as thermomineral sources.

The high-resolution regional reanalysis COSMO-REA6

NASA Astrophysics Data System (ADS)

Ohlwein, C.

2016-12-01

Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers the past 20 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.

A high-resolution regional reanalysis for Europe

NASA Astrophysics Data System (ADS)

Ohlwein, C.

2015-12-01

Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers the past 20 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glascoe, Lee; Gowardhan, Akshay; Lennox, Kristin

In the interest of promoting the international exchange of technical expertise, the US Department of Energy’s Office of Emergency Operations (NA-40) and the French Commissariat à l'Energie Atomique et aux énergies alternatives (CEA) requested that the National Atmospheric Release Advisory Center (NARAC) of Lawrence Livermore National Laboratory (LLNL) in Livermore, California host a joint table top exercise with experts in emergency management and atmospheric transport modeling. In this table top exercise, LLNL and CEA compared each other’s flow and dispersion models. The goal of the comparison is to facilitate the exchange of knowledge, capabilities, and practices, and to demonstrate themore » utility of modeling dispersal at different levels of computational fidelity. Two modeling approaches were examined, a regional scale modeling approach, appropriate for simple terrain and/or very large releases, and an urban scale modeling approach, appropriate for small releases in a city environment. This report is a summary of LLNL and CEA modeling efforts from this exercise. Two different types of LLNL and CEA models were employed in the analysis: urban-scale models (Aeolus CFD at LLNL/NARAC and Parallel- Micro-SWIFT-SPRAY, PMSS, at CEA) for analysis of a 5,000 Ci radiological release and Lagrangian Particle Dispersion Models (LODI at LLNL/NARAC and PSPRAY at CEA) for analysis of a much larger (500,000 Ci) regional radiological release. Two densely-populated urban locations were chosen: Chicago with its high-rise skyline and gridded street network and Paris with its more consistent, lower building height and complex unaligned street network. Each location was considered under early summer daytime and nighttime conditions. Different levels of fidelity were chosen for each scale: (1) lower fidelity mass-consistent diagnostic, intermediate fidelity Navier-Stokes RANS models, and higher fidelity Navier-Stokes LES for urban-scale analysis, and (2) lower-fidelity single-profile meteorology versus higher-fidelity three-dimensional gridded weather forecast for regional-scale analysis. Tradeoffs between computation time and the fidelity of the results are discussed for both scales. LES, for example, requires nearly 100 times more processor time than the mass-consistent diagnostic model or the RANS model, and seems better able to capture flow entrainment behind tall buildings. As anticipated, results obtained by LLNL and CEA at regional scale around Chicago and Paris look very similar in terms of both atmospheric dispersion of the radiological release and total effective dose. Both LLNL and CEA used the same meteorological data, Lagrangian particle dispersion models, and the same dose coefficients. LLNL and CEA urban-scale modeling results show consistent phenomenological behavior and predict similar impacted areas even though the detailed 3D flow patterns differ, particularly for the Chicago cases where differences in vertical entrainment behind tall buildings are particularly notable. Although RANS and LES (LLNL) models incorporate more detailed physics than do mass-consistent diagnostic flow models (CEA), it is not possible to reach definite conclusions about the prediction fidelity of the various models as experimental measurements were not available for comparison. Stronger conclusions about the relative performances of the models involved and evaluation of the tradeoffs involved in model simplification could be made with a systematic benchmarking of urban-scale modeling. This could be the purpose of a future US / French collaborative exercise.« less

[Characteristics of water and heat fluxes and its footprint climatology on farmland in low hilly region of red soil].

PubMed

Li, Yang; Jing, Yuan Shu; Qin, Ben Ben

2017-01-01

The analysis of the characteristics and footprint climatology of farmland water and heat fluxes has great significance to strengthen regional climate resource management and improve the hydrothermal resource utilization in the region of red soil. Based on quality controlled data from large aperture scintillometer and automatic meteorological station in hilly region of red soil, this paper analyzed in detail the characteristics of farmland water and heat fluxes at different temporal scales and the corresponding source area distribution of flux measurement in the non-rainy season and crop growth period in hilly region of red soil. The results showed that the diurnal variation of water and heat fluxes showed a unimodal trend, but compared with the sunny day, the diurnal variation curves fluctuated more complicatedly on cloudy day. In the whole, either ten-day periods or month scale, the water and heat fluxes were greater in August than in September, while the net radiation flux was more distributed to latent heat exchange. The proportion of net radiation to latent heat flux decreased in September compared to August, but the sensible heat flux was vice versa. With combined effects of weather conditions (particularly wind), stability, and surface condition, the source areas of flux measurement at different temporal scales showed different distribution characteristics. Combined with the underlying surface crops, the source areas at different temporal scales also had different contribution sources.

Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

PubMed

Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun

2013-04-15

Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.

Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)

NASA Astrophysics Data System (ADS)

Micu, Dana; Cosmin Sandric, Ionut

2017-04-01

Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in seasonal precipitation, especially at lower elevations in all the three divisions of the Romanian Carpathians (generally below 1,700-1,800 m). The space-time patterns of snow cover change are dominated by a significant decreasing trend of snow days and earlier spring snow melt. The key findings of this study provides robust indication of a decreasing snow trends across the Carpathian Mountain region and could provide valuable spatial and temporal snow information for other related research fields as well as for an effective environmental monitoring in the mountain ecosystems of the Carpathian region

Verification of GCM-generated regional seasonal precipitation for current climate and of statistical downscaling estimates under changing climate conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Busuioc, A.; Storch, H. von; Schnur, R.

Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). Themore » climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in time-slice mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 x CO{sub 2} GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.« less

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Dammed in Region Six. The Nez Perce Tribe, Agricultural Development, and the Inequality of Scale

ERIC Educational Resources Information Center

Colombi, Benedict J.

2005-01-01

This essay quantifies the rise and development of agriculture on the Nez Perce reservation and the surrounding watershed. Included in this study is an analysis of Nez Perce pre-contact economy, society, and environment and how the Nez Perces continue to operate from a collective and communal past. Social power and cultural scale provide a…

User group attitudes toward forest management treatments on the Shawnee National Forest: application of a photo-evaluation technique

Treesearch

Jonathan M. Cohen; Jean C. Mangun; Mae A. Davenport; Andrew D. Carver

2008-01-01

Diverse public opinions, competing management goals, and polarized interest groups combine with problems of scale to create a complex management arena for managers in the Central Hardwood Forest region. A mixed-methods approach that incorporated quantitative analysis of data from a photo evaluation-attitude scale survey instrument was used to assess attitudes toward...

Magnitude of anthropogenic phosphorus storage in the agricultural production and the waste management systems at the regional and country scales.

PubMed

Chowdhury, Rubel Biswas; Chakraborty, Priyanka

2016-08-01

Based on a systematic review of 17 recent substance flow analyses of phosphorus (P) at the regional and country scales, this study presents an assessment of the magnitude of anthropogenic P storage in the agricultural production and the waste management systems to identify the potential for minimizing unnecessary P storage to reduce the input of P as mineral fertilizer and the loss of P. The assessment indicates that in case of all (6) P flow analyses at the regional scale, the combined mass of annual P storage in the agricultural production and the waste management systems is greater than 50 % of the mass of annual P inflow as mineral fertilizer in the agricultural production system, while this is close to or more than 100 % in case of half of these analyses. At the country scale, in case of the majority (7 out of 11) of analyses, the combined mass of annual P storage in the agricultural production and the waste management systems has been found to be roughly equivalent or greater than 100 % of the mass of annual P inflow as mineral fertilizer in the agricultural production system, while it ranged from 30 to 60 % in the remaining analyses. A simple scenario analysis has revealed that the annual storage of P in this manner over 100 years could result in the accumulation of a massive amount of P in the agricultural production and the waste management systems at both the regional and country scales. This study suggests that sustainable P management initiatives at the regional and country scales should put more emphasis on minimizing unwanted P storage in the agricultural production and the waste management systems.

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

2016-01-01

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

Re-plumbing the Terrestrial Hydrosphere: Scope and Impact of Major Inter-basin Water Transfers

NASA Astrophysics Data System (ADS)

Shikhmacheva, K. V.; Vorosmarty, C. J.; Fekete, B. M.; Afshari, S.; Aside, B.; Chibisova, Y.; Dopson, I.; Link, H.; Mouden, A.

2013-12-01

The availability of water has become one of the main concerns in modern history and it is an important policymaking strategy. Increasing population, agricultural intensification, rapid urbanization, industrial expansion and environmental changes increase water demand on region and global scales. Inter-Basin Water Transfer (IBWT) is an important element of satisfying immediate water requirements. The complex engineering structures divert water flow between watersheds, thus ';re-plumbing' terrestrial hydrosphere. We report here an analysis of inter-basin water transfer for the Northeast region, which is a part of an NSF funded project entitled 'The NorthEast Regional Earth System Model (NE-RESM).' In addition, this work is also a part of a global IBWT study. First, we present the IBWT geo-referenced assembled data set, derived from from maps, published documents and online resources. The information in the data base was classified by project name, diverted volume, source location, usage, status of construction, transport distance and purpose. The key feature of the dataset is geo-location of the projects, that allows further analysis of the hydrologic impact of each of the projects as well as their collective significance. Upon completion of the data-collection phase, the inputs were verified using RiverGIS and ArcGIS software. In addition, we investigated some key measures of IBWT distortion of regional-scale hydrology as well as their socio-economic impacts across the Northeast region. We calculated several indicators to assess these impacts, for example the donor-to-recipient basin flow ratio, which represents the 'gain' and 'loss' of water relative to the natural flow on a basin scale. Elements of the regional IBWT data base will be incorporated into the regional-scale Water Balance Model (WBM), and linked to the operation of reservoirs and dams. While focused on the Northeastern U.S., we believe that this data, its testing and applications will yield broad use and interest across the community, giving researchers a next important resource in the arsenal of datasets depicting human-water interactions.

An upscaled two-equation model of transport in porous media through unsteady-state closure of volume averaged formulations

NASA Astrophysics Data System (ADS)

Chaynikov, S.; Porta, G.; Riva, M.; Guadagnini, A.

2012-04-01

We focus on a theoretical analysis of nonreactive solute transport in porous media through the volume averaging technique. Darcy-scale transport models based on continuum formulations typically include large scale dispersive processes which are embedded in a pore-scale advection diffusion equation through a Fickian analogy. This formulation has been extensively questioned in the literature due to its inability to depict observed solute breakthrough curves in diverse settings, ranging from the laboratory to the field scales. The heterogeneity of the pore-scale velocity field is one of the key sources of uncertainties giving rise to anomalous (non-Fickian) dispersion in macro-scale porous systems. Some of the models which are employed to interpret observed non-Fickian solute behavior make use of a continuum formulation of the porous system which assumes a two-region description and includes a bimodal velocity distribution. A first class of these models comprises the so-called ''mobile-immobile'' conceptualization, where convective and dispersive transport mechanisms are considered to dominate within a high velocity region (mobile zone), while convective effects are neglected in a low velocity region (immobile zone). The mass exchange between these two regions is assumed to be controlled by a diffusive process and is macroscopically described by a first-order kinetic. An extension of these ideas is the two equation ''mobile-mobile'' model, where both transport mechanisms are taken into account in each region and a first-order mass exchange between regions is employed. Here, we provide an analytical derivation of two region "mobile-mobile" meso-scale models through a rigorous upscaling of the pore-scale advection diffusion equation. Among the available upscaling methodologies, we employ the Volume Averaging technique. In this approach, the heterogeneous porous medium is supposed to be pseudo-periodic, and can be represented through a (spatially) periodic unit cell. Consistently with the two-region model working hypotheses, we subdivide the pore space into two volumes, which we select according to the features of the local micro-scale velocity field. Assuming separation of the scales, the mathematical development associated with the averaging method in the two volumes leads to a generalized two-equation model. The final (upscaled) formulation includes the standard first order mass exchange term together with additional terms, which we discuss. Our developments allow to identify the assumptions which are usually implicitly embedded in the usual adoption of a two region mobile-mobile model. All macro-scale properties introduced in this model can be determined explicitly from the pore-scale geometry and hydrodynamics through the solution of a set of closure equations. We pursue here an unsteady closure of the problem, leading to the occurrence of nonlocal (in time) terms in the upscaled system of equations. We provide the solution of the closure problems for a simple application documenting the time dependent and the asymptotic behavior of the system.

Liquid state isomorphism, Rosenfeld-Tarazona temperature scaling, and Riemannian thermodynamic geometry.

PubMed

Mausbach, Peter; Köster, Andreas; Vrabec, Jadran

2018-05-01

Aspects of isomorph theory, Rosenfeld-Tarazona temperature scaling, and thermodynamic geometry are comparatively discussed on the basis of the Lennard-Jones potential. The first two approaches approximate the high-density fluid state well when the repulsive interparticle interactions become dominant, which is typically the case close to the freezing line. However, previous studies of Rosenfeld-Tarazona scaling for the isochoric heat capacity and its relation to isomorph theory reveal deviations for the temperature dependence. It turns out that a definition of a state region in which repulsive interactions dominate is required for achieving consistent results. The Riemannian thermodynamic scalar curvature R allows for such a classification, indicating predominantly repulsive interactions by R>0. An analysis of the isomorphic character of the freezing line and the validity of Rosenfeld-Tarazona temperature scaling show that these approaches are consistent only in a small state region.

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

Multi-Scale Mapping of Vegetation Biomass

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Fekety, P.; Falkowski, M. J.; Kennedy, R. E.; Crookston, N.; Smith, A. M.; Mahoney, P.; Glenn, N. F.; Dong, J.; Kane, V. R.; Woodall, C. W.

2016-12-01

Vegetation biomass mapping at multiple scales is important for carbon inventory and monitoring, reporting, and verification (MRV). Project-level lidar collections allow biomass estimation with high confidence where associated with field plot measurements. Predictive models developed from such datasets are customarily used to generate landscape-scale biomass maps. We tested the feasibility of predicting biomass in landscapes surveyed with lidar but without field plots, by withholding plot datasets from a reduced model applied to the landscapes, and found support for a generalized model in the northern Idaho ecoregion. We are also upscaling a generalized model to all forested lands in Idaho. Our regional modeling approach is to sample the 30-m biomass predictions from the landscape-scale maps and use them to train a regional biomass model, using Landsat time series, topographic derivatives, and climate variables as predictors. Our regional map validation approach is to aggregate the regional, annual biomass predictions to the county level and compare them to annual county-level biomass summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. A national-scale forest cover map generated independently from 2010 PALSAR data at 25-m resolution is being used to mask non-forest pixels from the aggregations. Effects of climate change on future regional biomass stores are also being explored, using biomass estimates projected from stand-level inventory data collected in the National Forests and comparing them to FIA plot data collected independently on public and private lands, projected under the same climate change scenarios, with disturbance trends extracted from the Landsat time series. Our ultimate goal is to demonstrate, focusing on the ecologically diverse Northwest region of the USA, a carbon monitoring system (CMS) that is accurate, objective, repeatable, and transparent.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Cost analysis of large-scale implementation of the 'Helping Babies Breathe' newborn resuscitation-training program in Tanzania.

PubMed

Chaudhury, Sumona; Arlington, Lauren; Brenan, Shelby; Kairuki, Allan Kaijunga; Meda, Amunga Robson; Isangula, Kahabi G; Mponzi, Victor; Bishanga, Dunstan; Thomas, Erica; Msemo, Georgina; Azayo, Mary; Molinier, Alice; Nelson, Brett D

2016-12-01

Helping Babies Breathe (HBB) has become the gold standard globally for training birth-attendants in neonatal resuscitation in low-resource settings in efforts to reduce early newborn asphyxia and mortality. The purpose of this study was to do a first-ever activity-based cost-analysis of at-scale HBB program implementation and initial follow-up in a large region of Tanzania and evaluate costs of national scale-up as one component of a multi-method external evaluation of the implementation of HBB at scale in Tanzania. We used activity-based costing to examine budget expense data during the two-month implementation and follow-up of HBB in one of the target regions. Activity-cost centers included administrative, initial training (including resuscitation equipment), and follow-up training expenses. Sensitivity analysis was utilized to project cost scenarios incurred to achieve countrywide expansion of the program across all mainland regions of Tanzania and to model costs of program maintenance over one and five years following initiation. Total costs for the Mbeya Region were $202,240, with the highest proportion due to initial training and equipment (45.2%), followed by central program administration (37.2%), and follow-up visits (17.6%). Within Mbeya, 49 training sessions were undertaken, involving the training of 1,341 health providers from 336 health facilities in eight districts. To similarly expand the HBB program across the 25 regions of mainland Tanzania, the total economic cost is projected to be around $4,000,000 (around $600 per facility). Following sensitivity analyses, the estimated total for all Tanzania initial rollout lies between $2,934,793 to $4,309,595. In order to maintain the program nationally under the current model, it is estimated it would cost $2,019,115 for a further one year and $5,640,794 for a further five years of ongoing program support. HBB implementation is a relatively low-cost intervention with potential for high impact on perinatal mortality in resource-poor settings. It is shown here that nationwide expansion of this program across the range of health provision levels and regions of Tanzania would be feasible. This study provides policymakers and investors with the relevant cost-estimation for national rollout of this potentially neonatal life-saving intervention.

Climate change impacts on risks of groundwater pollution by herbicides: a regional scale assessment

NASA Astrophysics Data System (ADS)

Steffens, Karin; Moeys, Julien; Lindström, Bodil; Kreuger, Jenny; Lewan, Elisabet; Jarvis, Nick

2014-05-01

Groundwater contributes nearly half of the Swedish drinking water supply, which therefore needs to be protected both under present and future climate conditions. Pesticides are sometimes found in Swedish groundwater in concentrations exceeding the EU-drinking water limit and thus constitute a threat. The aim of this study was to assess the present and future risks of groundwater pollution at the regional scale by currently approved herbicides. We identified representative combinations of major crop types and their specific herbicide usage (product, dose and application timing) based on long-term monitoring data from two agricultural catchments in the South-West of Sweden. All these combinations were simulated with the regional version of the pesticide fate model MACRO (called MACRO-SE) for the periods 1970-1999 and 2070-2099 for a major crop production region in South West Sweden. To represent the uncertainty in future climate data, we applied a five-member ensemble based on different climate model projections downscaled with the RCA3-model (Swedish Meteorological and Hydrological Institute). In addition to the direct impacts of changes in the climate, the risks of herbicide leaching in the future will also be affected by likely changes in weed pressure and land use and management practices (e.g. changes in crop rotations and application timings). To assess the relative importance of such factors we performed a preliminary sensitivity analysis which provided us with a hierarchical structure for constructing future herbicide use scenarios for the regional scale model runs. The regional scale analysis gave average concentrations of herbicides leaching to groundwater for a large number of combinations of soils, crops and compounds. The results showed that future scenarios for herbicide use (more autumn-sown crops, more frequent multiple applications on one crop, and a shift from grassland to arable crops such as maize) imply significantly greater risks of herbicide leaching to groundwater in a changing climate, and that these indirect effects outweigh the direct effects of changes in climate driving variables. Due to the large uncertainties in climate change impact assessments, drawing firm conclusions is not possible, but this type of analysis provides indications of likely future concerns and can be used as an early-warning tool to inform the general public, responsible public authorities and decision makers.

Process metallurgy simulation for metal drawing process optimization by using two-scale finite element method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakamachi, Eiji; Yoshida, Takashi; Yamaguchi, Toshihiko

2014-10-06

We developed two-scale FE analysis procedure based on the crystallographic homogenization method by considering the hierarchical structure of poly-crystal aluminium alloy metal. It can be characterized as the combination of two-scale structure, such as the microscopic polycrystal structure and the macroscopic elastic plastic continuum. Micro polycrystal structure can be modeled as a three dimensional representative volume element (RVE). RVE is featured as by 3×3×3 eight-nodes solid finite elements, which has 216 crystal orientations. This FE analysis code can predict the deformation, strain and stress evolutions in the wire drawing processes in the macro- scales, and further the crystal texture andmore » hardening evolutions in the micro-scale. In this study, we analyzed the texture evolution in the wire drawing processes by our two-scale FE analysis code under conditions of various drawing angles of dice. We evaluates the texture evolution in the surface and center regions of the wire cross section, and to clarify the effects of processing conditions on the texture evolution.« less

Process metallurgy simulation for metal drawing process optimization by using two-scale finite element method

NASA Astrophysics Data System (ADS)

Nakamachi, Eiji; Yoshida, Takashi; Kuramae, Hiroyuki; Morimoto, Hideo; Yamaguchi, Toshihiko; Morita, Yusuke

2014-10-01

We developed two-scale FE analysis procedure based on the crystallographic homogenization method by considering the hierarchical structure of poly-crystal aluminium alloy metal. It can be characterized as the combination of two-scale structure, such as the microscopic polycrystal structure and the macroscopic elastic plastic continuum. Micro polycrystal structure can be modeled as a three dimensional representative volume element (RVE). RVE is featured as by 3×3×3 eight-nodes solid finite elements, which has 216 crystal orientations. This FE analysis code can predict the deformation, strain and stress evolutions in the wire drawing processes in the macro- scales, and further the crystal texture and hardening evolutions in the micro-scale. In this study, we analyzed the texture evolution in the wire drawing processes by our two-scale FE analysis code under conditions of various drawing angles of dice. We evaluates the texture evolution in the surface and center regions of the wire cross section, and to clarify the effects of processing conditions on the texture evolution.

Spectral saliency via automatic adaptive amplitude spectrum analysis

NASA Astrophysics Data System (ADS)

Wang, Xiaodong; Dai, Jialun; Zhu, Yafei; Zheng, Haiyong; Qiao, Xiaoyan

2016-03-01

Suppressing nonsalient patterns by smoothing the amplitude spectrum at an appropriate scale has been shown to effectively detect the visual saliency in the frequency domain. Different filter scales are required for different types of salient objects. We observe that the optimal scale for smoothing amplitude spectrum shares a specific relation with the size of the salient region. Based on this observation and the bottom-up saliency detection characterized by spectrum scale-space analysis for natural images, we propose to detect visual saliency, especially with salient objects of different sizes and locations via automatic adaptive amplitude spectrum analysis. We not only provide a new criterion for automatic optimal scale selection but also reserve the saliency maps corresponding to different salient objects with meaningful saliency information by adaptive weighted combination. The performance of quantitative and qualitative comparisons is evaluated by three different kinds of metrics on the four most widely used datasets and one up-to-date large-scale dataset. The experimental results validate that our method outperforms the existing state-of-the-art saliency models for predicting human eye fixations in terms of accuracy and robustness.

AQMEII3 evaluation of regional NA/EU simulations and ...

EPA Pesticide Factsheets

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impac

Fine-Scale Analysis Reveals Cryptic Landscape Genetic Structure in Desert Tortoises

PubMed Central

Latch, Emily K.; Boarman, William I.; Walde, Andrew; Fleischer, Robert C.

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately. PMID:22132143

Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises.

PubMed

Latch, Emily K; Boarman, William I; Walde, Andrew; Fleischer, Robert C

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately.

Localized Hotspots Drive Continental Geography of Abnormal Amphibians on U.S. Wildlife Refuges

PubMed Central

Reeves, Mari K.; Medley, Kimberly A.; Pinkney, Alfred E.; Holyoak, Marcel; Johnson, Pieter T. J.; Lannoo, Michael J.

2013-01-01

Amphibians with missing, misshapen, and extra limbs have garnered public and scientific attention for two decades, yet the extent of the phenomenon remains poorly understood. Despite progress in identifying the causes of abnormalities in some regions, a lack of knowledge about their broader spatial distribution and temporal dynamics has hindered efforts to understand their implications for amphibian population declines and environmental quality. To address this data gap, we conducted a nationwide, 10-year assessment of 62,947 amphibians on U.S. National Wildlife Refuges. Analysis of a core dataset of 48,081 individuals revealed that consistent with expected background frequencies, an average of 2% were abnormal, but abnormalities exhibited marked spatial variation with a maximum prevalence of 40%. Variance partitioning analysis demonstrated that factors associated with space (rather than species or year sampled) captured 97% of the variation in abnormalities, and the amount of partitioned variance decreased with increasing spatial scale (from site to refuge to region). Consistent with this, abnormalities occurred in local to regional hotspots, clustering at scales of tens to hundreds of kilometers. We detected such hotspot clusters of high-abnormality sites in the Mississippi River Valley, California, and Alaska. Abnormality frequency was more variable within than outside of hotspot clusters. This is consistent with dynamic phenomena such as disturbance or natural enemies (pathogens or predators), whereas similarity of abnormality frequencies at scales of tens to hundreds of kilometers suggests involvement of factors that are spatially consistent at a regional scale. Our characterization of the spatial and temporal variation inherent in continent-wide amphibian abnormalities demonstrates the disproportionate contribution of local factors in predicting hotspots, and the episodic nature of their occurrence. PMID:24260103

Numerical analysis of field-scale transport of bromacil

NASA Astrophysics Data System (ADS)

Russo, David; Tauber-Yasur, Inbar; Laufer, Asher; Yaron, Bruno

Field-scale transport of bromacil (5-bromo-3- sec-butyl-6-methyluracil) was analyzed using two different model processes for local description of the transport. The first was the classical, one-region convection dispersion equation (CDE) model while the second was the two-region, mobile-immobile (MIM) model. The analyses were performed by means of detailed three-dimensional, numerical simulations of the flow and the transport [Russo, D., Zaidel, J. and Laufer, A., Numerical analysis of flow and transport in a three-dimensional partially saturated heterogeneous soil. Water Resour. Res., 1998, in press], employing local soil hydraulic properties parameters from field measurements and local adsorption/desorption coefficients and the first-order degradation rate coefficient from laboratory measurements. Results of the analyses suggest that for a given flow regime, mass exchange between the mobile and the immobile regions retards the bromacil degradation, considerably affects the distribution of the bromacil resident concentration, c, at relatively large travel times, slightly affects the spatial moments of the distribution of c, and increases the skewing of the bromacil breakthrough and the uncertainty in its prediction, compared with the case in which the soil contained only a single (mobile) region. Mean and standard deviation of the simulated concentration profiles at various elapsed times were compared with measurements from a field-scale transport experiment [Tauber-Yasur, I., Hadas, A., Russo, D. and Yaron, B., Leaching of terbuthylazine and bromacil through field soils. Water, Air Soil Poln., 1998, in press] conducted at the Bet Dagan site. Given the limitations of the present study (e.g. the lack of detailed field data on the spatial variability of the soil chemical properties) the main conclusion of the present study is that the field-scale transport of bromacil at the Bet Dagan site is better quantified with the MIM model than the CDE model.

Feature analysis and primary causes of pre-flood season "cumulative effect" of torrential rain over South China

NASA Astrophysics Data System (ADS)

Chu, Qu-cheng; Wang, Qi-guang; Qiao, Shao-bo; Feng, Guo-lin

2018-01-01

When persistent rainfall occurs frequently over South China, meso-scale and micro-scale synoptic systems persist and expand in space and time and eventually form meso-scale and long-scale weather processes. The accumulation of multiple torrential rain processes is defined as a "cumulative effect" of torrential rain (CETR) event. In this paper, daily reanalysis datasets collected by the National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) during 1979-2014 are used to study the anomalous features and causes of heavy CETR events over South China. The results show that there is a significant difference in the spatial distribution of the heavy CETR events. Based on the center position of the CETR, the middle region displayed middle-region-heavy CETR events while the western region displayed west-region-heavy CETR events. El Niño events in the previous period (December, January, February, March (DJFM)) are major extra-forcing factors of middle-region-heavy CETR events, which is beneficial for the continuous, anomalous Philippine Sea anticyclone and strengthens the West Pacific Subtropical High (WPSH), extending it more westward than normal. The primary water vapor source for precipitation in middle-region-heavy CETR events is the Tropical Western Pacific Ocean. The major extra-forcing factor of a west-region-heavy CETR is the negative anomaly in the southern Tropical Indian Ocean (TIO) during the previous period (DJFM). This factor is beneficial for strengthening the cross-equatorial flow and westerly winds from the Bay of Bengal to the South China Sea (SCS) and early SCS summer monsoon onset. The primary water vapor source of precipitation in the west-region-heavy CETR is the southern TIO.

Spatial patterns of frequent floods in Switzerland

NASA Astrophysics Data System (ADS)

Schneeberger, Klaus; Rössler, Ole; Weingartner, Rolf

2017-04-01

Information about the spatial characteristics of high and extreme streamflow is often needed for an accurate analysis of flood risk and effective co-ordination of flood related activities, such as flood defence planning. In this study we analyse the spatial dependence of frequent floods in Switzerland across different scales. Firstly, we determine the average length of high and extreme flow events for 56 runoff time series of Swiss rivers. Secondly, a dependence measure expressing the probability that streamflow peaks are as high as peaks at a conditional site is used to describe and map the spatial extend of joint occurrence of frequent floods across Switzerland. Thirdly, we apply a cluster analysis to identify groups of sites that are likely to react similarly in terms of joint occurrence of high flow events. The results indicate that a time interval with a length of 3 days seems to be most appropriate to characterise the average length of high streamflow events across spatial scales. In the main Swiss basins, high and extreme streamflows were found to be asymptotically independent. In contrast, at the meso-scale distinct flood regions, which react similarly in terms of occurrence of frequent flood, were found. The knowledge about these regions can help to optimise flood defence planning or to estimate regional flood risk properly.

Differentiating the grades of thymic epithelial tumor malignancy using textural features of intratumoral heterogeneity via (18)F-FDG PET/CT.

PubMed

Lee, Hyo Sang; Oh, Jungsu S; Park, Young Soo; Jang, Se Jin; Choi, Ik Soo; Ryu, Jin-Sook

2016-05-01

We aimed to explore the ability of textural heterogeneity indices determined by (18)F-FDG PET/CT for grading the malignancy of thymic epithelial tumors (TETs). We retrospectively enrolled 47 patients with pathologically proven TETs who underwent pre-treatment (18)F-FDG PET/CT. TETs were classified by pathological results into three subgroups with increasing grades of malignancy: low-risk thymoma (LRT; WHO classification A, AB and B1), high-risk thymoma (B2 and B3), and thymic carcinoma (TC). Using (18)F-FDG PET/CT, we obtained conventional imaging indices including SUVmax and 20 intratumoral heterogeneity indices: i.e., four local-scale indices derived from the neighborhood gray-tone difference matrix (NGTDM), eight regional-scale indices from the gray-level run-length matrix (GLRLM), and eight regional-scale indices from the gray-level size zone matrix (GLSZM). Area under the receiver operating characteristic curve (AUC) was used to demonstrate the abilities of the imaging indices for differentiating subgroups. Multivariable logistic regression analysis was performed to show the independent significance of the textural indices. Combined criteria using optimal cutoff values of the SUVmax and a best-performing heterogeneity index were applied to investigate whether they improved differentiation between the subgroups. Most of the GLRLM and GLSZM indices and the SUVmax showed good or fair discrimination (AUC >0.7) with best performance for some of the GLRLM indices and the SUVmax, whereas the NGTDM indices showed relatively inferior performance. The discriminative ability of some of the GLSZM indices was independent from that of SUVmax in multivariate analysis. Combined use of the SUVmax and a GLSZM index improved positive predictive values for LRT and TC. Texture analysis of (18)F-FDG PET/CT scans has the potential to differentiate between TET tumor grades; regional-scale indices from GLRLM and GLSZM perform better than local-scale indices from the NGTDM. The SUVmax and heterogeneity indices may have complementary value in differentiating TET subgroups.

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)

USGS Publications Warehouse

Lowry, J.; Ramsey, R.D.; Thomas, K.; Schrupp, D.; Sajwaj, T.; Kirby, J.; Waller, E.; Schrader, S.; Falzarano, S.; Langs, L.; Manis, G.; Wallace, C.; Schulz, K.; Comer, P.; Pohs, K.; Rieth, W.; Velasquez, C.; Wolk, B.; Kepner, W.; Boykin, K.; O'Brien, L.; Bradford, D.; Thompson, B.; Prior-Magee, J.

2007-01-01

Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999-2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based "mapping zones". Over the course of 21/2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 land-cover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT = .60, n = 17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework. ?? 2006 Elsevier Inc. All rights reserved.

Land change variability and human-environment dynamics in the United States Great Plains

USGS Publications Warehouse

Drummond, M.A.; Auch, Roger F.; Karstensen, K.A.; Sayler, K. L.; Taylor, Janis L.; Loveland, Thomas R.

2012-01-01

Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is often hampered by change detection error and the tendency for land conversions to occur at the local-scale. To facilitate a regional-scale analysis, a statistical sampling design of randomly selected 10 km × 10 km blocks is used to efficiently identify the types and rates of land conversions for four time intervals between 1973 and 2000, stratified by relatively homogenous ecoregions. Nearly 8% of the overall Great Plains region underwent land-use and land-cover change during the study period, with a substantial amount of ecoregion variability that ranged from less than 2% to greater than 13%. Agricultural land cover declined by more than 2% overall, with variability contingent on the differential characteristics of regional human–environment systems. A large part of the Great Plains is in relatively stable land cover. However, other land systems with significant biophysical and climate limitations for agriculture have high rates of land change when pushed by economic, policy, technology, or climate forcing factors. The results indicate the regionally based potential for land cover to persist or fluctuate as land uses are adapted to spatially and temporally variable forcing factors.

Quantifying understorey vegetation in the US Lake States: a proposed framework to inform regional forest carbon stocks

USGS Publications Warehouse

Russell, Matthew B.; D'Amato, Anthony W.; Schulz, Bethany K.; Woodall, Christopher W.; Domke, Grant M.; Bradford, John B.

2014-01-01

The contribution of understorey vegetation (UVEG) to forest ecosystem biomass and carbon (C) across diverse forest types has, to date, eluded quantification at regional and national scales. Efforts to quantify UVEG C have been limited to field-intensive studies or broad-scale modelling approaches lacking field measurements. Although large-scale inventories of UVEG C are not common, species- and community-level inventories of vegetation structure are available and may prove useful in quantifying UVEG C stocks. This analysis developed a general framework for estimating UVEG C stocks by employing per cent cover estimates of UVEG from a region-wide forest inventory coupled with an estimate of maximum UVEG C across the US Lake States (i.e. Michigan, Minnesota and Wisconsin). Estimates of UVEG C stocks from this approach reasonably align with expected C stocks in the study region, ranging from 0.86 ± 0.06 Mg ha-1 in red pine-dominated to 1.59 ± 0.06 Mg ha-1 for aspen/birch-dominated forest types. Although the data employed here were originally collected to assess broad-scale forest structure and diversity, this study proposes a framework for using UVEG inventories as a foundation for estimating C stocks in an often overlooked, yet important ecosystem C pool.

Reverse flow events and small-scale effects in the cusp ionosphere

NASA Astrophysics Data System (ADS)

Spicher, A.; Ilyasov, A. A.; Miloch, W. J.; Chernyshov, A. A.; Clausen, L. B. N.; Moen, J. I.; Abe, T.; Saito, Y.

2016-10-01

We report in situ measurements of plasma irregularities associated with a reverse flow event (RFE) in the cusp F region ionosphere. The Investigation of Cusp Irregularities 3 (ICI-3) sounding rocket, while flying through a RFE, encountered several regions with density irregularities down to meter scales. We address in detail the region with the most intense small-scale fluctuations in both the density and in the AC electric field, which were observed on the equatorward edge of a flow shear, and coincided with a double-humped jet of fast flow. Due to its long-wavelength and low-frequency character, the Kelvin-Helmholtz instability (KHI) alone cannot be the source of the observed irregularities. Using ICI-3 data as inputs, we perform a numerical stability analysis of the inhomogeneous energy-density-driven instability (IEDDI) and demonstrate that it can excite electrostatic ion cyclotron waves in a wide range of wave numbers and frequencies for the electric field configuration observed in that region, which can give rise to the observed small-scale turbulence. The IEDDI can seed as a secondary process on steepened vortices created by a primary KHI. Such an interplay between macroprocesses and microprocesses could be an important mechanism for ion heating in relation to RFEs.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the role of boundary forcing and the potential predictability of the monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both SST and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. For regional monsoons, however, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

Influence of Average Income on Epidemics of Seasonal Influenza.

PubMed

Seike, Issei; Saito, Norihiro; Saito, Satoshi; Itoga, Masamichi; Kayaba, Hiroyuki

2016-11-22

Understanding the local factors influencing the transmission of communicable diseases is important to minimize social damage. The aim of this study was to investigate local factors influencing seasonal influenza epidemics in Aomori prefecture consisting of 6 regions, i.e., Seihoku, Chunan, and Tosei on the west side, and Sanpachi, Kamikita, and Shimokita on the east side. Four indices (epidemic onset, duration, scale, and steepness of epidemic curves) were defined, and their correlations with regional characteristics and meteorological factors were investigated. Data for influenza seasons from 2006-2007 to 2014-2015 were collected. The 2009-2010 season was excluded because of the pandemic of A (H1N1)pdm09. Average income was strongly correlated with epidemic onset, duration, and scale. The ratio of children aged ≤5 years to the total population was strongly correlated with epidemic duration and scale. Low temperature in January showed moderate correlation with epidemic duration and scale. Cluster analysis showed that 2 isolated regions, Seihoku and Chunan, belonged to the same cluster in the 4 indices of epidemic curves, and other 2 relatively urbanized regions formed another cluster in 3 of the 4 indices. This study highlights important local factors that influence seasonal influenza epidemics and may help in implementation of preventive measures.

Correlation of finite-element structural dynamic analysis with measured free vibration characteristics for a full-scale helicopter fuselage

NASA Technical Reports Server (NTRS)

Kenigsberg, I. J.; Dean, M. W.; Malatino, R.

1974-01-01

The correlation achieved with each program provides the material for a discussion of modeling techniques developed for general application to finite-element dynamic analyses of helicopter airframes. Included are the selection of static and dynamic degrees of freedom, cockpit structural modeling, and the extent of flexible-frame modeling in the transmission support region and in the vicinity of large cut-outs. The sensitivity of predicted results to these modeling assumptions are discussed. Both the Sikorsky Finite-Element Airframe Vibration analysis Program (FRAN/Vibration Analysis) and the NASA Structural Analysis Program (NASTRAN) have been correlated with data taken in full-scale vibration tests of a modified CH-53A helicopter.

Lateral fluid flow in a compacting sand-shale sequence: South Caspian basin.

USGS Publications Warehouse

Bredehoeft, J.D.; Djevanshir, R.D.; Belitz, K.R.

1988-01-01

The South Caspian basin contains both sands and shales that have pore-fluid pressures substantially in excess of hydrostatic fluid pressure. Pore-pressure data from the South Caspian basin demonstrate that large differences in excess hydraulic head exist between sand and shale. The data indicate that sands are acting as drains for overlying and underlying compacting shales and that fluid flows laterally through the sand on a regional scale from the basin interior northward to points of discharge. The major driving force for the fluid movement is shale compaction. We present a first- order mathematical analysis in an effort to test if the permeability of the sands required to support a regional flow system is reasonable. The results of the analysis suggest regional sand permeabilities ranging from 1 to 30 md; a range that seems reasonable. This result supports the thesis that lateral fluid flow is occurring on a regional scale within the South Caspian basin. If vertical conduits for flow exist within the basin, they are sufficiently impermeable and do not provide a major outlet for the regional flow system. The lateral fluid flow within the sands implies that the stratigraphic sequence is divided into horizontal units that are hydraulically isolated from one another, a conclusion that has important implications for oil and gas migration.-Authors

Utilizing Gravity Methods for Regional Studies in Basin Delineation: Case Study at Jornada del Muerto basin, New Mexico

NASA Astrophysics Data System (ADS)

Villalobos, J. I.

2005-12-01

The modeling of basin structures is an important step in the development of plans and policies for ground water management. To facilitate in the analysis of large scale regional structures, gravity data is implemented to examine the overall structural trend of the region. The gravitational attraction of structures in the upper mantle and crust provide vital information about the possible structure and composition of a region. Improved availability of gravity data via internet has promoted extensive construction and interpretation of gravity maps in the analysis of sub-surface structural anomalies. The utilization of gravity data appears to be particularly worthwhile because it is a non-invasive and inexpensive means of addressing the subsurface tectonic framework of large scale regions. In this paper, the author intends to illustrate 1) acquisition of gravity data and its processing; 2) interpretation of gravity data; and 3) sources of uncertainty and errors by using a case study of the Jornada del Muerto basin in South-Central New Mexico where integrated gravity data inferred several faults, sub-basins and thickness variations within the basins structure. The author also explores the integration of gravity method with other geophysical methods to further refine the delineation of basins.

Regionalization of subsurface stormflow parameters of hydrologic models: Derivation from regional analysis of streamflow recession curves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ye, Sheng; Li, Hongyi; Huang, Maoyi

2014-07-21

Subsurface stormflow is an important component of the rainfall–runoff response, especially in steep terrain. Its contribution to total runoff is, however, poorly represented in the current generation of land surface models. The lack of physical basis of these common parameterizations precludes a priori estimation of the stormflow (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global land surface models. This paper is aimed at deriving regionalized parameterizations of the storage–discharge relationship relating to subsurface stormflow from a top–down empirical data analysis of streamflow recession curves extracted from 50 eastern United Statesmore » catchments. Detailed regression analyses were performed between parameters of the empirical storage–discharge relationships and the controlling climate, soil and topographic characteristics. The regression analyses performed on empirical recession curves at catchment scale indicated that the coefficient of the power-law form storage–discharge relationship is closely related to the catchment hydrologic characteristics, which is consistent with the hydraulic theory derived mainly at the hillslope scale. As for the exponent, besides the role of field scale soil hydraulic properties as suggested by hydraulic theory, it is found to be more strongly affected by climate (aridity) at the catchment scale. At a fundamental level these results point to the need for more detailed exploration of the co-dependence of soil, vegetation and topography with climate.« less

A novel visual saliency analysis model based on dynamic multiple feature combination strategy

NASA Astrophysics Data System (ADS)

Lv, Jing; Ye, Qi; Lv, Wen; Zhang, Libao

2017-06-01

The human visual system can quickly focus on a small number of salient objects. This process was known as visual saliency analysis and these salient objects are called focus of attention (FOA). The visual saliency analysis mechanism can be used to extract the salient regions and analyze saliency of object in an image, which is time-saving and can avoid unnecessary costs of computing resources. In this paper, a novel visual saliency analysis model based on dynamic multiple feature combination strategy is introduced. In the proposed model, we first generate multi-scale feature maps of intensity, color and orientation features using Gaussian pyramids and the center-surround difference. Then, we evaluate the contribution of all feature maps to the saliency map according to the area of salient regions and their average intensity, and attach different weights to different features according to their importance. Finally, we choose the largest salient region generated by the region growing method to perform the evaluation. Experimental results show that the proposed model cannot only achieve higher accuracy in saliency map computation compared with other traditional saliency analysis models, but also extract salient regions with arbitrary shapes, which is of great value for the image analysis and understanding.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vissers, Daniel R.; Isheim, Dieter; Zhan, Chun

Lithium-ion batteries utilizing 5 V spinel material, LixMn1.5Ni0.5O4 have received considerable interest in recent years for their ability to deliver high energy and power densities. In this paper, we report an atomic scale analysis of the surface layer of a core–shell 5 V spinel structure where a small amount of the manganese lattice sites have been substituted with cobalt in the shell to reach a stoichiometry of LixMn1.18Ni0.55Co0.27O4. Our analyses include electrochemical analysis, atom probe tomography (APT) analysis, kinetic analysis of the interfacial reactions, and high resolution scanning transmission electron microscopy (HR-TEM) analysis. The APT analysis is performed on themore » material before and after long-term cycling at room temperature to provide insights into the atomic scale phenomena within the surface layer of the electrode material. Our APT data reveals a 25–30 nano-meter (nm) region which forms after cycling. From our analyses, we believe that the outer few nanometers of this region stabilizes the 5 V spinel within the chemical environment of the lithium-ion cell such that its structure is not compromised and thereby enables this material to cycle without significant capacity fading.« less

Visualization and Analysis of Light Pollution: a Case Study in Hong Kong

NASA Astrophysics Data System (ADS)

Wu, B.; Wong, H.

2012-07-01

The effects of light pollution problems in metropolitan areas are investigated in this study. Areas of Hong Kong are used as the source of three typical study cases. One case represents the regional scale, a second represents the district scale, and a third represents the street scale. Two light pollution parameters, Night Sky Brightness (NSB) and Street Light Level (SLL), are the focus of the analyses. Light pollution visualization approaches in relation to the different scales include various light pollution maps. They provide straightforward presentations of the light pollution situations in the study areas. The relationship between light pollution and several social-economic factors such as land use, household income, and types of outdoor lighting in the scale areas given, are examined. Results show that: (1) Land use may be one factor affecting light pollution in the regional scale; (2) A relatively strong correlation exists between light pollution and household income in the district scale; (3) The heaviest light pollution in the street scale is created by spotlights and also the different types of lighting from shops. The impact of the latter is in relation to the shop profile and size.

Effects of forcing time scale on the simulated turbulent flows and turbulent collision statistics of inertial particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosa, B., E-mail: bogdan.rosa@imgw.pl; Parishani, H.; Department of Earth System Science, University of California, Irvine, California 92697-3100

2015-01-15

In this paper, we study systematically the effects of forcing time scale in the large-scale stochastic forcing scheme of Eswaran and Pope [“An examination of forcing in direct numerical simulations of turbulence,” Comput. Fluids 16, 257 (1988)] on the simulated flow structures and statistics of forced turbulence. Using direct numerical simulations, we find that the forcing time scale affects the flow dissipation rate and flow Reynolds number. Other flow statistics can be predicted using the altered flow dissipation rate and flow Reynolds number, except when the forcing time scale is made unrealistically large to yield a Taylor microscale flow Reynoldsmore » number of 30 and less. We then study the effects of forcing time scale on the kinematic collision statistics of inertial particles. We show that the radial distribution function and the radial relative velocity may depend on the forcing time scale when it becomes comparable to the eddy turnover time. This dependence, however, can be largely explained in terms of altered flow Reynolds number and the changing range of flow length scales present in the turbulent flow. We argue that removing this dependence is important when studying the Reynolds number dependence of the turbulent collision statistics. The results are also compared to those based on a deterministic forcing scheme to better understand the role of large-scale forcing, relative to that of the small-scale turbulence, on turbulent collision of inertial particles. To further elucidate the correlation between the altered flow structures and dynamics of inertial particles, a conditional analysis has been performed, showing that the regions of higher collision rate of inertial particles are well correlated with the regions of lower vorticity. Regions of higher concentration of pairs at contact are found to be highly correlated with the region of high energy dissipation rate.« less

U.S. ENVIRONMENTAL PROTECTION AGENCY'S PM SUPERSITES PROGRAM - A MAJOR SUCCESSFUL COLLABORATIVE AIR QUALITY PROGRAM SUPPORTING STATES AND REGIONAL ORGANIZATIONS IN THEIR APPROACHES TO REDUCE PM LEVELS IN AIR ON URBAN AND REGIONAL SCALES

EPA Science Inventory

The U.S. Environmental Protection Agency's Particulate Matter (PM) Supersites Program (Program) is a nationwide air quality methods, measurement, modeling, and data analysis program initiated through cooperative agreements with leading universities in the United States. The Progr...

Moon-based visibility analysis for the observation of “The Belt and Road”

NASA Astrophysics Data System (ADS)

REN, Yuanzhen; GUO, Huadong; LIU, Guang; YE, Hanlin; DING, Yixing; RUAN, Zhixing; LV, Mingyang

2016-11-01

Aiming at promoting the economic prosperity and regional economic cooperation, the “Silk Road Economic Belt” and the “21st Century Maritime Silk Road” (hereinafter referred to as the Belt and Road) was raised. To get a better understanding of “the Belt and Road” whole region, considering the large-scale characteristic, the Moon platform is a good choice. In this paper, the ephemeris is taken as data source and the positions and attitudes of Sun, Earth and Moon are obtained based on the reference systems transformation. Then we construct a simplified observation model and calculate the spatial and angular visibility of the Moon platform for “the Belt and Road” region. It turns out that Moon-based observation of this region shows a good performance of spatial visibility and variable angular visibility, indicating the Moon being a new potential platform for large-scale Earth observation.

Spatiotemporal attention operator using isotropic contrast and regional homogeneity

NASA Astrophysics Data System (ADS)

Palenichka, Roman; Lakhssassi, Ahmed; Zaremba, Marek

2011-04-01

A multiscale operator for spatiotemporal isotropic attention is proposed to reliably extract attention points during image sequence analysis. Its consecutive local maxima indicate attention points as the centers of image fragments of variable size with high intensity contrast, region homogeneity, regional shape saliency, and temporal change presence. The scale-adaptive estimation of temporal change (motion) and its aggregation with the regional shape saliency contribute to the accurate determination of attention points in image sequences. Multilocation descriptors of an image sequence are extracted at the attention points in the form of a set of multidimensional descriptor vectors. A fast recursive implementation is also proposed to make the operator's computational complexity independent from the spatial scale size, which is the window size in the spatial averaging filter. Experiments on the accuracy of attention-point detection have proved the operator consistency and its high potential for multiscale feature extraction from image sequences.

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, Bruce

1990-01-01

Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

Automated Detection of Microaneurysms Using Scale-Adapted Blob Analysis and Semi-Supervised Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adal, Kedir M.; Sidebe, Desire; Ali, Sharib

2014-01-07

Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are then introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier to detect true MAs. The developed system is built using onlymore » few manually labeled and a large number of unlabeled retinal color fundus images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. A competition performance measure (CPM) of 0.364 shows the competitiveness of the proposed system against state-of-the art techniques as well as the applicability of the proposed features to analyze fundus images.« less

Diatoms Si uptake capacity drives carbon export in coastal upwelling systems

NASA Astrophysics Data System (ADS)

Abrantes, Fatima; Cermeno, Pedro; Lopes, Cristina; Romero, Oscar; Matos, Lélia; Van Iperen, Jolanda; Rufino, Marta; Magalhães, Vitor

2016-07-01

Coastal upwelling systems account for approximately half of global ocean primary production and contribute disproportionately to biologically driven carbon sequestration. Diatoms, silica-precipitating microalgae, constitute the dominant phytoplankton in these productive regions, and their abundance and assemblage composition in the sedimentary record is considered one of the best proxies for primary production. The study of the sedimentary diatom abundance (SDA) and total organic carbon content (TOC) in the five most important coastal upwelling systems of the modern ocean (Iberia-Canary, Benguela, Peru-Humboldt, California, and Somalia-Oman) reveals a global-scale positive relationship between diatom production and organic carbon burial. The analysis of SDA in conjunction with environmental variables of coastal upwelling systems such as upwelling strength, satellite-derived net primary production, and surface water nutrient concentrations shows different relations between SDA and primary production on the regional scale. On the global scale, SDA appears modulated by the capacity of diatoms to take up silicic acid, which ultimately sets an upper limit to global export production in these ocean regions.

Analysis of extreme hydrological phenomena in southern Italy (Calabria region)

NASA Astrophysics Data System (ADS)

Caloiero, Tommaso; Aceto, Luigi; Aurora Pasqua, A.; Petrucci, Olga

2017-04-01

Calabria (southern Italy) is a region exposed to the effects of contrasting climatic and hydrological phenomena. In fact, due to its oblong shape, to its position in the middle of the Mediterranean Basin, and for its mountainous nature, Calabria shows a high spatial variability of the climatic features and of related phenomena such as floods and drought. The present paper is based on the historical database ASICal (Historically flooded areas in Calabria), a catalogue of effects of floods and rain-related landslides that occurred in the region since the XIX Century. The catalogue has been built using the typical historical data sources as chronicles, diaries, historical books, local and regional agencies, press archives, scientific papers, and documents of civil protection offices. From these sources, we selected information on damage caused by rain related phenomena at a municipal scale and chronologically sorted by year, month and day. The analysis of the entire catalogue allows highlighting the regional Damaging Hydrogeological Events (DHE), defined as periods of intense rain causing damage on regional sectors conventionally selected as larger than 30% of the entire regional territory. For each event, as a measure of the magnitude of rainfall, the return period of the daily rainfall recorded during the event has been evaluated. In addition, we recently carried out a similar historical research to identify the main drought events affecting the region. In this case, due to the spatial and temporal characteristics of drought, data are collected both at municipal and regional scale, and the temporal scale is generally monthly or annual. For each event, we used as climatic descriptors a drought index for monitoring drought phenomena. Among drought indices, we used the Standardized Precipitation Index (SPI) which can be considered the most robust and effective, since it can be calculated for different time-scales and can be used to analyse different drought categories. Moreover, the SPI is easier to calculate than complex indices, as it is based on precipitation alone, and allows comparing drought conditions among different periods and regions. Both the series have been analysed jointly, in order to obtain the general trend of extreme rain and drought, characterised by mean of descriptive climatic features and damage caused. The results supply a glance in the past climatic history of the region that can be used to project to future and be prepared for ongoing changes related to climate changes. In fact, the identification of the most floods and drought prone areas can be useful for both civil protection mitigation strategies and water resources management (water used for home, industrial, and agricultural purposes).

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

The Technical Efficiency of Specialised Milk Farms: A Regional View

PubMed Central

Špička, Jindřich; Smutka, Luboš

2014-01-01

The aim of the article is to evaluate production efficiency and its determinants of specialised dairy farming among the EU regions. In the most of European regions, there is a relatively high significance of small specialised farms including dairy farms. The DEAVRS method (data envelopment analysis with variable returns to scale) reveals efficient and inefficient regions including the scale efficiency. In the next step, the two-sample t-test determines differences of economic and structural indicators between efficient and inefficient regions. The research reveals that substitution of labour by capital/contract work explains the variability of the farm net value added per AWU (annual work unit) income indicator by more than 30%. The significant economic determinants of production efficiency in specialised dairy farming are farm size, herd size, crop output per hectare, productivity of energy, and capital (at α = 0.01). Specialised dairy farms in efficient regions have significantly higher farm net value added per AWU than inefficient regions. Agricultural enterprises in inefficient regions have a more extensive structure and produce more noncommodity output (public goods). Specialised dairy farms in efficient regions have a slightly higher milk yield, specific livestock costs of feed, bedding, and veterinary services per livestock unit. PMID:25050408

Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke

PubMed Central

Zavaglia, Melissa; Forkert, Nils D.; Cheng, Bastian; Gerloff, Christian; Thomalla, Götz; Hilgetag, Claus C.

2015-01-01

Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a ‘map of stroke’. PMID:26448908

Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke.

PubMed

Zavaglia, Melissa; Forkert, Nils D; Cheng, Bastian; Gerloff, Christian; Thomalla, Götz; Hilgetag, Claus C

2015-01-01

Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a 'map of stroke'.

Visual unit analysis: a descriptive approach to landscape assessment

Treesearch

R. J. Tetlow; S. R. J. Sheppard

1979-01-01

Analysis of the visible attributes of landscapes is an important component of the planning process. When landscapes are at regional scale, economical and effective methodologies are critical. The Visual Unit concept appears to offer a logical and useful framework for description and evaluation. The concept subdivides landscape into coherent, spatially-defined units....

Improving National Capability in Biogeochemical Flux Modelling: the UK Environmental Virtual Observatory (EVOp)

NASA Astrophysics Data System (ADS)

Johnes, P.; Greene, S.; Freer, J. E.; Bloomfield, J.; Macleod, K.; Reaney, S. M.; Odoni, N. A.

2012-12-01

The best outcomes from watershed management arise where policy and mitigation efforts are underpinned by strong science evidence, but there are major resourcing problems associated with the scale of monitoring needed to effectively characterise the sources rates and impacts of nutrient enrichment nationally. The challenge is to increase national capability in predictive modelling of nutrient flux to waters, securing an effective mechanism for transferring knowledge and management tools from data-rich to data-poor regions. The inadequacy of existing tools and approaches to address these challenges provided the motivation for the Environmental Virtual Observatory programme (EVOp), an innovation from the UK Natural Environment Research Council (NERC). EVOp is exploring the use of a cloud-based infrastructure in catchment science, developing an exemplar to explore N and P fluxes to inland and coastal waters in the UK from grid to catchment and national scale. EVOp is bringing together for the first time national data sets, models and uncertainty analysis into cloud computing environments to explore and benchmark current predictive capability for national scale biogeochemical modelling. The objective is to develop national biogeochemical modelling capability, capitalising on extensive national investment in the development of science understanding and modelling tools to support integrated catchment management, and supporting knowledge transfer from data rich to data poor regions, The AERC export coefficient model (Johnes et al., 2007) has been adapted to function within the EVOp cloud environment, and on a geoclimatic basis, using a range of high resolution, geo-referenced digital datasets as an initial demonstration of the enhanced national capacity for N and P flux modelling using cloud computing infrastructure. Geoclimatic regions are landscape units displaying homogenous or quasi-homogenous functional behaviour in terms of process controls on N and P cycling, underpin this approach (Johnes & Butterfield, 2002). Ten regions have been defined across the UK using GIS manipulation of spatial data describing hydrogeology, runoff, topographical slope and soil parent material. The export coefficient model operates within this regional modelling framework, providing mapped, tabulated and statistical outputs at scales from 1km2 grid scale to river catchment, WFD river basin district, major coastal drainage units to the North Sea, North Atlantic and English Channel, to the international reporting units defined under OSPAR, the International Convention for the protection of the marine environment of the North-East Atlantic. Here the geoclimatic modelling framework is presented together with modelled fluxes for N and P for each scale of reporting unit, together with scenario analysis applied at regional scale and mapped at national scale. The ways in which the results can be used to further explore the primary drivers for spatial variation and identify waterbodies at risk, especially in unmonitored and data-poor catchments are discussed, and the technical and computational support of a cloud-based infrastructure is evaluated as a mechanism to explore potential water quality impacts of future mitigation strategies applied at catchment to national scale.

Scaling uncertainties in estimating canopy foliar maintenance respiration for black spruce ecosystems in Alaska

USGS Publications Warehouse

Zhang, X.; McGuire, A.D.; Ruess, Roger W.

2006-01-01

A major challenge confronting the scientific community is to understand both patterns of and controls over spatial and temporal variability of carbon exchange between boreal forest ecosystems and the atmosphere. An understanding of the sources of variability of carbon processes at fine scales and how these contribute to uncertainties in estimating carbon fluxes is relevant to representing these processes at coarse scales. To explore some of the challenges and uncertainties in estimating carbon fluxes at fine to coarse scales, we conducted a modeling analysis of canopy foliar maintenance respiration for black spruce ecosystems of Alaska by scaling empirical hourly models of foliar maintenance respiration (Rm) to estimate canopy foliar Rm for individual stands. We used variation in foliar N concentration among stands to develop hourly stand-specific models and then developed an hourly pooled model. An uncertainty analysis identified that the most important parameter affecting estimates of canopy foliar Rm was one that describes R m at 0??C per g N, which explained more than 55% of variance in annual estimates of canopy foliar Rm. The comparison of simulated annual canopy foliar Rm identified significant differences between stand-specific and pooled models for each stand. This result indicates that control over foliar N concentration should be considered in models that estimate canopy foliar Rm of black spruce stands across the landscape. In this study, we also temporally scaled the hourly stand-level models to estimate canopy foliar Rm of black spruce stands using mean monthly temperature data. Comparisons of monthly Rm between the hourly and monthly versions of the models indicated that there was very little difference between the estimates of hourly and monthly models, suggesting that hourly models can be aggregated to use monthly input data with little loss of precision. We conclude that uncertainties in the use of a coarse-scale model for estimating canopy foliar Rm at regional scales depend on uncertainties in representing needle-level respiration and on uncertainties in representing the spatial variability of canopy foliar N across a region. The development of spatial data sets of canopy foliar N represents a major challenge in estimating canopy foliar maintenance respiration at regional scales. ?? Springer 2006.

Monitoring Cloud-prone Complex Landscapes At Multiple Spatial Scales Using Medium And High Resolution Optical Data: A Case Study In Central Africa

NASA Astrophysics Data System (ADS)

Basnet, Bikash

Tracking land surface dynamics over cloud-prone areas with complex mountainous terrain and a landscape that is heterogeneous at a scale of approximately 10 m, is an important challenge in the remote sensing of tropical regions in developing nations, due to the small plot sizes. Persistent monitoring of natural resources in these regions at multiple spatial scales requires development of tools to identify emerging land cover transformation due to anthropogenic causes, such as agricultural expansion and climate change. Along with the cloud cover and obstructions by topographic distortions due to steep terrain, there are limitations to the accuracy of monitoring change using available historical satellite imagery, largely due to sparse data access and the lack of high quality ground truth for classifier training. One such complex region is the Lake Kivu region in Central Africa. This work addressed these problems to create an effective process for monitoring the Lake Kivu region located in Central Africa. The Lake Kivu region is a biodiversity hotspot with a complex and heterogeneous landscape and intensive agricultural development, where individual plot sizes are often at the scale of 10m. Procedures were developed that use optical data from satellite and aerial observations at multiple scales to tackle the monitoring challenges. First, a novel processing chain was developed to systematically monitor the spatio-temporal land cover dynamics of this region over the years 1988, 2001, and 2011 using Landsat data, complemented by ancillary data. Topographic compensation was performed on Landsat reflectances to avoid the strong illumination angle impacts and image compositing was used to compensate for frequent cloud cover and thus incomplete annual data availability in the archive. A systematic supervised classification, using the state-of-the-art machine learning classifier Random Forest, was applied to the composite Landsat imagery to obtain land cover thematic maps with overall accuracies of 90% and higher. Subsequent change analysis between these years found extensive conversions of the natural environment as a result of human related activities. The gross forest cover loss for 1988--2001 and 2001--2011 periods was 216.4 and 130.5 thousand hectares, respectively, signifying significant deforestation in the period of civil war and a relatively stable and lower deforestation rate later, possibly due to conservation and reforestation efforts in the region. The other dominant land cover changes in the region were aggressive subsistence farming and urban expansion displacing natural vegetation and arable lands. Despite limited data availability, this study fills the gap of much needed detailed and updated land cover change information for this biologically important region of Central Africa. While useful on a regional scale, Landsat data can be inadequate for more detailed studies of land cover change. Based on an increasing availability of high resolution imagery and light detection and ranging (LiDAR) data from manned and unmanned aerial platforms (<1m resolution), a study was performed leading to a novel generic framework for land cover monitoring at fine spatial scales. The approach fuses high spatial resolution aerial imagery and LiDAR data to produce land cover maps with high spatial detail using object-based image analysis techniques. The classification framework was tested for a scene with both natural and cultural features and was found to be more than 90 percent accurate, sufficient for detailed land cover change studies.

A new method for detecting, quantifying and monitoring diffuse contamination

NASA Astrophysics Data System (ADS)

Fabian, Karl; Reimann, Clemens; de Caritat, Patrice

2017-04-01

A new method is presented for detecting and quantifying diffuse contamination at the regional to continental scale. It is based on the analysis of cumulative distribution functions (CDFs) in cumulative probability (CP) plots for spatially representative datasets, preferably containing >1000 samples. Simulations demonstrate how different types of contamination influence elemental CDFs of different sample media. Contrary to common belief, diffuse contamination does not result in exceedingly high element concentrations in regional- to continental-scale datasets. Instead it produces a distinctive shift of concentrations in the background distribution of the studied element resulting in a steeper data distribution in the CP plot. Via either (1) comparing the distribution of an element in top soil samples to the distribution of the same element in bottom soil samples from the same area, taking soil forming processes into consideration, or (2) comparing the distribution of the contaminating element (e.g., Pb) to that of an element with a geochemically comparable behaviour but no contamination source (e.g., Rb or Ba in case of Pb), the relative impact of diffuse contamination on the element concentration can be estimated either graphically in the CP plot via a best fit estimate or quantitatively via a Kolmogorov-Smirnov or Cramer vonMiese test. This is demonstrated using continental-scale geochemical soil datasets from Europe, Australia, and the USA, and a regional scale dataset from Norway. Several different datasets from Europe deliver comparable results at regional to continental scales. The method is also suitable for monitoring diffuse contamination based on the statistical distribution of repeat datasets at the continental scale in a cost-effective manner.

Executive Order 12898 and Social, Economic, and Sociopolitical Factors Influencing Toxic Release Inventory Facility Location in EPA Region 6: A Multi-Scale Spatial Assessment of Environmental Justice

ERIC Educational Resources Information Center

Moore, Andrea Lisa

2013-01-01

Toxic Release Inventory facilities are among the many environmental hazards shown to create environmental inequities in the United States. This project examined four factors associated with Toxic Release Inventory, specifically, manufacturing facility location at multiple spatial scales using spatial analysis techniques (i.e., O-ring statistic and…

Winter precipitation forecast in the European and Mediterranean regions using cluster analysis

NASA Astrophysics Data System (ADS)

Molnos, S.

2017-12-01

The European and Mediterranean climates are sensitive to large-scale circulation of the atmosphere andocean making it difficult to forecast precipitation or temperature on seasonal time-scales. In addition, theMediterranean region has been identified as a hotspot for climate change and already today a drying in theMediterranean region is observed.Thus, it is critically important to predict seasonal droughts as early as possible such that water managersand stakeholders can mitigate impacts.We developed a novel cluster-based forecast method to empirically predict winter's precipitationanomalies in European and Mediterranean regions using precursors in autumn. This approach does notonly utilizes the amplitude but also the pattern of the precursors in generating the forecast.Using a toy model we show that it achieves a better forecast skill than more traditional regression models. Furthermore, we compare our algorithm with dynamic forecast models demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

LANDSAT and radar mapping of intrusive rocks in SE-Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dossantos, A. R.; Dosanjos, C. E.; Moreira, J. C.; Barbosa, M. P.; Veneziani, P.

1982-01-01

The feasibility of intrusive rock mapping was investigated and criteria for regional geological mapping established at the scale of 1:500,00 in polycyclic and polymetamorphic areas using the logic method of photointerpretation of LANDSAT imagery and radar from the RADAMBRASIL project. The spectral behavior of intrusive rocks, was evaluated using the interactive multispectral image analysis system (Image-100). The region of Campos (city) in northern Rio de Janeiro State was selected as the study area and digital imagery processing and pattern recognition techniques were applied. Various maps at the 2:250,000 scale were obtained to evaluate the results of automatic data processing.

Focal temporal pole atrophy and network degeneration in semantic variant primary progressive aphasia

PubMed Central

Collins, Jessica A; Montal, Victor; Hochberg, Daisy; Quimby, Megan; Mandelli, Maria Luisa; Makris, Nikos; Seeley, William W; Gorno-Tempini, Maria Luisa; Dickerson, Bradford C

2017-01-01

Abstract A wealth of neuroimaging research has associated semantic variant primary progressive aphasia with distributed cortical atrophy that is most prominent in the left anterior temporal cortex; however, there is little consensus regarding which region within the anterior temporal cortex is most prominently damaged, which may indicate the putative origin of neurodegeneration. In this study, we localized the most prominent and consistent region of atrophy in semantic variant primary progressive aphasia using cortical thickness analysis in two independent patient samples (n = 16 and 28, respectively) relative to age-matched controls (n = 30). Across both samples the point of maximal atrophy was located in the same region of the left temporal pole. This same region was the point of maximal atrophy in 100% of individual patients in both semantic variant primary progressive aphasia samples. Using resting state functional connectivity in healthy young adults (n = 89), we showed that the seed region derived from the semantic variant primary progressive aphasia analysis was strongly connected with a large-scale network that closely resembled the distributed atrophy pattern in semantic variant primary progressive aphasia. In both patient samples, the magnitude of atrophy within a brain region was predicted by that region’s strength of functional connectivity to the temporopolar seed region in healthy adults. These findings suggest that cortical atrophy in semantic variant primary progressive aphasia may follow connectional pathways within a large-scale network that converges on the temporal pole. PMID:28040670

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dry spell trend analysis in Kenya and the Murray Darling Basin using daily rainfall

NASA Astrophysics Data System (ADS)

Muita, R. R.; van Ogtrop, F. F.; Vervoort, R. W.

2012-04-01

Important agricultural areas in Kenya and the Murray Darling Basin (MDB) in Australia are largely semi-arid to arid. Persistent dry periods and timing of dry spells directly impact the availability of soil moisture and hence crop production in these regions. Most studies focus on the analysis of dry spell lengths at an annual scale. However, timing and length of dry spells at finer temporal scales is more beneficial for cropping when considering a trade-off between the time scale and the ability to analyse dry spell length. The aim of this study was to analyse the interannual and intra annual variations in dry spell lengths in the regions to inform crop management. This study analysed monthly dry spells based on daily rainfall for 1961-2010 on a limited dataset of 13 locations in Kenya and 17 locations in the MDB. This dataset was the most consistent across both regions and future analysis will incorporate more stations and longer time periods where available. Dry spell lengths were analysed by month and year and trends in monthly and annual dry spell lengths were analysed using Generalised Linear Models (GLM) and the Mann Kendall test (MK). Overall, monthly dryspell lengths are right skewed with higher frequency of shorter dryspells (3-25 days). In Kenya, significant increases in mean dry spell lengths (p≤0.02) are observed in inland arid-to semi humid locations but this temporal trend appears to decrease in highland and the coastal regions. Analysis of the MDB stations suggests changes in seasonality. For example, spatial trends suggest a North-South increase in dry spell length in summer (December - February), but a shortening after February. Generally, the GLM and MK results are similar in the two regions but the MK test tends to give higher values of positive slope coefficients and lower values for negative coefficients compared to GLM. This may limit the ability of finding the best estimates for model coefficients. Previous studies in Australia and Kenya have relied on continuous climatic indices based on global climate models and stochastic processes resulting in limited and mixed results. For agronomical purposes, our results show that direct assessment of dry spells lengths from daily rainfall also indicates changes in dry spells trends in Kenya and the MDB and that such an analysis is easy to use and requires limited assumptions. This initial analysis identifies significant increasing trends in the dry spell lengths in some areas and periods in Kenya and the MDB. This has major implications for crop production in these regions and it is recommended that this information be incorporated in the regions' management decisions. KEY WORDS: monthly dry spell length; Generalized Linear Models; Mann -Kendall test; month; Kenya, Murray Darling Basin (MDB).

Dynamical analysis of Jovian polar observations by Juno

NASA Astrophysics Data System (ADS)

Tabataba-Vakili, Fachreddin; Orton, Glenn S.; Adriani, Alberto; Eichstaedt, Gerald; Grassi, Davide; Ingersoll, Andrew P.; Li, Cheng; Hansen, Candice; Momary, Thomas W.; Moriconi, Maria Luisa; Mura, Alessandro; Read, Peter L.; Rogers, John; Young, Roland M. B.

2017-10-01

The JunoCAM and JIRAM instruments onboard the Juno spacecraft have generated unparalleled observations of the Jovian polar regions. These observations reveal a turbulent environment with an unexpected structure of cyclonic polar vortices. We measure the wind velocity in the polar region using correlation image velocimetry of consecutive images. From this data, we calculate the kinetic energy fluxes between different length scales. An analysis of the kinetic energy spectra and eddy-zonal flow interactions may improve our understanding of the mechanisms maintaining the polar macroturbulence in the Jovian atmosphere.

Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

NASA Astrophysics Data System (ADS)

Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

2015-12-01

Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

Effects of Large-Scale Solar Installations on Dust Mobilization and Air Quality

NASA Astrophysics Data System (ADS)

Pratt, J. T.; Singh, D.; Diffenbaugh, N. S.

2012-12-01

Large-scale solar projects are increasingly being developed worldwide and many of these installations are located in arid, desert regions. To examine the effects of these projects on regional dust mobilization and air quality, we analyze aerosol product data from NASA's Multi-angle Imaging Spectroradiometer (MISR) at annual and seasonal time intervals near fifteen photovoltaic and solar thermal stations ranging from 5-200 MW (12-4,942 acres) in size. The stations are distributed over eight different countries and were chosen based on size, location and installation date; most of the installations are large-scale, took place in desert climates and were installed between 2006 and 2010. We also consider air quality measurements of particulate matter between 2.5 and 10 micrometers (PM10) from the Environmental Protection Agency (EPA) monitoring sites near and downwind from the project installations in the U.S. We use monthly wind data from the NOAA's National Center for Atmospheric Prediction (NCEP) Global Reanalysis to select the stations downwind from the installations, and then perform statistical analysis on the data to identify any significant changes in these quantities. We find that fourteen of the fifteen regions have lower aerosol product after the start of the installations as well as all six PM10 monitoring stations showing lower particulate matter measurements after construction commenced. Results fail to show any statistically significant differences in aerosol optical index or PM10 measurements before and after the large-scale solar installations. However, many of the large installations are very recent, and there is insufficient data to fully understand the long-term effects on air quality. More data and higher resolution analysis is necessary to better understand the relationship between large-scale solar, dust and air quality.

Germany wide seasonal flood risk analysis for agricultural crops

NASA Astrophysics Data System (ADS)

Klaus, Stefan; Kreibich, Heidi; Kuhlmann, Bernd; Merz, Bruno; Schröter, Kai

2016-04-01

In recent years, large-scale flood risk analysis and mapping has gained attention. Regional to national risk assessments are needed, for example, for national risk policy developments, for large-scale disaster management planning and in the (re-)insurance industry. Despite increasing requests for comprehensive risk assessments some sectors have not received much scientific attention, one of these is the agricultural sector. In contrast to other sectors, agricultural crop losses depend strongly on the season. Also flood probability shows seasonal variation. Thus, the temporal superposition of high flood susceptibility of crops and high flood probability plays an important role for agricultural flood risk. To investigate this interrelation and provide a large-scale overview of agricultural flood risk in Germany, an agricultural crop loss model is used for crop susceptibility analyses and Germany wide seasonal flood-frequency analyses are undertaken to derive seasonal flood patterns. As a result, a Germany wide map of agricultural flood risk is shown as well as the crop type most at risk in a specific region. The risk maps may provide guidance for federal state-wide coordinated designation of retention areas.

“Modeling Trends in Air Pollutant Concentrations over the ...

EPA Pesticide Factsheets

Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculations and often confound interpretation of model results. Since transport is efficient in the free-troposphere and since simulations over Continental scales and annual cycles provide sufficient opportunity for “atmospheric turn-over”, i.e., exchange between the free-troposphere and the boundary-layer, a conceptual framework is needed wherein interactions between processes occurring at various spatial and temporal scales can be consistently examined. The coupled WRF-CMAQ model is expanded to hemispheric scales and model simulations over period spanning 1990-current are analyzed to examine changes in hemispheric air pollution resulting from changes in emissions over this period. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for pr

Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis.

PubMed

Goch, Caspar J; Stieltjes, Bram; Henze, Romy; Hering, Jan; Poustka, Luise; Meinzer, Hans-Peter; Maier-Hein, Klaus H

2014-05-01

Diagnosis of autism spectrum disorders (ASD) is difficult, as symptoms vary greatly and are difficult to quantify objectively. Recent work has focused on the assessment of non-invasive diffusion tensor imaging-based biomarkers that reflect the microstructural characteristics of neuronal pathways in the brain. While tractography-based approaches typically analyze specific structures of interest, a graph-based large-scale network analysis of the connectome can yield comprehensive measures of larger-scale architectural patterns in the brain. Commonly applied global network indices, however, do not provide any specificity with respect to functional areas or anatomical structures. Aim of this work was to assess the concept of network centrality as a tool to perform locally specific analysis without disregarding the global network architecture and compare it to other popular network indices. We create connectome networks from fiber tractographies and parcellations of the human brain and compute global network indices as well as local indices for Wernicke's Area, Broca's Area and the Motor Cortex. Our approach was evaluated on 18 children suffering from ASD and 18 typically developed controls using magnetic resonance imaging-based cortical parcellations in combination with diffusion tensor imaging tractography. We show that the network centrality of Wernicke's area is significantly (p<0.001) reduced in ASD, while the motor cortex, which was used as a control region, did not show significant alterations. This could reflect the reduced capacity for comprehension of language in ASD. The betweenness centrality could potentially be an important metric in the development of future diagnostic tools in the clinical context of ASD diagnosis. Our results further demonstrate the applicability of large-scale network analysis tools in the domain of region-specific analysis with a potential application in many different psychological disorders.

Study of Plume Impingement Effects in the Lunar Lander Environment

NASA Technical Reports Server (NTRS)

Marichalar, Jeremiah; Prisbell, A.; Lumpkin, F.; LeBeau, G.

2010-01-01

Plume impingement effects from the descent and ascent engine firings of the Lunar Lander were analyzed in support of the Lunar Architecture Team under the Constellation Program. The descent stage analysis was performed to obtain shear and pressure forces on the lunar surface as well as velocity and density profiles in the flow field in an effort to understand lunar soil erosion and ejected soil impact damage which was analyzed as part of a separate study. A CFD/DSMC decoupled methodology was used with the Bird continuum breakdown parameter to distinguish the continuum flow from the rarefied flow. The ascent stage analysis was performed to ascertain the forces and moments acting on the Lunar Lander Ascent Module due to the firing of the main engine on take-off. The Reacting and Multiphase Program (RAMP) method of characteristics (MOC) code was used to model the continuum region of the nozzle plume, and the Direct Simulation Monte Carlo (DSMC) Analysis Code (DAC) was used to model the impingement results in the rarefied region. The ascent module (AM) was analyzed for various pitch and yaw rotations and for various heights in relation to the descent module (DM). For the ascent stage analysis, the plume inflow boundary was located near the nozzle exit plane in a region where the flow number density was large enough to make the DSMC solution computationally expensive. Therefore, a scaling coefficient was used to make the DSMC solution more computationally manageable. An analysis of the effectiveness of this scaling technique was performed by investigating various scaling parameters for a single height and rotation of the AM. Because the inflow boundary was near the nozzle exit plane, another analysis was performed investigating three different inflow contours to determine the effects of the flow expansion around the nozzle lip on the final plume impingement results.

Increasing bioenergy production on arable land: Does the regional and local climate respond? Germany as a case study

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Gutjahr, Oliver; Busch, Gerald; Thiele, Jan C.

2014-03-01

The extent and magnitude of land cover change effect on local and regional future climate during the vegetation period due to different forms of bioenergy plants are quantified for extreme temperatures and energy fluxes. Furthermore, we vary the spatial extent of plant allocation on arable land and simulate alternative availability of transpiration water to mimic both rainfed agriculture and irrigation. We perform climate simulations down to 1 km scale for 1970-1975 C20 and 2070-2075 A1B over Germany with Consortium for Small-Scale Modeling in Climate Mode. Here an impact analysis indicates a strong local influence due to land cover changes. The regional effect is decreased by two thirds of the magnitude of the local-scale impact. The changes are largest locally for irrigated poplar with decreasing maximum temperatures by 1°C in summer months and increasing specific humidity by 0.15 g kg-1. The increased evapotranspiration may result in more precipitation. The increase of surface radiative fluxes Rnet due to changes in latent and sensible heat is estimated by 5 W m-2locally. Moreover, increases in the surface latent heat flux cause strong local evaporative cooling in the summer months, whereas the associated regional cooling effect is pronounced by increases in cloud cover. The changes on a regional scale are marginal and not significant. Increasing bioenergy production on arable land may result in local temperature changes but not in substantial regional climate change in Germany. We show the effect of agricultural practices during climate transitions in spring and fall.

Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis.

PubMed

Lee, Seohyun; Cho, Yoon-Min; Kim, Sun-Young

2017-08-22

Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran's I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the northern area shows extensive low-low association. This study aimed to shed some light on the potential for strategic regional collaboration for scale-up of mHealth and mobile penetration. Firstly, countries in the eastern area with much experience can take the lead role in pursuing regional collaboration for mHealth programs in sub-Saharan Africa. Secondly, collective effort in improving mobile penetration rates for the northern area is recommended.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

PubMed

Rueckl, Martin; Lenzi, Stephen C; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca 2+ -imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca 2+ imaging datasets, particularly when these have been acquired at different spatial scales.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

PubMed Central

Rueckl, Martin; Lenzi, Stephen C.; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W.

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales. PMID:28706482

Identifying and Mitigating Potential Nutrient and Sediment Hot Spots under a Future Scenario in the Missouri River Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, May; Zhang, Zhonglong

Using the Soil and Water Assessment Tool (SWAT) for large-scale watershed modeling could be useful for evaluating the quality of the water in regions that are dominated by nonpoint sources in order to identify potential “hot spots” for which mitigating strategies could be further developed. An analysis of water quality under future scenarios in which changes in land use would be made to accommodate increased biofuel production was developed for the Missouri River Basin (MoRB) based on a SWAT model application. The analysis covered major agricultural crops and biofuel feedstock in the MoRB, including pasture land, hay, corn, soybeans, wheat,more » and switchgrass. The analysis examined, at multiple temporal and spatial scales, how nitrate, organic nitrogen, and total nitrogen; phosphorus, organic phosphorus, inorganic phosphorus, and total phosphorus; suspended sediments; and water flow (water yield) would respond to the shifts in land use that would occur under proposed future scenarios. The analysis was conducted at three geospatial scales: (1) large tributary basin scale (two: Upper MoRB and Lower MoRB); (2) regional watershed scale (seven: Upper Missouri River, Middle Missouri River, Middle Lower Missouri River, Lower Missouri River, Yellowstone River, Platte River, and Kansas River); and (3) eight-digit hydrologic unit (HUC-8) subbasin scale (307 subbasins). Results showed that subbasin-level variations were substantial. Nitrogen loadings decreased across the entire Upper MoRB, and they increased in several subbasins in the Lower MoRB. Most nitrate reductions occurred in lateral flow. Also at the subbasin level, phosphorus in organic, sediment, and soluble forms was reduced by 35%, 45%, and 65%, respectively. Suspended sediments increased in 68% of the subbasins. The water yield decreased in 62% of the subbasins. In the Kansas River watershed, the water quality improved significantly with regard to every nitrogen and phosphorus compound. The improvement was clearly attributable to the conversion of a large amount of land to switchgrass. The Middle Lower Missouri River and Lower Missouri River were identified as hot regions. Further analysis identified four subbasins (10240002, 10230007, 10290402, and 10300200) as being the most vulnerable in terms of sediment, nitrogen, and phosphorus loadings. Overall, results suggest that increasing the amount of switchgrass acreage in the hot spots should be considered to mitigate the nutrient loads. The study provides an analytical method to support stakeholders in making informed decisions that balance biofuel production and water sustainability.« less

Meta-Analysis of the Detection of Plant Pigment Concentrations Using Hyperspectral Remotely Sensed Data

PubMed Central

Huang, Jingfeng; Wei, Chen; Zhang, Yao; Blackburn, George Alan; Wang, Xiuzhen; Wei, Chuanwen; Wang, Jing

2015-01-01

Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a. PMID:26356842

Time tracking and interaction of energy-eddies at different scales

NASA Astrophysics Data System (ADS)

Cardesa, Jose I.; Vela-Martin, Alberto; Jimenez, Javier

2016-11-01

We study the energy cascade through coherent structures obtained in time-resolved simulations of incompressible, statistically steady isotropic turbulence. The structures are defined as geometrically connected regions of the flow with high kinetic energy. We compute the latter by band-pass filtering the velocity field around a scale r. We analyse the dynamics of structures extracted with different r, which are a proxy for eddies containing energy at those r. We find that the size of these "energy-eddies" scales with r, while their lifetime scales with the local eddy-turnover r 2 / 3ɛ - 1 / 3 , where ɛ is the energy dissipation averaged over all space and time. Furthermore, a statistical analysis over the lives of the eddies shows a slight predominance of the splitting over the merging process. When we isolate the eddies which do not interact with other eddies of the same scale, we observe a parent-child dependence by which, on average, structures are born at scale r during the decaying part of the life of a structure at scale r' > r . The energy-eddy at r' lives in the same region of space as that at r. Finally, we investigate how interactions between eddies at the same scale are echoed across other scales. Funded by the ERC project Coturb.

A joint prevention and control mechanism for air pollution in the Beijing-Tianjin-Hebei region in china based on long-term and massive data mining of pollutant concentration

NASA Astrophysics Data System (ADS)

Wang, Hongbo; Zhao, Laijun

2018-02-01

China's Beijing-Tianjin-Hebei (BTH) region suffers from the country's worst air pollution. The problem has caused widespread concern both at home and abroad. Based on long-term and massive data mining of PM2.5 and PM10 concentration, we found that these pollutants showed similar variations in four seasons, but the most severe pollution was in winter. Through cluster analysis of the winter daily average concentration (DAC) of the two pollutants, we defined regions with similar variations in pollutant concentrations in winter. For the most polluted cities in BTH, the relationship between correlation coefficients for winter DAC and the distance between cities revealed that PM2.5 has regional, large-scale characteristics, with concentrated outbreaks, whereas PM10 has local, small-scale characteristics, with outbreaks at multiple locations. By selecting the key cities with the strongest linear relationship between the pollutant's DAC of each city and the daily individual air quality index values of the BTH region and through cluster analysis on the correlations between the pollutant DACs of the key cities, we defined regional divisions suitable for Joint Prevention and Control of Atmospheric Pollution (JPCAP) program to control PM2.5 and PM10. Comprehensively considering the degree of influence of regional atmospheric pollution control (RAPC) on air quality in BTH, as well as the elasticity and urgency of RAPC, we defined the control grades of the JPCAP regions. We found both the regions and corresponding control grades were consistent for PM2.5 and PM10. The thinking and methods of atmospheric pollution control we proposed will have broad significance for implementation of RAPC in other regions around the world.

The problem and promise of scale dependency in community phylogenetics.

PubMed

Swenson, Nathan G; Enquist, Brian J; Pither, Jason; Thompson, Jill; Zimmerman, Jess K

2006-10-01

The problem of scale dependency is widespread in investigations of ecological communities. Null model investigations of community assembly exemplify the challenges involved because they typically include subjectively defined "regional species pools." The burgeoning field of community phylogenetics appears poised to face similar challenges. Our objective is to quantify the scope of the problem of scale dependency by comparing the phylogenetic structure of assemblages across contrasting geographic and taxonomic scales. We conduct phylogenetic analyses on communities within three tropical forests, and perform a sensitivity analysis with respect to two scaleable inputs: taxonomy and species pool size. We show that (1) estimates of phylogenetic overdispersion within local assemblages depend strongly on the taxonomic makeup of the local assemblage and (2) comparing the phylogenetic structure of a local assemblage to a species pool drawn from increasingly larger geographic scales results in an increased signal of phylogenetic clustering. We argue that, rather than posing a problem, "scale sensitivities" are likely to reveal general patterns of diversity that could help identify critical scales at which local or regional influences gain primacy for the structuring of communities. In this way, community phylogenetics promises to fill an important gap in community ecology and biogeography research.

A wavelet analysis of scaling laws and long-memory in stock market volatility

NASA Astrophysics Data System (ADS)

Vuorenmaa, Tommi A.

2005-05-01

This paper studies the time-varying behavior of scaling laws and long-memory. This is motivated by the earlier finding that in the FX markets a single scaling factor might not always be sufficient across all relevant timescales: a different region may exist for intradaily time-scales and for larger time-scales. In specific, this paper investigates (i) if different scaling regions appear in stock market as well, (ii) if the scaling factor systematically differs from the Brownian, (iii) if the scaling factor is constant in time, and (iv) if the behavior can be explained by the heterogenuity of the players in the market and/or by intraday volatility periodicity. Wavelet method is used because it delivers a multiresolution decomposition and has excellent local adaptiviness properties. As a consequence, a wavelet-based OLS method allows for consistent estimation of long-memory. Thus issues (i)-(iv) shed light on the magnitude and behavior of a long-memory parameter, as well. The data are the 5-minute volatility series of Nokia Oyj at the Helsinki Stock Exchange around the burst of the IT-bubble. Period one represents the era of "irrational exuberance" and another the time after it. The results show that different scaling regions (i.e. multiscaling) may appear in the stock markets and not only in the FX markets, the scaling factor and the long-memory parameter are systematically different from the Brownian and they do not have to be constant in time, and that the behavior can be explained for a significant part by an intraday volatility periodicity called the New York effect. This effect was magnified by the frenzy trading of short-term speculators in the bubble period. The found stronger long-memory is also attributable to irrational exuberance.

Scaling analysis of the non-Abelian quasiparticle tunneling in [Formula: see text] FQH states.

PubMed

Li, Qi; Jiang, Na; Wan, Xin; Hu, Zi-Xiang

2018-06-27

Quasiparticle tunneling between two counter propagating edges through point contacts could provide information on its statistics. Previous study of the short distance tunneling displays a scaling behavior, especially in the conformal limit with zero tunneling distance. The scaling exponents for the non-Abelian quasiparticle tunneling exhibit some non-trivial behaviors. In this work, we revisit the quasiparticle tunneling amplitudes and their scaling behavior in a full range of the tunneling distance by putting the electrons on the surface of a cylinder. The edge-edge distance can be smoothly tuned by varying the aspect ratio for a finite size cylinder. We analyze the scaling behavior of the quasiparticles for the Read-Rezayi [Formula: see text] states for [Formula: see text] and 4 both in the short and long tunneling distance region. The finite size scaling analysis automatically gives us a critical length scale where the anomalous correction appears. We demonstrate this length scale is related to the size of the quasiparticle at which the backscattering between two counter propagating edges starts to be significant.

Assessment of Forest Conservation Value Using a Species Distribution Model and Object-based Image Analysis

NASA Astrophysics Data System (ADS)

Jin, Y.; Lee, D. K.; Jeong, S. G.

2015-12-01

The ecological and social values of forests have recently been highlighted. Assessments of the biodiversity of forests, as well as their other ecological values, play an important role in regional and national conservation planning. The preservation of habitats is linked to the protection of biodiversity. For mapping habitats, species distribution model (SDM) is used for predicting suitable habitat of significant species, and such distribution modeling is increasingly being used in conservation science. However, the pixel-based analysis does not contain contextual or topological information. In order to provide more accurate habitats predictions, a continuous field view that assumes the real world is required. Here we analyze and compare at different scales, habitats of the Yellow Marten's(Martes Flavigula), which is a top predator and also an umbrella species in South Korea. The object-scale, which is a group of pixels that have similar spatial and spectral characteristics, and pixel-scale were used for SDM. Our analysis using the SDM at different scales suggests that object-scale analysis provides a superior representation of continuous habitat, and thus will be useful in forest conservation planning as well as for species habitat monitoring.

Analysis of the trade-off between high crop yield and low yield instability at the global scale

NASA Astrophysics Data System (ADS)

Ben-Ari, Tamara; Makowski, David

2016-10-01

Yield dynamics of major crops species vary remarkably among continents. Worldwide distribution of cropland influences both the expected levels and the interannual variability of global yields. An expansion of cultivated land in the most productive areas could theoretically increase global production, but also increase global yield instability if the most productive regions are characterized by high interannual yield variability. In this letter, we use portfolio analysis to quantify the tradeoff between the expected values and the interannual variance of global yield. We compute optimal frontiers for four crop species i.e., maize, rice, soybean and wheat and show how the distribution of cropland among large world regions can be optimized to either increase expected global crop production or decrease its interannual variability. We also show that a preferential allocation of cropland in the most productive regions can increase global expected yield at the expense of yield stability. Theoretically, optimizing the distribution of a small fraction of total cultivated areas can help find a good compromise between low instability and high crop yields at the global scale.

Linking land-use projections and forest fragmentation analysis.

Treesearch

Andrew J. Plantinga; Ralph J. Alig; Henry Eichman; David J. Lewis

2007-01-01

An econometric model of private land-use decisions is used to project land use to 2030 for each county in the continental United States. On a national scale, forest area is projected to increase overall between 0.1 and 0.2 percent per year between now and 2030. However, forest area is projected to decrease in a majority of regions, including the key forestry regions of...

Analysis techniques for background rejection at the Majorana Demonstrator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cuestra, Clara; Rielage, Keith Robert; Elliott, Steven Ray

2015-06-11

The MAJORANA Collaboration is constructing the MAJORANA DEMONSTRATOR, an ultra-low background, 40-kg modular HPGe detector array to search for neutrinoless double beta decay in 76Ge. In view of the next generation of tonne-scale Ge-based 0νββ-decay searches that will probe the neutrino mass scale in the inverted-hierarchy region, a major goal of the MAJORANA DEMONSTRATOR is to demonstrate a path forward to achieving a background rate at or below 1 count/tonne/year in the 4 keV region of interest around the Q-value at 2039 keV. The background rejection techniques to be applied to the data include cuts based on data reduction, pulsemore » shape analysis, event coincidences, and time correlations. The Point Contact design of the DEMONSTRATOR's germanium detectors allows for significant reduction of gamma background.« less

A simulation of high energy cosmic ray propagation 1

NASA Technical Reports Server (NTRS)

Honda, M.; Kifune, T.; Matsubara, Y.; Mori, M.; Nishijima, K.; Teshima, M.

1985-01-01

High energy cosmic ray propagation of the energy region 10 to the 14.5 power - 10 to the 18th power eV is simulated in the inter steller circumstances. In conclusion, the diffusion process by turbulent magnetic fields is classified into several regions by ratio of the gyro-radius and the scale of turbulence. When the ratio becomes larger then 10 to the minus 0.5 power, the analysis with the assumption of point scattering can be applied with the mean free path E sup 2. However, when the ratio is smaller than 10 to the minus 0.5 power, we need a more complicated analysis or simulation. Assuming the turbulence scale of magnetic fields of the Galaxy is 10-30pc and the mean magnetic field strength is 3 micro gauss, the energy of cosmic ray with that gyro-radius is about 10 to the 16.5 power eV.

Study of the invariant structure function of the reaction. pi. /sup -/p. --> gamma. /sup +/xxx at 5 GeV/c

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amaglobeli, N.S.; Budagov, Y.A.; Valkar, S.

1977-07-01

The invariant differential cross section f (x,p/sub perpendicular/) of the reaction ..pi../sup -/p..--> gamma../sup +/xxx at 5 GeV/c was measured in a broad range of x and p/sub perpendicular/. An approximating formula is found for f (x,p/sub perpendicular/). It is shown that the function f (x,p/sub perpendicular/) is not factorizable in the variables x and p/sub perpendicular/. In some regions of phase space scale-invariant (scaling) behavior of the differential cross section is observed. Analysis of the asymmetry of the longitudinal momentum spectrum of the photons indicates that the production mechanisms of neutral and charged pions are similar in the centralmore » region. The results of the analysis are in qualitative agreement with the predictions of the quark model of hadrons.« less

Thermokarst Characteristics and Distribution in a Transitional Arctic Biome: New Discoveries and Possible Monitoring Directions in a Climate Change Scenario

NASA Astrophysics Data System (ADS)

Balser, A. W.; Gooseff, M. N.; Jones, J. B.; Bowden, W. B.; Sanzone, D. M.; Allen, A.; Larouche, J. R.

2006-12-01

In arctic regions, climate warming is leading to permafrost melting and wide-scale ecosystem alteration. A prominent pathway of permafrost loss is through thermokarst, which includes the catastrophic loss of soil structure and rapid subsidence. The regional-scale distribution of thermokarst is poorly documented throughout arctic regions. Remote landscapes and a lack of reliable, regional-scale detection techniques severely hamper our understanding of past prevalence and present distribution patterns. Intensive field campaigns are providing key data to bolster our understanding of the distribution and the characteristics of thermokarst formation, and enabling comprehensive method studies to develop remotely-sensed detection techniques. The Noatak Valley in northwestern Alaska's Brooks Range mountains harbors a transitional landscape from arctic and alpine tundra to boreal forest, all contained in a single 7,000,000 acre watershed. Preliminary field investigations augmented by photogrammetric measurements in 2006 revealed consistent patterns in the distribution of classifiable thermokarst feature types in a 2300 square-mile study area in the middle Noatak basin. Four distinct classes of thermokarst show remarkably tight relationships with ambient slope and local landcover. These investigations tie to larger efforts to document past and present regional distribution, testing remotely sensed data analysis techniques for baseline metrics and a future monitoring scheme.

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2017-03-01

We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics

NASA Technical Reports Server (NTRS)

Iyengar, N.; Peng, C. K.; Morin, R.; Goldberger, A. L.; Lipsitz, L. A.

1996-01-01

We postulated that aging is associated with disruption in the fractallike long-range correlations that characterize healthy sinus rhythm cardiac interval dynamics. Ten young (21-34 yr) and 10 elderly (68-81 yr) rigorously screened healthy subjects underwent 120 min of continuous supine resting electrocardiographic recording. We analyzed the interbeat interval time series using standard time and frequency domain statistics and using a fractal measure, detrended fluctuation analysis, to quantify long-range correlation properties. In healthy young subjects, interbeat intervals demonstrated fractal scaling, with scaling exponents (alpha) from the fluctuation analysis close to a value of 1.0. In the group of healthy elderly subjects, the interbeat interval time series had two scaling regions. Over the short range, interbeat interval fluctuations resembled a random walk process (Brownian noise, alpha = 1.5), whereas over the longer range they resembled white noise (alpha = 0.5). Short (alpha s)- and long-range (alpha 1) scaling exponents were significantly different in the elderly subjects compared with young (alpha s = 1.12 +/- 0.19 vs. 0.90 +/- 0.14, respectively, P = 0.009; alpha 1 = 0.75 +/- 0.17 vs. 0.99 +/- 0.10, respectively, P = 0.002). The crossover behavior from one scaling region to another could be modeled as a first-order autoregressive process, which closely fit the data from four elderly subjects. This implies that a single characteristic time scale may be dominating heartbeat control in these subjects. The age-related loss of fractal organization in heartbeat dynamics may reflect the degradation of integrated physiological regulatory systems and may impair an individual's ability to adapt to stress.

Foraging destinations and marine habitat use of short-tailed albatrosses: A multi-scale approach using first-passage time analysis

USGS Publications Warehouse

Suryan, R.M.; Sato, F.; Balogh, G.R.; David, Hyrenbach K.; Sievert, P.R.; Ozaki, K.

2006-01-01

We used satellite telemetry, remotely sensed data (bathymetry, chlorophyll a (chl a), sea-surface temperature (SST), wind speed) and first-passage time (FPT) analysis to determine the distribution, movement patterns, and habitat associations of short-tailed albatrosses (Phoebastria albatrus) during the non-breeding season, 2002 and 2003. Satellite transmitters were deployed on birds immediately prior to their departure from a breeding colony at Torishima, Japan (n = 11), or at-sea in the Aleutian Islands (n = 3). Tracking durations ranged from 51 to 138 days for a total of 6709 locations after filtering (131 - 808 per bird). FPT (time required to transit a circle of given radius) revealed the location and spatial scale of area-restricted search (ARS) patterns along flight paths. On average, ARS occurred within 70 km radii. Consequently, the fit of the habitat use models increased at spatial scales beyond a 40 km FPT radius (R2 = 0.31) and stabilized for scales of 70 km and larger (R2=0.40- 0.51). At all scales, wind speed, depth or depth gradient, and chl a or chl a gradient had a significant effect on FPT (i.e., residence time). FPT increased within regions of higher gradients of depth and chl a. In contrast, FPT decreased within regions of greater depth and wind speed, with a significant interaction of wind speed and depth at some scales. Sea-surface temperature or its interactions were only significant at large spatial scales (???160 km FPT radius). Albatrosses engaged in ARS activities primarily over the shelf break and slope, including Kuroshio and Oyashio regions off the western subarctic gyre. Occasionally, birds transited the northern boundary of the Kuroshio Extension while in-route to the Aleutian Islands and Bering Sea, but overall spent little time in the western gyre. In the Aleutian Islands, ARS occurred within straits, particularly along the central and western part of the archipelago. In the Bering Sea, ARS occurred along the northern continental shelf break, the Kamchatka Current region, and east of the Commander Islands. Non-breeding short-tailed albatross concentrate foraging in oceanic areas characterized by gradients in topography and water column productivity. This study provides an understanding of the foraging ecology for a highly migratory, imperiled seabird, and confirms the importance of shelf break and slope regions as hot spots for a variety of top marine predators in the North Pacific.

Quadrantal multi-scale distribution entropy analysis of heartbeat interval series based on a modified Poincaré plot

NASA Astrophysics Data System (ADS)

Huo, Chengyu; Huang, Xiaolin; Zhuang, Jianjun; Hou, Fengzhen; Ni, Huangjing; Ning, Xinbao

2013-09-01

The Poincaré plot is one of the most important approaches in human cardiac rhythm analysis. However, further investigations are still needed to concentrate on techniques that can characterize the dispersion of the points displayed by a Poincaré plot. Based on a modified Poincaré plot, we provide a novel measurement named distribution entropy (DE) and propose a quadrantal multi-scale distribution entropy analysis (QMDE) for the quantitative descriptions of the scatter distribution patterns in various regions and temporal scales. We apply this method to the heartbeat interval series derived from healthy subjects and congestive heart failure (CHF) sufferers, respectively, and find that the discriminations between them are most significant in the first quadrant, which implies significant impacts on vagal regulation brought about by CHF. We also investigate the day-night differences of young healthy people, and it is shown that the results present a clearly circadian rhythm, especially in the first quadrant. In addition, the multi-scale analysis indicates that the results of healthy subjects and CHF sufferers fluctuate in different trends with variation of the scale factor. The same phenomenon also appears in circadian rhythm investigations of young healthy subjects, which implies that the cardiac dynamic system is affected differently in various temporal scales by physiological or pathological factors.

Mapping permeability over the surface of the Earth

USGS Publications Warehouse

Gleeson, T.; Smith, L.; Moosdorf, N.; Hartmann, J.; Durr, H.H.; Manning, A.H.; Van Beek, L. P. H.; Jellinek, A. Mark

2011-01-01

Permeability, the ease of fluid flow through porous rocks and soils, is a fundamental but often poorly quantified component in the analysis of regional-scale water fluxes. Permeability is difficult to quantify because it varies over more than 13 orders of magnitude and is heterogeneous and dependent on flow direction. Indeed, at the regional scale, maps of permeability only exist for soil to depths of 1-2 m. Here we use an extensive compilation of results from hydrogeologic models to show that regional-scale (>5 km) permeability of consolidated and unconsolidated geologic units below soil horizons (hydrolithologies) can be characterized in a statistically meaningful way. The representative permeabilities of these hydrolithologies are used to map the distribution of near-surface (on the order of 100 m depth) permeability globally and over North America. The distribution of each hydrolithology is generally scale independent. The near-surface mean permeability is of the order of ???5 ?? 10-14 m2. The results provide the first global picture of near-surface permeability and will be of particular value for evaluating global water resources and modeling the influence of climate-surface-subsurface interactions on global climate change. Copyright ?? 2011 by the American Geophysical Union.

Mapping permeability over the surface of the Earth

USGS Publications Warehouse

Gleeson, Tom; Smith, Leslie; Moosdorf, Nils; Hartmann, Jens; Durr, Hans H.; Manning, Andrew H.; van Beek, Ludovicus P. H.; Jellinek, A. Mark

2011-01-01

Permeability, the ease of fluid flow through porous rocks and soils, is a fundamental but often poorly quantified component in the analysis of regional-scale water fluxes. Permeability is difficult to quantify because it varies over more than 13 orders of magnitude and is heterogeneous and dependent on flow direction. Indeed, at the regional scale, maps of permeability only exist for soil to depths of 1-2 m. Here we use an extensive compilation of results from hydrogeologic models to show that regional-scale (>5 km) permeability of consolidated and unconsolidated geologic units below soil horizons (hydrolithologies) can be characterized in a statistically meaningful way. The representative permeabilities of these hydrolithologies are used to map the distribution of near-surface (on the order of 100 m depth) permeability globally and over North America. The distribution of each hydrolithology is generally scale independent. The near-surface mean permeability is of the order of -5 x 10-14 m2. The results provide the first global picture of near-surface permeability and will be of particular value for evaluating global water resources and modeling the influence of climate-surface-subsurface interactions on global climate change.

Analysis of interstellar cloud structure based on IRAS images

NASA Technical Reports Server (NTRS)

Scalo, John M.

1992-01-01

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct densely sampled column density maps of star-forming clouds, column density images of four nearby cloud complexes were constructed from IRAS data. The regions have various degrees of star formation activity, and most of them have probably not been affected much by the disruptive effects of young massive stars. The largest region, the Scorpius-Ophiuchus cloud complex, covers about 1000 square degrees (it was subdivided into a few smaller regions for analysis). Much of the work during the early part of the project focused on an 80 square degree region in the core of the Taurus complex, a well-studied region of low-mass star formation.

Analysis and modeling of the seasonal South China Sea temperature cycle using remote sensing

NASA Astrophysics Data System (ADS)

Twigt, Daniel J.; de Goede, Erik D.; Schrama, Ernst J. O.; Gerritsen, Herman

2007-10-01

The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale. It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated tidal mixing and exchange. This is motivated by the possibility to significantly increase the model’s computational efficiency when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature (SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply a SST nudging method at the free water surface. This considerably improves the model’s vertical temperature representation in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal temperature cycle for the deep SCS basin can be represented to a good degree. For shallow regions, the absence of tidal mixing and exchange has a clear impact on the model’s temperature representation. This effect on the large-scale temperature cycle can be compensated to a good degree by SST nudging for diagnostic applications.

[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

PubMed

Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

2016-07-01

Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

Comparative analysis of meteorological and hydrological drought in the Pearl River basin during the period 1960-2012

NASA Astrophysics Data System (ADS)

Xu, K.; Wu, C.; Hu, B.; Niu, J.

2017-12-01

Drought is one of the major natural hazards that can have devastating impacts on the regional environment, agriculture, and water resources. Previous studies have conducted the assessment of historic changes in meteorological drought over various regional scales but rarely considered hydrological drought due to limited hydrological observations. Here, we use a long-term (1960-2012) gridded hydro-meteorological data to present a comparative analysis of meteorological and hydrological drought in the Pearl River basin in southern China using the standardized precipitation index (SPI) and the standardized runoff index (SRI). The variation in SPI and SRI at four different timescales (1-, 3-, 6-, and 12-month) is investigated using the Mann-Kendall (M-K) method and continuous wavelet transform (CWT). The results indicate that the correlation between SPI and SRI is strong over the Pearl River basin and tends to be stronger at the longer timescale. Meanwhile, the periodic oscillation pattern of SPI becomes more consistent with that of SRI with the increased timescale. The SPI can be used as a substitute for SRI to represent the hydrological drought at the long-term scale. Overall there is a noticeably wetting trend mainly in the eastern parts and a significant drying trend mainly in the western regions and the downstream area of the Pearl River basin. The variability of meteorological drought is significant mainly in the eastern and western regions, while the variability of hydrological drought tends to be larger mainly in the western region. CWT analysis indicates a period of 0.75-7 years in both meteorological and hydrological droughts during the period 1960-2012 in the study region.

Extreme air pollution events in Hokkaido, Japan, traced back to early snowmelt and large-scale wildfires over East Eurasia: Case studies.

PubMed

Yasunari, Teppei J; Kim, Kyu-Myong; da Silva, Arlindo M; Hayasaki, Masamitsu; Akiyama, Masayuki; Murao, Naoto

2018-04-25

To identify the unusual climate conditions and their connections to air pollutions in a remote area due to wildfires, we examine three anomalous large-scale wildfires in May 2003, April 2008, and July 2014 over East Eurasia, as well as how products of those wildfires reached an urban city, Sapporo, in the northern part of Japan (Hokkaido), significantly affecting the air quality. NASA's MERRA-2 (the Modern-Era Retrospective analysis for Research and Applications, Version 2) aerosol re-analysis data closely reproduced the PM 2.5 variations in Sapporo for the case of smoke arrival in July 2014. Results show that all three cases featured unusually early snowmelt in East Eurasia, accompanied by warmer and drier surface conditions in the months leading to the fires, inducing long-lasting soil dryness and producing climate and environmental conditions conducive to active wildfires. Due to prevailing anomalous synoptic-scale atmospheric motions, smoke from those fires eventually reached a remote area, Hokkaido, and worsened the air quality in Sapporo. In future studies, continuous monitoring of the timing of Eurasian snowmelt and the air quality from the source regions to remote regions, coupled with the analysis of atmospheric and surface conditions, may be essential in more accurately predicting the effects of wildfires on air quality.

Exploring Northwest China's agricultural water-saving strategy: analysis of water use efficiency based on an SE-DEA model conducted in Xi'an, Shaanxi Province.

PubMed

Mu, L; Fang, L; Wang, H; Chen, L; Yang, Y; Qu, X J; Wang, C Y; Yuan, Y; Wang, S B; Wang, Y N

Worldwide, water scarcity threatens delivery of water to urban centers. Increasing water use efficiency (WUE) is often recommended to reduce water demand, especially in water-scarce areas. In this paper, agricultural water use efficiency (AWUE) is examined using the super-efficient data envelopment analysis (DEA) approach in Xi'an in Northwest China at a temporal and spatial level. The grey systems analysis technique was then adopted to identify the factors that influenced the efficiency differentials under the shortage of water resources. From the perspective of temporal scales, the AWUE increased year by year during 2004-2012, and the highest (2.05) was obtained in 2009. Additionally, the AWUE was the best in the urban area at the spatial scale. Moreover, the key influencing factors of the AWUE are the financial situations and agricultural water-saving technology. Finally, we identified several knowledge gaps and proposed water-saving strategies for increasing AWUE and reducing its water demand by: (1) improving irrigation practices (timing and amounts) based on compatible water-saving techniques; (2) maximizing regional WUE by managing water resources and allocation at regional scales as well as enhancing coordination among Chinese water governance institutes.

Allee effects and the spatial dynamics of a locally endangered butterfly, the high brown fritillary (Argynnis adippe).

PubMed

Bonsall, Michael B; Dooley, Claire A; Kasparson, Anna; Brereton, Tom; Roy, David B; Thomas, Jeremy A

2014-01-01

Conservation of endangered species necessitates a full appreciation of the ecological processes affecting the regulation, limitation, and persistence of populations. These processes are influenced by birth, death, and dispersal events, and characterizing them requires careful accounting of both the deterministic and stochastic processes operating at both local and regional population levels. We combined ecological theory and observations on Allee effects by linking mathematical analysis and the spatial and temporal population dynamics patterns of a highly endangered butterfly, the high brown fritillary, Argynnis adippe. Our theoretical analysis showed that the role of density-dependent feedbacks in the presence of local immigration can influence the strength of Allee effects. Linking this theory to the analysis of the population data revealed strong evidence for both negative density dependence and Allee effects at the landscape or regional scale. These regional dynamics are predicted to be highly influenced by immigration. Using a Bayesian state-space approach, we characterized the local-scale births, deaths, and dispersal effects together with measurement and process uncertainty in the metapopulation. Some form of an Allee effect influenced almost three-quarters of these local populations. Our joint analysis of the deterministic and stochastic dynamics suggests that a conservation priority for this species would be to increase resource availability in currently occupied and, more importantly, in unoccupied sites.

Turbulence in simulated H II regions

NASA Astrophysics Data System (ADS)

Medina, S.-N. X.; Arthur, S. J.; Henney, W. J.; Mellema, G.; Gazol, A.

2014-12-01

We investigate the scale dependence of fluctuations inside a realistic model of an evolving turbulent H II region and to what extent these may be studied observationally. We find that the multiple scales of energy injection from champagne flows and the photoionization of clumps and filaments leads to a flatter spectrum of fluctuations than would be expected from top-down turbulence driven at the largest scales. The traditional structure function approach to the observational study of velocity fluctuations is shown to be incapable of reliably determining the velocity power spectrum of our simulation. We find that a more promising approach is the Velocity Channel Analysis technique of Lazarian & Pogosyan (2000), which, despite being intrinsically limited by thermal broadening, can successfully recover the logarithmic slope of the velocity power spectrum to a precision of ±0.1 from high-resolution optical emission-line spectroscopy.

Identification of high shears and compressive discontinuities in the inner heliosphere

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greco, A.; Perri, S.

2014-04-01

Two techniques, the Partial Variance of Increments (PVI) and the Local Intermittency Measure (LIM), have been applied and compared using MESSENGER magnetic field data in the solar wind at a heliocentric distance of about 0.3 AU. The spatial properties of the turbulent field at different scales, spanning the whole inertial range of magnetic turbulence down toward the proton scales have been studied. LIM and PVI methodologies allow us to identify portions of an entire time series where magnetic energy is mostly accumulated, and regions of intermittent bursts in the magnetic field vector increments, respectively. A statistical analysis has revealed thatmore » at small time scales and for high level of the threshold, the bursts present in the PVI and the LIM series correspond to regions of high shear stress and high magnetic field compressibility.« less

Scale problems in assessment of hydrogeological parameters of groundwater flow models

NASA Astrophysics Data System (ADS)

Nawalany, Marek; Sinicyn, Grzegorz

2015-09-01

An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i) spatial extent and geometry of hydrogeological system, (ii) spatial continuity and granularity of both natural and man-made objects within the system, (iii) duration of the system and (iv) continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale - scale of pores, meso-scale - scale of laboratory sample, macro-scale - scale of typical blocks in numerical models of groundwater flow, local-scale - scale of an aquifer/aquitard and regional-scale - scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical) block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here). Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.

Hybridized Kibble-Zurek scaling in the driven critical dynamics across an overlapping critical region

NASA Astrophysics Data System (ADS)

Zhai, Liang-Jun; Wang, Huai-Yu; Yin, Shuai

2018-04-01

The conventional Kibble-Zurek scaling describes the scaling behavior in the driven dynamics across a single critical region. In this paper, we study the driven dynamics across an overlapping critical region, in which a critical region (Region A) is overlaid by another critical region (Region B). We develop a hybridized Kibble-Zurek scaling (HKZS) to characterize the scaling behavior in the driven process. According to the HKZS, the driven dynamics in the overlapping region can be described by the critical theories for both Region A and Region B simultaneously. This results in a constraint on the scaling function in the overlapping critical region. We take the quantum Ising chain in an imaginary longitudinal field as an example. In this model, the critical region of the Yang-Lee edge singularity and the critical region of the ferromagnetic-paramagnetic phase transition overlap with each other. We numerically confirm the HKZS by simulating the driven dynamics in this overlapping critical region. The HKZSs in other models are also discussed.

Global maps of the magnetic thickness and magnetization of the Earth's lithosphere

NASA Astrophysics Data System (ADS)

Vervelidou, Foteini; Thébault, Erwan

2015-10-01

We have constructed global maps of the large-scale magnetic thickness and magnetization of Earth's lithosphere. Deriving such large-scale maps based on lithospheric magnetic field measurements faces the challenge of the masking effect of the core field. In this study, the maps were obtained through analyses in the spectral domain by means of a new regional spatial power spectrum based on the Revised Spherical Cap Harmonic Analysis (R-SCHA) formalism. A series of regional spectral analyses were conducted covering the entire Earth. The R-SCHA surface power spectrum for each region was estimated using the NGDC-720 spherical harmonic (SH) model of the lithospheric magnetic field, which is based on satellite, aeromagnetic, and marine measurements. These observational regional spectra were fitted to a recently proposed statistical expression of the power spectrum of Earth's lithospheric magnetic field, whose free parameters include the thickness and magnetization of the magnetic sources. The resulting global magnetic thickness map is compared to other crustal and magnetic thickness maps based upon different geophysical data. We conclude that the large-scale magnetic thickness of the lithosphere is on average confined to a layer that does not exceed the Moho.

An analysis of the impacts of global climate and emissions changes on regional tropospheric ozone

NASA Technical Reports Server (NTRS)

John, Kuruvilla; Crist, Kevin C.; Carmichael, Gregory R.

1994-01-01

Many of the synergistic impacts resulting from future changes in emissions as well as changes in ambient temperature, moisture, and UV flux have not been quantified. A three-dimensional regional-scale photo-chemical model (STEM-2) is used in this study to evaluate these perturbations to trace gas cycles over the eastern half of the United States of America. The model was successfully used to simulate a regional-scale ozone episode (base case - June 1984) and four perturbations scenarios - viz., perturbed emissions, temperature, water vapor column, and incoming UV flux cases, and a future scenario (for the year 2034). The impact of these perturbation scenarios on the distribution of ozone and other major pollutants such as SO2 and sulfates were analyzed in detail. The spatial distribution and the concentration of ozone at the surface increased by about 5-15 percent for most cases except for the perturbed water vapor case. The regional scale surface ozone concentration distribution for the year 2034 (future scenario) showed an increase of non-attainment areas. The rural areas of Pennsylvania, West Virginia, and Georgia showed the largest change in the surface ozone field for the futuristic scenario when compared to the base case.

Multi-scale linkages of winter drought variability to ENSO and the Arctic Oscillation: A case study in Shaanxi, North China

NASA Astrophysics Data System (ADS)

Liu, Zhiyong; Zhang, Xin; Fang, Ruihong

2018-02-01

Understanding the potential connections between climate indices such as the El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) and drought variability will be beneficial for making reasonable predictions or assumptions about future regional droughts, and provide valuable information to improve water resources planning and design for specific regions of interest. This study is to examine the multi-scale relationships between winter drought variability over Shaanxi (North China) and both ENSO and AO during the period 1960-2009. To accomplish this, we first estimated winter dryness/wetness conditions over Shaanxi based on the self-calibrating Palmer drought severity index (PDSI). Then, we identified the spatiotemporal variability of winter dryness/wetness conditions in the study area by using the empirical orthogonal function (EOF). Two primary sub-regions of winter dryness/wetness conditions across Shaanxi were identified. We further examined the periodical oscillations of dryness/wetness conditions and the multi-scale relationships between dryness/wetness conditions and both ENSO and AO in winter using wavelet analysis. The results indicate that there are inverse multi-scale relations between winter dryness/wetness conditions and ENSO (according to the wavelet coherence) for most of the study area. Moreover, positive multi-scale relations between winter dryness/wetness conditions and AO are mainly observed. The results could be beneficial for making reasonable predictions or assumptions about future regional droughts and provide valuable information to improve water resources planning and design within this study area. In addition to the current study area, this study may also offer a useful reference for other regions worldwide with similar climate conditions.

Large-scale coherent structures of suspended dust concentration in the neutral atmospheric surface layer: A large-eddy simulation study

NASA Astrophysics Data System (ADS)

Zhang, Yangyue; Hu, Ruifeng; Zheng, Xiaojing

2018-04-01

Dust particles can remain suspended in the atmospheric boundary layer, motions of which are primarily determined by turbulent diffusion and gravitational settling. Little is known about the spatial organizations of suspended dust concentration and how turbulent coherent motions contribute to the vertical transport of dust particles. Numerous studies in recent years have revealed that large- and very-large-scale motions in the logarithmic region of laboratory-scale turbulent boundary layers also exist in the high Reynolds number atmospheric boundary layer, but their influence on dust transport is still unclear. In this study, numerical simulations of dust transport in a neutral atmospheric boundary layer based on an Eulerian modeling approach and large-eddy simulation technique are performed to investigate the coherent structures of dust concentration. The instantaneous fields confirm the existence of very long meandering streaks of dust concentration, with alternating high- and low-concentration regions. A strong negative correlation between the streamwise velocity and concentration and a mild positive correlation between the vertical velocity and concentration are observed. The spatial length scales and inclination angles of concentration structures are determined, compared with their flow counterparts. The conditionally averaged fields vividly depict that high- and low-concentration events are accompanied by a pair of counter-rotating quasi-streamwise vortices, with a downwash inside the low-concentration region and an upwash inside the high-concentration region. Through the quadrant analysis, it is indicated that the vertical dust transport is closely related to the large-scale roll modes, and ejections in high-concentration regions are the major mechanisms for the upward motions of dust particles.

Tree growth and climate in the Pacific Northwest, North America: a broad-scale analysis of changing growth environments

Treesearch

Whitney L. Albright; David L. Peterson

2013-01-01

Climate change in the 21st century will affect tree growth in the Pacific Northwest region of North America, although complex climate–growth relationships make it difficult to identify how radial growth will respond across different species distributions. We used a novel method to examine potential growth responses to climate change at a broad geographical scale with a...

Antipsychotics reverse abnormal EEG complexity in drug-naïve schizophrenia: A multiscale entropy analysis

PubMed Central

Takahashi, Tetsuya; Cho, Raymond Y.; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Murata, Tetsuhito; Takahashi, Koichi; Wada, Yuji

2010-01-01

Multiscale entropy (MSE) analysis is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. To evaluate this analytic approach as an aid to elucidating the pathophysiologic mechanisms in schizophrenia, we examined MSE in EEG activity in drug-naïve schizophrenia subjects pre- and post-treatment with antipsychotics in comparison with traditional EEG analysis. We recorded eyes-closed resting state EEG from frontal, temporal, parietal and occipital regions in drug-naïve 22 schizophrenia and 24 age-matched healthy control subjects. Fifteen patients were re-evaluated within 2–8 weeks after the initiation of antipsychotic treatment. For each participant, MSE was calculated on one continuous 60 second epoch for each experimental session. Schizophrenia subjects showed significantly higher complexity at higher time scales (lower frequencies), than that of healthy controls in fronto-centro-temporal, but not in parieto-occipital regions. Post-treatment, this higher complexity decreased to healthy control subject levels selectively in fronto-central regions, while the increased complexity in temporal sites remained higher. Comparative power analysis identified spectral slowing in frontal regions in pre-treatment schizophrenia subjects, consistent with previous findings, whereas no antipsychotic treatment effect was observed. In summary, multiscale entropy measures identified abnormal dynamical EEG signal complexity in anterior brain areas in schizophrenia that normalized selectively in fronto-central areas with antipsychotic treatment. These findings show that entropy-based analytic methods may serve as a novel approach for characterizing and understanding abnormal cortical dynamics in schizophrenia, and elucidating the therapeutic mechanisms of antipsychotics. PMID:20149880

Techniques for spatio-temporal analysis of vegetation fires in the topical belt of Africa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brivio, P.A.; Ober, G.; Koffi, B.

1995-12-31

Biomass burning of forests and savannas is a phenomenon of continental or even global proportions, capable of causing large scale environmental changes. Satellite space observations, in particular from NOAA-AVHRR GAC data, are the only source of information allowing one to document burning patterns at regional and continental scale and over long periods of time. This paper presents some techniques, such as clustering and rose-diagram, useful in the spatial-temporal analysis of satellite derived fires maps to characterize the evolution of spatial patterns of vegetation fires at regional scale. An automatic clustering approach is presented which enables one to describe and parameterizemore » spatial distribution of fire patterns at different scales. The problem of geographical distribution of vegetation fires with respect to some location of interest, point or line, is also considered and presented. In particular rose-diagrams are used to relate fires patterns to some reference point, as experimental sites of tropospheric chemistry measurements. Different temporal data-sets in the tropical belt of Africa, covering both Northern and Southern Hemisphere dry seasons, using these techniques were analyzed and showed very promising results when compared with data from rain chemistry studies at different sampling sites in the equatorial forest.« less

Can Genre Be "Heard" in Scale as Well as Song Tasks? An Exploratory Study of Female Singing in Western Lyric and Musical Theater Styles.

PubMed

Kayes, Gillyanne; Welch, Graham F

2017-05-01

Using an empirical design, this study investigated perceptual and acoustic differences between the recorded vocal products of songs and scales of professional female singers of classical Western Lyric (WL) and non-legit Musical Theater (MT) styles. A total of 54 audio-recorded samples of songs and scales from professional female singers were rated in a blind randomized testing process by seven expert listeners as being performed by either a WL or MT singer. Songs and scales that were accurately perceived by genre were then analyzed intra- and inter-genre using long-term average spectrum analysis. A high level of agreement was found between judges in ratings for both songs and scales according to genre (P < 0.0001). Judges were more successful in locating WL than MT, but accuracy was always >50%. For the long-term average spectrum analysis intra-genre, song and scale matched better than chance. The highest spectral peak for the WL singers was at the mean fundamental frequency, whereas this spectral area was weaker for the MT singers, who showed a marked peak at 1 kHz. The other main inter-genre difference appeared in the higher frequency region, with a peak in the MT spectrum between 4 and 5 kHz-the region of the "speaker's formant." In comparing female singers of WL and MT styles, scales as well as song tasks appear to be indicative of singer genre behavior. This implied difference in vocal production may be useful to teachers and clinicians dealing with multiple genres. The addition of a scale-in-genre task may be useful in future research seeking to identify genre-distinctive behaviors. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Variation objective analyses for cyclone studies

NASA Technical Reports Server (NTRS)

Achtemeier, G. L.; Kidder, S. Q.; Ochs, H. T.

1985-01-01

The objectives were to: (1) develop an objective analysis technique that will maximize the information content of data available from diverse sources, with particular emphasis on the incorporation of observations from satellites with those from more traditional immersion techniques; and (2) to develop a diagnosis of the state of the synoptic scale atmosphere on a much finer scale over a much broader region than is presently possible to permit studies of the interactions and energy transfers between global, synoptic and regional scale atmospheric processes. The variational objective analysis model consists of the two horizontal momentum equations, the hydrostatic equation, and the integrated continuity equation for a dry hydrostatic atmosphere. Preliminary tests of the model with the SESMAE I data set are underway for 12 GMT 10 April 1979. At this stage of purpose of the analysis is not the diagnosis of atmospheric structures but rather the validation of the model. Model runs for rawinsonde data and with the precision modulus weights set to force most of the adjustment of the wind field to the mass field have produced 90 to 95 percent reductions in the imbalance of the initial data after only 4-cycles through the Euler-Lagrange equations. Sensitivity tests for linear stability of the 11 Euler-Lagrange equations that make up the VASP Model 1 indicate that there will be a lower limit to the scales of motion that can be resolved by this method. Linear stability criteria are violated where there is large horizontal wind shear near the upper tropospheric jet.

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

NASA Technical Reports Server (NTRS)

Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

2013-01-01

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

The Spatial-Kinematic Structure of the Region of Massive Star Formation S255N on Various Scales

NASA Astrophysics Data System (ADS)

Zemlyanukha, P. M.; Zinchenko, I. I.; Salii, S. V.; Ryabukhina, O. L.; Liu, S.-Y.

2018-05-01

The results of a detailed analysis of SMA, VLA, and IRAM observations of the region of massive star formation S255N in CO(2-1), N2H+(3-2), NH3(1, 1), C18O(2-1) and some other lines is presented. Combining interferometer and single-dish data has enabled a more detailed investigation of the gas kinematics in the moleclar core on various spatial scales. There are no signs of rotation or isotropic compression on the scale of the region as whole. The largest fragments of gas (≈0.3 pc) are located near the boundary of the regions of ionized hydrogen S255 and S257. Some smaller-scale fragments are associated with protostellar clumps. The kinetic temperatures of these fragments lie in the range 10-80 K. A circumstellar torus with inner radius R in ≈ 8000 AU and outer radius R out ≈ 12 000 AU has been detected around the clump SMA1. The rotation profile indicates the existence of a central object with mass ≈8.5/ sin2( i) M ⊙. SMA1 is resolved into two clumps, SMA1-NE and SMA1-SE, whose temperatures are≈150Kand≈25 K, respectively. To all appearances, the torus is involved in the accretion of surrounding gas onto the two protostellar clumps.

A first determination of the unpolarized quark TMDs from a global analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bacchetta, Alessandro; Delcarro, Filippo; Pisano, Cristian

Transverse momentum dependent distribution and fragmentation functions of unpolarized quarks inside unpolarized protons are extracted, for the first time, through a simultaneous analysis of semi-inclusive deep-inelastic scattering, Drell-Yan and Z boson hadroproduction processes. This study is performed at leading order in perturbative QCD, with energy scale evolution at the next-to-leading logarithmic accuracy. Moreover, some specific choices are made to deal with low scale evolution around 1 GeV2. Since only data in the low transverse momentum region are considered, no matching to fixed-order calculations at high transverse momentum is needed.

Comparison of the Defense Meteorological Satellite Program (DMSP) and the NOAA Polar-Orbiting Operational Environmental Satellite (POES) Program,

DTIC Science & Technology

1985-10-01

grid points on 1 /20 lat /long meshI 4 c. SST global scale analysis ( 1 or 100 km lat /long grid) .. d. SST climatic scale analysis (50 or 500 km lat ...long grid) e. SST monthly means (2 1 /20 or 250 km lat /long grid) 3. Analog Sea Surface Temperature Product Set ’-%". V" " a. GOSSTCOMP charts - weekly...Mercator contour charts, each a ., 500 by 500 lat /long segment, 1 °C contour interval b. Regional charts - set of three charts covering the U.S

Scale-Free and Multifractal Time Dynamics of fMRI Signals during Rest and Task

PubMed Central

Ciuciu, P.; Varoquaux, G.; Abry, P.; Sadaghiani, S.; Kleinschmidt, A.

2012-01-01

Scaling temporal dynamics in functional MRI (fMRI) signals have been evidenced for a decade as intrinsic characteristics of ongoing brain activity (Zarahn et al., 1997). Recently, scaling properties were shown to fluctuate across brain networks and to be modulated between rest and task (He, 2011): notably, Hurst exponent, quantifying long memory, decreases under task in activating and deactivating brain regions. In most cases, such results were obtained: First, from univariate (voxelwise or regionwise) analysis, hence focusing on specific cognitive systems such as Resting-State Networks (RSNs) and raising the issue of the specificity of this scale-free dynamics modulation in RSNs. Second, using analysis tools designed to measure a single scaling exponent related to the second order statistics of the data, thus relying on models that either implicitly or explicitly assume Gaussianity and (asymptotic) self-similarity, while fMRI signals may significantly depart from those either of those two assumptions (Ciuciu et al., 2008; Wink et al., 2008). To address these issues, the present contribution elaborates on the analysis of the scaling properties of fMRI temporal dynamics by proposing two significant variations. First, scaling properties are technically investigated using the recently introduced Wavelet Leader-based Multifractal formalism (WLMF; Wendt et al., 2007). This measures a collection of scaling exponents, thus enables a richer and more versatile description of scale invariance (beyond correlation and Gaussianity), referred to as multifractality. Also, it benefits from improved estimation performance compared to tools previously used in the literature. Second, scaling properties are investigated in both RSN and non-RSN structures (e.g., artifacts), at a broader spatial scale than the voxel one, using a multivariate approach, namely the Multi-Subject Dictionary Learning (MSDL) algorithm (Varoquaux et al., 2011) that produces a set of spatial components that appear more sparse than their Independent Component Analysis (ICA) counterpart. These tools are combined and applied to a fMRI dataset comprising 12 subjects with resting-state and activation runs (Sadaghiani et al., 2009). Results stemming from those analysis confirm the already reported task-related decrease of long memory in functional networks, but also show that it occurs in artifacts, thus making this feature not specific to functional networks. Further, results indicate that most fMRI signals appear multifractal at rest except in non-cortical regions. Task-related modulation of multifractality appears only significant in functional networks and thus can be considered as the key property disentangling functional networks from artifacts. These finding are discussed in the light of the recent literature reporting scaling dynamics of EEG microstate sequences at rest and addressing non-stationarity issues in temporally independent fMRI modes. PMID:22715328

Origins and spread of agriculture in Italy: a nonmetric dental analysis.

PubMed

Coppa, A; Cucina, A; Lucci, M; Mancinelli, D; Vargiu, R

2007-07-01

Dental morphological traits were employed in this study as direct indicators of biological affinities among the populations that inhabited the Italian peninsula from the Upper Paleolithic-Mesolithic to Medieval times. Our analysis aims at contributing to the ongoing debate regarding the origin and spread of agriculture in the peninsula by contrasting the dental evidence of archaeological and modern molecular samples. It is not possible to generalize given the complex and dynamic nature of these populations. However, the results from the principal component analysis, maximum likelihood, mean measure of divergence, and multidimensional scaling do indicate a net separation of the Paleo-Mesolithic sample from the other groups that is not related to dental reduction. This suggests that the shift in dental morphology was the product of Neolithic populations migrating into the peninsula from other areas. Nonetheless, the Paleo-Mesolithic populations share several discriminative traits with the Neolithic group. The biological relevance of such evidence suggests that, to some minor extent, the spread of agriculture did not occur by total population replacement. Because of regional small sample sizes, this hypothesis cannot be tested on a micro-regional scale. It is, however, feasible to depict a scenario where processes of genetic mixture or replacement probably took place at different rates on a macro-regional level. (c) 2007 Wiley-Liss, Inc.

Selective attention to temporal features on nested time scales.

PubMed

Henry, Molly J; Herrmann, Björn; Obleser, Jonas

2015-02-01

Meaningful auditory stimuli such as speech and music often vary simultaneously along multiple time scales. Thus, listeners must selectively attend to, and selectively ignore, separate but intertwined temporal features. The current study aimed to identify and characterize the neural network specifically involved in this feature-selective attention to time. We used a novel paradigm where listeners judged either the duration or modulation rate of auditory stimuli, and in which the stimulation, working memory demands, response requirements, and task difficulty were held constant. A first analysis identified all brain regions where individual brain activation patterns were correlated with individual behavioral performance patterns, which thus supported temporal judgments generically. A second analysis then isolated those brain regions that specifically regulated selective attention to temporal features: Neural responses in a bilateral fronto-parietal network including insular cortex and basal ganglia decreased with degree of change of the attended temporal feature. Critically, response patterns in these regions were inverted when the task required selectively ignoring this feature. The results demonstrate how the neural analysis of complex acoustic stimuli with multiple temporal features depends on a fronto-parietal network that simultaneously regulates the selective gain for attended and ignored temporal features. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Regional estimation of catchment-scale soil properties by means of streamflow recession analysis for use in distributed hydrological models

NASA Astrophysics Data System (ADS)

Vannier, Olivier; Braud, Isabelle; Anquetin, Sandrine

2013-04-01

The estimation of catchment-scale soil properties, such as water storage capacity and hydraulic conductivity, is of primary interest for the implementation of distributed hydrological models at the regional scale. This estimation is generally done on the basis of information provided by soil databases. However, such databases are often established for agronomic uses and generally do not document deep weathered rock horizons (i.e. pedologic horizons of type C and deeper), which can play a major role in water transfer and storages. Here we define the Drainable Storage Capacity Index (DSCI), an indicator that relies on the comparison of cumulated streamflow and precipitation to assess catchment-scale storage capacities. The DSCI is found to be reliable to detect underestimation of soil storage capacities in soil databases. We also use the streamflow recession analysis methodology defined by Brutsaert and Nieber (Water Resources Research 13(3), 1977) to estimate water storage capacities and lateral saturated hydraulic conductivities of the non-documented deep horizons. The analysis is applied to a sample of twenty-three catchments (0.2 km² - 291 km²) located in the Cévennes-Vivarais region (south of France). In a regionalisation purpose, the obtained results are compared to the dominant catchments geology. This highlights a clear hierarchy between the different geologies present in the area. Hard crystalline rocks are found to be associated to the thickest and less conductive deep soil horizons. Schist rocks present intermediate values of thickness and of saturated hydraulic conductivity, whereas sedimentary rocks and alluvium are found to be the less thick and the most conductive. Consequently, deep soil layers with thicknesses and hydraulic conductivities differing with the geology were added to a distributed hydrological model implemented over the Cévennes-Vivarais region. Preliminary simulations show a major improvement in terms of simulated discharge when compared to simulations done without deep soil layers. KEY WORDS: hydraulic soil properties, streamflow recession, deep soil horizons, soil databases, Boussinesq equation, storage capacity, regionalisation

Mid-21st century air quality at the urban scale under the influence of changed climate and emissions - case studies for Paris and Stockholm

NASA Astrophysics Data System (ADS)

Markakis, Konstantinos; Valari, Myrto; Engardt, Magnuz; Lacressonniere, Gwendoline; Vautard, Robert; Andersson, Camilla

2016-02-01

Ozone, PM10 and PM2.5 concentrations over Paris, France and Stockholm, Sweden were modelled at 4 and 1 km horizontal resolutions respectively for the present and 2050 periods employing decade-long simulations. We account for large-scale global climate change (RCP-4.5) and fine-resolution bottom-up emission projections developed by local experts and quantify their impact on future pollutant concentrations. Moreover, we identify biases related to the implementation of regional-scale emission projections by comparing modelled pollutant concentrations between the fine- and coarse-scale simulations over the study areas. We show that over urban areas with major regional contribution (e.g. the city of Stockholm) the bias related to coarse-scale projections may be significant and lead to policy misclassification. Our results stress the need to better understand the mechanism of bias propagation across the modelling scales in order to design more successful local-scale strategies. We find that the impact of climate change is spatially homogeneous in both regions, implying strong regional influence. The climate benefit for ozone (daily mean and maximum) is up to -5 % for Paris and -2 % for Stockholm city. The climate benefit on PM2.5 and PM10 in Paris is between -5 and -10 %, while for Stockholm we estimate mixed trends of up to 3 % depending on season and size class. In Stockholm, emission mitigation leads to concentration reductions up to 15 % for daily mean and maximum ozone and 20 % for PM. Through a sensitivity analysis we show that this response is entirely due to changes in emissions at the regional scale. On the contrary, over the city of Paris (VOC-limited photochemical regime), local mitigation of NOx emissions increases future ozone concentrations due to ozone titration inhibition. This competing trend between the respective roles of emission and climate change, results in an increase in 2050 daily mean ozone by 2.5 % in Paris. Climate and not emission change appears to be the most influential factor for maximum ozone concentration over the city of Paris, which may be particularly interesting from a health impact perspective.

Air-quality in the mid-21st century for the city of Paris under two climate scenarios; from regional to local scale

NASA Astrophysics Data System (ADS)

Markakis, K.; Valari, M.; Colette, A.; Sanchez, O.; Perrussel, O.; Honore, C.; Vautard, R.; Klimont, Z.; Rao, S.

2014-01-01

Ozone and PM2.5 concentrations over the city of Paris are modeled with the CHIMERE air-quality model at 4 km × 4 km horizontal resolution for two future emission scenarios. High-resolution (1 km × 1 km) emission projection until 2020 for the greater Paris region is developed by local experts (AIRPARIF) and is further extended to year 2050 based on regional scale emission projections developed by the Global Energy Assessment. Model evaluation is performed based on a 10 yr control simulation. Ozone is in very good agreement with measurements while PM2.5 is underestimated by 20% over the urban area mainly due to a large wet bias in wintertime precipitation. A significant increase of maximum ozone relative to present time levels over Paris is modeled under the "business as usual" scenario (+7 ppb) while a more optimistic mitigation scenario leads to moderate ozone decrease (-3.5 ppb) in year 2050. These results are substantially different to previous regional scale projections where 2050 ozone is found to decrease under both future scenarios. A sensitivity analysis showed that this difference is due to the fact that ozone formation over Paris at the current, urban scale study, is driven by VOC-limited chemistry, whereas at the regional scale ozone formation occurs under NOx-sensitive conditions. This explains why the sharp NOx reductions implemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas projections at both scales yield similar results showing that the longer time-scale processes of emission transport and ozone formation are less sensitive to model resolution. PM2.5 concentrations decrease by 78% and 89% under "business as usual" and "mitigation" scenarios respectively compared to present time period. The reduction is much more prominent over the urban part of the domain due to the effective reductions of road transport and residential emissions resulting in the smoothing of the large urban increment modelled in the control simulation.

The Impact of Amazonian Deforestation on Dry-Season Rainfall

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming; Surratt, Jason; Starr, David OC. (Technical Monitor)

2002-01-01

Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, deep convective cloudiness, as well as rainfall occurrence, all increase over the deforested and non-forested (savanna) regions. This is in response to a local circulation initiated by the differential heating of the region's varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift toward afternoon hours in the deforested and savanna regions, compared to the forested regions. Analysis of 14 years of data from the Special Sensor Microwave/Imager data revealed that only in August did rainfall amounts increase over the deforested region.

A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region

NASA Astrophysics Data System (ADS)

Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe

2018-06-01

Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.

Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions

PubMed Central

da Silva, Aleksandra do Socorro; de Brito, Silvana Rossy; Vijaykumar, Nandamudi Lankalapalli; da Rocha, Cláudio Alex Jorge; Monteiro, Maurílio de Abreu; Costa, João Crisóstomo Weyl Albuquerque; Francês, Carlos Renato Lisboa

2016-01-01

The published literature reveals several arguments concerning the strategic importance of information and communication technology (ICT) interventions for developing countries where the digital divide is a challenge. Large-scale ICT interventions can be an option for countries whose regions, both urban and rural, present a high number of digitally excluded people. Our goal was to monitor and identify problems in interventions aimed at certification for a large number of participants in different geographical regions. Our case study is the training at the Telecentros.BR, a program created in Brazil to install telecenters and certify individuals to use ICT resources. We propose an approach that applies social network analysis and mining techniques to data collected from Telecentros.BR dataset and from the socioeconomics and telecommunications infrastructure indicators of the participants’ municipalities. We found that (i) the analysis of interactions in different time periods reflects the objectives of each phase of training, highlighting the increased density in the phase in which participants develop and disseminate their projects; (ii) analysis according to the roles of participants (i.e., tutors or community members) reveals that the interactions were influenced by the center (or region) to which the participant belongs (that is, a community contained mainly members of the same region and always with the presence of tutors, contradicting expectations of the training project, which aimed for intense collaboration of the participants, regardless of the geographic region); (iii) the social network of participants influences the success of the training: that is, given evidence that the degree of the community member is in the highest range, the probability of this individual concluding the training is 0.689; (iv) the North region presented the lowest probability of participant certification, whereas the Northeast, which served municipalities with similar characteristics, presented high probability of certification, associated with the highest degree in social networking platform. PMID:26727472

Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions.

PubMed

da Silva, Aleksandra do Socorro; de Brito, Silvana Rossy; Vijaykumar, Nandamudi Lankalapalli; da Rocha, Cláudio Alex Jorge; Monteiro, Maurílio de Abreu; Costa, João Crisóstomo Weyl Albuquerque; Francês, Carlos Renato Lisboa

2016-01-01

The published literature reveals several arguments concerning the strategic importance of information and communication technology (ICT) interventions for developing countries where the digital divide is a challenge. Large-scale ICT interventions can be an option for countries whose regions, both urban and rural, present a high number of digitally excluded people. Our goal was to monitor and identify problems in interventions aimed at certification for a large number of participants in different geographical regions. Our case study is the training at the Telecentros.BR, a program created in Brazil to install telecenters and certify individuals to use ICT resources. We propose an approach that applies social network analysis and mining techniques to data collected from Telecentros.BR dataset and from the socioeconomics and telecommunications infrastructure indicators of the participants' municipalities. We found that (i) the analysis of interactions in different time periods reflects the objectives of each phase of training, highlighting the increased density in the phase in which participants develop and disseminate their projects; (ii) analysis according to the roles of participants (i.e., tutors or community members) reveals that the interactions were influenced by the center (or region) to which the participant belongs (that is, a community contained mainly members of the same region and always with the presence of tutors, contradicting expectations of the training project, which aimed for intense collaboration of the participants, regardless of the geographic region); (iii) the social network of participants influences the success of the training: that is, given evidence that the degree of the community member is in the highest range, the probability of this individual concluding the training is 0.689; (iv) the North region presented the lowest probability of participant certification, whereas the Northeast, which served municipalities with similar characteristics, presented high probability of certification, associated with the highest degree in social networking platform.

Multiscale Magnetic Underdense Regions on the Solar Surface: Granular and Mesogranular Scales

NASA Astrophysics Data System (ADS)

Berrilli, F.; Scardigli, S.; Giordano, S.

2013-02-01

The Sun is a non-equilibrium, dissipative system subject to an energy flow that originates in its core. Convective overshooting motions create temperature and velocity structures that show a temporal and spatial multiscale evolution. As a result, photospheric structures are generally considered to be a direct manifestation of convective plasma motions. The plasma flows in the photosphere govern the motion of single magnetic elements. These elements are arranged in typical patterns, which are observed as a variety of multiscale magnetic patterns. High-resolution magnetograms of the quiet solar surface revealed the presence of multiscale magnetic underdense regions in the solar photosphere, commonly called voids, which may be considered to be a signature of the underlying convective structure. The analysis of such patterns paves the way for the investigation of all turbulent convective scales, from granular to global. In order to address the question of magnetic structures driven by turbulent convection at granular and mesogranular scales, we used a voids-detection method. The computed distribution of void length scales shows an exponential behavior at scales between 2 and 10 Mm and the absence of features at mesogranular scales. The absence of preferred scales of organization in the 2 - 10 Mm range supports the multiscale nature of flows on the solar surface and the absence of a mesogranular convective scale.

Scaling up the diversity-resilience relationship with trait databases and remote sensing data: the recovery of productivity after wildfire.

PubMed

Spasojevic, Marko J; Bahlai, Christie A; Bradley, Bethany A; Butterfield, Bradley J; Tuanmu, Mao-Ning; Sistla, Seeta; Wiederholt, Ruscena; Suding, Katharine N

2016-04-01

Understanding the mechanisms underlying ecosystem resilience - why some systems have an irreversible response to disturbances while others recover - is critical for conserving biodiversity and ecosystem function in the face of global change. Despite the widespread acceptance of a positive relationship between biodiversity and resilience, empirical evidence for this relationship remains fairly limited in scope and localized in scale. Assessing resilience at the large landscape and regional scales most relevant to land management and conservation practices has been limited by the ability to measure both diversity and resilience over large spatial scales. Here, we combined tools used in large-scale studies of biodiversity (remote sensing and trait databases) with theoretical advances developed from small-scale experiments to ask whether the functional diversity within a range of woodland and forest ecosystems influences the recovery of productivity after wildfires across the four-corner region of the United States. We additionally asked how environmental variation (topography, macroclimate) across this geographic region influences such resilience, either directly or indirectly via changes in functional diversity. Using path analysis, we found that functional diversity in regeneration traits (fire tolerance, fire resistance, resprout ability) was a stronger predictor of the recovery of productivity after wildfire than the functional diversity of seed mass or species richness. Moreover, slope, elevation, and aspect either directly or indirectly influenced the recovery of productivity, likely via their effect on microclimate, while macroclimate had no direct or indirect effects. Our study provides some of the first direct empirical evidence for functional diversity increasing resilience at large spatial scales. Our approach highlights the power of combining theory based on local-scale studies with tools used in studies at large spatial scales and trait databases to understand pressing environmental issues. © 2015 John Wiley & Sons Ltd.

Earthquake Hazard and Risk Assessment based on Unified Scaling Law for Earthquakes: Altai-Sayan Region

NASA Astrophysics Data System (ADS)

Kossobokov, V. G.; Nekrasova, A.

2017-12-01

We continue applying the general concept of seismic risk analysis in a number of seismic regions worldwide by constructing regional seismic hazard maps based on morphostructural analysis, pattern recognition, and the Unified Scaling Law for Earthquakes, USLE, which generalizes the Gutenberg-Richter relationship making use of naturally fractal distribution of earthquake sources of different size in a seismic region. The USLE stands for an empirical relationship log10N(M, L) = A + B·(5 - M) + C·log10L, where N(M, L) is the expected annual number of earthquakes of a certain magnitude M within an seismically prone area of linear dimension L. We use parameters A, B, and C of USLE to estimate, first, the expected maximum credible magnitude in a time interval at seismically prone nodes of the morphostructural scheme of the region under study, then map the corresponding expected ground shaking parameters (e.g. peak ground acceleration, PGA, or macro-seismic intensity etc.). After a rigorous testing against the available seismic evidences in the past (usually, the observed instrumental PGA or the historically reported macro-seismic intensity), such a seismic hazard map is used to generate maps of specific earthquake risks for population, cities, and infrastructures (e.g., those based on census of population, buildings inventory, etc.). This, USLE based, methodology of seismic hazard and risks assessment is applied to the territory of Altai-Sayan Region, of Russia. The study supported by the Russian Science Foundation Grant No. 15-17-30020.

Precipitation recycling as a mechanism for ecoclimatological stability through local and non-local interactions

NASA Astrophysics Data System (ADS)

Dominguez, Francina

This study is the first to analyze the mechanisms that drive precipitation recycling variability at the daily to intraseasonal timescale. A new Dynamic Precipitation Recycling model is developed which, unlike previous models, includes the moisture storage term in the equation of conservation of atmospheric moisture. As shown using scaling analysis, the moisture storage term is non-negligible at small time scales, so the new model enables us to analyze precipitation recycling variability at shorter timescales than traditional models. The daily to intraseasonal analysis enables us to uncover key relationships between recycling and the moisture and energy fluxes. In the second phase of this work, a spatiotemporal analysis of daily precipitation recycling is performed over two regions of North America: the Midwestern United States, and the North American Monsoon System (NAMS) region. These regions were chosen because they present contrasting land-atmosphere interactions. Different physical mechanisms drive precipitation recycling in each region. In the Midwestern United States, evapotranspiration is not significantly affected by soil moisture anomalies, and there is a high recycling ratio during periods of reduced total precipitation. The reason is that, during periods of drier atmospheric conditions, transpiration will continue to provide moisture to the overlying atmosphere and contribute to total rainfall. Consequently, precipitation recycling variability in not driven by changes in evapotranspiration. Precipitable water, sensible heat and moisture fluxes are the main drivers of recycling variability in the Midwest. However, the drier soil moisture conditions over the NAMS region limit evapotranspiration, which will drive recycling variability. In this region, evapotranspiration becomes an important contribution to precipitation after Monsoon onset when total precipitation and evapotranspiration are highest. The precipitation recycling process in the NAMS region relocates moisture from regions of high evapotranspiration like the seasonally dry tropical forests of Mexico to drier regions downwind. During long monsoons, when soil moisture is abundant for a prolonged period of time, precipitation recycling significantly contributes to precipitation during periods of reduced total rainfall. In both the moisture abundant Midwestern region and the drier NAMS region, precipitation recycling plays an important role in maintaining a favorable hydroclimatological environment for vegetation.

Middle atmosphere measurements of small-scale electron density irregularities and ion properties during the MAC/Epsilon campaign

NASA Technical Reports Server (NTRS)

Blood, S. P.; Mitchell, J. D.; Croskey, C. L.

1989-01-01

Rocket payloads designed to measure small scale electron density irregularities and ion properties in the middle atmosphere were flown with each of the three main salvos of the MAC/Epsilon campaign conducted at the Andoya Rocket Range, Norway, during October to November 1987. Fixed bias, hemispheric nose tip probes measured small scale electron density irregularities, indicative of neutral air turbulence, during the rocket's ascent; and subsequently, parachute-borne Gerdien condensers measured the region's polar electrical conductivity, ion mobility and density. One rocket was launched during daylight (October 15, 1052:20 UT), and the other two launches occurred at night (October 21, 2134 UT: November 12, 0021:40 UT) under moderately disturbed conditions which enhanced the detection and measurement of turbulence structures. A preliminary analysis of the real time data displays indicates the presence of small scale electron density irregularities in the altitude range of 60 to 90 km. Ongoing data reduction will determine turbulence parameters and also the region's electrical properties below 90 km.

Similarity spectra analysis of high-performance jet aircraft noise.

PubMed

Neilsen, Tracianne B; Gee, Kent L; Wall, Alan T; James, Michael M

2013-04-01

Noise measured in the vicinity of an F-22A Raptor has been compared to similarity spectra found previously to represent mixing noise from large-scale and fine-scale turbulent structures in laboratory-scale jet plumes. Comparisons have been made for three engine conditions using ground-based sideline microphones, which covered a large angular aperture. Even though the nozzle geometry is complex and the jet is nonideally expanded, the similarity spectra do agree with large portions of the measured spectra. Toward the sideline, the fine-scale similarity spectrum is used, while the large-scale similarity spectrum provides a good fit to the area of maximum radiation. Combinations of the two similarity spectra are shown to match the data in between those regions. Surprisingly, a combination of the two is also shown to match the data at the farthest aft angle. However, at high frequencies the degree of congruity between the similarity and the measured spectra changes with engine condition and angle. At the higher engine conditions, there is a systematically shallower measured high-frequency slope, with the largest discrepancy occurring in the regions of maximum radiation.

Micron-scale coherence in interphase chromatin dynamics

PubMed Central

Zidovska, Alexandra; Weitz, David A.; Mitchison, Timothy J.

2013-01-01

Chromatin structure and dynamics control all aspects of DNA biology yet are poorly understood, especially at large length scales. We developed an approach, displacement correlation spectroscopy based on time-resolved image correlation analysis, to map chromatin dynamics simultaneously across the whole nucleus in cultured human cells. This method revealed that chromatin movement was coherent across large regions (4–5 µm) for several seconds. Regions of coherent motion extended beyond the boundaries of single-chromosome territories, suggesting elastic coupling of motion over length scales much larger than those of genes. These large-scale, coupled motions were ATP dependent and unidirectional for several seconds, perhaps accounting for ATP-dependent directed movement of single genes. Perturbation of major nuclear ATPases such as DNA polymerase, RNA polymerase II, and topoisomerase II eliminated micron-scale coherence, while causing rapid, local movement to increase; i.e., local motions accelerated but became uncoupled from their neighbors. We observe similar trends in chromatin dynamics upon inducing a direct DNA damage; thus we hypothesize that this may be due to DNA damage responses that physically relax chromatin and block long-distance communication of forces. PMID:24019504

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

NASA Astrophysics Data System (ADS)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.

Estimating regional-scale methane flux and budgets using CARVE aircraft measurements over Alaska

NASA Astrophysics Data System (ADS)

Hartery, Sean; Commane, Róisín; Lindaas, Jakob; Sweeney, Colm; Henderson, John; Mountain, Marikate; Steiner, Nicholas; McDonald, Kyle; Dinardo, Steven J.; Miller, Charles E.; Wofsy, Steven C.; Chang, Rachel Y.-W.

2018-01-01

Methane (CH4) is the second most important greenhouse gas but its emissions from northern regions are still poorly constrained. In this study, we analyze a subset of in situ CH4 aircraft observations made over Alaska during the growing seasons of 2012-2014 as part of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Net surface CH4 fluxes are estimated using a Lagrangian particle dispersion model which quantitatively links surface emissions from Alaska and the western Yukon with observations of enhanced CH4 in the mixed layer. We estimate that between May and September, net CH4 emissions from the region of interest were 2.2 ± 0.5 Tg, 1.9 ± 0.4 Tg, and 2.3 ± 0.6 Tg of CH4 for 2012, 2013, and 2014, respectively. If emissions are only attributed to two biogenic eco-regions within our domain, then tundra regions were the predominant source, accounting for over half of the overall budget despite only representing 18 % of the total surface area. Boreal regions, which cover a large part of the study region, accounted for the remainder of the emissions. Simple multiple linear regression analysis revealed that, overall, CH4 fluxes were largely driven by soil temperature and elevation. In regions specifically dominated by wetlands, soil temperature and moisture at 10 cm depth were important explanatory variables while in regions that were not wetlands, soil temperature and moisture at 40 cm depth were more important, suggesting deeper methanogenesis in drier soils. Although similar environmental drivers have been found in the past to control CH4 emissions at local scales, this study shows that they can be used to generate a statistical model to estimate the regional-scale net CH4 budget.

Analysis And Assistant Planning System Ofregional Agricultural Economic Inform

NASA Astrophysics Data System (ADS)

Han, Jie; Zhang, Junfeng

For the common problems existed in regional development and planning, we try to design a decision support system for assisting regional agricultural development and alignment as a decision-making tool for local government and decision maker. The analysis methods of forecast, comparative advantage, liner programming and statistical analysis are adopted. According to comparative advantage theory, the regional advantage can be determined by calculating and comparing yield advantage index (YAI), Scale advantage index (SAI), Complicated advantage index (CAI). Combining with GIS, agricultural data are presented as a form of graph such as area, bar and pie to uncover the principle and trend for decision-making which can't be found in data table. This system provides assistant decisions for agricultural structure adjustment, agro-forestry development and planning, and can be integrated to information technologies such as RS, AI and so on.

Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

PubMed

Medvigy, David; Moorcroft, Paul R

2012-01-19

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

The importance of lake-specific characteristics for water quality across the continental United States.

PubMed

Read, Emily K; Patil, Vijay P; Oliver, Samantha K; Hetherington, Amy L; Brentrup, Jennifer A; Zwart, Jacob A; Winters, Kirsten M; Corman, Jessica R; Nodine, Emily R; Woolway, R Iestyn; Dugan, Hilary A; Jaimes, Aline; Santoso, Arianto B; Hong, Grace S; Winslow, Luke A; Hanson, Paul C; Weathers, Kathleen C

2015-06-01

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

High Frequency Backscatter from the Polar and Auroral E-Region Ionosphere

NASA Astrophysics Data System (ADS)

Forsythe, Victoriya V.

The Earth's ionosphere contains collisional and partially-ionized plasma. The electric field, produced by the interaction between the Earth's magnetosphere and the solar wind, drives the plasma bulk motion, also known as convection, in the F-region of the ionosphere. It can also destabilize the plasma in the E-region, producing irregularities or waves. Intermediate-scale waves with wavelengths of hundreds of meters can cause scintillation and fading of the Global Navigation Satellite System (GNSS) signals, whereas the small-scale waves (lambda < 100 m) can scatter radar signals, making possible detection of these plasma structures and measurements of their characteristics such as their phase velocity and intensity. In this work, production of the decameter-scale (lambda ≈ 10 m) irregularities in the ionospheric E-region (100-120 km in altitude) at high latitudes is investigated both theoretically, using linear fluid theory of plasma instability processes that generate small-scale plasma waves, and experimentally, by analyzing data collected with the newly-deployed high-southern-latitude radars within the Super Dual Auroral Radar Network (SuperDARN). The theoretical part of this work focuses on symmetry properties of the general dispersion relation that describes wave propagation in the collisional plasma in the two-stream and gradient-drift instability regimes. The instability growth rate and phase velocity are examined under the presence of a background parallel electric field, whose influence is demonstrated to break the spatial symmetry of the wave propagation patterns. In the observational part of this thesis, a novel dual radar setup is used to examine E-region irregularities in the magnetic polar cap by probing the E-region along the same line from opposite directions. The phase velocity analysis together with raytracing simulations demonstrated that, in the polar cap, the radar backscatter is primarily controlled by the plasma density conditions. In particular, when the E-region layer is strong and stratified, the radar backscatter properties are controlled by the convection velocity, whereas for a tilted E-layer, the height and aspect angle conditions are more important. Finally, the fundamental dependence of the E-region irregularity phase velocity on the component of the plasma convection is investigated using two new SuperDARN radars at high southern latitudes where plasma convection estimates are accurately deduced from all SuperDARN radars in the southern hemisphere. Statistical analysis is presented showing that the predominance of the E-region echoes of a particular polarity is strongly dictated by the orientation of the convection plasma flow which itself has a significant asymmetry towards westward zonal flow.

Analysis of Land-Use Effects on Landscape Patterns and Biological Diversity in Pacific North Forests: 1972-1991

NASA Technical Reports Server (NTRS)

Wallin, David O.; Cohen, Warren B.; Bradshaw, G. A.; Spies, T. A.; Hansen, A.; Huff, M. H.; Lehmkuhl, J. F.; Raphael, M. G.; Ripple, W. J.

1998-01-01

While there is widespread recognition of the importance of preserving biological diversity there is considerable uncertainty about how to map current patterns of diversity and monitor changes through time. Ground-based approaches are impractical for examining regional patterns of biological diversity, for monitoring change, and they may actually overlook important higher-order phenomena. Thus, there is a critical need for innovative techniques to examine land-use effects on biological diversity at the landscape and regional scales. In this project, we have used satellite-based remote sensing to examine land-use effects on forest ecosystems in the Pacific NorthWest region (PNW) of the U.S.A. Rates and patterns of forest change throughout the region were quantified for the period from 1972 to 1993. This information was then used to map changes in the abundance and distribution of potential habitat for selected vertebrate species. The results of this project will be useful for identifying "keystone" stands that are important in maintaining habitat connectivity at the regional scale and for evaluating the impact of future land-use on vertebrate diversity throughout the region. The approaches developed here will also be useful in other forested regions throughout the world.

Spatial calibration and temporal validation of flow for regional scale hydrologic modeling

USDA-ARS?s Scientific Manuscript database

Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validat...

Regression analysis utilizing subjective evaluation of emotional experience in PET studies on emotions.

PubMed

Aalto, Sargo; Wallius, Esa; Näätänen, Petri; Hiltunen, Jaana; Metsähonkala, Liisa; Sipilä, Hannu; Karlsson, Hasse

2005-09-01

A methodological study on subject-specific regression analysis (SSRA) exploring the correlation between the neural response and the subjective evaluation of emotional experience in eleven healthy females is presented. The target emotions, i.e., amusement and sadness, were induced using validated film clips, regional cerebral blood flow (rCBF) was measured using positron emission tomography (PET), and the subjective intensity of the emotional experience during the PET scanning was measured using a category ratio (CR-10) scale. Reliability analysis of the rating data indicated that the subjects rated the intensity of their emotional experience fairly consistently on the CR-10 scale (Cronbach alphas 0.70-0.97). A two-phase random-effects analysis was performed to ensure the generalizability and inter-study comparability of the SSRA results. Random-effects SSRAs using Statistical non-Parametric Mapping 99 (SnPM99) showed that rCBF correlated with the self-rated intensity of the emotional experience mainly in the brain regions that were identified in the random-effects subtraction analyses using the same imaging data. Our results give preliminary evidence of a linear association between the neural responses related to amusement and sadness and the self-evaluated intensity of the emotional experience in several regions involved in the emotional response. SSRA utilizing subjective evaluation of emotional experience turned out a feasible and promising method of analysis. It allows versatile exploration of the neurobiology of emotions and the neural correlates of actual and individual emotional experience. Thus, SSRA might be able to catch the idiosyncratic aspects of the emotional response better than traditional subtraction analysis.

Geological-structural interpretation using products of remote sensing in the region of Carrancas, Minas Gerais, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dossantos, A. R.; Dosanjos, C. E.; Barbosa, M. P.; Veneziani, P.

1982-01-01

The efficiency of some criteria developed for the utilization of small scale and low resolution remote sensing products to map geological and structural features was demonstrated. Those criteria were adapted from the Logical Method of Photointerpretation which consists of textural qualitative analysis of landforms and drainage net patterns. LANDSAT images of channel 5 and 7, 4 LANDSAT-RBV scenes, and 1 radar mosiac were utilized. The region of study is characterized by supracrustal metassediments (quartzites and micaschist) folded according to a "zig-zag" pattern and gnaissic basement. Lithological-structural definition was considered outstanding when compared to data acquired during field work, bibliographic data and geologic maps acquired in larger scales.

Placing man in regional landscape classification: Use of Forest Survey data to assess human influences for southern U.S. forest ecosystems

Treesearch

Victor A. Rudis; John B. Tansey

1991-01-01

Information from plots surveyed by U.S.D.A., Forest Service, Forest Inventory and Analysis (FIA) units provides a basis for classifying human-dominated ecosystems at the regional scale of resolution.Attributes include forest stand measures, evidence of human influence, and other disturbances.Data from recent FIA surveys suggest that human influences are common to...

Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China

NASA Astrophysics Data System (ADS)

Wang, Wen; Cheng, Hui; Zhang, Li

2012-04-01

All countries around the world and many international bodies, including the United Nations Development Program (UNDP), United Nations Food and Agricultural Organization (FAO), the International Fund for Agricultural Development (IFAD) and the International Labor Organization (ILO), have to eliminate rural poverty. Estimation of regional poverty level is a key issue for making strategies to eradicate poverty. Most of previous studies on regional poverty evaluations are based on statistics collected typically in administrative units. This paper has discussed the deficiencies of traditional studies, and attempted to research regional poverty evaluation issues using 3-year DMSP/OLS night-time light satellite imagery. In this study, we adopted 17 socio-economic indexes to establish an integrated poverty index (IPI) using principal component analysis (PCA), which was proven to provide a good descriptor of poverty levels in 31 regions at a provincial scale in China. We also explored the relationship between DMSP/OLS night-time average light index and the poverty index using regression analysis in SPSS and a good positive linear correlation was modelled, with R2 equal to 0.854. We then looked at provincial poverty problems in China based on this correlation. The research results indicated that the DMSP/OLS night-time light data can assist analysing provincial poverty evaluation issues.

Functional network alterations and their structural substrate in drug-resistant epilepsy

PubMed Central

Caciagli, Lorenzo; Bernhardt, Boris C.; Hong, Seok-Jun; Bernasconi, Andrea; Bernasconi, Neda

2014-01-01

The advent of MRI has revolutionized the evaluation and management of drug-resistant epilepsy by allowing the detection of the lesion associated with the region that gives rise to seizures. Recent evidence indicates marked chronic alterations in the functional organization of lesional tissue and large-scale cortico-subcortical networks. In this review, we focus on recent methodological developments in functional MRI (fMRI) analysis techniques and their application to the two most common drug-resistant focal epilepsies, i.e., temporal lobe epilepsy related to mesial temporal sclerosis and extra-temporal lobe epilepsy related to focal cortical dysplasia. We put particular emphasis on methodological developments in the analysis of task-free or “resting-state” fMRI to probe the integrity of intrinsic networks on a regional, inter-regional, and connectome-wide level. In temporal lobe epilepsy, these techniques have revealed disrupted connectivity of the ipsilateral mesiotemporal lobe, together with contralateral compensatory reorganization and striking reconfigurations of large-scale networks. In cortical dysplasia, initial observations indicate functional alterations in lesional, peri-lesional, and remote neocortical regions. While future research is needed to critically evaluate the reliability, sensitivity, and specificity, fMRI mapping promises to lend distinct biomarkers for diagnosis, presurgical planning, and outcome prediction. PMID:25565942

Spectro-spatial analysis of wave packet propagation in nonlinear acoustic metamaterials

NASA Astrophysics Data System (ADS)

Zhou, W. J.; Li, X. P.; Wang, Y. S.; Chen, W. Q.; Huang, G. L.

2018-01-01

The objective of this work is to analyze wave packet propagation in weakly nonlinear acoustic metamaterials and reveal the interior nonlinear wave mechanism through spectro-spatial analysis. The spectro-spatial analysis is based on full-scale transient analysis of the finite system, by which dispersion curves are generated from the transmitted waves and also verified by the perturbation method (the L-P method). We found that the spectro-spatial analysis can provide detailed information about the solitary wave in short-wavelength region which cannot be captured by the L-P method. It is also found that the optical wave modes in the nonlinear metamaterial are sensitive to the parameters of the nonlinear constitutive relation. Specifically, a significant frequency shift phenomenon is found in the middle-wavelength region of the optical wave branch, which makes this frequency region behave like a band gap for transient waves. This special frequency shift is then used to design a direction-biased waveguide device, and its efficiency is shown by numerical simulations.

TWO-STAGE FRAGMENTATION FOR CLUSTER FORMATION: ANALYTICAL MODEL AND OBSERVATIONAL CONSIDERATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, Nicole D.; Basu, Shantanu, E-mail: nwityk@uwo.ca, E-mail: basu@uwo.ca

2012-12-10

Linear analysis of the formation of protostellar cores in planar magnetic interstellar clouds shows that molecular clouds exhibit a preferred length scale for collapse that depends on the mass-to-flux ratio and neutral-ion collision time within the cloud. We extend this linear analysis to the context of clustered star formation. By combining the results of the linear analysis with a realistic ionization profile for the cloud, we find that a molecular cloud may evolve through two fragmentation events in the evolution toward the formation of stars. Our model suggests that the initial fragmentation into clumps occurs for a transcritical cloud onmore » parsec scales while the second fragmentation can occur for transcritical and supercritical cores on subparsec scales. Comparison of our results with several star-forming regions (Perseus, Taurus, Pipe Nebula) shows support for a two-stage fragmentation model.« less

Statistical properties of edge plasma turbulence in the Large Helical Device

NASA Astrophysics Data System (ADS)

Dewhurst, J. M.; Hnat, B.; Ohno, N.; Dendy, R. O.; Masuzaki, S.; Morisaki, T.; Komori, A.

2008-09-01

Ion saturation current (Isat) measurements made by three tips of a Langmuir probe array in the Large Helical Device are analysed for two plasma discharges. Absolute moment analysis is used to quantify properties on different temporal scales of the measured signals, which are bursty and intermittent. Strong coherent modes in some datasets are found to distort this analysis and are consequently removed from the time series by applying bandstop filters. Absolute moment analysis of the filtered data reveals two regions of power-law scaling, with the temporal scale τ ≈ 40 µs separating the two regimes. A comparison is made with similar results from the Mega-Amp Spherical Tokamak. The probability density function is studied and a monotonic relationship between connection length and skewness is found. Conditional averaging is used to characterize the average temporal shape of the largest intermittent bursts.

Spatial data analysis for exploration of regional scale geothermal resources

NASA Astrophysics Data System (ADS)

Moghaddam, Majid Kiavarz; Noorollahi, Younes; Samadzadegan, Farhad; Sharifi, Mohammad Ali; Itoi, Ryuichi

2013-10-01

Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry analysis as a spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m2. In general, geochemical and geophysical data were better evidence layers than geological data for exploring geothermal resources. The spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.

Evaluation of a High-Resolution Regional Reanalysis for Europe

NASA Astrophysics Data System (ADS)

Ohlwein, C.; Wahl, S.; Keller, J. D.; Bollmeyer, C.

2014-12-01

Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers 6 years (2007-2012) and is currently extended to 16 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.

Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example

NASA Astrophysics Data System (ADS)

Anderson, C. J.; Wildhaber, M. L.; Wikle, C. K.; Moran, E. H.; Franz, K. J.; Dey, R.

2012-12-01

Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario.

Lithofacies control in detrital zircon provenance studies: Insights from the Cretaceous Methow basin, southern Canadian Cordillera

USGS Publications Warehouse

DeGraaff-Surpless, K.; Mahoney, J.B.; Wooden, J.L.; McWilliams, M.O.

2003-01-01

High-frequency sampling for detrital zircon analysis can provide a detailed record of fine-scale basin evolution by revealing the temporal and spatial variability of detrital zircon ages within clastic sedimentary successions. This investigation employed detailed sampling of two sedimentary successions in the Methow/Methow-Tyaughton basin of the southern Canadian Cordillera to characterize the heterogeneity of detrital zircon signatures within single lithofacies and assess the applicability of detrital zircon analysis in distinguishing fine-scale provenance changes not apparent in lithologic analysis of the strata. The Methow/Methow-Tyaughton basin contains two distinct stratigraphic sequences of middle Albian to Santonian clastic sedimentary rocks: submarine-fan deposits of the Harts Pass Formation/Jackass Mountain Group and fluvial deposits of the Winthrop Formation. Although both stratigraphic sequences displayed consistent ranges in detrital zircon ages on a broad scale, detailed sampling within each succession revealed heterogeneity in the detrital zircon age distributions that was systematic and predictable in the turbidite succession but unpredictable in the fluvial succession. These results suggest that a high-density sampling approach permits interpretation of finescale changes within a lithologically uniform turbiditic sedimentary succession, but heterogeneity within fluvial systems may be too large and unpredictable to permit accurate fine-scale characterization of the evolution of source regions. The robust composite detrital zircon age signature developed for these two successions permits comparison of the Methow/Methow-Tyaughton basin age signature with known plutonic source-rock ages from major plutonic belts throughout the Cretaceous North American margin. The Methow/Methow-Tyaughton basin detrital zircon age signature matches best with source regions in the southern Canadian Cordillera, requiring that the basin developed in close proximity to the southern Canadian Cordillera and providing evidence against large-scale dextral translation of the Methow terrane.

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

NASA Astrophysics Data System (ADS)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

Hydroclimatic variability in the Lake Mondsee region and its relationships with large-scale climate anomaly patterns

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Swierczynski, Tina; Brauer, Achim; Kämpf, Lucas; Czymzik, Markus

2017-04-01

Flood triggered detrital layers in varved sediments of Lake Mondsee, located at the northern fringe of the European Alps (47°48'N,13°23'E), provide an important archive of regional hydroclimatic variability during the mid- to late Holocene. To improve the interpretation of the flood layer record in terms of large-scale climate variability, we investigate the relationships between observational hydrological records from the region, like the Mondsee lake level, the runoff of the lake's main inflow Griesler Ache, with observed precipitation and global climate patterns. The lake level shows a strong positive linear trend during the observational period in all seasons. Additionally, lake level presents important interannual to multidecadal variations. These variations are associated with distinct seasonal atmospheric circulation patterns. A pronounced anomalous anticyclonic center over the Iberian Peninsula is associated with high lake levels values during winter. This center moves southwestward during spring, summer and autumn. In the same time, a cyclonic anomaly center is recorded over central and western Europe. This anomalous circulation extends southwestward from winter to autumn. Similar atmospheric circulation patterns are associated with river runoff and precipitation variability from the region. High lake levels are associated with positive local precipitation anomalies in all seasons as well as with negative local temperature anomalies during spring, summer and autumn. A correlation analysis reveals that lake level, runoff and precipitation variability is related to large-scale sea surface temperature anomaly patterns in all seasons suggesting a possible impact of large-scale climatic modes, like the North Atlantic Oscillation and Atlantic Multidecadal Oscillation on hydroclimatic variability in the Lake Mondsee region. The results presented in this study can be used for a more robust interpretation of the long flood layer record from Lake Mondsee sediments in terms of regional and large-scale climate variability during the past.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers

PubMed Central

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell’Aquila, Alessandro

2014-01-01

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests. PMID:24706833

The statistical power to detect cross-scale interactions at macroscales

USGS Publications Warehouse

Wagner, Tyler; Fergus, C. Emi; Stow, Craig A.; Cheruvelil, Kendra S.; Soranno, Patricia A.

2016-01-01

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers.

PubMed

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell'Aquila, Alessandro

2014-04-15

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

The Eagle Nebula: a spectral template for star forming regions

NASA Astrophysics Data System (ADS)

Flagey, Nicolas; Boulanger, Francois; Carey, Sean; Compiegne, Mathieu; Dwek, Eli; Habart, Emilie; Indebetouw, Remy; Montmerle, Thierry; Noriega-Crespo, Alberto

2008-03-01

IRAC and MIPS have revealed spectacular images of massive star forming regions in the Galaxy. These vivid illustrations of the interaction between the stars, through their winds and radiation, and their environment, made of gas and dust, still needs to be explained. The large scale picture of layered shells of gas components, is affected by the small scale interaction of stars with the clumpy medium that surrounds them. To understand spatial variations of physical conditions and dust properties on small scales, spectroscopic imaging observations are required on a nearby object. The iconic Eagle Nebula (M16) is one of the nearest and most observed star forming region of our Galaxy and as such, is a well suited template to obtain this missing data set. We thus propose a complete spectral map of the Eagle Nebula (M16) with the IRS/Long Low module (15-38 microns) and MIPS/SED mode (55-95 microns). Analysis of the dust emission, spectral features and continuum, and of the H2 and fine-structure gas lines within our models will provide us with constraints on the physical conditions (gas ionization state, pressure, radiation field) and dust properties (temperature, size distribution) at each position within the nebula. Only such a spatially and spectrally complete map will allow us to characterize small scale structure and dust evolution within the global context and understand the impact of small scale structure on the evolution of dusty star forming regions. This project takes advantage of the unique ability of IRS at obtaining sensitive spectral maps covering large areas.

Transition-Region Ultraviolet Explosive Events in IRIS Si IV: A Statistical Analysis

NASA Astrophysics Data System (ADS)

Bartz, Allison

2018-01-01

Explosive events (EEs) in the solar transition region are characterized by broad, non-Gaussian line profiles with wings at Doppler velocities exceeding the speed of sound. We present a statistical analysis of 23 IRIS (Interface Region Imaging Spectrograph) sit-and-stare observations, observed between April 2014 and March 2017. Using the IRIS Si IV 1394 Å and 1403 Å spectral windows and the 1400Å Slit Jaw images we have identified 581 EEs. We found that most EEs last less than 20 min. and have a spatial scale on the slit less than 10”, agreeing with measurements in previous work. We observed most EEs in active regions, regardless of date of observation, but selection bias of IRIS observations cannot be ruled out. We also present preliminary findings of optical depth effects from our statistical study.

Automated detection of microaneurysms using scale-adapted blob analysis and semi-supervised learning.

PubMed

Adal, Kedir M; Sidibé, Désiré; Ali, Sharib; Chaum, Edward; Karnowski, Thomas P; Mériaudeau, Fabrice

2014-04-01

Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier which can detect true MAs. The developed system is built using only few manually labeled and a large number of unlabeled retinal color fundus images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. A competition performance measure (CPM) of 0.364 shows the competitiveness of the proposed system against state-of-the art techniques as well as the applicability of the proposed features to analyze fundus images. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Effects of Freestream Turbulence on Turbine Blade Heat Transfer

NASA Technical Reports Server (NTRS)

Boyle, Robert J.; Giel, Paul W.; Ames, Forrest E.

2004-01-01

Experiments have shown that moderate turbulence levels can nearly double turbine blade stagnation region heat transfer. Data have also shown that heat transfer is strongly affected by the scale of turbulence as well as its level. In addition to the stagnation region, turbulence is often seen to increase pressure surface heat transfer. This is especially evident at low to moderate Reynolds numbers. Vane and rotor stagnation region, and vane pressure surface heat transfer augmentation is often seen in a pre-transition environment. Accurate predictions of transition and relaminarization are critical to accurately predicting blade surface heat transfer. An approach is described which incorporates the effects of both turbulence level and scale into a CFD analysis. The model is derived from experimental data for cylindrical and elliptical leadng edges. Results using this model are compared to experimental data for both vane and rotor geometries. The comparisons are made to illustrate that using a model which includes the effects of turbulence length scale improves agreement with data, and to illustrate where improvements in the modeling are needed.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

PubMed

Reeves, Anthony P; Xie, Yiting; Liu, Shuang

2017-04-01

With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

Determination of GMPE functional form for an active region with limited strong motion data: application to the Himalayan region

NASA Astrophysics Data System (ADS)

Bajaj, Ketan; Anbazhagan, P.

2018-01-01

Advancement in the seismic networks results in formulation of different functional forms for developing any new ground motion prediction equation (GMPE) for a region. Till date, various guidelines and tools are available for selecting a suitable GMPE for any seismic study area. However, these methods are efficient in quantifying the GMPE but not for determining a proper functional form and capturing the epistemic uncertainty associated with selection of GMPE. In this study, the compatibility of the recent available functional forms for the active region is tested for distance and magnitude scaling. Analysis is carried out by determining the residuals using the recorded and the predicted spectral acceleration values at different periods. Mixed effect regressions are performed on the calculated residuals for determining the intra- and interevent residuals. Additionally, spatial correlation is used in mixed effect regression by changing its likelihood function. Distance scaling and magnitude scaling are respectively examined by studying the trends of intraevent residuals with distance and the trend of the event term with magnitude. Further, these trends are statistically studied for a respective functional form of a ground motion. Additionally, genetic algorithm and Monte Carlo method are used respectively for calculating the hinge point and standard error for magnitude and distance scaling for a newly determined functional form. The whole procedure is applied and tested for the available strong motion data for the Himalayan region. The functional form used for testing are five Himalayan GMPEs, five GMPEs developed under NGA-West 2 project, two from Pan-European, and one from Japan region. It is observed that bilinear functional form with magnitude and distance hinged at 6.5 M w and 300 km respectively is suitable for the Himalayan region. Finally, a new regression coefficient for peak ground acceleration for a suitable functional form that governs the attenuation characteristic of the Himalayan region is derived.

SEISMIC SOURCE SCALING AND DISCRIMINATION IN DIVERSE TECTONIC ENVIRONMENTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abercrombie, R E; Mayeda, K; Walter, W R

2008-07-08

The objectives of this study are to improve low-magnitude (concentrating on M2.5-5) regional seismic discrimination by performing a thorough investigation of earthquake source scaling using diverse, high-quality datasets from varied tectonic regions. Local-to-regional high-frequency discrimination requires an estimate of how earthquakes scale with size. Walter and Taylor (2002) developed the MDAC (Magnitude and Distance Amplitude Corrections) method to empirically account for these effects through regional calibration. The accuracy of these corrections has a direct impact on our ability to identify clandestine explosions in the broad regional areas characterized by low seismicity. Unfortunately our knowledge at small magnitudes (i.e., m{sub b}more » < {approx} 4.0) is poorly resolved, and source scaling remains a subject of on-going debate in the earthquake seismology community. Recently there have been a number of empirical studies suggesting scaling of micro-earthquakes is non-self-similar, yet there are an equal number of compelling studies that would suggest otherwise. It is not clear whether different studies obtain different results because they analyze different earthquakes, or because they use different methods. Even in regions that are well studied, such as test sites or areas of high seismicity, we still rely on empirical scaling relations derived from studies taken from half-way around the world at inter-plate regions. We investigate earthquake sources and scaling from different tectonic settings, comparing direct and coda wave analysis methods that both make use of empirical Green's function (EGF) earthquakes to remove path effects. Analysis of locally recorded, direct waves from events is intuitively the simplest way of obtaining accurate source parameters, as these waves have been least affected by travel through the earth. But finding well recorded earthquakes with 'perfect' EGF events for direct wave analysis is difficult, limits the number of earthquakes that can be studied. We begin with closely-located, well-correlated earthquakes. We use a multi-taper method to obtain time-domain source-time-functions by frequency division. We only accept an earthquake and EGF pair if they are able to produce a clear, time-domain source pulse. We fit the spectral ratios and perform a grid-search about the preferred parameters to ensure the fits are well constrained. We then model the spectral (amplitude) ratio to determine source parameters from both direct P and S waves. We analyze three clusters of aftershocks from the well-recorded sequence following the M5 Au Sable Forks, NY, earthquake to obtain some of the first accurate source parameters for small earthquakes in eastern North America. Each cluster contains a M{approx}2, and two contain M{approx}3, as well as smaller aftershocks. We find that the corner frequencies and stress drops are high (averaging 100 MPa) confirming previous work suggesting that intraplate continental earthquakes have higher stress drops than events at plate boundaries. We also demonstrate that a scaling breakdown suggested by earlier work is simply an artifact of their more band-limited data. We calculate radiated energy, and find that the ratio of Energy to seismic Moment is also high, around 10{sup -4}. We estimate source parameters for the M5 mainshock using similar methods, but our results are more doubtful because we do not have a EGF event that meets our preferred criteria. The stress drop and energy/moment ratio for the mainshock are slightly higher than for the aftershocks. Our improved, and simplified coda wave analysis method uses spectral ratios (as for the direct waves) but relies on the averaging nature of the coda waves to use EGF events that do not meet the strict criteria of similarity required for the direct wave analysis. We have applied the coda wave spectral ratio method to the 1999 Hector Mine mainshock (M{sub w} 7.0, Mojave Desert) and its larger aftershocks, and also to several sequences in Italy with M{approx}6 mainshocks. The Italian earthquakes have higher stress drops than the Hector Mine sequence, but lower than Au Sable Forks. These results show a departure from self-similarity, consistent with previous studies using similar regional datasets. The larger earthquakes have higher stress drops and energy/moment ratios. We perform a preliminary comparison of the two methods using the M5 Au Sable Forks earthquake. Both methods give very consistent results, and we are applying the comparison to further events.« less

Partition of some key regulating services in terrestrial ecosystems: Meta-analysis and review.

PubMed

Viglizzo, E F; Jobbágy, E G; Ricard, M F; Paruelo, J M

2016-08-15

Our knowledge about the functional foundations of ecosystem service (ES) provision is still limited and more research is needed to elucidate key functional mechanisms. Using a simplified eco-hydrological scheme, in this work we analyzed how land-use decisions modify the partition of some essential regulatory ES by altering basic relationships between biomass stocks and water flows. A comprehensive meta-analysis and review was conducted based on global, regional and local data from peer-reviewed publications. We analyzed five datasets comprising 1348 studies and 3948 records on precipitation (PPT), aboveground biomass (AGB), AGB change, evapotranspiration (ET), water yield (WY), WY change, runoff (R) and infiltration (I). The conceptual framework was focused on ES that are associated with the ecological functions (e.g., intermediate ES) of ET, WY, R and I. ES included soil protection, carbon sequestration, local climate regulation, water-flow regulation and water recharge. To address the problem of data normality, the analysis included both parametric and non-parametric regression analysis. Results demonstrate that PPT is a first-order biophysical factor that controls ES release at the broader scales. At decreasing scales, ES are partitioned as result of PPT interactions with other biophysical and anthropogenic factors. At intermediate scales, land-use change interacts with PPT modifying ES partition as it the case of afforestation in dry regions, where ET and climate regulation may be enhanced at the expense of R and water-flow regulation. At smaller scales, site-specific conditions such as topography interact with PPT and AGB displaying different ES partition formats. The probable implications of future land-use and climate change on some key ES production and partition are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

A Psychometric Analysis of the Italian Version of the eHealth Literacy Scale Using Item Response and Classical Test Theory Methods

PubMed Central

Dima, Alexandra Lelia; Schulz, Peter Johannes

2017-01-01

Background The eHealth Literacy Scale (eHEALS) is a tool to assess consumers’ comfort and skills in using information technologies for health. Although evidence exists of reliability and construct validity of the scale, less agreement exists on structural validity. Objective The aim of this study was to validate the Italian version of the eHealth Literacy Scale (I-eHEALS) in a community sample with a focus on its structural validity, by applying psychometric techniques that account for item difficulty. Methods Two Web-based surveys were conducted among a total of 296 people living in the Italian-speaking region of Switzerland (Ticino). After examining the latent variables underlying the observed variables of the Italian scale via principal component analysis (PCA), fit indices for two alternative models were calculated using confirmatory factor analysis (CFA). The scale structure was examined via parametric and nonparametric item response theory (IRT) analyses accounting for differences between items regarding the proportion of answers indicating high ability. Convergent validity was assessed by correlations with theoretically related constructs. Results CFA showed a suboptimal model fit for both models. IRT analyses confirmed all items measure a single dimension as intended. Reliability and construct validity of the final scale were also confirmed. The contrasting results of factor analysis (FA) and IRT analyses highlight the importance of considering differences in item difficulty when examining health literacy scales. Conclusions The findings support the reliability and validity of the translated scale and its use for assessing Italian-speaking consumers’ eHealth literacy. PMID:28400356

NASA'S SERVIR Gulf of Mexico Project: The Gulf of Mexico Regional Collaborative (GoMRC)

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Irwin, Daniel; Presson, Joan; Estes, Maury; Estes, Sue; Judd, Kathleen

2006-01-01

The Gulf of Mexico Regional Collaborative (GoMRC) is a NASA-funded project that has as its goal to develop an integrated, working, prototype IT infrastructure for Earth science data, knowledge and models for the five Gulf U.S. states and Mexico, and to demonstrate its ability to help decision-makers better understand critical Gulf-scale issues. Within this preview, the mission of this project is to provide cross cutting solution network and rapid prototyping capability for the Gulf of Mexico region, in order to demonstrate substantial, collaborative, multi-agency research and transitional capabilities using unique NASA data sets and models to address regional problems. SERVIR Mesoamerica is seen as an excellent existing framework that can be used to integrate observational and GIs data bases, provide a sensor web interface, visualization and interactive analysis tools, archival functions, data dissemination and product generation within a Rapid Prototyping concept to assist decision-makers in better understanding Gulf-scale environmental issues.

Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado

USGS Publications Warehouse

Rockwell, Barnaby W.

2012-01-01

The efficacy of airborne spectroscopic, or "hyperspectral," remote sensing for geoenvironmental watershed evaluations and deposit-scale mapping of exposed mineral deposits has been demonstrated. However, the acquisition, processing, and analysis of such airborne data at regional and national scales can be time and cost prohibitive. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried by the NASA Earth Observing System Terra satellite was designed for mineral mapping and the acquired data can be efficiently used to generate uniform mineral maps over very large areas. Multispectral remote sensing data acquired by the ASTER sensor were analyzed to identify and map minerals, mineral groups, hydrothermal alteration types, and vegetation groups in the western San Juan Mountains, Colorado, including the Silverton and Lake City calderas. This mapping was performed in support of multidisciplinary studies involving the predictive modeling of surface water geochemistry at watershed and regional scales. Detailed maps of minerals, vegetation groups, and water were produced from an ASTER scene using spectroscopic, expert system-based analysis techniques which have been previously described. New methodologies are presented for the modeling of hydrothermal alteration type based on the Boolean combination of the detailed mineral maps, and for the entirely automated mapping of alteration types, mineral groups, and green vegetation. Results of these methodologies are compared with the more detailed maps and with previously published mineral mapping results derived from analysis of high-resolution spectroscopic data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Such comparisons are also presented for other mineralized and (or) altered areas including the Goldfield and Cuprite mining districts, Nevada and the central Marysvale volcanic field, Wah Wah Mountains, and San Francisco Mountains, Utah. The automated mineral group mapping products described in this study are ideal for application to mineral resource and mineral-environmental assessments at regional and national scales.

Large-scale structures of solar wind and dynamics of parameters in them

NASA Astrophysics Data System (ADS)

Yermolaev, Yuri; Lodkina, Irina; Yermolaev, Michael

2017-04-01

On the basis of OMNI dataset and our catalog of large-scale solar wind (SW) phenomena (see web-site ftp://ftp.iki.rssi.ru/pub/omni/ and paper by Yermolaev et al., 2009) we study temporal profile of interplanetary and magnetospheric parameters in following SW phenomena: interplanetary manifestation of coronal mass ejection (ICME) including magnetic cloud (MC) and Ejecta, Sheath—compression region before ICME and corotating interaction region (CIR)—compression region before high-speed stream (HSS) of solar wind. To take into account a possible influence of other SW types, following sequences of phenomena, which include all typical sequences of non-stationary SW events, are analyzed: (1) SW/ CIR/ SW, (2) SW/ IS/ CIR/ SW, (3) SW/ Ejecta/ SW, (4) SW/ Sheath/Ejecta/ SW, (5) SW/ IS/ Sheath/ Ejecta/ SW, (6) SW/ MC/ SW, (7) SW/Sheath/ MC/ SW, (8) SW/ IS/ Sheath/ MC/ SW (where SW is undisturbed solar wind, and IS is interplanetary shock) (Yermolaev et al., 2015) using the method of double superposed epoch analysis for large numbers of events (Yermolaev et al., 2010). Similarities and distinctions of different SW phenomena depending on neighboring SW types and their geoeffectiveness are discussed. The work was supported by the Russian Science Foundation, projects 16-12-10062. References: Yermolaev, Yu. I., N. S. Nikolaeva, I. G. Lodkina, and M. Yu. Yermolaev (2009), Catalog of Large-Scale Solar Wind Phenomena during 1976-2000, Cosmic Research, , Vol. 47, No. 2, pp. 81-94. Yermolaev, Y. I., N. S. Nikolaeva, I. G. Lodkina, and M. Y. Yermolaev (2010), Specific interplanetary conditions for CIR-induced, Sheath-induced, and ICME-induced geomagnetic storms obtained by double superposed epoch analysis, Ann. Geophys., 28, pp. 2177-2186. Yermolaev, Yu. I., I. G. Lodkina, N. S. Nikolaeva, and M. Yu. Yermolaev (2015), Dynamics of large-scale solar wind streams obtained by the double superposed epoch analysis, J. Geophys. Res. Space Physics, 120, doi:10.1002/2015JA021274.

Understanding the ignition mechanism of high-pressure spray flames

DOE PAGES

Dahms, Rainer N.; Paczko, Günter A.; Skeen, Scott A.; ...

2016-10-25

A conceptual model for turbulent ignition in high-pressure spray flames is presented. The model is motivated by first-principles simulations and optical diagnostics applied to the Sandia n-dodecane experiment. The Lagrangian flamelet equations are combined with full LLNL kinetics (2755 species; 11,173 reactions) to resolve all time and length scales and chemical pathways of the ignition process at engine-relevant pressures and turbulence intensities unattainable using classic DNS. The first-principles value of the flamelet equations is established by a novel chemical explosive mode-diffusion time scale analysis of the fully-coupled chemical and turbulent time scales. Contrary to conventional wisdom, this analysis reveals thatmore » the high Damköhler number limit, a key requirement for the validity of the flamelet derivation from the reactive Navier–Stokes equations, applies during the entire ignition process. Corroborating Rayleigh-scattering and formaldehyde PLIF with simultaneous schlieren imaging of mixing and combustion are presented. Our combined analysis establishes a characteristic temporal evolution of the ignition process. First, a localized first-stage ignition event consistently occurs in highest temperature mixture regions. This initiates, owed to the intense scalar dissipation, a turbulent cool flame wave propagating from this ignition spot through the entire flow field. This wave significantly decreases the ignition delay of lower temperature mixture regions in comparison to their homogeneous reference. This explains the experimentally observed formaldehyde formation across the entire spray head prior to high-temperature ignition which consistently occurs first in a broad range of rich mixture regions. There, the combination of first-stage ignition delay, shortened by the cool flame wave, and the subsequent delay until second-stage ignition becomes minimal. A turbulent flame subsequently propagates rapidly through the entire mixture over time scales consistent with experimental observations. As a result, we demonstrate that the neglect of turbulence-chemistry-interactions fundamentally fails to capture the key features of this ignition process.« less

An Oceanographic and Climatological Atlas of Bristol Bay

DTIC Science & Technology

1987-10-01

36 Forecasting Method ................................ 38 SUPERSTRUCTURE ICING.............................. 41 WIND...slicks and risk general advection of oil by large-scale ice move- analysis to coastal regions were computed. ment, and specific advection of oil by the...tide 1) Fetch wind (speed and direction) from tables or other sources. Forecast time of a surface map analysis of pressure highest range based on loss of

Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

NASA Technical Reports Server (NTRS)

Tang, Wei; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-01-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

NASA Astrophysics Data System (ADS)

Tang, W.; Cohan, D. S.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-11-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

NASA Astrophysics Data System (ADS)

Tang, W.; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-07-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Formability analysis of sheet metals by cruciform testing

NASA Astrophysics Data System (ADS)

Güler, B.; Alkan, K.; Efe, M.

2017-09-01

Cruciform biaxial tests are increasingly becoming popular for testing the formability of sheet metals as they achieve frictionless, in-plane, multi-axial stress states with a single sample geometry. However, premature fracture of the samples during testing prevents large strain deformation necessary for the formability analysis. In this work, we introduce a miniature cruciform sample design (few mm test region) and a test setup to achieve centre fracture and large uniform strains. With its excellent surface finish and optimized geometry, the sample deforms with diagonal strain bands intersecting at the test region. These bands prevent local necking and concentrate the strains at the sample centre. Imaging and strain analysis during testing confirm the uniform strain distributions and the centre fracture are possible for various strain paths ranging from plane-strain to equibiaxial tension. Moreover, the sample deforms without deviating from the predetermined strain ratio at all test conditions, allowing formability analysis under large strains. We demonstrate these features of the cruciform test for three sample materials: Aluminium 6061-T6 alloy, DC-04 steel and Magnesium AZ31 alloy, and investigate their formability at both the millimetre scale and the microstructure scale.

Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder

USGS Publications Warehouse

Menke, S.B.; Holway, D.A.; Fisher, R.N.; Jetz, W.

2009-01-01

Aim: Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location: California, USA. Methods: We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results: We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions: These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching. ?? 2009 The Authors Journal compilation ?? 2009 Blackwell Publishing.

Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis

NASA Astrophysics Data System (ADS)

Wahl, T.; Haigh, I. D.; Nicholls, R. J.; Arns, A.; Dangendorf, S.; Hinkel, J.; Slangen, A. B. A.

2017-07-01

One of the main consequences of mean sea level rise (SLR) on human settlements is an increase in flood risk due to an increase in the intensity and frequency of extreme sea levels (ESL). While substantial research efforts are directed towards quantifying projections and uncertainties of future global and regional SLR, corresponding uncertainties in contemporary ESL have not been assessed and projections are limited. Here we quantify, for the first time at global scale, the uncertainties in present-day ESL estimates, which have by default been ignored in broad-scale sea-level rise impact assessments to date. ESL uncertainties exceed those from global SLR projections and, assuming that we meet the Paris agreement goals, the projected SLR itself by the end of the century in many regions. Both uncertainties in SLR projections and ESL estimates need to be understood and combined to fully assess potential impacts and adaptation needs.

Modelling the elements of country vulnerability to earthquake disasters.

PubMed

Asef, M R

2008-09-01

Earthquakes have probably been the most deadly form of natural disaster in the past century. Diversity of earthquake specifications in terms of magnitude, intensity and frequency at the semicontinental scale has initiated various kinds of disasters at a regional scale. Additionally, diverse characteristics of countries in terms of population size, disaster preparedness, economic strength and building construction development often causes an earthquake of a certain characteristic to have different impacts on the affected region. This research focuses on the appropriate criteria for identifying the severity of major earthquake disasters based on some key observed symptoms. Accordingly, the article presents a methodology for identification and relative quantification of severity of earthquake disasters. This has led to an earthquake disaster vulnerability model at the country scale. Data analysis based on this model suggested a quantitative, comparative and meaningful interpretation of the vulnerability of concerned countries, and successfully explained which countries are more vulnerable to major disasters.

Correlative Tomography

PubMed Central

Burnett, T. L.; McDonald, S. A.; Gholinia, A.; Geurts, R.; Janus, M.; Slater, T.; Haigh, S. J.; Ornek, C.; Almuaili, F.; Engelberg, D. L.; Thompson, G. E.; Withers, P. J.

2014-01-01

Increasingly researchers are looking to bring together perspectives across multiple scales, or to combine insights from different techniques, for the same region of interest. To this end, correlative microscopy has already yielded substantial new insights in two dimensions (2D). Here we develop correlative tomography where the correlative task is somewhat more challenging because the volume of interest is typically hidden beneath the sample surface. We have threaded together x-ray computed tomography, serial section FIB-SEM tomography, electron backscatter diffraction and finally TEM elemental analysis all for the same 3D region. This has allowed observation of the competition between pitting corrosion and intergranular corrosion at multiple scales revealing the structural hierarchy, crystallography and chemistry of veiled corrosion pits in stainless steel. With automated correlative workflows and co-visualization of the multi-scale or multi-modal datasets the technique promises to provide insights across biological, geological and materials science that are impossible using either individual or multiple uncorrelated techniques. PMID:24736640

Analysis of precipitable water vapor from GPS measurements in Chengdu region: Distribution and evolution characteristics in autumn

NASA Astrophysics Data System (ADS)

Wang, Hao; Wei, Ming; Li, Guoping; Zhou, Shenghui; Zeng, Qingfeng

2013-08-01

The rainfall process of Chengdu region in autumn has obvious regional features. Especially, the night-time rain rate of this region in this season is very high in China. Studying the spatial distribution and temporal variation of regional atmospheric precipitable water vapor (PWV) is important for our understanding of water vapor related processes, such as rainfall, evaporation, convective activity, among others in this area. Since GPS detection technology has the unique characteristics, such as all-weather, high accuracy, high spatial and temporal resolution as well as low cost, tracking and monitoring techniques on water vapor has achieved rapid developments in recent years. With GPS-PWV data at 30-min interval gathered from six GPS observational stations in Chengdu region in two autumns (September 2007-December 2007 and September 2008-December 2008), it is revealed that negative correlations exist between seasonally averaged value of GPS-PWV as well as its variation amplitude and local terrain altitude. The variation of PWV in the upper atmosphere of this region results from the water vapor variation from surface to 850 hPa. With the help of Fast Fourier Transform (FFT), it is found that the autumn PWV in Chengdu region has a multi-scale feature, which includes a seasonal cycle, 22.5 days period (quasi-tri-weekly oscillation). The variation of the GPS-PWV is related to periodical change in the transmitting of the water vapor caused by zonal and meridional wind strengths’ change and to the East Asian monsoon system. According to seasonal variation characteristics, we concluded that the middle October is the critical turning point in PWV content. On a shorter time scale, the relationship between autumn PWV and ground meteorological elements was obtained using the composite analysis approach.

Impact of lateral boundary conditions on regional analyses

NASA Astrophysics Data System (ADS)

Chikhar, Kamel; Gauthier, Pierre

2017-04-01

Regional and global climate models are usually validated by comparison to derived observations or reanalyses. Using a model in data assimilation results in a direct comparison to observations to produce its own analyses that may reveal systematic errors. In this study, regional analyses over North America are produced based on the fifth-generation Canadian Regional Climate Model (CRCM5) combined with the variational data assimilation system of the Meteorological Service of Canada (MSC). CRCM5 is driven at its boundaries by global analyses from ERA-interim or produced with the global configuration of the CRCM5. Assimilation cycles for the months of January and July 2011 revealed systematic errors in winter through large values in the mean analysis increments. This bias is attributed to the coupling of the lateral boundary conditions of the regional model with the driving data particularly over the northern boundary where a rapidly changing large scale circulation created significant cross-boundary flows. Increasing the time frequency of the lateral driving and applying a large-scale spectral nudging improved significantly the circulation through the lateral boundaries which translated in a much better agreement with observations.

Comparison of aquifer characteristics derived from local and regional aquifer tests.

USGS Publications Warehouse

Randolph, R.B.; Krause, R.E.; Maslia, M.L.

1985-01-01

A comparison of the aquifer parameter values obtained through the analysis of a local and a regional aquifer test involving the same area in southeast Georgia is made in order to evaluate the validity of extrapolating local aquifer-test results for use in large-scale flow simulations. Time-drawdown and time-recovery data were analyzed by using both graphical and least-squares fitting of the data to the Theis curve. Additionally, directional transmissivity, transmissivity tensor, and angle of anisotropy were computed for both tests. -from Authors Georgia drawdown transmissivity regional aquifer tests

Process, pattern and scale: hydrogeomorphology and plant diversity in forested wetlands across multiple spatial scales

NASA Astrophysics Data System (ADS)

Alexander, L.; Hupp, C. R.; Forman, R. T.

2002-12-01

Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.

Multi-time-scale hydroclimate dynamics of a regional watershed and links to large-scale atmospheric circulation: Application to the Seine river catchment, France

NASA Astrophysics Data System (ADS)

Massei, N.; Dieppois, B.; Hannah, D. M.; Lavers, D. A.; Fossa, M.; Laignel, B.; Debret, M.

2017-03-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating correlation between large and local scales, empirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: (i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and (ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the links between large and local scales were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach, which integrated discrete wavelet multiresolution analysis for reconstructing monthly regional hydrometeorological processes (predictand: precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector). This approach basically consisted in three steps: 1 - decomposing large-scale climate and hydrological signals (SLP field, precipitation or streamflow) using discrete wavelet multiresolution analysis, 2 - generating a statistical downscaling model per time-scale, 3 - summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either precipitation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with alternating flood and extremely low-flow/drought periods (e.g., winter/spring 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. In accordance with previous studies, the wavelet components detected in SLP, precipitation and streamflow on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation.

Implementation of a flow-dependent background error correlation length scale formulation in the NEMOVAR OSTIA system

NASA Astrophysics Data System (ADS)

Fiedler, Emma; Mao, Chongyuan; Good, Simon; Waters, Jennifer; Martin, Matthew

2017-04-01

OSTIA is the Met Office's Operational Sea Surface Temperature (SST) and Ice Analysis system, which produces L4 (globally complete, gridded) analyses on a daily basis. Work is currently being undertaken to replace the original OI (Optimal Interpolation) data assimilation scheme with NEMOVAR, a 3D-Var data assimilation method developed for use with the NEMO ocean model. A dual background error correlation length scale formulation is used for SST in OSTIA, as implemented in NEMOVAR. Short and long length scales are combined according to the ratio of the decomposition of the background error variances into short and long spatial correlations. The pre-defined background error variances vary spatially and seasonally, but not on shorter time-scales. If the derived length scales applied to the daily analysis are too long, SST features may be smoothed out. Therefore a flow-dependent component to determining the effective length scale has also been developed. The total horizontal gradient of the background SST field is used to identify regions where the length scale should be shortened. These methods together have led to an improvement in the resolution of SST features compared to the previous OI analysis system, without the introduction of spurious noise. This presentation will show validation results for feature resolution in OSTIA using the OI scheme, the dual length scale NEMOVAR scheme, and the flow-dependent implementation.

Analysis of Atmospheric Moisture Transport over the Himalaya-Karakoram-Hindukush Region

NASA Astrophysics Data System (ADS)

Minallah, S.; Ivanov, V. Y.

2017-12-01

The high-altitude region of the Himalaya-Karakoram-Hindukush (HKH) ranges is susceptible to natural disasters due to their extreme topographic features and climatic conditions. The region, where large population resides in deep valleys and mountain foothills, is prone to riverine flooding, flash floods, and extreme precipitation events whose frequency is perceived to be increasing, often with attribution to climate change. It is thus imperative to study the causation using modern hydrometeorological products. In this study, we identify regions with documented trends in extreme flooding and precipitation and carry out a statistical analysis of the atmospheric moisture transport at the synoptic scale for these regions using ERA-Interim and NASA MERRA-2 reanalysis products. We focus on the two main sources for the atmospheric moisture in the region: the summer South-East Asian Monsoon and the winter Westerlies, and explore how variations in these systems affect the moisture convergence and divergence over the region. Our findings indicate that the Monsoon precipitation has been intensifying in the western Himalayas over the past decade and a half and that these changes are likely related to moisture advection into the region.

Distinct patterns of brain atrophy in Genetic Frontotemporal Dementia Initiative (GENFI) cohort revealed by visual rating scales.

PubMed

Fumagalli, Giorgio G; Basilico, Paola; Arighi, Andrea; Bocchetta, Martina; Dick, Katrina M; Cash, David M; Harding, Sophie; Mercurio, Matteo; Fenoglio, Chiara; Pietroboni, Anna M; Ghezzi, Laura; van Swieten, John; Borroni, Barbara; de Mendonça, Alexandre; Masellis, Mario; Tartaglia, Maria C; Rowe, James B; Graff, Caroline; Tagliavini, Fabrizio; Frisoni, Giovanni B; Laforce, Robert; Finger, Elizabeth; Sorbi, Sandro; Scarpini, Elio; Rohrer, Jonathan D; Galimberti, Daniela

2018-05-24

In patients with frontotemporal dementia, it has been shown that brain atrophy occurs earliest in the anterior cingulate, insula and frontal lobes. We used visual rating scales to investigate whether identifying atrophy in these areas may be helpful in distinguishing symptomatic patients carrying different causal mutations in the microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame (C9ORF72) genes. We also analysed asymptomatic carriers to see whether it was possible to visually identify brain atrophy before the appearance of symptoms. Magnetic resonance imaging of 343 subjects (63 symptomatic mutation carriers, 132 presymptomatic mutation carriers and 148 control subjects) from the Genetic Frontotemporal Dementia Initiative study were analysed by two trained raters using a protocol of six visual rating scales that identified atrophy in key regions of the brain (orbitofrontal, anterior cingulate, frontoinsula, anterior and medial temporal lobes and posterior cortical areas). Intra- and interrater agreement were greater than 0.73 for all the scales. Voxel-based morphometric analysis demonstrated a strong correlation between the visual rating scale scores and grey matter atrophy in the same region for each of the scales. Typical patterns of atrophy were identified: symmetric anterior and medial temporal lobe involvement for MAPT, asymmetric frontal and parietal loss for GRN, and a more widespread pattern for C9ORF72. Presymptomatic MAPT carriers showed greater atrophy in the medial temporal region than control subjects, but the visual rating scales could not identify presymptomatic atrophy in GRN or C9ORF72 carriers. These simple-to-use and reproducible scales may be useful tools in the clinical setting for the discrimination of different mutations of frontotemporal dementia, and they may even help to identify atrophy prior to onset in those with MAPT mutations.

Climate Change Studies over Bangalore using Multi-source Remote Sensing Data and GIS

NASA Astrophysics Data System (ADS)

B, S.; Gouda, K. C.; Laxmikantha, B. P.; Bhat, N.

2014-12-01

Urbanization is a form of metropolitan growth that is a response to often bewildering sets of economic, social, and political forces and to the physical geography of an area. Some of the causes of the sprawl include - population growth, economy, patterns of infrastructure initiatives like the construction of roads and the provision of infrastructure using public money encouraging development. The direct implication of such urban sprawl is the change in land use and land cover of the region. In this study the long term climate data from multiple sources like NCEP reanalysis, IMD observations and various satellite derived products from MAIRS, IMD, ERSL and TRMM are considered and analyzed using the developed algorithms for the better understanding of the variability in the climate parameters over Bangalore. These products are further mathematically analyzed to arrive at desired results by extracting land surface temperature (LST), Potential evapo-transmission (PET), Rainfall, Humidity etc. Various satellites products are derived from NASA (National Aeronautics Space Agency), Indian meteorological satellites and global satellites are helpful in massive study of urban issues at global and regional scale. Climate change analysis is well studied by using either single source data such as Temperature or Rainfall from IMD (Indian Meteorological Department) or combined data products available as in case of MAIRS (Monsoon Asia Integrated Regional Scale) program to get rainfall at regional scale. Finally all the above said parameters are normalized and analyzed with the help of various open source available software's for pre and post processing our requirements to obtain desired results. A sample of analysis i.e. the Inter annual variability of annual averaged Temperature over Bangalore is presented in figure 1, which clearly shows the rising trend of the temperature (0.06oC/year). Also the Land use and land cover (LULC) analysis over Bangalore, Day light hours from satellite derived products are analyzed and the correlation of climate parameters with LULC are presented.

Representativeness of the ground observational sites and up-scaling of the point soil moisture measurements

NASA Astrophysics Data System (ADS)

Chen, Jinlei; Wen, Jun; Tian, Hui

2016-02-01

Soil moisture plays an increasingly important role in the cycle of energy-water exchange, climate change, and hydrologic processes. It is usually measured at a point site, but regional soil moisture is essential for validating remote sensing products and numerical modeling results. In the study reported in this paper, the minimal number of required sites (NRS) for establishing a research observational network and the representative single sites for regional soil moisture estimation are discussed using the soil moisture data derived from the ;Maqu soil moisture observational network; (101°40‧-102°40‧E, 33°30‧-35°45‧N), which is supported by Chinese Academy of Science. Furthermore, the best up-scaling method suitable for this network has been studied by evaluating four commonly used up-scaling methods. The results showed that (1) Under a given accuracy requirement R ⩾ 0.99, RMSD ⩽ 0.02 m3/m3, NRS at both 5 and 10 cm depth is 10. (2) Representativeness of the sites has been validated by time stability analysis (TSA), time sliding correlation analysis (TSCA) and optimal combination of sites (OCS). NST01 is the most representative site at 5 cm depth for the first two methods; NST07 and NST02 are the most representative sites at 10 cm depth. The optimum combination sites at 5 cm depth are NST01, NST02, and NST07. NST05, NST08, and NST13 are the best group at 10 cm depth. (3) Linear fitting, compared with other three methods, is the best up-scaling method for all types of representative sites obtained above, and linear regression equations between a single site and regional soil moisture are established hereafter. ;Single site; obtained by OCS has the greatest up-scaling effect, and TSCA takes the second place. (4) Linear fitting equations show good practicability in estimating the variation of regional soil moisture from July 3, 2013 to July 3, 2014, when a large number of observed soil moisture data are lost.

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

PubMed

Vasseur, David A; Fox, Jeremy W; Gonzalez, Andrew; Adrian, Rita; Beisner, Beatrix E; Helmus, Matthew R; Johnson, Catherine; Kratina, Pavel; Kremer, Colin; de Mazancourt, Claire; Miller, Elizabeth; Nelson, William A; Paterson, Michael; Rusak, James A; Shurin, Jonathan B; Steiner, Christopher F

2014-08-07

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

Cost-Risk Trade-off of Solar Radiation Management and Mitigation under Probabilistic Information on Climate Sensitivity

NASA Astrophysics Data System (ADS)

Khabbazan, Mohammad Mohammadi; Roshan, Elnaz; Held, Hermann

2017-04-01

In principle solar radiation management (SRM) offers an option to ameliorate anthropogenic temperature rise. However we cannot expect it to simultaneously compensate for anthropogenic changes in further climate variables in a perfect manner. Here, we ask to what extent a proponent of the 2°C-temperature target would apply SRM in conjunction with mitigation in view of global or regional disparities in precipitation changes. We apply cost-risk analysis (CRA), which is a decision analytic framework that makes a trade-off between the expected welfare-loss from climate policy costs and the climate risks from transgressing a climate target. Here, in both global-scale and 'Giorgi'-regional-scale analyses, we evaluate the optimal mixture of SRM and mitigation under probabilistic information about climate sensitivity. To do so, we generalize CRA for the sake of including not only temperature risk, but also globally aggregated and regionally disaggregated precipitation risks. Social welfare is maximized for the following three valuation scenarios: temperature-risk-only, precipitation-risk-only, and equally weighted both-risks. For now, the Giorgi regions are treated by equal weight. We find that for regionally differentiated precipitation targets, the usage of SRM will be comparably more restricted. In the course of time, a cooling of up to 1.3°C can be attributed to SRM for the latter scenario and for a median climate sensitivity of 3°C (for a global target only, this number reduces by 0.5°C). Our results indicate that although SRM would almost completely substitute for mitigation in the globally aggregated analysis, it only saves 70% to 75% of the welfare-loss compared to a purely mitigation-based analysis (from economic costs and climate risks, approximately 4% in terms of BGE) when considering regional precipitation risks in precipitation-risk-only and both-risks scenarios. It remains to be shown how the inclusion of further risks or different regional weights would change that picture.

Spatial Analysis of PAHs in Soils along an Urban-Suburban-Rural Gradient: scale effect, distribution patterns, diffusion and influencing factors

NASA Astrophysics Data System (ADS)

Peng, Chi; Wang, Meie; Chen, Weiping

2016-11-01

Spatial statistical methods including Cokriging interpolation, Morans I analysis, and geographically weighted regression (GWR) were used for studying the spatial characteristics of polycyclic aromatic hydrocarbon (PAH) accumulation in urban, suburban, and rural soils of Beijing. The concentrations of PAHs decreased spatially as the level of urbanization decreased. Generally, PAHs in soil showed two spatial patterns on the regional scale: (1) regional baseline depositions with a radius of 16.5 km related to the level of urbanization and (2) isolated pockets of soil contaminated with PAHs were found up to around 3.5 km from industrial point sources. In the urban areas, soil PAHs showed high spatial heterogeneity on the block scale, which was probably related to vegetation cover, land use, and physical soil disturbance. The distribution of total PAHs in urban blocks was unrelated to the indicators of the intensity of anthropogenic activity, namely population density, light intensity at night, and road density, but was significantly related to the same indicators in the suburban and rural areas. The moving averages of molecular ratios suggested that PAHs in the suburban and rural soils were a mix of local emissions and diffusion from urban areas.

High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California

NASA Astrophysics Data System (ADS)

Welle, Paul D.; Mauter, Meagan S.

2017-09-01

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by 3.7 billion (1.7-7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

Single-Image Super-Resolution Based on Rational Fractal Interpolation.

PubMed

Zhang, Yunfeng; Fan, Qinglan; Bao, Fangxun; Liu, Yifang; Zhang, Caiming

2018-08-01

This paper presents a novel single-image super-resolution (SR) procedure, which upscales a given low-resolution (LR) input image to a high-resolution image while preserving the textural and structural information. First, we construct a new type of bivariate rational fractal interpolation model and investigate its analytical properties. This model has different forms of expression with various values of the scaling factors and shape parameters; thus, it can be employed to better describe image features than current interpolation schemes. Furthermore, this model combines the advantages of rational interpolation and fractal interpolation, and its effectiveness is validated through theoretical analysis. Second, we develop a single-image SR algorithm based on the proposed model. The LR input image is divided into texture and non-texture regions, and then, the image is interpolated according to the characteristics of the local structure. Specifically, in the texture region, the scaling factor calculation is the critical step. We present a method to accurately calculate scaling factors based on local fractal analysis. Extensive experiments and comparisons with the other state-of-the-art methods show that our algorithm achieves competitive performance, with finer details and sharper edges.

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

Identifying the regional-scale groundwater-surface water interaction on the Sanjiang Plain, Northeast China.

PubMed

Wang, Xihua; Zhang, Guangxin; Xu, Y Jun; Sun, Guangzhi

2015-11-01

Assessment on the interaction between groundwater and surface water (GW-SW) can generate information that is critical to regional water resource management, especially for regions that are highly dependent on groundwater resources for irrigation. This study investigated such interaction on China's Sanjiang Plain (10.9 × 10(4) km(2)) and produced results to assist sustainable regional water management for intensive agricultural activities. Methods of hierarchical cluster analysis (HCA), principal component analysis (PCA), and statistical analysis were used in this study. One hundred two water samplings (60 from shallow groundwater, 7 from deep groundwater, and 35 from surface water) were collected and grouped into three clusters and seven sub-clusters during the analyses. The PCA analysis identified four principal components of the interaction, which explained 85.9% variance of total database, attributed to the dissolution and evolution of gypsum, feldspar, and other natural minerals in the region that was affected by anthropic and geological (sedimentary rock mineral) activities. The analyses showed that surface water in the upper region of the Sanjiang Plain gained water from local shallow groundwater, indicating that the surface water in the upper region was relatively more resilient to withdrawal for usage, whereas in the middle region, there was only a weak interaction between shallow groundwater and surface water. In the lower region of the Sanjiang Plain, surface water lost water to shallow groundwater, indicating that the groundwater was vulnerable to pollution by pesticides and fertilizers from terrestrial sources.

WE-E-17A-06: Assessing the Scale of Tumor Heterogeneity by Complete Hierarchical Segmentation On MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gensheimer, M; Trister, A; Ermoian, R

2014-06-15

Purpose: In many cancers, intratumoral heterogeneity exists in vascular and genetic structure. We developed an algorithm which uses clinical imaging to interrogate different scales of heterogeneity. We hypothesize that heterogeneity of perfusion at large distance scales may correlate with propensity for disease recurrence. We applied the algorithm to initial diagnosis MRI of rhabdomyosarcoma patients to predict recurrence. Methods: The Spatial Heterogeneity Analysis by Recursive Partitioning (SHARP) algorithm recursively segments the tumor image. The tumor is repeatedly subdivided, with each dividing line chosen to maximize signal intensity difference between the two subregions. This process continues to the voxel level, producing segmentsmore » at multiple scales. Heterogeneity is measured by comparing signal intensity histograms between each segmented region and the adjacent region. We measured the scales of contrast enhancement heterogeneity of the primary tumor in 18 rhabdomyosarcoma patients. Using Cox proportional hazards regression, we explored the influence of heterogeneity parameters on relapse-free survival (RFS). To compare with existing methods, fractal and Haralick texture features were also calculated. Results: The complete segmentation produced by SHARP allows extraction of diverse features, including the amount of heterogeneity at various distance scales, the area of the tumor with the most heterogeneity at each scale, and for a given point in the tumor, the heterogeneity at different scales. 10/18 rhabdomyosarcoma patients suffered disease recurrence. On contrast-enhanced MRI, larger scale of maximum signal intensity heterogeneity, relative to tumor diameter, predicted for shorter RFS (p=0.05). Fractal dimension, fractal fit, and three Haralick features did not predict RFS (p=0.09-0.90). Conclusion: SHARP produces an automatic segmentation of tumor regions and reports the amount of heterogeneity at various distance scales. In rhabdomyosarcoma, RFS was shorter when the primary tumor exhibited larger scale of heterogeneity on contrast-enhanced MRI. If validated on a larger dataset, this imaging biomarker could be useful to help personalize treatment.« less

Small-Scale Features in Pulsating Aurora

NASA Technical Reports Server (NTRS)

Jones, Sarah; Jaynes, Allison N.; Knudsen, David J.; Trondsen, Trond; Lessard, Marc

2011-01-01

A field study was conducted from March 12-16, 2002 using a narrow-field intensified CCD camera installed at Churchill, Manitoba. The camera was oriented along the local magnetic zenith where small-scale black auroral forms are often visible. This analysis focuses on such forms occurring within a region of pulsating aurora. The observations show black forms with irregular shape and nonuniform drift with respect to the relatively stationary pulsating patches. The pulsating patches occur within a diffuse auroral background as a modulation of the auroral brightness in a localized region. The images analyzed show a decrease in the brightness of the diffuse background in the region of the pulsating patch at the beginning of the offphase of the modulation. Throughout the off phase the brightness of the diffuse aurora gradually increases back to the average intensity. The time constant for this increase is measured as the first step toward determining the physical process.

El Niño-Southern Oscillation-time scale covariation of sea surface salinity and freshwater flux in the western tropical and northern subtropical Pacific

NASA Astrophysics Data System (ADS)

Nagano, Akira; Hasegawa, Takuya; Ueki, Iwao; Ando, Kentaro

2017-07-01

We examined the covariation of sea surface salinity (SSS) and freshwater flux in the western tropical and northern subtropical Pacific on the El Niño-Southern Oscillation time scale, using a canonical correlation analysis of monthly data between 2001 and 2013. The dominant covariation, i.e., the first canonical mode, has large positive and negative amplitudes in regions east of the Philippines and New Guinea, respectively, and reaches peaks in autumn to winter of El Niño years. The positive SSS anomaly east of the Philippines is advected to the Kuroshio Extension region. We found that the second canonical mode is another coupled variation with localized amplitudes of SSS under the atmospheric convergence zones in winter to spring of La Niña years. However, the negative SSS anomaly is annihilated possibly by the evaporation in the subtropical region.

Observational evidence for cloud cover enhancement over western European forests.

PubMed

Teuling, Adriaan J; Taylor, Christopher M; Meirink, Jan Fokke; Melsen, Lieke A; Miralles, Diego G; van Heerwaarden, Chiel C; Vautard, Robert; Stegehuis, Annemiek I; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-11

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas.

Observational evidence for cloud cover enhancement over western European forests

PubMed Central

Teuling, Adriaan J.; Taylor, Christopher M.; Meirink, Jan Fokke; Melsen, Lieke A.; Miralles, Diego G.; van Heerwaarden, Chiel C.; Vautard, Robert; Stegehuis, Annemiek I.; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-01

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas. PMID:28074840

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

NASA Astrophysics Data System (ADS)

Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

2018-04-01

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

Regional-Scale High-Latitude Extreme Geoelectric Fields Pertaining to Geomagnetically Induced Currents

NASA Technical Reports Server (NTRS)

Pulkkinen, Antti; Bernabeu, Emanuel; Eichner, Jan; Viljanen, Ari; Ngwira, Chigomezyo

2015-01-01

Motivated by the needs of the high-voltage power transmission industry, we use data from the high-latitude IMAGE magnetometer array to study characteristics of extreme geoelectric fields at regional scales. We use 10-s resolution data for years 1993-2013, and the fields are characterized using average horizontal geoelectric field amplitudes taken over station groups that span about 500-km distance. We show that geoelectric field structures associated with localized extremes at single stations can be greatly different from structures associated with regionally uniform geoelectric fields, which are well represented by spatial averages over single stations. Visual extrapolation and rigorous extreme value analysis of spatially averaged fields indicate that the expected range for 1-in-100-year extreme events are 3-8 V/km and 3.4-7.1 V/km, respectively. The Quebec reference ground model is used in the calculations.

Analysis of Large-Scale Resurfacing Processes on Mercury: Mapping the Derain (H-10) Quadrangle

NASA Astrophysics Data System (ADS)

Whitten, J. L.; Ostrach, L. R.; Fassett, C. I.

2018-05-01

The Derain (H-10) Quadrangle of Mercury contains a large region of "average" crustal materials, with minimal smooth plains and basin ejecta, allowing the relative contribution of volcanic and impact processes to be assessed through geologic mapping.

Sea level anomaly in the North Atlantic and seas around Europe: Long-term variability and response to North Atlantic teleconnection patterns.

PubMed

Iglesias, Isabel; Lorenzo, M Nieves; Lázaro, Clara; Fernandes, M Joana; Bastos, Luísa

2017-12-31

Sea level anomaly (SLA), provided globally by satellite altimetry, is considered a valuable proxy for detecting long-term changes of the global ocean, as well as short-term and annual variations. In this manuscript, monthly sea level anomaly grids for the period 1993-2013 are used to characterise the North Atlantic Ocean variability at inter-annual timescales and its response to the North Atlantic main patterns of atmospheric circulation variability (North Atlantic Oscillation, Eastern Atlantic, Eastern Atlantic/Western Russia, Scandinavian and Polar/Eurasia) and main driven factors as sea level pressure, sea surface temperature and wind fields. SLA variability and long-term trends are analysed for the North Atlantic Ocean and several sub-regions (North, Baltic and Mediterranean and Black seas, Bay of Biscay extended to the west coast of the Iberian Peninsula, and the northern North Atlantic Ocean), depicting the SLA fluctuations at basin and sub-basin scales, aiming at representing the regions of maximum sea level variability. A significant correlation between SLA and the different phases of the teleconnection patterns due to the generated winds, sea level pressure and sea surface temperature anomalies, with a strong variability on temporal and spatial scales, has been identified. Long-term analysis reveals the existence of non-stationary inter-annual SLA fluctuations in terms of the temporal scale. Spectral density analysis has shown the existence of long-period signals in the SLA inter-annual component, with periods of ~10, 5, 4 and 2years, depending on the analysed sub-region. Also, a non-uniform increase in sea level since 1993 is identified for all sub-regions, with trend values between 2.05mm/year, for the Bay of Biscay region, and 3.98mm/year for the Baltic Sea (no GIA correction considered). The obtained results demonstrated a strong link between the atmospheric patterns and SLA, as well as strong long-period fluctuations of this variable in spatial and temporal scales. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterizing Methane Emission Response to the Past 60 Years of Permafrost Thaw in Thermokarst Lakes

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Walter Anthony, K. M.; Regmi, P.; Engram, M. J.; Wirth, L.; Grosse, G.

2016-12-01

In this NASA ABoVE-funded project, we combine geospatial data products derived from airborne and spaceborne remote sensing (RS) data with targeted field observations and modeling in order to quantify ecosystem responses to Arctic and boreal environmental change. Specifically, we quantify methane (CH4) ebullition (bubbling) emissions associated with 60 years of permafrost thaw in thousands of Alaskan and NW Canadian lakes by direct observation with RS systems. To achieve our goals, we have developed statistically-significant models that are using SAR, optical and infrared RS data in order to detect and quantify CH4 ebullition emissions at intra-, whole- and regional-lake scales. We also established a relationship between observed CH4 ebullition and average annual soil organic carbon (SOC) inputs to a handful of Alaskan lakes via thermokarst-margin expansion during recent decades using field data, radiocarbon dating and modeling. Our paper we will provide an overview of the goals, datasets, and methods used for the various components of this project. We will present on (1) the collection of new and synthesis of existing field data on CH4 ebullition, thaw-bulbs and SOC; (2) the analysis of existing data from aerial surveys, SAR and optical RS of CH4 in lake ice; (3) the orthorectification of historic aerial photos for comparison to high-resolution satellite imagery to produce fine-scale regional maps of lake area change, (4) the modelling of permafrost SOC quantities eroded into lakes; (5) the radiocarbon dating of CH4 and SOC, (6) GIS modeling to produce multi-temporal regional maps of historic lake area change, associated CH4 emissions, and permafrost SOC stocks; and (7) outreach to stakeholders at Alaska village and rural community field sites. To demonstrate the scientific relevance of our work we will also showcase a set of research results that we have been able to achieve so far. These will include (1) first regional-scale RS-based estimates of lake-borne CH4 ebullition emissions; (2) regional scale estimates of lake area change from an analysis of 50 years of remote sensing data; and (3) regression models linking lake area change to CH4 emissions.

Mid-21st century air quality at the urban scale under the influence of changed climate and emissions: case studies for Paris and Stockholm

NASA Astrophysics Data System (ADS)

Markakis, K.; Valari, M.; Engardt, M.; Lacressonnière, G.; Vautard, R.; Andersson, C.

2015-10-01

Ozone, PM10 and PM2.5 concentrations over Paris, France and Stockholm, Sweden were modeled at 4 and 1 \\unit{km} horizontal resolutions respectively for the present and 2050 periods employing decade-long simulations. We account for large-scale global climate change (RCP-4.5) and fine resolution bottom-up emission projections developed by local experts and quantify their impact on future pollutant concentrations. Moreover, we identify biases related to the implementation of regional scale emission projections over the study areas by comparing modeled pollutant concentrations between the fine and coarse scale simulations. We show that over urban areas with major regional contribution (e.g., the city of Stockholm) the bias due to coarse emission inventory may be significant and lead to policy misclassification. Our results stress the need to better understand the mechanism of bias propagation across the modeling scales in order to design more successful local-scale strategies. We find that the impact of climate change is spatially homogeneous in both regions, implying strong regional influence. The climate benefit for ozone (daily average and maximum) is up to -5 % for Paris and -2 % for Stockholm city. The joined climate benefit on PM2.5 and PM10 in Paris is between -10 and -5 % while for Stockholm we observe mixed trends up to 3 % depending on season and size class. In Stockholm, emission mitigation leads to concentration reductions up to 15 % for daily average and maximum ozone and 20 % for PM and through a sensitivity analysis we show that this response is entirely due to changes in emissions at the regional scale. On the contrary, over the city of Paris (VOC-limited photochemical regime), local mitigation of NOx emissions increases future ozone concentrations due to ozone titration inhibition. This competing trend between the respective roles of emission and climate change, results in an increase in 2050 daily average ozone by 2.5 % in Paris. Climate and not emission change appears to be the most influential factor for maximum ozone concentration over the city of Paris, which may be particularly interesting in a health impact perspective.

Air quality in the mid-21st century for the city of Paris under two climate scenarios; from the regional to local scale

NASA Astrophysics Data System (ADS)

Markakis, K.; Valari, M.; Colette, A.; Sanchez, O.; Perrussel, O.; Honore, C.; Vautard, R.; Klimont, Z.; Rao, S.

2014-07-01

Ozone and PM2.5 concentrations over the city of Paris are modeled with the CHIMERE air-quality model at 4 km × 4 km horizontal resolution for two future emission scenarios. A high-resolution (1 km × 1 km) emission projection until 2020 for the greater Paris region is developed by local experts (AIRPARIF) and is further extended to year 2050 based on regional-scale emission projections developed by the Global Energy Assessment. Model evaluation is performed based on a 10-year control simulation. Ozone is in very good agreement with measurements while PM2.5 is underestimated by 20% over the urban area mainly due to a large wet bias in wintertime precipitation. A significant increase of maximum ozone relative to present-day levels over Paris is modeled under the "business-as-usual" scenario (+7 ppb) while a more optimistic "mitigation" scenario leads to a moderate ozone decrease (-3.5 ppb) in year 2050. These results are substantially different to previous regional-scale projections where 2050 ozone is found to decrease under both future scenarios. A sensitivity analysis showed that this difference is due to the fact that ozone formation over Paris at the current urban-scale study is driven by volatile organic compound (VOC)-limited chemistry, whereas at the regional-scale ozone formation occurs under NOx-sensitive conditions. This explains why the sharp NOx reductions implemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas, projections at both scales yield similar results showing that the longer timescale processes of emission transport and ozone formation are less sensitive to model resolution. PM2.5 concentrations decrease by 78% and 89% under business-as-usual and mitigation scenarios, respectively, compared to the present-day period. The reduction is much more prominent over the urban part of the domain due to the effective reductions of road transport and residential emissions resulting in the smoothing of the large urban increment modeled in the control simulation.

Weak climatic control of stand-scale fire history during the late holocene.

PubMed

Gavin, Daniel G; Hu, Feng Sheng; Lertzman, Kenneth; Corbett, Peter

2006-07-01

Forest fire occurrence is affected by multiple controls that operate at local to regional scales. At the spatial scale of forest stands, regional climatic controls may be obscured by local controls (e.g., stochastic ignitions, topography, and fuel loads), but the long-term role of such local controls is poorly understood. We report here stand-scale (<100 ha) fire histories of the past 5000 years based on the analysis of sediment charcoal at two lakes 11 km apart in southeastern British Columbia. The two lakes are today located in similar subalpine forests, and they likely have experienced the same late-Holocene climatic changes because of their close proximity. We evaluated two independent properties of fire history: (1) fire-interval distribution, a measure of the overall incidence of fire, and (2) fire synchroneity, a measure of the co-occurrence of fire (here, assessed at centennial to millennial time scales due to the resolution of sediment records). Fire-interval distributions differed between the sites prior to, but not after, 2500 yr before present. When the entire 5000-yr period is considered, no statistical synchrony between fire-episode dates existed between the two sites at any temporal scale, but for the last 2500 yr marginal levels of synchrony occurred at centennial scales. Each individual fire record exhibited little coherency with regional climate changes. In contrast, variations in the composite record (average of both sites) matched variations in climate evidenced by late-Holocene glacial advances. This was probably due to the increased sample size and spatial extent represented by the composite record (up to 200 ha) plus increased regional climatic variability over the last several millennia, which may have partially overridden local, non-climatic controls. We conclude that (1) over past millennia, neighboring stands with similar modern conditions may have experienced different fire intervals and asynchronous patterns in fire episodes, likely because local controls outweighed the synchronizing effect of climate; (2) the influence of climate on fire occurrence is more strongly expressed when climatic variability is relatively great; and (3) multiple records from a region are essential if climate-fire relations are to be reliably described.

Prospective and participatory integrated assessment of agricultural systems from farm to regional scales: Comparison of three modeling approaches.

PubMed

Delmotte, Sylvestre; Lopez-Ridaura, Santiago; Barbier, Jean-Marc; Wery, Jacques

2013-11-15

Evaluating the impacts of the development of alternative agricultural systems, such as organic or low-input cropping systems, in the context of an agricultural region requires the use of specific tools and methodologies. They should allow a prospective (using scenarios), multi-scale (taking into account the field, farm and regional level), integrated (notably multicriteria) and participatory assessment, abbreviated PIAAS (for Participatory Integrated Assessment of Agricultural System). In this paper, we compare the possible contribution to PIAAS of three modeling approaches i.e. Bio-Economic Modeling (BEM), Agent-Based Modeling (ABM) and statistical Land-Use/Land Cover Change (LUCC) models. After a presentation of each approach, we analyze their advantages and drawbacks, and identify their possible complementarities for PIAAS. Statistical LUCC modeling is a suitable approach for multi-scale analysis of past changes and can be used to start discussion about the futures with stakeholders. BEM and ABM approaches have complementary features for scenarios assessment at different scales. While ABM has been widely used for participatory assessment, BEM has been rarely used satisfactorily in a participatory manner. On the basis of these results, we propose to combine these three approaches in a framework targeted to PIAAS. Copyright © 2013 Elsevier Ltd. All rights reserved.

Defense Meteorological Satellite Program Data in Dynamic Auroral Boundary Coordinates: New insights into Polar Cap and Auroral Dynamics

NASA Astrophysics Data System (ADS)

Knipp, D.

2016-12-01

Using reprocessed (Level-2) data from the Defense Meteorology Satellite Program magnetometer (SSM) and particle precipitation (SSJ) instruments we determine the boundaries of the central plasma sheet auroral oval, and then consider the relative locations and intensities of field aligned currents. Large-scale field-aligned currents (FAC) are determined using the Minimum Variance Analysis technique, and their influence is then removed from the magnetic perturbations allowing us to estimate intensity and scale-size of the smaller-scale currents. When sorted by dynamic auroral boundary coordinates we find that large- scale Region 1 (R1) FAC are often within the polar cap and Region 2 (R2) FAC show a strong dawn-dusk asymmetry (as in Ohtani et al., 2010). We find that mesoscale FAC are stronger in the summer and are most consistently present in the vicinity of dawnside (downward) R1 FAC. Further, mesoscale FAC are confined to auroral latitudes and above on the dawnside, but can be subaroural on the dusk side. Hotspots of mesoscale FAC occur in pre-midnight regions especially during summer. Finally, we show how this information can be combined with measurements from above and below the ionosphere-thermosphere to help explain significant perturbations in polar cap dynamics.

Estimation of regional-scale groundwater flow properties in the Bengal Basin of India and Bangladesh

USGS Publications Warehouse

Michael, H.A.; Voss, C.I.

2009-01-01

Quantitative evaluation of management strategies for long-term supply of safe groundwater for drinking from the Bengal Basin aquifer (India and Bangladesh) requires estimation of the large-scale hydrogeologic properties that control flow. The Basin consists of a stratified, heterogeneous sequence of sediments with aquitards that may separate aquifers locally, but evidence does not support existence of regional confining units. Considered at a large scale, the Basin may be aptly described as a single aquifer with higher horizontal than vertical hydraulic conductivity. Though data are sparse, estimation of regional-scale aquifer properties is possible from three existing data types: hydraulic heads, 14C concentrations, and driller logs. Estimation is carried out with inverse groundwater modeling using measured heads, by model calibration using estimated water ages based on 14C, and by statistical analysis of driller logs. Similar estimates of hydraulic conductivities result from all three data types; a resulting typical value of vertical anisotropy (ratio of horizontal to vertical conductivity) is 104. The vertical anisotropy estimate is supported by simulation of flow through geostatistical fields consistent with driller log data. The high estimated value of vertical anisotropy in hydraulic conductivity indicates that even disconnected aquitards, if numerous, can strongly control the equivalent hydraulic parameters of an aquifer system. ?? US Government 2009.

Transport pathway and source area for Artemisia pollen in Beijing, China

NASA Astrophysics Data System (ADS)

Qin, Xiaoxin; Li, Yiyin; Sun, Xu; Meng, Ling; Wang, Xiaoke

2017-12-01

Artemisia pollen is an important allergen responsible for allergic rhinitis in Beijing, China. To explore the transport pathways and source areas of Artemisia pollen, we used Burkard 7-day traps to monitor daily pollen concentrations in 2016 in an urban and suburban locality. Backward trajectories of 24- and 96-h and their cluster analysis were performed to identify transport pathways of Artemisia pollen using the HYSPLIT model on 0.5° × 0.5° GADS meteorological data. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were calculated to further identify the major potential source areas at local, regional, and long-range scales. Our results showed significant differences in Artemisia pollen concentration between urban and suburban areas, attributed to differences in plant distribution and altitude of the sampling locality. Such differences arisen from both pollen emission and air mass movements, hence pollen dispersal. At local or regional scales, source area of northwestern parts of Beijing City, Hebei Province and northern and northwestern parts of Inner Mongolia influenced the major transport pathways of Artemisia pollen. Transport pathway at a long-range scale and its corresponding source area extended to northwestern parts of Mongolia. The regional-scale transport affected by wind and altitude is more profound for Artemisia pollen at the suburban than at the urban station.

Can global hydrological models reproduce large scale river flood regimes?

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Flörke, Martina

2013-04-01

River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk analysis and the assessment of potential regional impacts of climate change on river flooding.

Seasonal prediction of lightning activity in North Western Venezuela: Large-scale versus local drivers

NASA Astrophysics Data System (ADS)

Muñoz, Á. G.; Díaz-Lobatón, J.; Chourio, X.; Stock, M. J.

2016-05-01

The Lake Maracaibo Basin in North Western Venezuela has the highest annual lightning rate of any place in the world (~ 200 fl km- 2 yr- 1), whose electrical discharges occasionally impact human and animal lives (e.g., cattle) and frequently affect economic activities like oil and natural gas exploitation. Lightning activity is so common in this region that it has a proper name: Catatumbo Lightning (plural). Although short-term lightning forecasts are now common in different parts of the world, to the best of the authors' knowledge, seasonal prediction of lightning activity is still non-existent. This research discusses the relative role of both large-scale and local climate drivers as modulators of lightning activity in the region, and presents a formal predictability study at seasonal scale. Analysis of the Catatumbo Lightning Regional Mode, defined in terms of the second Empirical Orthogonal Function of monthly Lightning Imaging Sensor (LIS-TRMM) and Optical Transient Detector (OTD) satellite data for North Western South America, permits the identification of potential predictors at seasonal scale via a Canonical Correlation Analysis. Lightning activity in North Western Venezuela responds to well defined sea-surface temperature patterns (e.g., El Niño-Southern Oscillation, Atlantic Meridional Mode) and changes in the low-level meridional wind field that are associated with the Inter-Tropical Convergence Zone migrations, the Caribbean Low Level Jet and tropical cyclone activity, but it is also linked to local drivers like convection triggered by the topographic configuration and the effect of the Maracaibo Basin Nocturnal Low Level Jet. The analysis indicates that at seasonal scale the relative contribution of the large-scale drivers is more important than the local (basin-wide) ones, due to the synoptic control imposed by the former. Furthermore, meridional CAPE transport at 925 mb is identified as the best potential predictor for lightning activity in the Lake Maracaibo Basin. It is found that the predictive skill is slightly higher for the minimum lightning season (Jan-Feb) than for the maximum one (Sep-Oct), but that in general the skill is high enough to be useful for decision-making processes related to human safety, oil and natural gas exploitation, energy and food security.

Transposon Insertions, Structural Variations, and SNPs Contribute to the Evolution of the Melon Genome.

PubMed

Sanseverino, Walter; Hénaff, Elizabeth; Vives, Cristina; Pinosio, Sara; Burgos-Paz, William; Morgante, Michele; Ramos-Onsins, Sebastián E; Garcia-Mas, Jordi; Casacuberta, Josep Maria

2015-10-01

The availability of extensive databases of crop genome sequences should allow analysis of crop variability at an unprecedented scale, which should have an important impact in plant breeding. However, up to now the analysis of genetic variability at the whole-genome scale has been mainly restricted to single nucleotide polymorphisms (SNPs). This is a strong limitation as structural variation (SV) and transposon insertion polymorphisms are frequent in plant species and have had an important mutational role in crop domestication and breeding. Here, we present the first comprehensive analysis of melon genetic diversity, which includes a detailed analysis of SNPs, SV, and transposon insertion polymorphisms. The variability found among seven melon varieties representing the species diversity and including wild accessions and highly breed lines, is relatively high due in part to the marked divergence of some lineages. The diversity is distributed nonuniformly across the genome, being lower at the extremes of the chromosomes and higher in the pericentromeric regions, which is compatible with the effect of purifying selection and recombination forces over functional regions. Additionally, this variability is greatly reduced among elite varieties, probably due to selection during breeding. We have found some chromosomal regions showing a high differentiation of the elite varieties versus the rest, which could be considered as strongly selected candidate regions. Our data also suggest that transposons and SV may be at the origin of an important fraction of the variability in melon, which highlights the importance of analyzing all types of genetic variability to understand crop genome evolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Development of incremental dynamical downscaling and analysis system for regional scale climate change projections

NASA Astrophysics Data System (ADS)

Wakazuki, Yasutaka; Hara, Masayuki; Fujita, Mikiko; Ma, Xieyao; Kimura, Fujio

2013-04-01

Regional scale climate change projections play an important role in assessments of influences of global warming and include statistical (SD) and dynamical downscaling (DD) approaches. One of DD methods is developed basing on the pseudo-global-warming (PGW) method developed by Kimura and Kitoh (2007) in this study. In general, DD uses regional climate model (RCM) with lateral boundary data. In PGW method, the climatological mean difference estimated by GCMs are added to the objective analysis data (ANAL), and the data are used as the lateral boundary data in the future climate simulations. The ANAL is also used as the lateral boundary conditions of the present climate simulation. One of merits of the PGW method is that influences of biases of GCMs in RCM simulations are reduced. However, the PGW method does not treat climate changes in relative humidity, year-to-year variation, and short-term disturbances. The developing new downscaling method is named as the incremental dynamical downscaling and analysis system (InDDAS). The InDDAS treat climate changes in relative humidity and year-to-year variations. On the other hand, uncertainties of climate change projections estimated by many GCMs are large and are not negligible. Thus, stochastic regional scale climate change projections are expected for assessments of influences of global warming. Many RCM runs must be performed to make stochastic information. However, the computational costs are huge because grid size of RCM runs should be small to resolve heavy rainfall phenomena. Therefore, the number of runs to make stochastic information must be reduced. In InDDAS, climatological differences added to ANAL become statistically pre-analyzed information. The climatological differences of many GCMs are divided into mean climatological difference (MD) and departures from MD. The departures are analyzed by principal component analysis, and positive and negative perturbations (positive and negative standard deviations multiplied by departure patterns (eigenvectors)) with multi modes are added to MD. Consequently, the most likely future states are calculated with climatological difference of MD. For example, future states in cases that temperature increase is large and small are calculated with MD plus positive and negative perturbations of the first mode.

Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics.

PubMed

Kelly, Benjamin J; Fitch, James R; Hu, Yangqiu; Corsmeier, Donald J; Zhong, Huachun; Wetzel, Amy N; Nordquist, Russell D; Newsom, David L; White, Peter

2015-01-20

While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.

Self-organizing map network-based precipitation regionalization for the Tibetan Plateau and regional precipitation variability

NASA Astrophysics Data System (ADS)

Wang, Nini; Yin, Jianchuan

2017-12-01

A precipitation-based regionalization for the Tibetan Plateau (TP) was investigated for regional precipitation trend analysis and frequency analysis using data from 1113 grid points covering the period 1900-2014. The results utilizing self-organizing map (SOM) network suggest that four clusters of precipitation coherent zones can be identified, including the southwestern edge, the southern edge, the southeastern region, and the north central region. Regionalization results of the SOM network satisfactorily represent the influences of the atmospheric circulation systems such as the East Asian summer monsoon, the south Asian summer monsoon, and the mid-latitude westerlies. Regionalization results also well display the direct impacts of physical geographical features of the TP such as orography, topography, and land-sea distribution. Regional-scale annual precipitation trend as well as regional differences of annual and seasonal total precipitation were investigated by precipitation index such as precipitation concentration index (PCI) and Standardized Anomaly Index (SAI). Results demonstrate significant negative long-term linear trends in southeastern TP and the north central part of the TP, indicating arid and semi-arid regions in the TP are getting drier. The empirical mode decomposition (EMD) method shows an evolution of the main cycle with 4 and 12 months for all the representative grids of four sub-regions. The cross-wavelet analysis suggests that predominant and effective period of Indian Ocean Dipole (IOD) on monthly precipitation is around ˜12 months, except for the representative grid of the northwestern region.

Influence of regional-scale anthropogenic activity in northeast Asia on seasonal variations of surface ozone and carbon monoxide observed at Oki, Japan

NASA Astrophysics Data System (ADS)

Pochanart, Pakpong; Hirokawa, Jun; Kajii, Yoshizumi; Akimoto, Hajime; Nakao, Makoto

1999-02-01

Surface O3 and CO measurements were carried out at Oki, Japan during March 1994 to February 1996 in order to elucidate the processes determining temporal variations of O3 and CO in the northeast Asian Pacific rim region. The isentropic trajectory analysis was applied to sort out the influences of the air mass exchange under the Asian monsoon system and the regional-scale photochemical buildup of O3. The trajectories were categorized into five groups which cover background and regionally polluted air masses. The seasonal cycles of O3 and CO in the background continental air mass revealed spring maximum-summer minimum with averaged concentrations ranging from 32 and 120 ppb to 45 and 208 ppb, respectively. In contrast, O3 concentrations in the regionally polluted continental air mass ranged from 44 to 57 ppb and showed a winter minimum and a spring-summer-autumn broad maximum, which was characterized by photochemical O3 production due to anthropogenic activities in northeast Asia. CO concentrations in the same air mass showed a spring maximum of 271 ppb and a summer-autumn minimum of 180 ppb. The photochemical buildup of O3 resulting from anthropogenic activities in this region was estimated to be 21 ppb in summer, while its production was insignificant, an average 3 ppb, in winter. A comparison between data in northeast Asia and in Europe shows many similarities, supporting the contention that photochemical buildup of O3 from large-scale precursor emissions in both regions is very significant.

Global View of Aerosol Vertical Distributions from CALIPSO Lidar Measurements and GOCART Simulations: Regional and Seasonal Variations

NASA Technical Reports Server (NTRS)

Yu, Hongbin; Chin, Mian; Winker, David M.; Omar, Ali H.; Liu, Zhaoyan; Kittaka, Chieko; Diehl, Thomas

2010-01-01

This study examines seasonal variations of the vertical distribution of aerosols through a statistical analysis of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar observations from June 2006 to November 2007. A data-screening scheme is developed to attain good quality data in cloud-free conditions, and the polarization measurement is used to separate dust from non-dust aerosol. The CALIPSO aerosol observations are compared with aerosol simulations from the Goddard Chemistry Aerosol Radiation Transport (GOCART) model and aerosol optical depth (AOD) measurements from the MODerate resolution Imaging Spectroradiometer (MODIS). The CALIPSO observations of geographical patterns and seasonal variations of AOD are generally consistent with GOCART simulations and MODIS retrievals especially near source regions, while the magnitude of AOD shows large discrepancies in most regions. Both the CALIPSO observation and GOCART model show that the aerosol extinction scale heights in major dust and smoke source regions are generally higher than that in industrial pollution source regions. The CALIPSO aerosol lidar ratio also generally agrees with GOCART model within 30% on regional scales. Major differences between satellite observations and GOCART model are identified, including (1) an underestimate of aerosol extinction by GOCART over the Indian sub-continent, (2) much larger aerosol extinction calculated by GOCART than observed by CALIPSO in dust source regions, (3) much weaker in magnitude and more concentrated aerosol in the lower atmosphere in CALIPSO observation than GOCART model over transported areas in midlatitudes, and (4) consistently lower aerosol scale height by CALIPSO observation than GOCART model. Possible factors contributing to these differences are discussed.

Risk-based consequences of extreme natural hazard processes in mountain regions - Multi-hazard analysis in Tyrol (Austria)

NASA Astrophysics Data System (ADS)

Huttenlau, Matthias; Stötter, Johann

2010-05-01

Reinsurance companies are stating a high increase in natural hazard related losses, both insured and economic losses, within the last decades on a global scale. This ongoing trend can be described as a product of the dynamic in the natural and in the anthroposphere. To analyze the potential impact of natural hazard process to a certain insurance portfolio or to the society in general, reinsurance companies or risk management consultants have developed loss models. However, those models are generally not fitting the scale dependent demand on regional scales like it is appropriate (i) for analyses on the scale of a specific province or (ii) for portfolio analyses of regional insurance companies. Moreover, the scientific basis of most of the models is not transparent documented and therefore scientific evaluations concerning the methodology concepts are not possible (black box). This is contrary to the scientific principles of transparency and traceability. Especially in mountain regions like the European Alps with their inherent (i) specific characteristic on small scales, (ii) the relative high process dynamics in general, (iii) the occurrence of gravitative mass movements which are related to high relief energy and thus only exists in mountain regions, (iv) the small proportion of the area of permanent settlement on the overall area, (v) the high value concentration in the valley floors, (vi) the exposition of important infrastructures and lifelines, and others, analyses must consider these circumstances adequately. Therefore, risk-based analyses are methodically estimating the potential consequences of hazard process on the built environment standardized with the risk components (i) hazard, (ii) elements at risk, and (iii) vulnerability. However, most research and progress have been made in the field of hazard analyses, whereas the other both components are not developed accordingly. Since these three general components are influencing factors without any weighting within the risk concept, this has sufficient implications on the results of risk analyses. Thus, an equal and scale appropriated balance of those risk components is a fundamental key factor for effective natural hazard risk analyses. The results of such analyses inform especially decision makers in the insurance industry, the administration, and politicians on potential consequences and are the basis for appropriate risk management strategies. Thereby, results (i) on an annual or probabilistic risk comprehension have to be distinguished from (ii) scenario-based analyses. The first analyses are based on statistics of periodically or episodically occurring events whereas the latter approach is especially applied for extreme, non-linear, stochastic events. Focusing on the needs especially of insurance companies, the first approaches are appropriate for premium pricing and reinsurance strategies with an annual perspective, whereas the latter is focusing on events with extreme loss burdens under worst-case criteria to guarantee accordant reinsurance coverage. Moreover, the demand of adequate loss model approaches and methods is strengthened by the risk-based requirements of the upcoming capital requirement directive Solvency II. The present study estimates the potential elements at risk, their corresponding damage potentials and the Probable Maximum Losses (PMLs) of extreme natural hazards events in Tyrol (Austria) and considers adequatly the scale dependency and balanced application of the introduced risk components. Beside the introduced analysis an additionally portfolio analysis of a regional insurance company was executed. The geocoded insurance contracts of this portfolio analysis were the basis to estimate spatial, socio-economical and functional differentiated mean insurance values for the different risk categories of (i) buildings, (ii) contents or inventory, (iii) vehicles, and (iv) persons in the study area. The estimated mean insurance values were incorporated with additional GIS and statistic data to a comprehensive property-by-property geodatabase of the existing elements and values. This stock of elements and values geodatabase is furthermore the consistent basis for all natural hazard analyses and enables the comparison of the results. The study follows the general accepted moduls (i) hazard analysis, (ii) exposition analysis, and (iii) consequence analysis, whereas the exposition analysis estimates the elements at risk with their corresponding damage potentials and the consequence analysis estimates the PMLs. This multi-hazard analysis focuses on process types with a high to extreme potential of negative consequences on a regional scale. In this context, (i) floodings, (ii) rockslides with the potential of corresponding consequence effects (backwater ponding and outburst flood), (iii) earthquakes, (iv) hail events, and (v) winter storms were considered as hazard processes. Based on general hazard analyses (hazard maps) concrete scenarios and their spatial affectedness were determined. For the different hazard processes, different vulnerability approaches were considered to demonstrate their sensitivity and implication on the results. Thus, no absolute values of losses but probable loss ranges were estimated. It can be shown, that the most serious amount of losses would arise from extreme earthquake events with loss burdens up to more than € 7 bn. solely on buildings and inventory. Possible extreme flood events could lead to losses between € 2 and 2.5 bn., whereas a severe hail swath which affects the central Inn valley could result in losses of ca. € 455 mill. (thereof € 285 mill. on vehicles). The potential most serious rockslide with additional consequence effects would result in losses up to ca. € 185 mill. and extreme winter storms can induce losses between € 100 mill. and 150 mill..

Outer region scaling using the freestream velocity for nonuniform open channel flow over gravel

NASA Astrophysics Data System (ADS)

Stewart, Robert L.; Fox, James F.

2017-06-01

The theoretical basis for outer region scaling using the freestream velocity for nonuniform open channel flows over gravel is derived and tested for the first time. Owing to the gradual expansion of the flow within the nonuniform case presented, it is hypothesized that the flow can be defined as an equilibrium turbulent boundary layer using the asymptotic invariance principle. The hypothesis is supported using similarity analysis to derive a solution, followed by further testing with experimental datasets. For the latter, 38 newly collected experimental velocity profiles across three nonuniform flows over gravel in a hydraulic flume are tested as are 43 velocity profiles previously published in seven peer-reviewed journal papers that focused on fluid mechanics of nonuniform open channel over gravel. The findings support the nonuniform flows as equilibrium defined by the asymptotic invariance principle, which is reflective of the consistency of the turbulent structure's form and function within the expanding flow. However, roughness impacts the flow structure when comparing across the published experimental datasets. As a secondary objective, we show how previously published mixed scales can be used to assist with freestream velocity scaling of the velocity deficit and thus empirically account for the roughness effects that extend into the outer region of the flow. One broader finding of this study is providing the theoretical context to relax the use of the elusive friction velocity when scaling nonuniform flows in gravel bed rivers; and instead to apply the freestream velocity. A second broader finding highlighted by our results is that scaling of nonuniform flow in gravel bed rivers is still not fully resolved theoretically since mixed scaling relies to some degree on empiricism. As researchers resolve the form and function of macroturbulence in the outer region, we hope to see the closing of this research gap.

Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania

USGS Publications Warehouse

Gross, Eliza L.; Low, Dennis J.

2013-01-01

Logistic regression models were created to predict and map the probability of elevated arsenic concentrations in groundwater statewide in Pennsylvania and in three intrastate regions to further improve predictions for those three regions (glacial aquifer system, Gettysburg Basin, Newark Basin). Although the Pennsylvania and regional predictive models retained some different variables, they have common characteristics that can be grouped by (1) geologic and soils variables describing arsenic sources and mobilizers, (2) geochemical variables describing the geochemical environment of the groundwater, and (3) locally specific variables that are unique to each of the three regions studied and not applicable to statewide analysis. Maps of Pennsylvania and the three intrastate regions were produced that illustrate that areas most at risk are those with geology and soils capable of functioning as an arsenic source or mobilizer and geochemical groundwater conditions able to facilitate redox reactions. The models have limitations because they may not characterize areas that have localized controls on arsenic mobility. The probability maps associated with this report are intended for regional-scale use and may not be accurate for use at the field scale or when considering individual wells.

Scale-dependent approaches to modeling spatial epidemiology of chronic wasting disease.

USGS Publications Warehouse

Conner, Mary M.; Gross, John E.; Cross, Paul C.; Ebinger, Michael R.; Gillies, Robert; Samuel, Michael D.; Miller, Michael W.

2007-01-01

For each scale, we presented a focal approach that would be useful for understanding the spatial pattern and epidemiology of CWD, as well as being a useful tool for CWD management. The focal approaches include risk analysis and micromaps for the regional scale, cluster analysis for the landscape scale, and individual based modeling for the fine scale of within population. For each of these methods, we used simulated data and walked through the method step by step to fully illustrate the “how to”, with specifics about what is input and output, as well as what questions the method addresses. We also provided a summary table to, at a glance, describe the scale, questions that can be addressed, and general data required for each method described in this e-book. We hope that this review will be helpful to biologists and managers by increasing the utility of their surveillance data, and ultimately be useful for increasing our understanding of CWD and allowing wildlife biologists and managers to move beyond retroactive fire-fighting to proactive preventative action.

Application of Mortar Coupling in Multiscale Modelling of Coupled Flow, Transport, and Biofilm Growth in Porous Media

NASA Astrophysics Data System (ADS)

Laleian, A.; Valocchi, A. J.; Werth, C. J.

2017-12-01

Multiscale models of reactive transport in porous media are capable of capturing complex pore-scale processes while leveraging the efficiency of continuum-scale models. In particular, porosity changes caused by biofilm development yield complex feedbacks between transport and reaction that are difficult to quantify at the continuum scale. Pore-scale models, needed to accurately resolve these dynamics, are often impractical for applications due to their computational cost. To address this challenge, we are developing a multiscale model of biofilm growth in which non-overlapping regions at pore and continuum spatial scales are coupled with a mortar method providing continuity at interfaces. We explore two decompositions of coupled pore-scale and continuum-scale regions to study biofilm growth in a transverse mixing zone. In the first decomposition, all reaction is confined to a pore-scale region extending the transverse mixing zone length. Only solute transport occurs in the surrounding continuum-scale regions. Relative to a fully pore-scale result, we find the multiscale model with this decomposition has a reduced run time and consistent result in terms of biofilm growth and solute utilization. In the second decomposition, reaction occurs in both an up-gradient pore-scale region and a down-gradient continuum-scale region. To quantify clogging, the continuum-scale model implements empirical relations between porosity and continuum-scale parameters, such as permeability and the transverse dispersion coefficient. Solutes are sufficiently mixed at the end of the pore-scale region, such that the initial reaction rate is accurately computed using averaged concentrations in the continuum-scale region. Relative to a fully pore-scale result, we find accuracy of biomass growth in the multiscale model with this decomposition improves as the interface between pore-scale and continuum-scale regions moves downgradient where transverse mixing is more fully developed. Also, this decomposition poses additional challenges with respect to mortar coupling. We explore these challenges and potential solutions. While recent work has demonstrated growing interest in multiscale models, further development is needed for their application to field-scale subsurface contaminant transport and remediation.

Initial Development and Validation of the Mexican Intercultural Competence Scale

PubMed Central

Torres, Lucas

2013-01-01

The current project sought to develop the Mexican Intercultural Competence Scale (MICS), which assesses group-specific skills and attributes that facilitate effective cultural interactions, among adults of Mexican descent. Study 1 involved an Exploratory Factor Analysis (N = 184) that identified five factors including Ambition/Perseverance, Networking, the Traditional Latino Culture, Family Relationships, and Communication. In Study 2, a Confirmatory Factor Analysis provided evidence for the 5-factor model for adults of Mexican origin living in the Midwest (N = 341) region of the U.S. The general findings are discussed in terms of a competence-based formulation of cultural adaptation and include theoretical and clinical implications. PMID:24058890

Initial Development and Validation of the Mexican Intercultural Competence Scale.

PubMed

Torres, Lucas

2013-01-01

The current project sought to develop the Mexican Intercultural Competence Scale (MICS), which assesses group-specific skills and attributes that facilitate effective cultural interactions, among adults of Mexican descent. Study 1 involved an Exploratory Factor Analysis ( N = 184) that identified five factors including Ambition/Perseverance, Networking, the Traditional Latino Culture, Family Relationships, and Communication. In Study 2, a Confirmatory Factor Analysis provided evidence for the 5-factor model for adults of Mexican origin living in the Midwest ( N = 341) region of the U.S. The general findings are discussed in terms of a competence-based formulation of cultural adaptation and include theoretical and clinical implications.

Analysis of the boundary conditions for a Hele--Shaw bubble

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burgess, D.; Foster, M.R.

1990-07-01

Effective boundary conditions are derived to be used with the classical Hele--Shaw equations in calculating the shape and motion of a Hele--Shaw bubble. The main assumptions of this analysis are that the displaced fluid wets the plates, and that the capillary number Ca and the ratio of gap width to characteristic bubble length {epsilon} are both small. In a small region at the sides of the bubble, it is found that the thin-film thickness scales with {epsilon}{sup 2/5} Ca{sup 4/5}, rather than the Ca{sup 2/3} scaling that is valid over most of the thin film above and below the bubble.

Application of Earth Resources Technology Satellite data to urban development and regional planning: Test site, County of Los Angeles

NASA Technical Reports Server (NTRS)

Raje, S. (Principal Investigator); Economy, R.; Mcknight, J. S.; Garofalo, P.

1973-01-01

The author has identified the following significant results. Signigicant results have been obtained from the analyses of ERTS-1 imagery from five cycles over Test Site SR 124 by classical photointerpretation and by an interactive hybrid multispectral information extraction system (GEMS). Photointerpretation has produced over 25 overlays at 1:1,000,000 scale depicting regional relations and urban structure in terms of several hundred linear and areal features. A possible new fault lineament has been discovered on the northern slope of the Santa Monica mountains. GEMS analysis of the ERTS-1 products has provided new or improved information in the following planning data categories: urban vegetation; land cover segregation; manmade and natural impact monitoring; urban design; land suitability. ERTS-1 data analysis has allowed planners to establish trends that directly impact planning policies. For example, detectable grading and new construction sites quantitatively indicated the extent, direction, and rate of urban expansion which enable planners to forecast demand and growth patterns on a regional scale. This new source of information will not only assist current methods to be more efficient, but permits entirely new planning methodologies to be employed.

Maintaining a Local Data Integration System in Support of Weather Forecast Operations

NASA Technical Reports Server (NTRS)

Watson, Leela R.; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian

2010-01-01

Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) at Johnson Space Center in Houston, TX have used a local data integration system (LDIS) as part of their forecast and warning operations. The original LDIS was developed by NASA's Applied Meteorology Unit (AMU; Bauman et ai, 2004) in 1998 (Manobianco and Case 1998) and has undergone subsequent improvements. Each has benefited from three-dimensional (3-D) analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive understanding of evolving fine-scale weather features

Colorado River Vegetation, and Climate: Five Decades of Spatio-Temporal Dynamics in the Grand Canyon in Response to River Regulation

NASA Astrophysics Data System (ADS)

Ralston, B. E.; Sankey, J. B.

2013-12-01

Recent analysis of remotely sensed imagery of 400 km of the Colorado River confirms a net increase in vegetated area has occurred since the completion of Glen Canyon Dam in 1963. The rates and magnitude of vegetation change appear to be river stage-dependent. Riparian vegetation expansion on geomorphic surfaces at lower elevations relative to the river was greater for decades with lower peak and average discharges. Vegetation change at higher elevation relative to the river indicate that increases and decreases in vegetated area reflect regional precipitation patterns, and respectively coincide with regionally significant wet and dry periods that include the current early 21st century drought. The objective of this work was to examine the temporal persistence, and changes, in the spatial distribution of riparian vegetation relative to geomorphic characteristics of the Colorado River in Grand Canyon, dam and reservoir management, and regional climate over the 5-decade period from the mid-1960s to present. We employed archived riparian vegetation classifications that used aerial imagery from 1965, 1973, 1984, 1992, 2002, and 2009 coupled with flow regime data that is primarily related to operations of Glen Canyon Dam, field-measured rating relations, predictions of rating relations based on 1-D modeling, and detailed, geomorphic field mapping. Documentation of the effects of river regulation on riparian habitats in the SW USA has traditionally been limited to either small segments of river channels (e.g., 0.1-10km), or focused on specific plant species. The smaller geographic scale approach evaluates local hydrology, river channel changes, and serial recruitment events of riparian plants. The species-specific plant response informs larger scale patterns of riparian plant distributions across the landscape, but is less sensitive to differences of climate and hydrology among rivers. Our study is unique in that it employs datasets that allow both large-scale change detection and local-scale analysis to address questions about transferability of local-scale plant response to the larger river system. Furthermore, we assess the independent and interacting effects of river regulation and regional climate on plant response. Our results show promise for improved understanding of the interplay of river regulation and climate effects for riparian vegetation at a local and river-wide scale in this highly modified river system.

Probing turbulence with infrared observations in OMC1

NASA Astrophysics Data System (ADS)

Gustafsson, M.; Field, D.; Lemaire, J. L.; Pijpers, F. P.

2006-01-01

A statistical analysis is presented of the turbulent velocity structure in the Orion Molecular Cloud at scales ranging from 70 AU to 3×104 AU. Results are based on IR Fabry-Perot interferometric observations of shock and photon-excited H2 in the K-band S(1) v=1{-}0 line at 2.121 μm and refer to the dynamical characteristics of warm perturbed gas. Data consist of a spatially resolved image with a measured velocity for each resolution limited region (70 AU× 70 AU) in the image. The effect of removal of apparent large scale velocity gradients is discussed and the conclusion drawn that these apparent gradients represent part of the turbulent cascade and should remain within the data. Using our full data set, observations establish that the Larson size-linewidth relation is obeyed to the smallest scales studied here extending the range of validity of this relationship by nearly 2 orders of magnitude. The velocity probability distribution function (PDF) is constructed showing extended exponential wings, providing evidence of intermittency, further supported by the skewness (third moment) and kurtosis (fourth moment) of the velocity distribution. Variance and kurtosis of the PDF of velocity differences are constructed as a function of lag. The variance shows an approximate power law dependence on lag, with exponent significantly lower than the Kolmogorov value, and with deviations below 2000 AU which are attributed to outflows and possibly disk structures associated with low mass star formation within OMC1. The kurtosis shows strong deviation from a Gaussian velocity field, providing evidence of velocity correlations at small lags. Results agree accurately with semi-empirical simulations in Eggers & Wang (1998). In addition, 170 individual H2 emitting clumps have been analysed with sizes between 500 and 2200 AU. These show considerable diversity with regard to PDFs and variance functions (related to second order structure functions) displaying a variety of shapes of the PDF and different values of the scaling exponent within a restricted spatial region. However, a region associated with an outflow from a deeply embedded O-star shows high values of the scaling exponent of the variance function, representing a strong segregation of high and low exponent clumps. Our analysis constitutes the first characterization of the turbulent velocity field at the scale of star formation and provide a dataset which models of star-forming regions should aim to reproduce.

Towards the 1 mm/y stability of the radial orbit error at regional scales

NASA Astrophysics Data System (ADS)

Couhert, Alexandre; Cerri, Luca; Legeais, Jean-François; Ablain, Michael; Zelensky, Nikita P.; Haines, Bruce J.; Lemoine, Frank G.; Bertiger, William I.; Desai, Shailen D.; Otten, Michiel

2015-01-01

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS, SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West “order-1” pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

Spectral analysis of near-wall turbulence in channel flow at Reτ=4200 with emphasis on the attached-eddy hypothesis

NASA Astrophysics Data System (ADS)

Agostini, Lionel; Leschziner, Michael

2017-01-01

Direct numerical simulation data for channel flow at a friction Reynolds number of 4200, generated by Lozano-Durán and Jiménez [J. Fluid Mech. 759, 432 (2014), 10.1017/jfm.2014.575], are used to examine the properties of near-wall turbulence within subranges of eddy-length scale. Attention is primarily focused on the intermediate layer (mesolayer) covering the logarithmic velocity region within the range of wall-scaled wall-normal distance of 80-1500. The examination is based on a number of statistical properties, including premultiplied and compensated spectra, the premultiplied derivative of the second-order structure function, and three scalar parameters that characterize the anisotropic or isotropic state of the various length-scale subranges. This analysis leads to the delineation of three regions within the map of wall-normal-wise premultiplied spectra, each characterized by distinct turbulence properties. A question of particular interest is whether the Townsend-Perry attached-eddy hypothesis (AEH) can be shown to be valid across the entire mesolayer, in contrast to the usual focus on the outer portion of the logarithmic-velocity layer at high Reynolds numbers, which is populated with very-large-scale motions. This question is addressed by reference to properties in the premultiplied scalewise derivative of the second-order structure function (PMDS2) and joint probability density functions of streamwise-velocity fluctuations and their streamwise and spanwise derivatives. This examination provides evidence, based primarily on the existence of a plateau region in the PMDS2, for the qualified validity of the AEH right down the lower limit of the logarithmic velocity range.

Towards the 1 mm/y Stability of the Radial Orbit Error at Regional Scales

NASA Technical Reports Server (NTRS)

Couhert, Alexandre; Cerri, Luca; Legeais, Jean-Francois; Ablain, Michael; Zelensky, Nikita P.; Haines, Bruce J.; Lemoine, Frank G.; Bertiger, William I.; Desai, Shailen D.; Otten, Michiel

2015-01-01

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS, SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West "order-1" pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

Towards the 1 mm/y Stability of the Radial Orbit Error at Regional Scales

NASA Technical Reports Server (NTRS)

Couhert, Alexandre; Cerri, Luca; Legeais, Jean-Francois; Ablain, Michael; Zelensky, Nikita P.; Haines, Bruce J.; Lemoine, Frank G.; Bertiger, William I.; Desai, Shailen D.; Otten, Michiel

2014-01-01

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS,SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West "order-1" pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Surface-wave amplitude analysis for array data with non-linear waveform fitting: Toward high-resolution attenuation models of the upper mantle

NASA Astrophysics Data System (ADS)

Hamada, K.; Yoshizawa, K.

2013-12-01

Anelastic attenuation of seismic waves provides us with valuable information on temperature and water content in the Earth's mantle. While seismic velocity models have been investigated by many researchers, anelastic attenuation (or Q) models have yet to be investigated in detail mainly due to the intrinsic difficulties and uncertainties in the amplitude analysis of observed seismic waveforms. To increase the horizontal resolution of surface wave attenuation models on a regional scale, we have developed a new method of fully non-linear waveform fitting to measure inter-station phase velocities and amplitude ratios simultaneously, using the Neighborhood Algorithm (NA) as a global optimizer. Model parameter space (perturbations of phase speed and amplitude ratio) is explored to fit two observed waveforms on a common great-circle path by perturbing both phase and amplitude of the fundamental-mode surface waves. This method has been applied to observed waveform data of the USArray from 2007 to 2008, and a large-number of inter-station amplitude and phase speed data are corrected in a period range from 20 to 200 seconds. We have constructed preliminary phase speed and attenuation models using the observed phase and amplitude data, with careful considerations of the effects of elastic focusing and station correction factors for amplitude data. The phase velocity models indicate good correlation with the conventional tomographic results in North America on a large-scale; e.g., significant slow velocity anomaly in volcanic regions in the western United States. The preliminary results of surface-wave attenuation achieved a better variance reduction when the amplitude data are inverted for attenuation models in conjunction with corrections for receiver factors. We have also taken into account the amplitude correction for elastic focusing based on a geometrical ray theory, but its effects on the final model is somewhat limited and our attenuation model show anti-correlation with the phase velocity models; i.e., lower attenuation is found in slower velocity areas that cannot readily be explained by the temperature effects alone. Some former global scale studies (e.g., Dalton et al., JGR, 2006) indicated that the ray-theoretical focusing corrections on amplitude data tend to eliminate such anti-correlation of phase speed and attenuation, but this seems not to work sufficiently well for our regional scale model, which is affected by stronger velocity gradient relative to global-scale models. Thus, the estimated elastic focusing effects based on ray theory may be underestimated in our regional-scale studies. More rigorous ways to estimate the focusing corrections as well as data selection criteria for amplitude measurements are required to achieve a high-resolution attenuation models on regional scales in the future.

Integrated management of water resources demand and supply in irrigated agriculture from plot to regional scale

NASA Astrophysics Data System (ADS)

Schütze, Niels; Wagner, Michael

2016-05-01

Growing water scarcity in agriculture is an increasing problem in future in many regions of the world. Recent trends of weather extremes in Saxony, Germany also enhance drought risks for agricultural production. In addition, signals of longer and more intense drought conditions during the vegetation period can be found in future regional climate scenarios for Saxony. However, those climate predictions are associated with high uncertainty and therefore, e.g. stochastic methods are required to analyze the impact of changing climate patterns on future crop water requirements and water availability. For assessing irrigation as a measure to increase agricultural water security a generalized stochastic approach for a spatial distributed estimation of future irrigation water demand is proposed, which ensures safe yields and a high water productivity at the same time. The developed concept of stochastic crop water production functions (SCWPF) can serve as a central decision support tool for both, (i) a cost benefit analysis of farm irrigation modernization on a local scale and (ii) a regional water demand management using a multi-scale approach for modeling and implementation. The new approach is applied using the example of a case study in Saxony, which is dealing with the sustainable management of future irrigation water demands and its implementation.

Studies of small scale irregularities in the cusp ionosphere using sounding rockets: recent results

NASA Astrophysics Data System (ADS)

Spicher, A.; Ilyasov, A. A.; Miloch, W. J.; Chernyshov, A. A.; Moen, J.; Clausen, L. B. N.; Saito, Y.

2017-12-01

Plasma irregularities occurring over many scale sizes are common in the ionosphere. Understanding and characterizing the phenomena responsible for these irregularities is not only important from a theoretical point of view, but also in the context of space weather, as the irregularities can disturb HF communication and Global Navigation Satellite Systems signals. Overall, research about the small-scale turbulence has not progressed as fast for polar regions as for the equatorial ones, and for the high latitude ionosphere there is still no agreement nor detailed explanation regarding the formation of irregularities. To investigate plasma structuring at small scales in the cusp ionosphere, we use high resolution measurements from the Investigation of Cusp Irregularities (ICI) sounding rockets, and investigate a region associated with density enhancements and a region characterized by flow shears. Using the ICI-2 electron density data, we give further evidence of the importance of the gradient drift instability for plasma structuring inside the polar cap. In particular, using higher-order statistics, we provide new insights into the nature of the resulting plasma structures and show that they are characterized by intermittency. Using the ICI-3 data, we show that the entire region associated with a reversed flow event (RFE), with the presence of meter-scale irregularities, several flow shears and particle precipitation, is highly structured. By performing a numerical stability analysis, we show that the inhomogeneous-energy-density-driven instability (IEDDI) may be active in relation to RFEs at the rocket's altitude. In particular, we show that the presence of particle precipitation decreases the growth rates of IEDDI and, using a Local Intermittency Measure, we observe a correlation between IEDDI growth rates and electric field fluctuations over several scales. These findings support the view that large-scale inhomogeneities may provide a background for the development of micro-scale instabilities. Such interplay between macro- and micro-processes might be an important mechanism for the development of small-scale plasma gradients, and as a source for ion heating in the cusp ionosphere.

Regional-specific Stochastic Simulation of Spatially-distributed Ground-motion Time Histories using Wavelet Packet Analysis

NASA Astrophysics Data System (ADS)

Huang, D.; Wang, G.

2014-12-01

Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.

Collaboration and nested environmental governance: Scale dependency, scale framing, and cross-scale interactions in collaborative conservation.

PubMed

Wyborn, Carina; Bixler, R Patrick

2013-07-15

The problem of fit between social institutions and ecological systems is an enduring challenge in natural resource management and conservation. Developments in the science of conservation biology encourage the management of landscapes at increasingly larger scales. In contrast, sociological approaches to conservation emphasize the importance of ownership, collaboration and stewardship at scales relevant to the individual or local community. Despite the proliferation of initiatives seeking to work with local communities to undertake conservation across large landscapes, there is an inherent tension between these scales of operation. Consequently, questions about the changing nature of effective conservation across scales abound. Through an analysis of three nested cases working in a semiautonomous fashion in the Northern Rocky Mountains in North America, this paper makes an empirical contribution to the literature on nested governance, collaboration and communication across scales. Despite different scales of operation, constituencies and scale frames, we demonstrate a surprising similarity in organizational structure and an implicit dependency between these initiatives. This paper examines the different capacities and capabilities of collaborative conservation from the local to regional to supra regional. We draw on the underexplored concept of 'scale-dependent comparative advantage' (Cash and Moser, 2000), to gain insight into what activities take place at which scale and what those activities contribute to nested governance and collaborative conservation. The comparison of these semiautonomous cases provides fruitful territory to draw lessons for understanding the roles and relationships of organizations operating at different scales in more connected networks of nested governance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Atmospheric mercury distribution in Northern Europe and in the Mediterranean region

NASA Astrophysics Data System (ADS)

Wängberg, I.; Munthe, J.; Pirrone, N.; Iverfeldt, Å.; Bahlman, E.; Costa, P.; Ebinghaus, R.; Feng, X.; Ferrara, R.; Gårdfeldt, K.; Kock, H.; Lanzillotta, E.; Mamane, Y.; Mas, F.; Melamed, E.; Osnat, Y.; Prestbo, E.; Sommar, J.; Schmolke, S.; Spain, G.; Sprovieri, F.; Tuncel, G.

Mercury species in air have been measured at five sites in Northwest Europe and at five coastal sites in the Mediterranean region during measurements at four seasons. Observed concentrations of total gaseous mercury (TGM), total particulate mercury (TPM) and reactive gaseous mercury (RGM) were generally slightly higher in the Mediterranean region than in Northwest Europe. Incoming clean Atlantic air seems to be enriched in TGM in comparison to air in Scandinavia. Trajectory analysis of events where high concentrations of TPM simultaneously were observed at sites in North Europe indicate source areas in Central Europe and provide evidence of transport of mercury on particles on a regional scale.

Free Global Dsm Assessment on Large Scale Areas Exploiting the Potentialities of the Innovative Google Earth Engine Platform

NASA Astrophysics Data System (ADS)

Nascetti, A.; Di Rita, M.; Ravanelli, R.; Amicuzi, M.; Esposito, S.; Crespi, M.

2017-05-01

The high-performance cloud-computing platform Google Earth Engine has been developed for global-scale analysis based on the Earth observation data. In particular, in this work, the geometric accuracy of the two most used nearly-global free DSMs (SRTM and ASTER) has been evaluated on the territories of four American States (Colorado, Michigan, Nevada, Utah) and one Italian Region (Trentino Alto- Adige, Northern Italy) exploiting the potentiality of this platform. These are large areas characterized by different terrain morphology, land covers and slopes. The assessment has been performed using two different reference DSMs: the USGS National Elevation Dataset (NED) and a LiDAR acquisition. The DSMs accuracy has been evaluated through computation of standard statistic parameters, both at global scale (considering the whole State/Region) and in function of the terrain morphology using several slope classes. The geometric accuracy in terms of Standard deviation and NMAD, for SRTM range from 2-3 meters in the first slope class to about 45 meters in the last one, whereas for ASTER, the values range from 5-6 to 30 meters. In general, the performed analysis shows a better accuracy for the SRTM in the flat areas whereas the ASTER GDEM is more reliable in the steep areas, where the slopes increase. These preliminary results highlight the GEE potentialities to perform DSM assessment on a global scale.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

Analysis of the variability of extra-tropical cyclones at the regional scale for the coasts of Northern Germany and investigation of their coastal impacts

NASA Astrophysics Data System (ADS)

Schaaf, Benjamin; Feser, Frauke

2015-04-01

The evaluation of long-term changes in wind speeds is very important for the coastal areas and the protection measures. Therefor the wind variability at the regional scale for the coast of Northern Germany shall be analysed. In order to derive changes in storminess it is essential to analyse long, homogeneous meteorological time series. Wind measurements often suffer from inconsistencies which arise from changes in instrumentation, observation method, or station location. Reanalysis data take into account such inhomogeneities of observation data and convert these measurements into a consistent, gridded data set with the same grid spacing and time intervals. This leads to a smooth, homogeneous data set, but with relatively low resolution (about 210 km for the longest reanalysis data set, the NCEP reanalysis starting in 1948). Therefore a high-resolution regional atmospheric model will be used to bring these reanalyses to a higher resolution, using in addition to a dynamical downscaling approach the spectral nudging technique. This method 'nudges' the large spatial scales of the regional climate model towards the reanalysis, while the smaller spatial scales are left unchanged. It was applied successfully in a number of applications, leading to realistic atmospheric weather descriptions of the past. With the regional climate model COSMO-CLM a very high-resolution data set was calculated for the last 67 years, the period from 1948 until now. The model area is North Germany with the coastal area of the North sea and parts of the Baltic sea. This is one of the first model simulations on climate scale with a very high resolution of 2.8 km, so even small scale effects can be detected. With this hindcast-simulation there are numerous options of evaluation. One can create wind climatologies for regional areas such as for the metropolitan region of Hamburg. Otherwise one can investigate individual storms in a case study. With a filtering and tracking program the course of individual storms can be tracked and compared with observations. Also statistical studies can be done and one can calculate percentiles, return periods and other different extreme value statistic variables. Later, with a further nesting simulation, the resolution can be reduced to 1 km for individual areas of interest to analyse small islands (as Foehr or Amrum) and their effects on the atmospheric flow more closely.

New insights into the use of stable water isotopes at the northern Antarctic Peninsula as a tool for regional climate studies

NASA Astrophysics Data System (ADS)

Fernandoy, Francisco; Tetzner, Dieter; Meyer, Hanno; Gacitúa, Guisella; Hoffmann, Kirstin; Falk, Ulrike; Lambert, Fabrice; MacDonell, Shelley

2018-03-01

Due to recent atmospheric and oceanic warming, the Antarctic Peninsula is one of the most challenging regions of Antarctica to understand in terms of both local- and regional-scale climate signals. Steep topography and a lack of long-term and in situ meteorological observations complicate the extrapolation of existing climate models to the sub-regional scale. Therefore, new techniques must be developed to better understand processes operating in the region. Isotope signals are traditionally related mainly to atmospheric conditions, but a detailed analysis of individual components can give new insight into oceanic and atmospheric processes. This paper aims to use new isotopic records collected from snow and firn cores in conjunction with existing meteorological and oceanic datasets to determine changes at the climatic scale in the northern extent of the Antarctic Peninsula. In particular, a discernible effect of sea ice cover on local temperatures and the expression of climatic modes, especially the Southern Annular Mode (SAM), is demonstrated. In years with a large sea ice extension in winter (negative SAM anomaly), an inversion layer in the lower troposphere develops at the coastal zone. Therefore, an isotope-temperature relationship (δ-T) valid for all periods cannot be obtained, and instead the δ-T depends on the seasonal variability of oceanic conditions. Comparatively, transitional seasons (autumn and spring) have a consistent isotope-temperature gradient of +0.69 ‰ °C-1. As shown by firn core analysis, the near-surface temperature in the northern-most portion of the Antarctic Peninsula shows a decreasing trend (-0.33 °C year-1) between 2008 and 2014. In addition, the deuterium excess (dexcess) is demonstrated to be a reliable indicator of seasonal oceanic conditions, and therefore suitable to improve a firn age model based on seasonal dexcess variability. The annual accumulation rate in this region is highly variable, ranging between 1060 and 2470 kg m-2 year-1 from 2008 to 2014. The combination of isotopic and meteorological data in areas where data exist is key to reconstruct climatic conditions with a high temporal resolution in polar regions where no direct observations exist.

Mapping regional patterns of large forest fires in Wildland-Urban Interface areas in Europe.

PubMed

Modugno, Sirio; Balzter, Heiko; Cole, Beth; Borrelli, Pasquale

2016-05-01

Over recent decades, Land Use and Cover Change (LUCC) trends in many regions of Europe have reconfigured the landscape structures around many urban areas. In these areas, the proximity to landscape elements with high forest fuels has increased the fire risk to people and property. These Wildland-Urban Interface areas (WUI) can be defined as landscapes where anthropogenic urban land use and forest fuel mass come into contact. Mapping their extent is needed to prioritize fire risk control and inform local forest fire risk management strategies. This study proposes a method to map the extent and spatial patterns of the European WUI areas at continental scale. Using the European map of WUI areas, the hypothesis is tested that the distance from the nearest WUI area is related to the forest fire probability. Statistical relationships between the distance from the nearest WUI area, and large forest fire incidents from satellite remote sensing were subsequently modelled by logistic regression analysis. The first European scale map of the WUI extent and locations is presented. Country-specific positive and negative relationships of large fires and the proximity to the nearest WUI area are found. A regional-scale analysis shows a strong influence of the WUI zones on large fires in parts of the Mediterranean regions. Results indicate that the probability of large burned surfaces increases with diminishing WUI distance in touristic regions like Sardinia, Provence-Alpes-Côte d'Azur, or in regions with a strong peri-urban component as Catalunya, Comunidad de Madrid, Comunidad Valenciana. For the above regions, probability curves of large burned surfaces show statistical relationships (ROC value > 0.5) inside a 5000 m buffer of the nearest WUI. Wise land management can provide a valuable ecosystem service of fire risk reduction that is currently not explicitly included in ecosystem service valuations. The results re-emphasise the importance of including this ecosystem service in landscape valuations to account for the significant landscape function of reducing the risk of catastrophic large fires. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Eddy Fluxes and Sensitivity of the Water Cycle to Spatial Resolution in Idealized Regional Aquaplanet Model Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson M.; Leung, Lai-Yung R.; Gustafson, William I.

2014-02-28

A multi-scale moisture budget analysis is used to identify the mechanisms responsible for the sensitivity of the water cycle to spatial resolution using idealized regional aquaplanet simulations. In the higher resolution simulations, moisture transport by eddies fluxes dry the boundary layer enhancing evaporation and precipitation. This effect of eddies, which is underestimated by the physics parameterizations in the low-resolution simulations, is found to be responsible for the sensitivity of the water cycle both directly, and through its upscale effect, on the mean circulation. Correlations among moisture transport by eddies at adjacent ranges of scales provides the potential for reducing thismore » sensitivity by representing the unresolved eddies by their marginally resolved counterparts.« less

Impact of geostationary satellite water vapor channel data on weather analysis and forecasting

NASA Technical Reports Server (NTRS)

Velden, Christopher S.

1995-01-01

Preliminary results from NWP impact studies are indicating that upper-tropospheric wind information provided by tracking motions in sequences of geostationary satellite water vapor imagery can positively influence forecasts on regional scales, and possibly on global scales as well. The data are complimentary to cloud-tracked winds by providing data in cloud-free regions, as well as comparable in quality. First results from GOES-8 winds are encouraging, and further efforts and model impacts will be directed towards optimizing these data in numerical weather prediction (NWP). Assuming successful launches of GOES-J and GMS-5 satellites in 1995, high quality and resolution water vapor imagers will be available to provide nearly complete global upper-tropospheric wind coverage.

Emissions of methane in Europe inferred by total column measurements

NASA Astrophysics Data System (ADS)

Wunch, D.; Deutscher, N. M.; Hase, F.; Notholt, J.; Sussmann, R.; Toon, G. C.; Warneke, T.

2017-12-01

Atmospheric total column measurements have been used to infer emissions of methane in urban centres around the world. These measurements have been shown to be useful for verifying city-scale bottom-up inventories, and they can provide both timely and sub-annual emission information. We will present our analysis of atmospheric total column measurements of methane and carbon monoxide to infer annual and seasonal regional emissions of methane within Europe using five long-running atmospheric observatories. These observatories are part of the Total Carbon Column Observing Network, part of a global network that has been carefully designed to measure these gases on a consistent scale. Our inferred emissions will then be used to evaluate gridded emissions inventories in the region.

Dynamics of Large-Scale Solar-Wind Streams Obtained by the Double Superposed Epoch Analysis: 2. Comparisons of CIRs vs. Sheaths and MCs vs. Ejecta

NASA Astrophysics Data System (ADS)

Yermolaev, Y. I.; Lodkina, I. G.; Nikolaeva, N. S.; Yermolaev, M. Y.

2017-12-01

This work is a continuation of our previous article (Yermolaev et al. in J. Geophys. Res. 120, 7094, 2015), which describes the average temporal profiles of interplanetary plasma and field parameters in large-scale solar-wind (SW) streams: corotating interaction regions (CIRs), interplanetary coronal mass ejections (ICMEs including both magnetic clouds (MCs) and ejecta), and sheaths as well as interplanetary shocks (ISs). As in the previous article, we use the data of the OMNI database, our catalog of large-scale solar-wind phenomena during 1976 - 2000 (Yermolaev et al. in Cosmic Res., 47, 2, 81, 2009) and the method of double superposed epoch analysis (Yermolaev et al. in Ann. Geophys., 28, 2177, 2010a). We rescale the duration of all types of structures in such a way that the beginnings and endings for all of them coincide. We present new detailed results comparing pair phenomena: 1) both types of compression regions ( i.e. CIRs vs. sheaths) and 2) both types of ICMEs (MCs vs. ejecta). The obtained data allow us to suggest that the formation of the two types of compression regions responds to the same physical mechanism, regardless of the type of piston (high-speed stream (HSS) or ICME); the differences are connected to the geometry ( i.e. the angle between the speed gradient in front of the piston and the satellite trajectory) and the jumps in speed at the edges of the compression regions. In our opinion, one of the possible reasons behind the observed differences in the parameters in MCs and ejecta is that when ejecta are observed, the satellite passes farther from the nose of the area of ICME than when MCs are observed.

A Decadal (2004-2014) Analysis of Global-to-Regional Tropospheric Ozone Column Trends Using GFDL-AM3 Model Simulations and OMI Observations

NASA Astrophysics Data System (ADS)

Huang, G.; Liu, X.; Lin, M.; Ziemke, J. R.; Chance, K.; Zoogman, P.; Sun, K.

2017-12-01

Tropospheric ozone is a greenhouse gas, biological irritant, and significant source of highly reactive hydroxyl radicals, which remove many hazardous trace gases from the atmosphere. The decadal trend of tropospheric ozone columns (TOCs) can be influenced by many factors including anthropogenic and natural emissions of ozone precursors, large-scale atmospheric circulation patterns, and stratosphere-to-troposphere exchange. Since 2000, anthropogenic emissions of NOx have tended to shift from North America and Europe to Asia. This rapid shift has been implicated in raising background tropospheric ozone burden. However, large meteorologically-driven ozone variability complicates the unambiguous attribution of TOC trends calculated over short periods. In this study, we examine global-to-regional TOC trends during 2004-2014 using two independent satellite retrievals from OMI SAO (Smithsonian Astrophysical Observatory) and OMI/MLS, and interpret the results with a suite of GFDL-AM3 chemistry-climate model hindcasts designed to isolate the response of ozone to anthropogenic emissions, wildfires, and meteorology. Generally, OMI SAO, OMI/MLS and GFDL-AM3 BASE simulations agree on regional hot spots of TOC trends. On the regional scale, we find strong positive TOC trends during 2004-2014 in Mid-East (0.3-0.6 DU yr-1), South Asia (0.3-0.5 DU yr-1), Southeast Asia, East Asia ( 0.1-0.6 DU yr-1) and Central Africa ( 0.6 DU yr-1). Our initial analysis indicates that meteorological variability and anthropogenic emission trends play equally important roles in the positive TOC trends in East Asia and on a global scale during 2004-2014. We are working to investigate the potential influences from lightening NOx emissions, forest fires, and the stratosphere-to-troposphere exchange.

Small-scale plasma turbulence and intermittency in the high latitude F region based on the ICI-2 sounding rocket experiment

NASA Astrophysics Data System (ADS)

Spicher, A.; Miloch, W.; Moen, J. I.; Clausen, L. B. N.

2015-12-01

Small-scale plasma irregularities and turbulence are common phenomena in the F layer of the ionosphere, both in the equatorial and polar regions. A common approach in analyzing data from experiments on space and ionospheric plasma irregularities are power spectra. Power spectra give no information about the phases of the waveforms, and thus do not allow to determine whether some of the phases are correlated or whether they exhibit a random character. The former case would imply the presence of nonlinear wave-wave interactions, while the latter suggests a more turbulent-like process. Discerning between these mechanisms is crucial for understanding high latitude plasma irregularities and can be addressed with bispectral analysis and higher order statistics. In this study, we use higher order spectra and statistics to analyze electron density data observed with the ICI-2 sounding rocket experiment at a meter-scale resolution. The main objective of ICI-2 was to investigate plasma irregularities in the cusp in the F layer ionosphere. We study in detail two regions intersected during the rocket flight and which are characterized by large density fluctuations: a trailing edge of a cold polar cap patch, and a density enhancement subject to cusp auroral particle precipitation. While these two regions exhibit similar power spectra, our analysis reveals that their internal structure is different. The structures on the edge of the polar cap patch are characterized by significant coherent mode coupling and intermittency, while the plasma enhancement associated with precipitation exhibits stronger random characteristics. This indicates that particle precipitation may play a fundamental role in ionospheric plasma structuring by creating turbulent-like structures.

Wave Turning and Flow Angle in the E-Region Ionosphere

NASA Astrophysics Data System (ADS)

Young, M.; Oppenheim, M. M.; Dimant, Y. S.

2016-12-01

This work presents results of particle-in-cell (PIC) simulations of Farley-Buneman (FB) turbulence at various altitudes in the high-latitude E-region ionosphere. In that region, the FB instability regularly produces meter-scale plasma irregularities. VHF radars observe coherent echoes via Bragg scatter from wave fronts parallel or anti-parallel to the radar line of sight (LoS) but do not necessarily measure the mean direction of wave propagation. Haldoupis (1984) conducted a study of diffuse radar aurora and found that the spectral width of back-scattered power depends critically on the angle between the radar LoS and the true flow direction, called the flow angle. Knowledge of the flow angle will allow researchers to better interpret observations of coherent back-scatter. Experiments designed to observe meter-scale irregularities in the E-region ionosphere created by the FB instability typically assume that the predominant flow direction is the E×B direction. However, linear theory of Dimant and Oppenheim (2004) showed that FB waves should turn away from E×B and particle-in-cell simulations by Oppenheim and Dimant (2013) support the theory. The present study comprises a quantitative analysis of the dependence of back-scattered power, flow velocity, and spectral width as functions of the flow angle. It also demonstrates that the mean direction of meter-scale wave propagation may differ from the E×B direction by tens of degrees. The analysis includes 2-D and 3-D simulations at a range of altitudes in the auroral ionosphere. Comparison between 2-D and 3-D simulations illustrates the relative importance to the irregularity spectrum of a small but finite component in the direction parallel to B. Previous work has shown this small parallel component to be important to turbulent electron heating and nonlinear transport.

Genetic analysis across different spatial scales reveals multiple dispersal mechanisms for the invasive hydrozoan Cordylophora in the Great Lakes.

PubMed

Darling, John A; Folino-Rorem, Nadine C

2009-12-01

Discerning patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. The globally invasive colonial hydrozoan Cordylophora produces propagules both sexually and vegetatively and is associated with multiple potential dispersal mechanisms, making it a promising system to investigate complex patterns of population structure generated throughout the course of rapid range expansion. Here, we explore genetic patterns associated with the spread of this taxon within the North American Great Lakes basin. We collected intensively from eight harbours in the Chicago area in order to conduct detailed investigation of local population expansion. In addition, we collected from Lakes Michigan, Erie, and Ontario, as well as Lake Cayuga in the Finger Lakes of upstate New York in order to assess genetic structure on a regional scale. Based on data from eight highly polymorphic microsatellite loci we examined the spatial extent of clonal genotypes, assessed levels of neutral genetic diversity, and explored patterns of migration and dispersal at multiple spatial scales through assessment of population level genetic differentiation (pairwise F(ST) and factorial correspondence analysis), Bayesian inference of population structure, and assignment tests on individual genotypes. Results of these analyses indicate that Cordylophora populations in this region spread predominantly through sexually produced propagules, and that while limited natural larval dispersal can drive expansion locally, regional expansion likely relies on anthropogenic dispersal vectors.

Axisymmetric computational fluid dynamics analysis of Saturn V/S1-C/F1 nozzle and plume

NASA Technical Reports Server (NTRS)

Ruf, Joseph H.

1993-01-01

An axisymmetric single engine Computational Fluid Dynamics calculation of the Saturn V/S 1-C vehicle base region and F1 engine plume is described. There were two objectives of this work, the first was to calculate an axisymmetric approximation of the nozzle, plume and base region flow fields of S1-C/F1, relate/scale this to flight data and apply this scaling factor to a NLS/STME axisymmetric calculations from a parallel effort. The second was to assess the differences in F1 and STME plume shear layer development and concentration of combustible gases. This second piece of information was to be input/supporting data for assumptions made in NLS2 base temperature scaling methodology from which the vehicle base thermal environments were being generated. The F1 calculations started at the main combustion chamber faceplate and incorporated the turbine exhaust dump/nozzle film coolant. The plume and base region calculations were made for ten thousand feet and 57 thousand feet altitude at vehicle flight velocity and in stagnant freestream. FDNS was implemented with a 14 species, 28 reaction finite rate chemistry model plus a soot burning model for the RP-1/LOX chemistry. Nozzle and plume flow fields are shown, the plume shear layer constituents are compared to a STME plume. Conclusions are made about the validity and status of the analysis and NLS2 vehicle base thermal environment definition methodology.

Seasonal Drought Prediction in East Africa: Can National Multi-Model Ensemble Forecasts Help?

NASA Technical Reports Server (NTRS)

Shukla, Shraddhanand; Roberts, J. B.; Funk, Christopher; Robertson, F. R.; Hoell, Andrew

2015-01-01

The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as in 2011 part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However seasonal drought prediction in this region faces several challenges. Lack of skillful seasonal rainfall forecasts; the focus of this presentation, is one of those major challenges. In the past few decades, major strides have been taken towards improvement of seasonal scale dynamical climate forecasts. The National Centers for Environmental Prediction's (NCEP) National Multi-model Ensemble (NMME) is one such state-of-the-art dynamical climate forecast system. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ ensemble member forecasts. Recent studies have indicated that in general NMME offers improvement over forecasts from any single model. However thus far the skill of NMME for forecasting rainfall in a vulnerable region like the East Africa has been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons for the region. (i.e. March-April-May, July-August-September and October-November- December). Simultaneously we also describe hybrid approaches; that combine statistical approaches with NMME forecasts; to improve rainfall forecast skill in the region when raw NMME forecasts lack in skill.

Seasonal Drought Prediction in East Africa: Can National Multi-Model Ensemble Forecasts Help?

NASA Technical Reports Server (NTRS)

Shukla, Shraddhanand; Roberts, J. B.; Funk, Christopher; Robertson, F. R.; Hoell, Andrew

2014-01-01

The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as in 2011 part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However seasonal drought prediction in this region faces several challenges. Lack of skillful seasonal rainfall forecasts; the focus of this presentation, is one of those major challenges. In the past few decades, major strides have been taken towards improvement of seasonal scale dynamical climate forecasts. The National Centers for Environmental Prediction's (NCEP) National Multi-model Ensemble (NMME) is one such state-of-the-art dynamical climate forecast system. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ ensemble member forecasts. Recent studies have indicated that in general NMME offers improvement over forecasts from any single model. However thus far the skill of NMME for forecasting rainfall in a vulnerable region like the East Africa has been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons for the region. (i.e. March-April-May, July-August-September and October-November- December). Simultaneously we also describe hybrid approaches; that combine statistical approaches with NMME forecasts; to improve rainfall forecast skill in the region when raw NMME forecasts lack in skill.

Discontinuities, cross-scale patterns, and the organization of ecosystems

USGS Publications Warehouse

Nash, Kirsty L.; Allen, Craig R.; Angeler, David G.; Barichievy, Chris; Eason, Tarsha; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Knutson, Melinda; Nelson, R. John; Nystrom, Magnus; Stow, Craig A.; Sandstrom, Shana M.

2014-01-01

Ecological structures and processes occur at specific spatiotemporal scales, and interactions that occur across multiple scales mediate scale-specific (e.g., individual, community, local, or regional) responses to disturbance. Despite the importance of scale, explicitly incorporating a multi-scale perspective into research and management actions remains a challenge. The discontinuity hypothesis provides a fertile avenue for addressing this problem by linking measureable proxies to inherent scales of structure within ecosystems. Here we outline the conceptual framework underlying discontinuities and review the evidence supporting the discontinuity hypothesis in ecological systems. Next we explore the utility of this approach for understanding cross-scale patterns and the organization of ecosystems by describing recent advances for examining nonlinear responses to disturbance and phenomena such as extinctions, invasions, and resilience. To stimulate new research, we present methods for performing discontinuity analysis, detail outstanding knowledge gaps, and discuss potential approaches for addressing these gaps.

Preliminary GIS analysis of the agricultural landscape of Cuyo Cuyo, Department of Puno, Peru

NASA Technical Reports Server (NTRS)

Winterhalder, Bruce; Evans, Tom

1991-01-01

Computerized analysis of a geographic database (GIS) for Cuyo Cuyo, (Dept. Puno, Peru) is used to correlate the agricultural production zones of two adjacent communities to altitude, slope, aspect, and other geomorphological features of the high-altitude eastern escarpment landscape. The techniques exemplified will allow ecological anthropologists to analyze spatial patterns at regional scales with much greater control over the data.

Transmission Infrastructure | Energy Analysis | NREL

Science.gov Websites

aggregating geothermal with other complementary generating technologies, in renewable energy zones infrastructure planning and expansion to enable large-scale deployment of renewable energy in the future. Large Energy, FERC, NERC, and the regional entities, transmission providers, generating companies, utilities

Regulation of eutrophication susceptibility in oligohaline zones of a northern Gulf of Mexico estuary, Mobile Bay, Alabama

EPA Science Inventory

Variability in estuarine eutrophication susceptibility to nutrinets was examined in a comparative empirical analysis of 7 oligohaline tidal river regions. Eutrophication response, in terms of phytoplankton biomass (chlorophylla), was related to estuarine mixing times scales and ...

Estimating monetary damages from flooding in the United States under a changing climate

EPA Science Inventory

A national-scale analysis of potential changes in monetary damages from flooding under climate change. The approach uses empirically based statistical relationships between historical precipitation and flood damage records from 18 hydrologic regions of the United States, along w...